Psychopharmacology

, Volume 199, Issue 3, pp 331–388

Realistic expectations of prepulse inhibition in translational models for schizophrenia research

Authors

    • Department of PsychiatryUCSD School of Medicine
    • Department of PsychiatryUniversity of California, San Diego
  • Martin Weber
    • Department of PsychiatryUCSD School of Medicine
  • Ying Qu
    • Department of PsychiatryUCSD School of Medicine
  • Gregory A. Light
    • Department of PsychiatryUCSD School of Medicine
  • David L. Braff
    • Department of PsychiatryUCSD School of Medicine
Review

DOI: 10.1007/s00213-008-1072-4

Cite this article as:
Swerdlow, N.R., Weber, M., Qu, Y. et al. Psychopharmacology (2008) 199: 331. doi:10.1007/s00213-008-1072-4

Abstract

Introduction

Under specific conditions, a weak lead stimulus, or “prepulse”, can inhibit the startling effects of a subsequent intense abrupt stimulus. This startle-inhibiting effect of the prepulse, termed “prepulse inhibition” (PPI), is widely used in translational models to understand the biology of brain‑based inhibitory mechanisms and their deficiency in neuropsychiatric disorders. In 1981, four published reports with “prepulse inhibition” as an index term were listed on Medline; over the past 5 years, new published Medline reports with “prepulse inhibition” as an index term have appeared at a rate exceeding once every 2.7 days (n = 678). Most of these reports focus on the use of PPI in translational models of impaired sensorimotor gating in schizophrenia. This rapid expansion and broad application of PPI as a tool for understanding schizophrenia has, at times, outpaced critical thinking and falsifiable hypotheses about the relative strengths vs. limitations of this measure.

Objectives

This review enumerates the realistic expectations for PPI in translational models for schizophrenia research, and provides cautionary notes for the future applications of this important research tool.

Conclusion

In humans, PPI is not “diagnostic”; levels of PPI do not predict clinical course, specific symptoms, or individual medication responses. In preclinical studies, PPI is valuable for evaluating models or model organisms relevant to schizophrenia, “mapping” neural substrates of deficient PPI in schizophrenia, and advancing the discovery and development of novel therapeutics. Across species, PPI is a reliable, robust quantitative phenotype that is useful for probing the neurobiology and genetics of gating deficits in schizophrenia.

Keywords

Animal modelsAntipsychoticDopaminePrepulse inhibitionSchizophreniaSensorimotor gatingStartle

Introduction

Among the paths to understanding the neurobiology of schizophrenia, one heavily traveled, has been the study through preclinical and clinical models of sensorimotor gating and its neural and genetic substrates. A laboratory paradigm frequently used to operationally measure sensorimotor gating is prepulse inhibition of the startle reflex (PPI). Medline lists over 1400 published reports utilizing the key word “prepulse inhibition” and over 580 that also include the key word “schizophrenia”. Research using PPI to probe the neural and genetic bases of schizophrenia has crossed every level of the “top‑down” and “bottom‑up” investigations of this disorder—from studies of the psychological implications of PPI to those assessing the control of PPI by signal transduction pathways and the genes that regulate them. Arising implicitly and explicitly from such a broad application of the PPI paradigm have been assumptions and expectations that we hope to examine critically in this review. In so doing, we hope to offer some perspectives on both potentially productive directions of this work, and the degree to which some assumptions and expectations may, or may not, be reasonable.

Historical overview

The popularity of PPI as an experimental paradigm for understanding schizophrenia comes from its conceptual linkage to clinical observations that schizophrenia patients are unable to optimally filter or “gate” irrelevant, intrusive sensory stimuli (Bleuler 1911; Kraepelin and Robertson 1919; McGhie and Chapman 1961; Venables 1964). These clinical observations led to the formulation of a construct—“gating deficits” in schizophrenia—that has been extended to refer to deficient inhibition of both sensory and cognitive information. The PPI paradigm was developed as a measure of automatic or preconscious inhibition in normal comparison subjects, as one variant of numerous paired-pulse paradigms in which the presentation of a lead stimulus led to the reduced perceptual or motor response to a second stimulus (Peak 1939; Graham 1975) (Fig. 1). Braff et al. (1978) first merged the construct and its operational measurement by identifying PPI deficits in schizophrenia patients, a finding that has since been replicated by many independent groups and [as reviewed previously (Braff et al. 2001b) and below], has become among the most influential paradigms in the field of schizophrenia psychophysiology. A comprehensive review through the year 2000 of all reports linking PPI deficits to schizophrenia in clinical populations is found in Braff et al. (2001b); reports subsequent to this date are listed in Table 1. Animal studies first linked this finding to a neurochemical (DA) and anatomical (ventral striatum) substrate (Sorenson and Swerdlow 1982; Swerdlow et al. 1986), and subsequent reports centered these substrates within an extended forebrain and pontine circuit that regulates PPI in rodents (Koch and Schnitzler 1997; Swerdlow et al. 1992, 2000a; see Table 4). Animal studies have identified developmental (Geyer et al. 1993; Lipska et al. 1995; see Table 3) and genetic (Carter et al. 1999; Ralph et al. 1999; Geyer et al. 2002; see Table 3) influences on PPI and have led to predictive models for antipsychotic development (Swerdlow et al. 1994) that have been modified and widely applied towards antipsychotic discovery. A comprehensive review through the year 2000 of all reports using PPI in models predicting antipsychotic properties is found in Geyer et al. (2001); reports subsequent to this date are listed in Table 2.
https://static-content.springer.com/image/art%3A10.1007%2Fs00213-008-1072-4/MediaObjects/213_2008_1072_Fig1_HTML.gif
Fig. 1

Schematic representation, adapted from Swerdlow et al. (1994), of stimuli used to elicit PPI in laboratory measures (a). b shows superimposed tracings of electromyography of the right orbicularis oculi in an adult male subject, from sequential trials that included either a prepulse [20 ms noise burst 4 dB over a 70-dB(A) background] followed 100 ms later by a 118-dB(A) 40 ms startle noise pulse (solid black area), or the startle pulse alone (open area). Tracings in (b) begin at pulse onset. The amount of inhibition generated by the prepulse can be appreciated visually by subtracting the solid area from the open area

Table 1

Studies of PPI in schizophrenia patients and related groups, ca. 2001–2007a

I. Studies reporting PPI deficits in schizophrenia patients

II. Studies reporting PPI deficits in subgroups of schizophrenia patients

III. Studies reporting PPI deficits in schizophrenia patients under specific experimental conditions

IV. Studies reporting PPI deficits in schizophrenia patients

V. Studies reporting PPI deficits in populations conceptually linked to schizophrenia

Reference

Sex, medications, n, other characteristics

PPI deficits compared to normal comparison subjects (NCS)?

Other measures or factors examined in relation to PPIb

Eye side

Background DBc

Startle stimuli

Prepulse stimuli

Prepulse interval (ms)

I. Studies reporting PPI deficits in schizophrenia patients

Braff et al. 2005

F, MED (n = 25)

Yes

 

R

70

40 ms 115 dB WN

20 ms 78 and 86 dB WN

30, 120

Cadenhead et al. 2002

M/F 10/11, MED (n = 4), UNMED (n = 17)

33% of PTS < 1 SD of PPI of NCS

Medication, clinical characteristics, P50, AS

R,L

70

40 ms 115 dB WN

20 ms 86 dB WN

30, 120

Duncan et al. 2003a

M, MED (n = 27), UNMED (n = 14)

Yes

Medication

R

70

40 ms 116 dB 1 KHz

20 ms 85 dB 1 KHz

30–120

Duncan et al. 2003b

M, study 1: pre- and post-medication (n = 16); study 2: MED (n = 43), UNMED (n = 21)

Yes, independent of medication status

Medication

R

70

40 ms 116 dB 1 KHz

20 ms dB 1 KHz

30–120

Heresco-Levy et al. 2007

M/F 18/12, MED

Yes

Clinical characteristics, serum glycine and glutamate levels

R

70

40 ms 115 dB 1 KHz

20 ms 84 dB 1 KHz

30–120

Hong et al. 2007

M/F 46/13, MED

Yes

Medication, P50

R

70

40 ms 116 dB WN

20 ms 80 dB WN

30–500

Kumari et al. 2003a

M, MED (n = 7).

Trend towards lower PPI

fMRI

R

None

40 ms airpuff 30 psi

20 ms airpuff 10 psi

100

Kumari et al. 2005a

M, MED (n = 23)

Yes

Medication, violence ratings, clinical characteristics, illness duration

R

70

40 ms 115 dB WN

20 ms 85 dB WN

30–150

Kumari et al. 2005b

Study 1: M, MED (n = 35–39); study 2: M/F 23/12, MED

Yes

Medication, clinical characteristics, AS

R

70

40 ms 115 dB WN

20 ms 85 dB WN

30–120

Kumari et al. 2007B

M/F 17/3, UNMED

Yes

 

R,L

70

40 ms 115 dB WN

20 ms 85 dB WN

30–120

Ludewig and Vollenweider 2002

M/F 49/18, MED

Yes

Medication, clinical characteristics

R

70

40 ms 115 dB WN

20 ms 86 dB WN

30–2000

Ludewig et al. 2002

M/F 15/4, MED

Yes

 

R

70

40 ms 115 dB

20 ms 86 dB

30–2000

Ludewig et al. 2003

M, UNMED (n = 24)

Yes

Clinical characteristics

R

70

40 ms 115 dB WN

20 ms 86 dB WN

30–2000

Mackeprang et al. 2002

M/F 14/6, MED

Yes independent of medication status

Medication

R

70

40 ms 116 dB

85 dB

30–120

Perry et al. 2002

M and F (n = 41); M/F 25/16, MED (n = 20), UNMED (n = 21)

Yes

Medication

R

70

40 ms 115 dB WN

20 ms 95 dB WN

30–120

Perry et al. 2004

M/F 8/6, MED

Yes

Sex

R

70

40 ms 115 dB WN

20 ms 85 dB WN

30–120

Swerdlow et al. 2006f

M/F 72/31, MED (n = 94), UNMED (n = 9)

Yes

Medication, sex, clinical characteristics, neurocognitive and functional measures, smoking

R,L

70

40 ms 115 dB WN

20 ms 85 dB WN

20–120

II. Studies reporting PPI deficits in subgroups of schizophrenia patients

Kumari et al. 2004

M/F 27/15, MED

Yes in men, but not in women

Medication, sex, clinical characteristics, PPF

R

70

40 ms 115 dB WN

20 ms 78 or 85 dB WN

30–150

Leumann et al. 2002

M/F 25/8, MED

Yes with typical but not atypical APs

Medication, LI

R

70

40 ms 115 dB

20 ms 86 dB

30–2000

Meincke et al. 2004

M/F 22/14, MED

Yes during acute, but not remitted clinical state

Clinical characteristics, psychopathological symptoms

R

65

20 ms 115 dB WN

20 ms 73 dB WN

30, 100

Minassian et al. 2007

M/F 16/7, admission: MED (n = 15), UNMED (n = 8), 2 weeks later: MED (n = 23), UNMED (n = 1)

Yes at hospital admission, but not 2 weeks later

Medication, clinical characteristics

R

70

40 ms 115 dB WN

20 ms 85 dB WN

30–120

Oranje et al. 2002

M/F 31/13, MED

Yes in PTS with typical but not with atypical APs

Medication

R

NS

30 ms 115 dB 1 KHz

30 ms 80 dB 1.5 KHz

120

Quednow et al. 2006

M/F 19/9, pre-study: MED (n = 9), UNMED (n = 16), post-randomization: typical APs (n = 12), atypical APs (n = 16)

Yes during baseline session in first week of treatment, but not after prolonged treatment

Number of previous episodes, clinical characteristics, therapeutic success

R

70

40 ms 116 dB

20 ms 86 dB

120

III. Studies reporting PPI deficits in schizophrenia patients under specific experimental conditions

George et al. 2006

M/F 9/6, smokers, MED

Smoking abstinence: ↓PPI; smoking reinstatement: ↑PPI

Smoking

NS

70

40 ms 115 dB WN

20 ms 85 dB WN

30–120

Hazlett et al. 2003

M/F 14/4, UNMED PTS with schizotypical personality disorder

Greater PPI during attended vs. ignored prepulses in NCS, but not in PTS

PPF

R

45

40 ms 104 dB WN

5 or 8 s 70 dB 0.8 or 1 KHz

120, 240

Kedzior and Martin-Iverson 2007

M/F 7/1, MED

deficits in “attend” condition only

Smoking

Ld

60

50 ms 100 dB WN

20 ms 70 dB 5 KHz

20–200

Kumari et al. 2002

M, MED (n = 30)

Yes in PTS treated with typical APs but not with RIS

Medication, clinical characteristics, duration of illness

R

70

40 ms 115 dB WN

20 ms 85 dB WN

30–120

Kumari et al. 2003b

M/F 7/4, MED (n = 11)

↓ PPI in response to procyclidine

 

R

70

40 ms 115 dB WN

20 ms 78 or 85 dB WN

30–120

Wynn et al. 2004

PTS: M/F 74/2, MED (typical APs (n = 22), atypical APs (n = 43), mixed or unknown (n = 11), unaffected siblings: M/F 17/19

No PPI deficits in PTS or unaffected siblings

Medication, PPF, sex, clinical characteristics

L

None

50 ms 105 dB WN

20 ms 75 dB WN

120

IV. Studies reporting no PPI deficits in schizophrenia patients

Duncan et al. 2006a

M, MED (n = 52), UNMED (n = 21)

No

Medication, clinical characteristics

R

70

40 ms 116 dB 1 KHz

20 ms 85 dB 1 KHz

30–120

Postma et al. 2006

M, MED (n = 9)

No. Smoking enhanced PPI in PTS and NCS

fMRI

R

None

40 ms airpuff 30 psi

20 ms air airpuff 10 psi

30–120

Volz et al. 2003

M/F 23/26, MED (n = 42), UNMED (n = 7)

No

 

L

NS

50 ms 100 dB WN

Pictures presented for 6 s

150–3,800

V. Studies reporting PPI deficits in populations conceptually linked to schizophrenia

Kumari et al. 2005d

M/F 4/15, unaffected siblings of SZ PTS

Reduced PPI in siblings of SZ PTS with binaural stimulus presentation

Schizotypy ratings

R

70

40 ms 115 dB WN

20 ms 85 dB WN

30–120

Sobin et al. 2005a

M/F 11/14, children with 22q11 DS

Yes

Sex, age, clinical characteristics, latency reduction, attention network test, reaction time

R

50

50 ms 104 dB WN

40 ms 70 dB WN

100

Sobin et al. 2005b

M/F 13/12, children with 22q11 DS

Yes

Sex, age, clinical characteristics, symptom severity, subsyndromal symptoms of other disorders

R

56

50 ms 104 dB WN

30 ms 70 dB WN

100

Weike et al. 2001

Ss “believe in extraordinary phenomena” (n = 16, M/F = 5/11) or not (n = 16, M/F = 10/6)

PPI not different between believers and non-believers

Sex, age, schizotypal personality, magical ideation/perceptual aberration scales

L

NS

50 ms 105 dB WN

20 ms 1000 Hz

30–480

APs Antipsychotics, AS anti-saccade measures, F female, fMRI functional magnetic resonance imaging, L left, LI latent inhibition, M male, MED medicated, NCS normal comparison subjects, NS not specified, P50 P50 event-related potential suppression, PPF prepulse facilitation, PPI prepulse inhibition, PTS patients, R right, RIS risperidone, Ss subjects, SZ schizophrenia, UNMED unmedicated, WN white noise, ↓ reduced, ↑ increased

aAll tables are preceded by outlines describing their organizational structure. In distilling this substantial literature into tabular form, a substantial amount of information is lost. The abbreviated descriptions herein cannot do justice to the wealth of data and interpretations found in the original reports. References are provided to guide readers to the source material.

bDemographics reported as independent measures in most studies

cAll dB A scale unless not specified in text; stimuli described in KHz are pure tones.

dRight eye, n = 1

Table 2

Examples of studies using PPI to assess or predict antipsychotic properties, ca. 2001–2007

I. Anti-dopaminergics

VII. Cannabinoid mechanism

           A. D2/mixed receptor antagonists

           A. CB1-antagonists

           B. D3-preferential antagonists

           B. Endocannabinoid transport inhibitor

           C. D4-preferential antagonists

           C. Cannabidiol

II. Glutamatergic mechanisms

VII. Neuropeptide mechanisms

           A. mGLUR

           A. Neurotensin agonists

           B. NMDA

           B. Opioids

           C. GLY

           C. CCK

III. Serotonergic mechanisms

IX. Adenosine mechanisms

IV. Noradrenergic mechanisms

X. GABA agonists

V. Cholinergic mechanisms

XI. GABA agonists

           A. Nicotinic agonists

XII. Hormones

           B. Muscarinic agonists

XIII. Second-messenger inhibitors

           C. AChE inhibitors

           A. Nitric oxide synthase inhibitors

VI. Histaminergic mechanisms

           B. Guanylate cyclase + NOS inhibitors

           C. PDE-inhibitors

XIV. Miscellaneous

References

Species, strain, sex

PPI deficit induced by

Primary drug/mechanism tested

Effects

Other drug types tested

I. Anti-dopaminergics

A. D2/mixed receptor antagonists

 

Rats

  

Bast et al. 2001

WI, M

Intra-VHPC NMDA infusion

HAL D2 family antagonist

∅NMDA

CLO (∅NMDA)

Cilia et al. 2007

SD, M

KET

HAL

∅KET, not potentiated by mGLUR5 antagonist MPEP

CLO, RIS, lamotrigine, SB-271046-A (all similar effects to HAL)

Conti et al. 2005

WKY, M; BN, M

ICV CRF infusion

HAL

↓CRF in WKY rats, ∅CRF in BN rats

CLO (↓CRF in WKY rats, overcompensation of PPI-deficit in BN rats)

van den Buuse and Gogos 2007

SD, M

8‑OHDPAT

HAL

↓8‑OHDPAT (at 100 ms PP interval)

RAC, ARI, BUS (all ↓8-OHDPAT), CLO, OLA, RIS, AMI, MDL73,005EF (partial 5-HT1A agonist) (all ∅8-OHDPAT) all at 100 ms PP interval

 

Rats + mice

 

Metzger et al. 2007

Mice, C57; Rats, SD, M

AMP or APO

HAL (implanted HAL polymer, or acute HAL)

HAL implants: ↓AMP in mice, ↓APO in rats Acute HAL: ↓APO in rats

 
 

Mice

Russig et al. 2004

C57, M

APO

HAL

↓APO

CLO (∅APO)

 

Human subgroups (+rats)

Vollenweider et al. 2006

Humans (“low vs. high gaters”)

Basal PPI, differences between subgroups

CLO D1‑4/5-HT21/muscarinic antagonist

↑PPI in “low gaters” (at short PP intervals), ∅PPI in “high gaters”

 

Swerdlow et al. 2006a

Humans (“low vs. high gaters”), M; rats, SD, M; rats, BN, M

Basal PPI, differences between human subgroups or rat strains

Quetiapine D1‑2/5-HT21/H1/muscarinic antagonist

↑PPI in human low gaters and SD rats (at short PP intervals), ↑PPI in BN rats

CLO (↑PPI at short PP intervals), HAL (∅PPI) in SD rats

 

Primates

Linn et al. 2003

Capuchin monkeys, F

PCP

CLO

↓PCP

HAL (∅PCP)

 

Rats

Erhardt et al. 2004

SD, M

↑Endogenous KYNA by kynurine or PNU 156561A

CLO

↓KYNA

HAL (↓KYNA)

Le Pen and Moreau 2002

SD, M

nHPC lesion

CLO

↑PPI

OLA (↑PPI), RIS (↑PPI), HAL (∅PPI)

Depoortere et al. 2007b

SD, M

APO

F15063 D2/D3-Antagonist, D4-partial agonist, 5-HT1A-agonist

↓APO

 

Depoortere et al. 2007a

SD, M

Basal PPI

F15063

∅PPI

 

Barr et al. 2006

SD, M

IR vs. induction of PPI deficits by APO, PCP, or CIR in SR rats

Iloperidone DA/5-HAT/NA antagonist

∅PPI in IR rats, but ↓APO, ↓PCP, ↓CIR in SR rats

 

Ellenbroek et al. 2001

WI, M

Basal PPI, APO, or AMP

JL13 Predominant D1/5-HT2 binding

↑PPI (basal), ↓APO, ↓AMP

HAL, CLO (both, ∅PPI (basal), ↓APO, ↓AMP)

Ojima et al. 2004

SD, M

Basal PPI

Perospirone D2/5-HT2A/5-HT1A antagonist

↑PPI

HAL (∅PPI), RIS (↑PPI (relative to HAL))

Rueter et al. 2004

SD, M

nVHPC lesion

Risperidone D2/5-HT2/α antagonist (chronic low-dose treatment)

↑PPI

CLO (↑PPI)

Bubenikova et al. 2005

WI, M

DIZ

Zotepine D1/D2/ D3/5-HT2A/5-HT2C5-HT6/5-HT71/H1/NET-affinity

∅DIZ

RIS (∅DIZ), CLO, OLA (both ↓DIZ, but ↓PPI relative to vehicle (no DIZ))

 

Mice

 

Fejgin et al. 2007

NMRI, M

Basal PPI or PCP

Aripiprazole partial agonist at D2/5-HT1A and antagonist at 5-HT2A

↑PPI (basal), ↓PCP

CLO (↑PPI (trend), ∅PCP), OLA, (∅PPI, ∅PCP), HAL (↑PPI, ∅PCP)

Brea et al. 2006

Swiss, M

APO or DOI

QF2004B D1‑4/5-HT1A,2A,2C1,2/M1,2/H1-binding

↓APO, ↓DOI

CLO, HAL (both ↓APO, ↓DOI)

Flood et al. 2008

DBA/2NCrl, DBA/2J, 2NHsd, 2NTac1, 2NTac2,C57BL/6Tac, 129S6/SvEvTac

Basal PPI

Olanzapine D1/D2/5-HT21/muscarinic/H1 antagonist

Reversal of PPI deficit (tested only in DBA/2NCrl mice)

ARI (reversal of PPI deficit), β-CD (reversal of PPI deficit compared to H2O) in DBA/2NCrl mice; both drugs were not tested in other strains

B. D3-preferential antagonists

 

Rats

Zhang et al. 2007b

WI, M

PD128907 (D3 agonist), or APO

A-691990

↓PD128907, ∅APO

HAL (∅PD128907, ↓APO), RAC (∅PD128907), CLO, RIS (both: ↓PD128907, ↓APO), SB 277011 (↓PD128907, ∅APO)

 

Mice

Zhang et al. 2006

DBA, M

Basal PPI or nVHPC lesion

A-437203

↑PPI in unlesioned animals, but ∅PPI after nVHPC lesion)

Intact mice: HAL (↑PPI), RIS (↑PPI), SB277011 (D3 antagonist, ↑PPI), AVE 5997 (D3 antagonist, ∅PPI); nVHPC lesion: HAL (↑PPI), AVE 5997 (∅PPI); BP897 (preferential D3/D2 antagonist, ↑PPI in lesioned and intact mice)

Park et al. 2005

ICR, M

APO

KKHA‑761

↓APO

 

C. D4-preferential antagonists

Boeckler et al. 2004

Rats, WI, M

 

FAUC 213

↓APO

 

II. Glutamatergic mechanisms

A. mGLUR

 

Rats

Kinney et al. 2005

SD, M

AMP

CDPPB Metabotropic GLU 5 allosteric potentiator

↓AMP

 
 

Mice

Galici et al. 2005

C57, M

AMP or PCP

LY487379 Metabotropic GLU 2 allosteric potentiator

↓AMP, ∅PCP

LY379268 (GLU 2/3 agonist; ∅AMP, ∅PCP)

B. NMDA

 

Rats

Zajaczkowski et al. 2003

WI, M

DIZ

CGP 40116 Competitive NMDA antagonist

↓DIZ

 

C. GLY

 

Rats

Le Pen et al. 2003

SD, M

nVHPC lesion

Glycine

↑PPI

ORG 24598 (GLYT1 inhibitor, ↑PPI)

 

Mice

Adage et al. 2007

C57, M

PCP

AS057278 DAAO inhibitor; DAAO is the enzyme which oxidizes D‑serine (→ see below)

↓PCP

CLO (↓PCP)

Depoortere et al. 2005

DBA, M

Basal PPI

SSR5504734 GLYT antagonist

↑PPI

 

Kinney et al. 2003

DBA, M

Basal PPI

NFPS GLYT1 antagonist

↑PPI

CLO (↑PPI)

Lipina et al. 2005

C57, M

Basal PPI or DIZ

d-Serine modulator of the GLY site of the NMDA receptor

↑PPI (basal PPI), ∅DIZ

l-Serine (∅PPI), ALX 5407 (GLYT1 inhibitor, ↓PPI, ↓DIZ), CLO (↑PPI, ↓DIZ)

III. Serotonergic mechanisms

 

5‑HT1

 

Rats

Auclair et al. 2006

SD, M

APO

SSR181507 5-HT1A agonist, partial D2 agonist

∅APO ↓APO (when co-administered with WAY100635)

SLV313 (similar to SSR81507), sarizotan (∅APO), bifeprunox, HAL, ARI, RIS, OLA, QUE, ZIP (all ↓APO)

Auclair et al. 2007

SD, M

Basal PPI

SSR181507

↓PPI (reversed by WAY100,635)

Sarizotan, bifeprunox, 8-OHDPAT, (all ↓PPI), HAL, ARI, RIS, OLA, QUE, ZIP (all ∅PPI)

Krebs-Thomson et al. 2006

 

5-MeO-DMT (hallucinogen)

Way100,635 5-HT1A antagonist

↓5‑MeO-DMT

M100907 (5-HT2A antagonist, ∅5-MeO-DMT), SER-082 (5-HT2C antagonist ↓5-MeO-DMT)

 

Mice

Sakaue et al. 2003

ddY, M

IR, APO or DIZ

MC-242 5-HT1A agonist

↑PPI (in IR mice, antagonized by Way100,635), ∅APO (in SR mice), ∅DIZ (in SR mice)

RIS (↑PPI in IR mice, ↓APO in SR mice)

5‑HT2

 

Rats

Vanover et al. 2006

SD, M

DOI

ACP-103 5-HT2A inverse agonist

↓DOI

 

Siuciak et al. 2007

WI, M

APO

CP-809,101 5-HT2C agonist

↓APO

HAL (↓APO)

Ouagazzal et al. 2001a, b

SD, M

LSD (hallucinogen)

M100907

↓LSD

SB 242084 (5-HT2C antagonist), SDZ SER 082 (5-HT2b/2C antagonist), RO 04-6790 (5-HT6 antagonist), HAL (all ∅LSD)

 

Mice

Barr et al. 2004

DAT-KO, M

Basal PPI

M100907 5-HT2A antagonist

↑PPI

 

Marquis et al. 2007

DBA/2N, M

Basal PPI, DIZ, or DOI

WAY 163909 5-HT2C agonist

↑PPI, ↓DIZ, ↓DOI, ↑AMP

 

5-HT6

Pouzet et al. 2002a

Rats, WI, M

AMP or PCP

SB-271046 5-HT6 antagonist

↓AMP, ∅PCP

CLO (↓AMP, ∅PCP)

5-HT7

 

Rats (+ mice)

Pouzet et al. 2002b

WI, M

AMP or PCP

SB-258741 5-HT7 antagonist

∅AMP, ↓PCP

RIS (↓AMP, ↓PCP)

 

Rats + mice

Semenova et al. 2008

5-HT7KO, M; Mice, C57, M; Rats, SD, M

APO, AMP, or PCP

SB-269970 5-HT7 antagonist

No SB-269970: ↓PCP in KO vs. WT mice; ↓APO and ↓AMP in both KO and WT. SB-269970: ∅PCP in C57 mice and SD rats

 

IV. Noradrenergic mechanisms

 

Rats

Ballmaier et al. 2001a

SD, M

 

Coapplication of Idazoxan α2 antagonist) + RAC (D2/D3 antagonist)

↓APO, but no additional impact of idazoxan over RAC

 

Sallinen et al. 2007

SD, M; WI, M

PCP

JP-1302 α2C antagonist

↓PCP in both strains

Atipamezole (α2 antagonist, ∅PCP)

V. Cholinergic mechanisms

A. Nicotinic agonists

 

Rats

Cilia et al. 2005

LH, M

IR

Compound A α7-agonist

↑PPI

 

Suemaru et al. 2004

WI, M

APO or PCP

Nicotine

∅PPI, ↓APO (eliminated by mecamylamine, but not hexamethonium), ∅PCP

Methyllycaconitine (α7 antagonist), dihydro-beta-erthoidine (α4β2 antagonist), both ∅PPI, HAL (↓APO, ∅PCP), CLO (↓PCP)

 

Mice

Andreasen et al. 2006

BALB, M; NMRI, M

PCP

Nicotine

↓PCP in BALB mice, ∅PCP in NMRI mice

CLO (similar pattern than nicotine), RIS (∅PCP in either strain)

Spielewoy and Markou 2004

DBA, C3H, C57BL or 129, all M

PCP

Nicotine

∅PPI in all strains, ↓PCP in DBA and C3H (trend), ∅PCP in C57 and 129 mice

 

B. Muscarinic agonists

 

Rats

Jones et al. 2005

SD, M

APO or SCO

Xanomeline M1/M4 muscarinic agonist

↓APO, ↓SCO

BuTAC (M2/4-preferring agonist, ↓APO), oxotremorine, RS86, pilocarpine, milameline,sabcomeline (all muscarinic agonists, all ↓APO), HAL (↓APO, ↓SCO), OLA (↓APO), SCH23390 (∅CLO)

Stanhope et al. 2001

SD, M

APO

Xanomeline

∅PPI, ↓APO

HAL (∅PPI, ↓APO), pilocarpine (↓PPI, ∅APO), MUS (↓PPI), SCO (↓PPI), methyoscopolamine (∅PPI)

C. AChE-inhibitors

 

Rats

Hohnadel et al. 2007

WI, M

APO, DIZ, or SCO

Donepezil

↓APO, ∅DIZ, ↓SCO

Galantamine (↓APO, ↓DIZ, ↓SCO)

Ballmaier et al. 2002

SD, M

Immunolesioning of cholinergic neurons in nucleus basalis

Rivastigmine

↑PPI

 

VI. Histaminergic mechanisms

Roegge et al. 2007

Rats, SD, M

DIZ

Pyrilamine H1 antagonist

↓DIZ

 
 

Mice

Fox et al. 2005

DBA, M

Basal PPI

ABT-239 H3 receptor antagonist

↑PPI

RIS (↑PPI)

Ligneau et al. 2007

Swiss, M

APO

BF2.649 H3 receptor antagonist/inverse agonist

↓APO

 

Browman et al. 2004

DBA, M; C57, M

Basal PPIa,(b)

Thioperamide H3 receptor antagonist/inverse agonist

↑PPI in DBA, ∅PPI in C57 mice

Ciproxifan (↑PPI in DBA and C57 (trend), RIS (↑PPI in both strains)

VII. Cannabinoid mechanisms

A. CB1 antagonists

 

Rats

Ballmaier et al. 2007

SD, M

PCP, DIZ, APO

AM251

↓PCP, ↓DIZ, ↓APO

Rimonabant (↓APO, ↓ DIZ, ↓PCP), CLO (↓PCP)

 

Mice

Malone et al. 2004

Swiss, M

APO

SR 141716

↓APO

 

Nagai et al. 2006

ddY, M

Δ9-THC

SR 141716

↓THC

HAL (↓THC), RIS (↓THC)

B. Endocannabinoid transport inhibitor

Bortolato et al. 2006

Rats, SD, M

Basal PPI

AM404

∅PPI

Win55,212 (∅PPI), APO (↓PPI), DIZ (↓PPI)

C. Cannabidiol

Long et al. 2006

Mice, Swiss, M

DIZ

Non-psychoactive constituent of the Cannabis sativa plant, agonist of the TRP receptor VAN1, inhibitor of anandamide-uptake

↓DIZ, ∅DIZ (if pretreated with TRP agonist capsazepine)

CLO (↓DIZ)

VIII. Neuropeptide mechanisms

A. Neurotensin agonists

 

Rats

Shilling et al. 2004

SD, M

DOI or CIR

NT69L

↓DOI, ↓CIR

PD149163 (NT antagonist, ↓CIR)

Shilling et al. 2003

SD, M

AMP or DIZ

NT69L

↑PPI, ↓AMP, ↓DIZ

 

B. Opioids

Bortolato et al. 2005

Rats, SD, M

U50488 kappa-opioid agonist

Nor-BNI Kappa-opioid antagonist

↓U50488, but ∅APO, ∅DIZ

CLO (↓U50488), HAL (∅U50488)

Ukai and Okuda 2003

Mice, ddY, M

APO

Endomorphin-1 Endogenous mu opioid agonist (ICV-infusion)

∅PPI, ↓APO (antagonized by the mu1 antagonist naloxonazine, but not by ICV-infusion of the mu antagonist β-funaltrexamine)

Naloxonazine (∅APO)

C. CCK

Shilling and Feifel 2002

Rats, SD, M

AMP, DIZ or DOI

SR146131 CCKA antagonist

∅AMP, ↓DIZ, ↓DOI

 

IX. Adenosine

Wardas et al. 2003

Rats, WI, M

PCP

CGS 21680 Adenosine A2 agonist

↓PCP

 

X. GABA agonists

Bortolato et al. 2004

Rats, SD, M

PPI, APO or DIZ

Baclofen

∅PPI, ∅APO,↓DIZ, (prevented by SCH50911)

 

Bortolato et al. 2007

Juvenile mice: DBA, M; C57, M

Basal PPI in DBA (and C57)

Baclofen

↑PPI (prevented by SCH50911) in DBA, ∅PPI in C57 mice

CLO (↑PPI in DBA, ∅PPI in C57), HAL (∅PPI in both strains)

XI. Anticonvulsants/mood stabilizers

 

Rats

Frau et al. 2007

SD, M

Basal PPI, APO or DIZ

Topiramate GABAA agonist, voltage‑gated Na‑channel, AMPA/Kainate blocker

↑PPI, ↓APO, potentiation of HAL (↓APO) and CLO (↓APO) effects, ∅DIZ, attenuation of CLO (↓DIZ)

HAL (↓APO), CLO (↓APO, ↓DIZ)

 

Mice

Brody et al. 2003a, b

129, M; C57, M

AMP, KET

Lamotrigine Na-channel blocker

↓KET in 129 mice, ∅AMP in both strains, ↑PPI in KET and ctrl mice (C57)

 
 

Mice

Ong et al. 2005

129, M; C57, M

AMP or KET

Lithium

∅PPI1,2, ↓AMP1,2, ∅KET1

Carbamazepine (∅PPI, ↓KET, ∅AMP), Phenytoin (↑↓PPI (dose-dependent), ∅KET, ∅AMP), valproate (∅PPI, ∅KET, ∅AMP); all in 129 mice

Umeda et al. 2006

ddY, M

APO or DIZ

Valproate

∅PPI, ↓APO, ∅DIZ

Lithium (∅PPI, ↓APO, DIZ), carbamazepine (∅PPI, ↓APO, ↑DIZ)

XII. Hormones

 

Rats

Czyrak et al. 2003

WI, M

8-OHDPAT

Corticosterone hormone

↓8-OHDPAT (repeated CORT), ∅8-OHDPAT (acute CORT)

Way100,135 (↓8OHDPAT)

Gogos and Van den Buuse 2004

SD, F, OVX

8-OHDPAT

Estrogen (implant, 2 weeks) sex hormone

↓8-OHDPAT, ↓8-OHDPAT (in cotreatment with progesterone)

Progesterone (implant, ∅8-OHDPAT)

Myers et al. 2005

SD, M

PCP

Secretin peptide functional in gut and brain

↓PCP

 

XIII. Second-messenger inhibitors

A. Nitric oxide synthase inhibitors

 

Rats

Salum et al. 2006

WI, M

AMP, APO, BRO, QUI

L-NOARG (two injections)

↓AMP, but ∅APO, ∅BRO, (↓QUI (trend))

SKF38393 (∅PPI-independent of pretreatment with L-NOARG)

 

Mice

Klamer et al. 2005b

Mice deficient of neuronal NOS vs. B6129SF2 (ctrl), M

PCP or DIZ

L-NAME

↓PCP

 

Klamer et al. 2004b

NMRI, M

PCP

N-propyl-arginine

↓PCP

 

B. Guanylate cyclase + nos inhibitors

Klamer et al. 2004a

Mice, NMRI, M

PCP

Methylene blue

↓PCP

 

C. PDE-inhibitors

Kanes et al. 2007

Mice, C57, M

PPI or AMP

Rolipram Phosphodiesterase (PDE)4 inhibitor

↑PPI, ↓AMP

HAL (↑PPI)

XIV. Miscellaneous

 

Rats

Wang et al. 2003a

SD,

Perinatal PCP (3 applications)

M40403 Superoxide Dismustase Mimetic

↓PCP (by both short and long-term treatment with M40403)

 
 

Mice

Palsson et al. 2007

NMRI, M

PCP

l-Lysine (subchronic; l-artinine transport inhibitor)

↓PCP

 

Zhang et al. 2007a

Std:ddy, M

DIZ

Minocycline Second generation antibiotic

↓DIZ

 

AChE acetylcholinesterase, AMP amphetamine, APO apomorphine, ARI aripipazole, BN Brown Norway, BRO bromocriptine, CB cannabinoid receptor, β-CD (2-hdroxypropyl)-beta-cyclodextrin, CIR cirazoline, CLO clozapine, CORT corticosterone, DAAOd-aminoacid oxidase, DA dopamine, DAT dopamine transporter, DIZ dizocilpine, F female, GLU glutamate, GLY glycine, GLYT glycine transporter, HAL haloperidol, ICV intracerebroventricular, IR isolation rearing, KET ketamine, KYNA kynuric acid, LE Long Evans, LH Lister hooded, LSD lysergic acid dyethylamide, M male, MPEP 2-methyl-t-(phenylethnyl)-pyridine, MUS muscarine, NE norepinephrine, NET norepinephrine transporter, nHPC neonatal hippocampus, NOS nitric oxyde synthase, NT neurotensin, OLA olanzapine, OVX ovariectomized, ppm parts per million, PND postnatal day, PP prepulse, QUE quetiapine, QUI quinpirole, RAC raclopride, RIS risperidone, Rx treatment, SCO scopolamine, SD Sprague‑Dawley, SR social rearing, THC tetrahydracannabinol, TRP transient receptor potential channel, V ventral, VAN vanilloid, WI Wistar, WKYs Wistar‑Kyoto, WT wild type, ZIP ziprasidone, ↓XYZ reduction of effect XYZ, ↑XYZ enhancement of effect XYZ, ∅XYZ no change of effect XYZ

Table 3

Model organisms, ca. 2001–2007

I. Low and high baseline PPI levels

II. Sub-strains selected by drug sensitivity

IV. Developmental models

III. Genetically engineered organisms, based on genes

               A. Isolation/Deprivation/Stress-related

related to:

                        1. Isolation rearing

           A. Vulnerability for schizophrenia

                        2. Maternal deprivation

           B. Dopamine

                        3. Developmental stressors

           C. Glutamate

                        4. Immune-related

           D. Noradrenaline

               B. Developmental drug exposure

           E. Histamine

               C. Developmental hypoxia

           F. Catecholamines (general)

               D. Developmental nutritional deprivation

           G. Acetylcholine

               E. Neonatal lesions

           H. GABA

      V. Drug-related models

           I. Second Messenger Systems

               A. Drug withdrawal

           J. Neuropeptides

               B. Toxin exposure

           K. Other

      VI. Other

           L. Models for specific disorders

Superscript designates study-specific findings

References

Species, Strain, Sex

Model description/ background/rationale

Basal PPI

Effects of drugs typically used to induce PPI‑deficits

Effects of (presumed) antipsychotics/other treatments

I. Low and high baseline PPI levels

 

Humans

Bitsios et al. 20051; Swerdlow et al. 2006a2; Vollenweider et al. 20063

M

Basal PPI differences between subgroups (“low vs. high gaters”)

 

∅PER, ∅AMA1 in low gaters ↓PER1, ↓AMA1 in high gaters

QUE (↑PPI2), CLO (↑PPI3), both at short PP intervals and in low gaters; ∅PPI3 in high gaters

 

Rats

Feifel and Priebe 20011; Feifel et al. 20042

BB, M

Basal PPI deficits

↓PPI1,2

 

CLO and PD 149 163 (a neurotensin mimetic; both ↑PPI), but HAL (∅PPI)1,2; subchronic HAL (↑PPI)1

Ferguson and Cada 20041; van den Buuse 20042

SHR vs. SD and WKY, M, F

SHR rats display behavioral abnormalities thought to model clinical symptoms

↓PA1,2, ↓PPI relative to SD and WKY1; ↓PPI relative to SD (trend only)2, but ∅PPI relative to WKY rats2

AMP (↓PPI in SHR and WKY, but ∅PPI in SD rats)2; APO (↓PPI in SD, but ∅PPI in SHR and WKY rats)2; DIZ , 8-OHDPAT (both ↓PPI in SHR, WKY, and SD)2

 

Freudenberg et al. 2007

Former WI, M

Selective breeding of rats with high vs. low PPI

   

Fujiwara et al. 2006

LEC and WI, M

A putative animal model of WD

↓PPI in LEC rats

CU (↓PPI in both LEC and WI rats)

 

II. Sub-strains selected by drug sensitivity

 

Rats

 APO Susceptibility

Sontag et al. 20031; van der Elst et al. 20062, 20073

APO-SUS and APO-UNSUS, M

APO-SUS and APO-UNSUS rats were selectively bred to achieve high (SUS) vs. low APO (UNSUS) susceptibility

↓PPI in APO-SUS vs. APO-UNSUS rats1,3 (not apparent in2)

Sensitivity to the PPI-disruptive effects of COC2 or AMP3 (APO-SUS > APO-UNSUS)2,3

Removal of isolation stress: ↑PPI in APO-SUS, but ↓PPI in APO-UNSUS rats1; REMO (↓AMP in APO-SUS, but ∅AMP in APO-UNSUS)3; aMpT (depleted cytosolic DA, ∅PPI in both strains, ∅AMP in APO-SUS, ↓AMP in APO-UNSUS)3, RES (∅PPI in both strains, ∅AMP in both strains)3; Tests in APO‑SUS only: REMO (∅PPI, ↓COC)2, PRAZ (↑PPI, ↓COC)2, KETS (↑PPI, ∅COC)2, aMpT + RES (↓AMP)3

 Alcohol preference

Bell et al. 20031; Ehlers et al. 20072

F, M

Selective breeding of female rats or selection of male rats with high (P) vs. low (NP) alcohol preference

∅PPI after selective breeding; ↑PPI in P rats2; ↓PPI in P rats housed in isolation2

Adult rats: AMP (↓PPI in P, but ↑PPI in NP rats); Adolescent rats: AMP (↓PPI in P, but ∅PPI in NP rats)

 

III. Genetically engineered organisms, based on genes related to:

 A. Vulnerability for schizophrenia

 

Mice

Clapcote et al. 2007

Missense mutations in exon 2 of the DISC1 gene

DISC1 is a proposed schizophrenia susceptibility gene

↓PPI in mice with missense mutation at residues 31L or 100P

 

CLO, HAL, BUP, Rolipram (PDE4 inhibitor; all ↑PPI; reversal of PPI was dependent on the specific type of missense mutation)

Barr et al. 2007

KO for reelin receptors VLDLR or APOER2, M, F

Reelin is reportedly reduced in brains of schizophrenia patients

∅ acoustic PPI in both KO, ↓ crossmodal PPI in VLDLR mice, ↑crossmodal PPI in APOER2 mice

PPI-disruptive effects of PCP: KO > WT

 

Podhorna and Didriksen 2004

Heterozygous, reeler mutants, M, F

Reeler mice have a mutation in the gene for reelin and have been suggested as an animal model for schizophrenia

↓PPI only in fully adult F (trend only)

  

Boucher et al. 2007

Heterozygous NRG1 KO, M

NRG1 is a proposed schizophrenia susceptibility gene

∅PPI

PPI-disruptive effects of THC: KO > WT

 

Mukai et al. 2004

ZDHH8-KO, M, F

ZDHH8 is a proposed schizophrenia susceptibility gene

↓PPI in F, but ∅PPI in M

  

 B. Dopamine

 

DA receptors

 

Mice

Ralph-Williams et al. 2002

D1-KO, or D2-KO, M, F

 

∅PPI in D1-KO, but ↓PPI in D2-KO

APO, SKF82958 (both ∅PPI in D1-KO, but ↓PPI in WT; ↓PPI in D2-KO and WT); AMP (↓PPI in D1-KO and WT, ∅PPI in D2-KO, but ↓PPI in WT); DIZ (↓PPI in D1-KO, D2-KO, and WT)

 

Holmes et al. 2001

DA D5 null mutants, M, F

 

∅PPI

SKF 81297 (∅PPI in mutants, but ↓PPI in WT)

 
 

DAT

 

Mice

Barr et al. 20041; Yamashita et al. 20062

DAT-KO, M

Increase dopamine activity has been proposed in schizophrenia

↓PPI1,2

COC, METP (both ↑PPI in KO, but ↓PPI in WT)2

M100907 (5-HT2A antagonist, ↑PPI in KO, but ∅PPI in WT)1; FLX, NSX (a NET inhibitor, both ↑PPI in KO, but ∅PPI in WT)2, CIT (∅PPI in KO and WT)2

Ralph-Williams et al. 2003b

DAT-knock-downs, M, F

 

∅PPI

  
 

Other Dopamine related

Eells et al. 2006

Mice, nuclear receptor Nurr1 null mutants

Nurr1 is important for development of DA neurons; early postnatal isolation

↓PPI after postnatal isolation in Nurr1+/− mice

  

 C. Glutamate

 

NR1

 

Rats

Inada et al. 2003

WI, M

Antisense knock-down of HPC NR1 by HPJ-liposome vector

↓PPI

  
 

Mice

Bickel et al. 20081; Duncan et al. 20042, 2006a3; Moy et al. 20064

TG with reduced expression of NR1, M, F

NMDA receptor signaling may be reduced in schizophrenia. Microtubule stabilization in neurons depends on STOP

↑PA1,2,3,4, ↓PPI1,2,3,4

Sensitivity to PPI-disruptive effects of AMP: TG > WT4

HAL, CLO, RIS (all ↑PPI in both TG and controls)3

Fradley et al. 2005

TG with reduced expression of NR1 or STOP-KO, M, F

 

↓PPI (in both mouse types)

 

CLO (∅PPI in both mouse types)

 

NR2

 

Mice

Boyce-Rustay and Holmes 20061; Spooren et al. 20042

NR2A-KO, M, F

 

∅PPI1,2

Ro 63-1908 (a selective NR2B receptor antagonist,↓PPI)2

 

Takeuchi et al. 2001

NR2A, NR2B, N2C, N2D, or GLURδ2 mutants

NR2A-D are known subunits of the NMDA receptor channel. GLURδ2 is a relatively novel GLU receptor subunit

↑PA in NR2A, B, C and D mutants, ∅PAin GLURδ2, ↑PPI in NR2B and GLURδ2, ∅PPI in NR2A, C and D

  
 

NR3

Brody et al. 2005

Mice NR3A-KO or TG NR3A overexpressors, M, F

 

↑PPI at 3–4 weeks old M, but ∅PPI in FKO; ∅PPI in TG

  
 

AMPA

Wiedholz et al. 2008

Mice, AMPA GLUR1-KO, M, F

The gene encoding GLUR1 lies within a chromosomal region that is associated with schizophrenia

↓PPI

  
 

mGLU

 

Mice

Brody et al. 2003a, b

mGLU1-KO, M

Reduced glutamate function has been proposed in schizophrenia

↓PPI1,2,3

PCP (↓PPI in KO and WT)

RAC (∅PPI in KO and WT), LAM (↑PPI in KO and WT)

Brody and Geyer 2004b1; Brody et al. 2004a2; Lipina et al. 20073

mGLU5-KO, M, F

 

↓PPI

PPI deficit of KO mice could not be mimicked in WT mice with the mGLU5 antagonist MPEP1, no further disruption of PPI by DIZ in KO3

RAC, CLO, LAM (all ∅PPI)2, CX546 and ARIR (positive modulators of AMPA, both ↑PPI (less pronounced with ARIR))3

 

Other glutamate related

 

Mice

Szumlinski et al. 2005

Homer1-KO or Homer2-KO, M, F

Homer proteins interact with mGLU, and modify the morphology of GLU synapses. A SNP in Homer1 was associated with schizophrenia

↓PPI in Homer1-KO, but ∅PPI in Homer2-KO

 

HAL (↑PPI in Homer1-KO)

Tsai et al. 2004

Heterozygous GLYT-KO, M

GLY is a co-agonist at the NMDA-receptor with presumed sub-saturating concentrations at the receptor

∅PPI

Sensitivity to the PPI-disrupting effects of AMP (KO < WT) or DIZ (KO > WT)

 

Wolf et al. 2007

CPB-K vs. Balb, M

CPB-K mice display low levels of NMDA receptors

↑PA, ↓PPI relative to BalbC mice

 

Acute or subchronic CLO (∅PPI)

 D. Noradrenaline

Lahdesmaki et al. 2004

Mice, adrenergic α2A-KO, M, F

Adrenergic α2A receptors modulate transmitter release of DA and 5-HT neurons

↑PPI

AMP (↓PPI in KO, and WT; greater sensitivity to AMP in KO), DEXM (an α2 agonist, ∅PPI, ↓AMP in KO, but not WT)

ATI (an α2 antagonist, ∅PPI, ∅AMP)

 E. Histamine

Dai et al. 2005

Mice, H1-KO, M

Histaminic abnormalities have been implicated in the pathophysiology of schizophrenia

↓PPI in WT, but ∅PPI in KO after IR

 

Sensitization to METH enhanced effects of IR on PPI in WT, but not in KO mice

 F. Cathecholamines (General)

Klejbor et al. 2006

Mice, FGFR1-TG, M, F

FGFR1-TG express a dominant-negative mutant from the catecholaminergic, neuron-specific TH promoter

↑PA, ↓PPI

 

FLUP (a DA antagonist, ↑PPI)

 G. Acethylcholine (ACh)

 

Nicotinic

 

Mice

Bowers et al. 2005

Nicotinic α7-KO, M

Evidence suggests reduced α7 expression in schizophrenia patients

∅PPI

PPI-disruptive effects of EtOH: KO=WT

 

Cui et al. 2003

Nicotinic β3-KO, M, F

β3-subunit of the nACH is highly expressed in DA neurons of the SN and VTA

↓PPI

  
 

Muscarinic

Thomsen et al. 2007

Mice, M5-KO, M, F

The M5 muscarinic ACh receptor has been implicated in susceptibility to schizophrenia

↓PPI

AMP (↓PPI in KO and WT)

CLO (↑PPI in KO, but ∅PPI in WT; ∅AMP in both KO and WT), HAL (↑PPI in KO and WT; ↓APO in both KO and WT)

 H. GABA

 

GABAA

 

Mice

Hauser et al. 2005

GABAA α5 mutants, M, F

The α5 subunit of the GABAA channel is strongly expressed in the HPC

↓PPI

  

Yee et al. 2005

GABAA α3-KO, M, F

The α3-GABAA receptor is the main receptor subtype expressed by GABA-ergic neurons involved in controlling monoaminergic neurons

↓PPI

 

HAL (↑PPI)

 

Other GABA related

 

Mice

Chiu et al. 2005

GAT1-KO, M, F

GAT1-KOs display behavioral abnormalities proposed to model some aspects of psychopathology

↓PPI

  

Heldt et al. 2004

GAD65-KO, M, F

GAD65 is a GABA synthesizing enzyme

↓PPI

 

CLO reversed the PPI deficit of KO

 I. Second messenger systems

 

Mice

Gould et al. 20041; Kelly et al. 20072

TG with a constituitively active Gsα or TG with R(AB), or Gsα x PKA double TG mice, M, F

R(AB) TG express a PKA type inhibitor. G-protein signaling related to the cAMP/PKA pathway may be abnormal in schizophrenia

↓PPI in Gsα TG, but ∅PPI in PKA TG1,2 and Gsα x R(AB) double TG2

 

HAL (↑PPI in Gsα TG, but ∅PPI in R(AB) TG), ROL (↑PPI in Gsα TG)2

Harrison et al. 2003

LAP1, M, F

LAP1 is a G-protein coupled receptor with developmental expression suggesting a role in psychopathology

↓PPI

  

Koh et al. 2008

PLCβ1-KO, M, F

PLCβ1 may be altered in brains of schizophrenia patients

↓PPI

 

HAL (↑PPI in KO, but ∅PPI in WT)

Shum et al. 2005

CaMKIV-KO, M

CaMKIV is thought to be involved in neuroplasticity and aspects emotional behavior

↓PPI (and ↓PA)

  

van den Buuse et al. 2005a

Gzα-KO, M

Gzα is a G-protein of the Gi type and associated with DA D2-receptors

∅PPI

Sensitivity to the PPI disruptive effects of AMP, APO (both: KO > WT) or DIZ (KO = WT)

 

 J. Neuropeptides

 

Neurotensin

 

Rats

Caceda et al. 2005

M

Virally mediated over expression of NT1 in the NAC

∅PPI

↓AMP, ↓DIZ

 
 

Mice

Kinkead et al. 2005

NT null mutants, M, F

NT is proposed to have “endogenous antipsychotic” properties

↑PA, ↓PPI

AMP (∅PPI in mutants, but ↓PPI in WT)

HAL, QUET (both ∅PPI in mutants, but ↑PPI in WT), CLO (↑PPI in mutants and WT), OLA (∅PPI in mutants amd WT)

 

CRF

 

Mice

Dirks et al. 20021, 20032; Groenink et al. 20083

TG CRF1 overexpressors, M

CRF abnormalities may play a role in psychopathology

↓PPI1,2,3

 

CRF1 antagonists (↑PPI in TG, but ∅PPI in WT), GR antagonists (∅PPI in TG and WT), adrenelectomy (∅PPI in TG and WT)3; HAL, CLO, RIS, but not CDP all reduce PPI deficit of TG relative to WT

Risbrough et al. 2004

CRF1-KO, M

 

∅PPI

CRF (↑PPI in KO, but ↓PPI (and ↑PA) in WT)

 
 

Arginine Vasopressin

Egashira et al. 2005

Mice, V1b-KO, M

V1b plays a role in regulation of the physiological response to stress

↑PA, ↓PPI

 

CLO, RIS (both ↑PPI), but HAL (∅PPI)

 

Gastrin

van den Buuse et al. 2005b

Gastrin-KO, M

Gastrin is a peptide hormone. It is also produced in the brain and binds to the CCK receptor. CCK interacts with DA in the brain

∅PPI

Sensitivity to the PPI-disruptive effects of AMP (KO < WT), but for APO, DIZ, 8-OHDPAT (all KO = WT)

 
 

Neurexin

Beglopoulos et al. 2005

Mice, Nxph3-KO, M

Nxph3 is a ligand of synaptic α-neurexins

↑PA, ↓PPI

  
 

PACAP

Tanaka et al. 2006

Mice, Adcyap1-mutants

Adcyap1 mutants lack the gene encoding for PACAP and display marked behavioral abnormalities including hyperlocomotion and jumping behavior

↓PPI

AMP (↑PPI)

HAL (∅PPI)

 K. Other

Wang et al. 2003a, b

Mice, adenosine A2-KO, M

Adenosine may influence PPI by interacting with the DA system of the brain

↓PA, ↓PPI

AMP (∅PPI in KO and WT (slight trend towards ↓PPI in KO, but ↑PPI in WT); DIZ (↓PPI in KO and somewhat more pronounced in WT)

 

Wolinsky et al. 2007

Mice, TA1-KO, M

Trace amines have been implicated in schizophrenia

↓PPI

  
 

Mice

Gogos et al. 20061; van den Buuse et al. 20032

Aro-KO, M, M (castrated), F

Gender differences in psychiatric disease; aromatase converts testosterone into estrogen

∅PPI in M, castrated M, and F1; age-dependent ↓PPI in M, but ∅PPI in F (slight trends only)2

PPI-disruptive effect of 8-OHDPAT (F K0 = F WT; M KO > M WT; enhanced in castrated M WT, but not in KO)1

 

Weil et al. 2006

MT1-KO, M, F

Melatonin has been implicated in psychiatric disease

↓PPI

  
 

Mice

Petitto et al. 2002a

Double deletion of IL2/IL15Rβ-double-KO, M, F

IL2 and IL15 are cytokines that share a common β-receptor subunit, which is essential for intracellular signaling. Expression levels are high in HPC and limbic regions

↓PA, ↓PPI

  

Petitto et al. 2002b

MRL-lpr substrain, M

MRL-lpr mice develop lupus-like autoimmune disease, but also reduced IL2 production. Schizophrenia may involve immune processes of the CNS

∅PPI in pre-disease MRL-lpr, but ↓PPI with evidence of autoimmune disease

  
 

Mice

Irintchev et al. 2004

L1 or CHL1, M, F

The cell-adhesion molecule L1 and its close homologue CHL1 may be linked to schizophrenia

↓PPI

  

Jaworski et al. 2005

TIMP-2-KO or knock-down, M, F

TIMP influence extracellular matrix molecules and may be involved in brain plasticity and possibly brain development

↓PPI in KO when compared to heterozygous, but not knock-down or WT animals

  

Pillai-Nair et al. 2005

NCAM-TG, M, F

NCAM is elevated in brains from schizophrenia patients

↓PPI

 

CLO (↑PPI), HAL (∅PPI)

 

Mice

Brunskill et al. 20051; Erbel-Sieler et al. 20042

Npas1-KO, Npas3-KO, M, F

Npas is a transcription factor highly expressed in developing neuroepithelium

↓PPI in Npas12 and Npas31,2-KO

  

Burne et al. 2005

Vitamin D receptor KO, M, F

Vitamin D contributes to normal brain development.

↓PPI at long PP intervals

  

Cao and Li 2002

Emx1 mutants, M, F

Emx1 is implicated in forebrain development and behavioral processes.

(↓PPI; trend only)

  

McDonald et al. 2001

FGFR3-null mutants, M, F

FGFR may contribute to neuronal growth, angiogenesis, mitagenesis and skeletal development

↓PPI

  

Miyakawa et al. 2003

CN-mutants, M

CN is involved in neurite extension and neuronal plasticity. CN-mutants display behavioral abnormalities

↓PPI

  

Park et al. 2002

CDF‑mutants and Catna2-TG (of CDF mutants)

CDF-mutants show morphological abnormalities in the HPC and cerebellum as well as behavioral abnormalities. Catna2-TG have partially restored CDF regions and normal HPC and cerebellum morphology

↓PPI in CDF-mutants; ∅PPI in Catna2-TG

  

Porras-Garcia et al. 2005

Heterozygous Lurcher mutants, M

Lurcher mutants display a progressive loss of Purkinje neurons

↓PPI

  

Yukawa et al. 2005

STAT6-deficient, M

STAT6 is expressed in the CTX, HPC, striatum (developing brain), and basal forebrain (adults). STAT are signaling molecules that mediate cytokine-related mechanisms

↓PPI

  

 L. Models for specific disorders

 

Fragile X-syndrome

 

Humans + mice

Frankland et al. 20041; Spencer et al. 20062

Human children with FXS, Fmr1-KO, Fmr2, or Fmr1+2 double KO mice, M

Fmr-KO mice are putative animal models of FXS

↓PPI in children with FXS1 and in Fmr1-KO1, but ∅PPI in Fmr1-KO2 and FMR1+2 double KO2

  

Bontekoe et al. 2002

FXR2-KO, M

FXR2 is a homolog of the FMRP protein, which is lacking or mutated in FXS.

↓PPI

  

Chen and Toth 2001

FMR1-KO, M

FMR1-gene encodes the FMRP protein, which is lacking or mutated in FXS.

↑PPI

  
 

Nasu-Hasu-Hikala disease

Kaifu et al. 2003

Mice, DAP12-deficient, M, F

DAP12 deletions lead to the Nasu-Hikala disease

↓PA, ↓PPI

  
 

22q11 deletion syndrome

Paylor et al. 2006

Mice, with chromosomal deletions Df1, 2, 3, 4 or 5, or mutations of genes Tbx1, Gnb1l, or Cdcrel1, M, F

Chromosomal Df1 deletions are a putative animal model of 22q11 deletion syndrome, which is linked to high schizophrenia rates. Df1 deletions were “behaviorally mapped” to mutations of single genes via PPI

↓PPI in mice with deletions of Df1, Df2, Df3 and mutations of TbX1, Gnb1l. ∅PPI in mice with deletions of Df4 or Df5, and mutations of Cdcrel1

  
 

Huntington’s disease

Van Raamsdonk et al. 2005

Mice, YAC128

HD patients have motor-, cognitive- and psychiatric disturbances. YAC128 mice express mutant huntingtin and are a presumed animal model for HD

↓PPI in older mice

  
 

Alzheimer’s disease

 

Mice

Ewers et al. 2006

APP&PS1 double-KO, M, F

AD involves neuropathological changes in the HIP

∅PPI, but correlation between PPI deficits and neuropathological changes

  

McCool et al. 2003

CRND8-TG, M

CRND8-TG show over expression of Swedish/Indiana familial mutations of APP and an age‑dependent increase of amyloid production

↓PPI (small effects)

  

Taniguchi et al. 2005

WILD and N279K mutants, M, F

TAU mutations may play a causal role in forms of dementia and PD. N279K and WILD mutants contain a mutation of the human TAU gene

↓PPI in N279K mutants, ∅PPI in WILD mutants

  

IV. Developmental models

 A. Isolation/deprivation/stress-related

 1. Isolation Rearing

 

Rats

Barr et al. 20061; Cilia et al. 20052; Day-Wilson et al. 20063; Harte et al. 20074; Powell et al. 20025, 20036; Rosa et al. 20057

SD, FLH, M; LE, M; WI, M

IR

↓PPI in M and F, and all strains 1,2,3,4,5,6,7

Water deprivation (∅PPI)5

Iloperidone (broad spectrum DA/5-HT/NE antagonist, maternal dep 3. ∅PPI)1; compound A (α7 agonist, ↑PPI2); DA-depletion with 6-OHDA (↑PPI)6; handling (↑PPI)7

Nunes Mamede Rosa et al. 2005

WI, M

Post-weaning isolation for 10 days

↑PPI (not reversed by resocialization)

  
 

Mice

Dai et al. 20041, 20052; Sakaue et al. 20033; Varty et al. 20064

C57, ddY, 129 and H1-KO, all M

IR

↓PPI in WT mice 1,2,3; ↓PPI (C57 and 129 mice in at least one of the two test sessions)4 ∅PPI in H1-KO2

 

Sensitization to AMP enhanced effects of IR on PPI in WT1,2 but not in H1-KO2, RIS and MKC-242 (a 5HT1a agonist, both ↑PPI)3

 2. Maternal deprivation

 

Rats

Choy and van den Buuse 2007

 

Early stress: MD. Later stress: implantation of CORT pellets

↓PPI (trend only in MD rats)

APO (↓PPI in CTR and rats treated with either MD or CORT, but ∅PPI in rats exposed to MD and CORT); AMP (↓PPI in CTR, but ∅PPI in rats exposed to MD); 8-OHDPAT (↓PPI in all groups)

 

Ellenbroek and Cools 2002

WI, M, nulliparous F

IR, MD, rearing by MD mother

↓PPI in IR rats; ↓PPI in MD rats; ∅PPI in MD+IR rats; ↓PPI in pups reared by a MD mother; ↓PPI in MD pups reared by a non-MD mother

  

Garner et al. 2007

WI, F

Early stress: MD. Later stress: Implantation of CORT pellets

↓PPI in MD rats, ∅PPI in CORT treated rats

  

Husum et al. 2002

WI, M

MD

↓PPI

  

 3. Developmental stressors

 

Rats

Hauser et al. 2006

WI, M, F

Prenatal DEX exposure

↑PPI in M (not replicated in a second study)

  

Koenig et al. 2005

SD, M

Exposure of pregnant females to stressors

↓PPI

  

Burton et al. 20061; Lovic and Fleming 20042

SD, M, F

Exposure of pregnant females to restraint stress or exposure of offspring to AR with or without mechanical stimulation

∅PPI in response to restraint condition1.↓PPI after AR with minimal stimulation1,2, but ∅PPI after AR with maximal stimulation2

  

Iso et al. 2007

Mice, C57, M

Animals were exposed to enriched or impoverished conditions during development

↓PPI in mice continuously kept in impoverished conditions

  

 4. Immune-related

 

Rats

Borrell et al. 20021; Romero et al. 20072

WI, M, F

Prenatal bacterial immune challenge with LPS

↓ acoustic PPI in M rats 1,2, ↓ visual PPI in F rats2

 

HAL, CLO (both ↑PPI in M and F)1; chronic HAL (↑PPI)2

Fortier et al. 2007

SD, M

Prenatal (or postnatal) systemic bacterial (LPS), viral (poly I:C) or local (TUR) immune challenge

LPS (↓PPI at E15-16 and E18-19); poly I:C (∅PPI); TUR (↓PPI at E15-16)

  

Pletnikov et al. 2002

Lewis or Fisher, M

IC-infusion of BDV on PND0

↓PPI in Fisher rats, but ∅PPI in Lewis rats

  
 

Mice

Nyffeler et al. 20061; Ozawa et al. 20062

C57, M, F; Balb, M, F

Prenatal viral (poly I:C) immune challenge

↓PPI in adults, but ∅PPI in Balb juveniles2. Correlation between immunoreactivity for α2 GABAA immunoreactivity in the ventral dentate gyrus and PPI in CTR, but not in immune-challenged C557 mice1

  

Rajakumar et al. 2004

SD, M

IC-injection of antibody against the p75 neurotrophin receptor at PND0 to suppress neurotrophin activity

↓PPI

  

Shi et al. 2003

Balb or C57, M, F

Prenatal systemic immune challenge with influenza or poly I:C virus

↓PPI under both conditions

 

CLO, CHLO (both ↑PPI following challenge with influenza virus)1

 B. Developmental drug exposure

 

Rats

Tan 2003

WI, M, F

Exposure to AMP or vehicle during pregnancy (GD8 to parturition) followed by an acute AMP or vehicle exposure challenge on the day of testing

↓PPI and ↑PA after prenatal AMP treatment

  

Harris et al. 2003

SD, M, F

Neonatal DIZ exposure

↓PPI in F, but ∅PPI in M

  

Rasmussen et al. 2007

SD, M, F

Neonatal PCP or vehicle exposure on PND 7, 9 and 11 followed by a single PCP or vehicle exposure at PND45. Rats were tested at PND32-34 and 1,4 and 6 weeks after the PND45 treatment

∅PPI after neonatal PCP treatment only; transient ↓PPI after neonatal + adolescent PCP; ↑PPI in F, but ∅PPI in M after adolescent PCP only

  

Takahashi et al. 2006

WI, M, F

Daily exposure to PCP over 2 weeks in neonatal vs. adult rats

Persistent ↓PPI after neonatal PCP treatment, in M and F, transient ↓PPI after adult PCP administration in M

  

Wang et al. 2003a

SD

Neonatal PCP or vehicle exposure on PND 7, 9 and 11

↓PPI

 

M40403 (a SOD mimetic, ∅PCP after short term treatment, but ↓PCP after long term treatment)

Slawecki and Ehlers 2005

SD, M

Alcohol exposure during adolescence or adulthood

↑PPI after adolescent exposure, but ∅PPI after adult exposure (↓PA for both groups)

  

Schneider and Koch 20031; Schneider et al. 20052

WI, M

Chronic prepubertal, pubertal, or adult exposure to the CB agonist WIN 55,212-2

↓PPI in prepubertal2 and pubertal1 rats, but ∅PPI in adult1 rats

 

HAL (↑PPI)1,2

Schneider et al. 2006

WI, M

Prenatal valproate exposure

↓PPI

 

Environmental enrichment (↑PPI)

Gizerian et al. 20061; Grobin et al. 20062

SD, M, F

Neonatal ALO administration on PND2 or PND5 or PND1 and PND5

↓PPI at PND 801,2 and 202, but not at PND 402 and 602

 

CLO (↑PPI in the ALO PND2 group; ∅PPI in the PND5 group)1

Watanabe et al. 2004

SD, M

Cytokines have been implicated in the pathophysiology of schizophrenia. Neonatal challenge with the cytokine LIF from PND2 to PND10

↓PPI during and after adolescence

  

Futamura et al. 20031; Sotoyama et al. 20072

SD, M, F

Neonatal perturbation of neurotrophic signaling via EGF administration

↑PA1,2, ↓PPI1,2

Sensitivity to the PPI-disruptive effects of subthreshold APO or QUIN in EGF-treated rats > controls; SKF38393 (∅PPI)2

Subchronic CLO (↑PPI), but subchronic HAL (∅PPI)1

Henck et al. 2001

WI, M, F

Neonatal exposure to supraphysiological doses of the mitogen EGF

↓PPI in F, but ∅PPI in males

  
 

Mice

Thomsen et al. 2007

DBA, C57, C3H, ddyY, M, F

Neonatal EGF administration

↑PA for all strains, ↓PPI in DBA and C57, but ∅PPI in C3H and ddyY mice

  
 

Rats

Elmer et al. 2004

SD, M

Prenatal challenge with antimitotic Ara-C.

↓PA, ↓PPI in post-adolescent rats

APO (∅PPI)

 

Jongen-Relo et al. 20041; Le Pen et al. 20062

WI, F, M; SD, M

Prenatal challenge with antimitotic MAM (at different time points during pregnancy)

↓PPI in M SD rats 2, (↓PPI for specific PP and PND of MAM challenge in WI rats, trend only)1

  

Shishkina et al. 2004

WI, M

Neonatal short-term reduction of brainstem α2 adrenergic receptors via injection of antisense oligonucleotides

↓PPI at PND 34, but ∅PPI at PND 22 and 80

  

Howland et al. 2004a

Rats, LE, M

Neonatal i.p. injections of KA

↓PPI

Sensitivity to the PPI-disruptive effects of APO in KA-treated rats = controls

 

 C. Developmental hypoxia

 

Guinea pigs

Rehn et al. 2004

DH, Dunkin-Hartley, F

Reduction in utero-placental blood flow via unilateral ligation of the uterine artery

↓PPI

  
 

Rats

Tejkalova et al. 2007

WI, M

Hypoxia on PND12 via bilateral carotid arterial occlusion

↓PPI

  

Sandager-Nielsen et al. 2004

SPF-WI, M

Anoxia on PND9

(↓PPI in 1 of 2 experiments only)

AMP (↓PPI to low dose, trend only)

 

Schmitt et al. 2007

SD, M

Repeated mild hypoxia from PND4-8

↓PPI

  

 D. Developmental nutritional deprivation

 

Rats

Burne et al. 2004

SD, M, F

Pre- and postnatal vitamin D deprivation.

↓PPI only after combined pre- and chronic postnatal vitamin D deficiency

  

Palmer et al. 2004

WKY, M, F

Prenatal protein deprivation. Prenatal malnutrition may increase the risk for schizophrenia

↓PPI in F at PND56, but ∅PPI at PND35; ∅PPI in M

  

 E. Neonatal lesions

 

Rats

Daenen et al. 2003

WI, M

Neonatal IA-lesion of the vHPC or AMY

↓PPI in adult rats lesioned at PND7, ∅PPI in adult rats lesioned at PND21

  

Laplante et al. 20051; Powell et al. 2006; Le Pen and Moreau 20022; Le Pen et al. 20032; Rueter et al. 20044; Zhang et al. 20065

SD, M

Neonatal IA-lesion of the vHPC

↓PPI in lesioned post-pubertal rats1,2,3,4,5

OXO (a muscarinic agonist, ∅PPI in lesioned rats, but ↓PPI in non-lesioned rats)1

HAL (∅PPI in lesioned rats and ↓PPI in non-lesioned rats2, but ↑PPI in lesioned rats and ∅PPI in non-lesioned rats)5, CLO and OLA (↑PPI in lesioned rats, ↓PPI in non-lesioned rats)2, RIS2, BIP1 (a muscarinic antagonist), GLY3, and ORG 245983 (a NMDA co-agonist, all ↑PPI in lesioned rats, ∅PPI in non-lesioned rats)3; chronic CLO or RIS (↑PPI); BP 897, AVE 5997, A-437203 (all preferential D3 antagonists, ∅PPI)5

Schneider and Koch 2005

Rats, WI, M

Neonatal IA-lesion of the mPFC. Morphological changes in the mPFC in schizophrenia patients have been reported

↑PPI after neonatal lesion in juvenile rats, but ∅PPI in adult rats

Sensitivity to the PPI-disruptive effects of APO in adults: lesioned > non-lesioned

 

Schwabe et al. 2004

Rats, WI, M

Neonatal or adult IA-lesion of the mPFC

↑PPI in adult rats after neonatal lesion, but ∅PPI after adult lesions

APO (↓PPI)

 

V. Drug-related models

 A. Drug withdrawal

 

Rats

Peleg-Raibstein et al. 2006a1, b2; Tenn et al. 20033

WI, M, SD, M

Withdrawal from repeated, escalating AMP administration schedules (up to 5 mg/kg, 8 mg/kg, or 10 mg/kg). The endogenous DA system of unmedicated schizophrenia patients has been hypothesized to be “sensitized”

∅PPI with up to 5mg/kg AMP in WI1, but ↓PPI in SD3; ↓PPI under all other conditions

  

Wilmouth and Spear 2006

SD, M

Withdrawal from nicotine (7 days of exposure). Withdrawal was induced by mecamylamine after nicotine treatment

↓PPI in adolescents on day 1, but ∅PPI on day 4 of withdrawal. ∅PPI at either day in adults

  

 B. Toxin exposure

 

Rats

Terry et al. 2007

SD, M

Chronic, intermittent exposure to the organophosphate pesticide chlorpyrifos

↓PPI

  

Tadros et al. 2005

WI, M

Repeated injection of the mitochondrial toxin 3-NP leads to selective striatal lesions and behavioral changes linked to HD

↓PPI (↓PA)

 

TAUR (a semi-essential β-amino acid, when administered prior to 3-NP: ↓3-NP)

VI. Other

 

Rats

Pijlman et al. 2003

WI, M

Exposure to physical stress (PS, foot shock) or emotional stress (ES, witness of foot shock to PS rat)

↑PPI in PS, but ∅PPI in ES rats

  
 

Mice

van den Buuse et al. 2004

C57, M

ADX. CORT replacement. Stress is a risk factor in psychiatric disease

∅PPI (for ADX, ADX+CORT)

 

HAL (↑PPI in ADX+CORT and CTRL mice, but ∅PPI in ADX mice)

 

Rats

Byrnes et al. 2007

SD, F postpartum rats

Postpartum female rats

∅PPI

Sensitivity to the PPI-disrupting effects of QUIN: Postpartum rats < controls

 
 

Mice

Tremolizzo et al. 2005

BtC3Fe, M

Hypermethylation may be related to downregulation of Reelin and GAD67 in schizophrenia patients. Methionine exposure for 2 weeks is used as an epigenetic model for schizophrenia

↓PPI

 

Chronic VAL (↓Methionine), acute IMID (↓Methionine)

ACH Acetylcholine (receptor), AD Alzheimer’s disease, ADX adrenalectomy, ALO allopregnanolone, AMA amantadine, AMP amphetamine, aMpT alpha-methyl-para-tyrosine, AMY amygdala, APP amyloid precursor protein, AR artificial rearing, ARIR ariracepam, APO apomorphine, ATI atipamezole, BB Brattleboro, BDV Borna Disease virus, BIP biperiden, BUP bupropion, CaMKIV Calcium–calmodulin-dependent protein kinease IV, CCK cholecystokinin, CB cannabinoid (receptor), CDP chlordiazepoxide, CHLO chlorpromazine, CIT citalopram, CLO clozapine, CNS central nervous system, COC cocaine, CORT corticosterone, CRF corticotropin releasing factor, CTR controls, CU copper, DA dopamine (receptor), DAT dopamine transporter, DEX dexamethasone, DEXM dexmedetomidene, DIZ dizocilpine, E embryonic day, EGF epidermal growth factor, F female, FGFR fibroblast growth factor receptor, Fmr1 fragile X mental retardation 1 gene, FLUP flupenthixol, FLX fluoxetine, FXS Fragile X syndrome, GAD glutamic acid decarboxylase, GAT GABA transporter, GD gestation day, GR glucocorticoid receptor, GLU glutamate, GLY glycine, H histamine (receptor), HAL haloperidol, HD Huntington’s disease, HPC hippocampus, IMID imidazenil, KA kainic acid, KETS ketanserin, KO knock-out, LAM lamotrigine, LAP lysophosphatidic acid receptor, LE Long–Evans rat, LEC Long–Evans Cinnamon rat, LIF leukemia inhibitory factor, LPS lipopolysaccharide, M male, m metabotropic, MAM metholazoxymethanol acetate, MD maternal deprivation/maternally deprived, MT melatonin (receptor), n nicotinic, METH metamphetamine, METP methylphenidate, NAC nucleus accumbens, NBM nucleus basalis magnocellularis, NCAM neural cell adhesion molecule, NET norepinephrine transporter, 3-NP 3-nitropropionic acid, NR NMDA receptor subunit, NRG neuregulin, NSX nisoxetine, NT neurotensin, Nxph neurexophilin, OLA olanzapine, OXO oxotremorine, PA response to pulse alone, PACAP pituitary adenylate-cyclase-activating polypeptide, PD Parkinson’s disease, PND postnatal day, PER pergolide, PLC phospholipase C, poly I:C polyinosinic:polycytidylic acid, PRAZ prazosin, PS1 presinilin1, QUET quetiapine, QUIN quinpirole, RAC raclopride, REMO remoxipride, RIS risperidone, ROL rolipram, ROP ropinirole, SD Sprague–Dawley rat, SHR spontaneously hypertensive rat, SN substantia nigra, SOD superoxide dismutase, STAT signal transducers and activators of transcription, SUS susceptible, TA trace amine (receptor), TAUR taurine, TG transgenic, TH tyrosine hydroxylase, THC tetrahydrocannabinol, TIMP tissue inhibitor of metalloprotease, TUR turpentine, UNSUS unsusceptible, VAL valproate, VTA ventral tegmental area, V1b Vasopressin receptor 1b, WD Wilson’s Disease, WI Wistar rat, WKY Wistar–Kyoto rat, WT wild-type, decreased, increased, unchanged

Table 4

Examples of studies providing anatomically-specific information regarding the neural substrates of PPI, ca. 2001–2007

I. Nucleus accumbens

VI. Dorsomedial thalamus

X. Inferior Colliculus

II. Hippocampus

VII. Habenula

XI. Pedunculopontine nucleus

III. Prefrontal cortex

VIII. Medial septum

XII. Laterodorsal tegmental nucleus

IV. Entorhinal cortex

IX. Nucleus Basalis of Meynert

XIII. Raphe complex

V. Amygdala

XIV. Brainstem

Reference

Rat strain, sex

Brain regions

Manipulation

Effect on PPI

 

I. NAC

 

Adults

Caceda et al. 2005

LE, M

 

Virally mediated increase in NT1 receptor

Blocked AMP & DIZ-induced PPI deficits

Culm et al. 2003

SD, M

 

Infusion of PTX

Blocked QUIN-induced PPI deficit

Culm et al. 2004

SD, M

 

Infusion of Sp-cAMP

Blocked QUIN-induced PPI deficit

Mohr et al. 2007

Mice, C3H, F

 

Infusion of DIH or QUIN

↑ PPI after QUIN, but ∅ PPI after DIH

Nagel et al. 2003

SD, M

 

Infusion of MSX-3 (A2 antagonist)

↓ PPI

Pothuizen et al. 2005

WI, M

Core, shell

Infusion of muscimol

Loss of PP intensity dependency after infusion into NAC core but not shell

Pothuizen et al. 2006

WI, M

Core

NMDA-lesion of the NAC core

enhanced PPI disruption by DIZ but not APO

Powell et al. 2003

LE, F

 

Intra-NAC 6-OHDA in SR & IR rats

blocked ↓ in PPI in IR rats

Schwienbacher et al. 2002

SD, M

+ VTA

Infusion of DAergic, adenosinergic, or GABAergic compounds into NAC and/or VTA

↑ PPI after combined VTA PTX + NAC SCH23390

Swerdlow et al. 2006d

SD, LE and F1 (SDxLE), M

+ Striatum

Measured DA-stimulated [35S]GTPγS-binding in NAC, striatum

PPI-APO sensitivity: SD > F1 > LE. [35S]GTPγS-binding in NAC, striatum: LE > F1 > SD

 

II. HPC

 

Adults

Ellenbroek et al. 2002b

WI, M

CA1

Infusion of AMP, SKF81297 or QUIN

↓ PPI after AMP, SKF81297 or QUIN; AMP-induced PPI deficits blocked by intra-NAC SCH23390 but not sulpiride

Ma and Leung 2004

LE, M

CA1

Electrical kindling

↓ PPI (and ↓ PA)

Finamore et al. 2001

Rats

 

Infusion of KA or NMDA antagonists

↓ PPI with infusion of NMDA antagonists

Fitting et al. 2006a

SD, M

 

Infusion of viral toxin TAT

↑ PPI (and ↓ PA)

Inada et al. 2003

WI, M

 

Antisense NR1 knockdown

↓ PPI with knockdown 6, but not 14d pre-testing

 

Neonates

Fitting et al. 2006c

SD, M, F

 

Neonatal infusion of viral toxin gp120

↓ PPI (and ↑ PA); + Vehicle: ↓ PPI with increasing gp120 doses. + APO: ↑ PPI with increasing gp120 doses

Fitting et al. 2006b

SD, M, F

 

Neonatal TAT infusion

Males: ↓ PPI at d 30 and 60, but not d 90

 

vHPC

 

Adults

Howland et al. 2004b

LE, M

+ dHPC

Electrical stimulation VHPC vs. DHPC combined with NAC microdialysis

↓ PPI after VHPC but not DHPC stim.; ↑DA efflux: ipsi- but not contralateral NAC after unilateral stim. VHPC but not DHPC

Klamer et al. 2005b

SD, M

 

Microdialysis of the VHPC after systemic (or local) PCP

↓ PPI and ↑ cAMP after PCP; blocked by NO-synthase inhibitor L-NAME

Kusljic and van den Buuse 2004

SD, M

+ dHPC

5,7-DHT lesion

↓ PPI for DHPC lesioned rats, and partially for VHPC lesioned rats

Zhang et al. 2002a

WI, M

+ dHPC

Infusion of NMDA

↓ PPI after intra-VHPC but not -DHPC infusion

Swerdlow et al. 2004b

SD, M

+ FX

Infusion of NMDA into the VHPC in rats with EL lesions of the FX

↓ PPI after NMDA infusion into VHPC, unaffected by FX lesion; IA lesion of the VHPC but not EL FX lesion enhanced ↓PPI by APO

 

Neonates

Laplante et al. 2005

SD, M

 

IA-neonatal lesion

↓ PPI; blocked by biperiden

Zhang et al. 2002b

WI, M

+ dHPC

Muscimol or TTX infusion

↓ PPI, not blocked by HAL or CLO

Risterucci et al. 2005

SD, M

 

IA-neonatal lesion

↓ PPI, ↓ blood flow in NAC, BLA,VP, BNST, entorhinal–piriform and orbital CTX

 

Adults

Caine et al. 2001

LH, M

dSUB or vSUB

QA‑lesions

↓ PPI after vSUB lesions. ↓ PPI to AMP (not APO) after vSUB lesions.

 

III. PFC

 

Adults

de Jong and van den Buuse 2006

SD, M

 

Infusion of SCH23390

enhanced PPI deficits to APO but not DIZ

 

Neonates

Grobin et al. 2006

M, F

+ MD

Neonatal elevation of allopregnanolone

↓ PPI in castrates before and after puberty (PD20 and 80), but ∅ PPI during puberty (PD40 and 60)

Rajakumar et al. 2004

SD, M

 

Neonatal infusion of antibody to the p75 neurtrophin receptor

↓ PPI at age 10 wks, but not 5 wks

 

mPFC

 

Adults

Afonso et al. 2007

SD, F

 

NMDA-lesion

↓ PPI

Bast et al. 2001

WI, M

 

Infusion of NMDA

↓ PPI, not blocked by HAL or CLO

Day-Wilson et al. 2006

LH, M

 

IR (associated with ↓mPFC volume)

↓ PPI

Schwabe and Koch 2004

WI, M

 

IA-lesion

lesion blocked DIZ-induced ↓ PPI but not APO-induced ↓ PPI

Shoemaker et al. 2005

SD, M

 

Infusion of SCH23390 into the mPFC; infusion of NMDA into the VHPC in rats with IA mPFC lesion

↓ PPI after infusion of SCH23390 in mPFC; mPFC lesions block ↓ PPI after intra-VHPC NMDA infusion

Swerdlow et al. 2006c

SD, M

+ NAC

Systemic SCH23390, IA lesion of mPFC, 6-OHDA DA depletion of mPFC or NAC

↓ PPI after SCH23390, not blocked by either NAC DA depletion or mPFC lesion; ↓ PPI after mPFC DA depletion

 

Neonates

Schneider and Koch 2005

WI, M

 

IA-neonatal lesion

↑ PPI in juveniles; enhanced PPI deficits to APO in adults

Schwabe et al. 2004

WI, M

 

IA-neonatal lesion

↑ PPI after neonatal lesions; ↓ PPI in both lesioned and intact rats after APO

 

IV. eCTX

 

Adults

Goto et al. 2002

WI, M

 

IA‑lesion

↓ PPI, partially blocked by HAL

Goto et al. 2004

WI, M

+ NAC

eCTX lesion with IA, microdialysis of NAC

↓ PPI, ↑ DA concentration in NAC

Uehara et al. 2007

WI, M

+ mPFC

eCTX lesion with QA, mPFC lidocaine infusion

↓ PPI after eCTX lesion or mPFC lidocaine

 

V. AMY

 

Neonatal

Daenen et al. 2003

F1 of WI/UWU, M

AMY (or vHPC)

Neonatal AMY or VHPC lesions with IA

↓ PPI in rats lesioned in the AMY or VHPC on d 7, but not on d 21

 

BLA

 

Adults

Howland et al. 2007

LE, M

+ eCTX, + vHPC

Electrical kindling

↓ PPI shortly after kindling of BLA, but not of eCTX or VHPC

Kusljic and van den Buuse 2006

SD, M

+ CnA

5,7-DHT lesion

↓ PPI with lesions of CnA but not BLA

Shoemaker et al. 2003

SD, M

 

QA lesion of the BLA

↓ PPI, blocked by quetiapine

Stevenson and Gratton 2004

LE, M

+ Striatum

Infusion of SCH23390 or raclopride

↑ PPI after intra-BLA SCH23390, ↓ PPI after intra-BLA raclopride

 

VI. MD

 

Adults

Swerdlow et al. 2002c

SD, M

 

Infusion of QUIN or TTX

↓ PPI after TTX but not QUIN, not blocked by quetiapine

 

VII. Habenula

 

Adults

Heldt and Ressler 2006

Mice, C57, M

 

Electrolytic lesion

∅ PPI in the absence of stress; but ↓ PPI after stress in habenula lesioned rats; blocked by CLO

 

VIII. mS

 

Adults

Ma and Leung 2007

LE, M

+ SUM

Infusion of muscimol

Muscimol into mS or SUM blocked ketamine- or DIZ-induced PPI deficits

Ma et al. 2004

LE, M

 

Infusion of muscimol

Infusion of muscimol into mS blocked PCP-induced PPI deficits

 

IX. NBM

Ballmaier et al. 2002

SD, M

 

Immunolesion of cholinergic NBM neurons

↓ PPI, blocked by single or repeated admin. of rivastigmine

 

X. IC

 

Adults

Silva et al. 2005

LE, M

 

Electrical stimulation

↓ PPI

Sandner et al. 2002

SD, M

+ PnC

Evoked potentials from IC or PnC

↓ PPI by ketamine and ↑ evoked potentials

Yeomans et al. 2006

WI, M

SC, + intercollicular nuc. or PPTg

Electrical PP and pulses via electrodes to the SC, IC, intercollicular nucleus, or PPTg

PPI after electrical PP to most SC sites. Longer PPI latencies for electrical PP to the SC than IC, intercollicular nuc. or PPTg

 

XI. PPTg

 

Adults

Diederich and Koch 2005

WI, M

 

Infusion of muscimol

↓ PPI at intervals ≥ 120 ms

Takahashi et al. 2007

Mice, ICR, M

+ lGP, ssCTX

Infusion of phaclofen into the PPTg or lidocain into the lGP, c-fos labeling of brain regions after acoustic pulses or prepulses

↓ PPI after intra-PPTg phaclofen or intra-lGP lidocaine; ↑c-fos in lGP after prepulses; ↑c-fos in NAC shell, PnC, and ssCTX after pulses, blocked in NAC and PnC by prepulses

 

XII. LDTN, SN

 

Adults

Jones and Shannon 2004

SD, M

 

IA-lesion of the LDTN or SN

↓ PPI after lesion of LDTN but not SN

 

XIII. DRN or MRN

 

Adults

Kusljic et al. 2006

SD, M

 

5,7-DHT lesion

↓ PPI in MRN but not DRN lesioned rats, blocked by HAL or CLO

Kusljic et al. 2003

SD, M

 

5,7-DHT lesion

↓ PPI at all PP intensities for MRN-lesioned rats and for some PP intensities for DRN lesioned rats

 

XIV. Brainstem

 

Neonates

Shishkina et al. 2004

WI, M

 

Neonatal infusion of antisense oligonucleotide complementary to the α2 adrenoceptor

↓ PPI at PD34, associated with ↑α2 adrenoceptors in HPC, AMY

AMP Amphetamine, AMY amygdala, APO apomorphine, BG background, BLA basolateral amygdala, BNST bed nucleus of the stria terminalis, C57 C57BL/6J, CLO clozapine, CnA central nucleus of the amygdala, CPA N(6)-cyclopentanyladenosine, CTX cortex, d dorsal, 5,7-DHT 5,7 dihydroxytryptamine, DIH dihydrexidine, DIZ dizocilpine, DRN dorsal raphe nucleus, e entorhinal, EL electrolytic, F females, FX fornix, HAL haloperdidol, HPC hippocampus, IA ibotenic acid, IC inferior colliculus, IR isolation rearing, KA kainic acid, l lateral, LDTN laterodorsal tegmental nucleus, LE Long Evans, LH Lister Hooded, M males, m medial, MD dorsomedial thalamus, MET methamphetamine, MRN median raphe nucleus, NAC nucleus accumbens, NBM nucleus basalis of Meynert, NMDA N-methyl-d-aspartate, NO nitric oxide, OVX ovariectomized, NT neurotensin, 6-OHDA 6-hydroxydopamine, PD postnatal day, PA pulse alone trial, PCP phencyclidine, PFC prefrontal cortex, PnC nucleus reticularis pontis caudalis, PPI prepulse inhibition, PPTg pendunculopontine nucleus, PTX pertussis toxin, QA quinolinic acid, QUIN quinpirole, S septum, SD Sprague–Dawley, SC superior colliculus, SN substantia nigra, Sp-cAMP cyclic adenosine monophosphate analogue, SR socially reared, ss somatosensory, SUB subiculum, SUM supramamillary area, v ventral, VP ventral pallidum, VTA ventral tegmental area, WI Wistar, decreased, increased, unchanged

This quantitative physiological abnormality in schizophrenia patients, conceptually linked to an intuitive clinical construct and neurochemical, anatomical, developmental, and genetic substrates, has provided a powerful focus for scientific developments. With the rapid expansion and broad application of variations of PPI measures, new expectations for its use to inform us about the biology of schizophrenia have at times outpaced critical thinking and falsifiable hypotheses about the relative strengths vs limitations of these complex studies. Here, we hope to enumerate some of these expectations and the future promises and potential limitations of PPI studies.

Human studies: What can our field realistically expect to learn about schizophrenia based on studies of PPI in humans?

Diagnosis

As an isolated measure, PPI is not a “diagnostic instrument”. There is substantial variability and significant overlap in PPI distributions among normal and disordered populations. In addition, there are many different disorders in which affected individuals are characterized by reduced PPI, on average, compared to a normal comparison population (cf. Braff et al. 2001b). The reason for the “non-pathognomonic” nature of PPI deficits is simple: the amount of PPI exhibited by any organism at any given moment reflects activity at many different levels of integrated cortico–striato–pallido–thalamic (CSPT) circuitry and its output via the pontine tegmentum. Low levels of PPI can result from normal variations at several levels of this circuitry; alternatively, disease processes can impact different levels of this circuit, with synergistic effects on pontine activity that mediates PPI. Conceivably, disease processes might even impact this circuitry in such a way as to bias it towards elevated levels of PPI, and compensatory or allostatic changes within feedback or downstream elements of the circuitry might offset the effects of otherwise PPI-disruptive disease processes. Thus, absolute levels of PPI—either low or high—are neither diagnostically nor neurophysiologically specific.

A corollary of this fact—that PPI is not “diagnostic”—is that no simple qualitative value of “normal” or “deficient” can accurately be applied to any particular level of PPI, particularly among clinically normal individuals. It is common in the literature (including our own reports) to describe relatively low levels of PPI as “deficient”, “impaired”, or “poor”. In fact, we know of no clear adaptive or functional advantage of higher vs. lower levels of PPI among clinically normal individuals. Perhaps, this idea is most easily conveyed in the comparison between clinically normal men and women: on average, under specific stimulus conditions (e.g., 20 ms white noise prepulses, 10 dB over a 70-dB(A) white nose background, 100 ms before a 115-dB(A) 40 white noise pulse), men exhibit more PPI than do women (Swerdlow et al. 1993b, 2006f; Kumari et al. 2004; Aasen et al. 2005). Furthermore, there is some evidence that among normal women, PPI shifts across the menstrual cycle (Swerdlow et al. 1997; Jovanovic et al. 2004). Clearly, there is no basis for describing PPI in women vs. men as “deficient”, nor for describing luteal- vs. follicular-phase PPI as “impaired”. Similarly, drugs that increase PPI in normals cannot be accurately claimed to “improve” PPI.

At a more basic level, at any given moment in time, individuals are not characterized by a single “PPI” value, in the same manner in which they might be characterized by other quantitative traits such as height, Q–T interval, or fasting glucose level. One of PPI’s strengths as an experimental measure is its exquisite sensitivity to stimulus parameters and test conditions [as described for the startle reflex by Davis 1984]. The inhibition generated by prepulses under different stimulus conditions likely reflects different underlying physiological substrates. Thus, under a variety of test/stimulus conditions, the same clinical population might conceivably exhibit PPI levels that are reduced, equal to, or elevated, compared to normal comparison subjects. An instructive example from preclinical studies of PPI is found in the report that inbred Brown Norway (BN) rats exhibit “deficient” PPI compared to outbred Sprague Dawley (SD) rats, based on measurements with 100 ms prepulse intervals (Palmer et al. 2000). Subsequent studies reproduced this finding, but also demonstrated that at shorter prepulse intervals, the opposite relationship existed: BN rats exhibited significantly more PPI compared to SD rats (Swerdlow et al. 2006a, 2008). Thus, depending on the stimulus parameters, populations can exhibit either relatively reduced or excessive PPI.

PPI is also highly sensitive to state variables and influences, such as medications (Table 1), cigarette smoking (Table 1), fatigue (van der Linden et al. 2006), stress (Grillon et al. 1998), and hormonal status (Swerdlow et al. 1997; Jovanovic et al. 2004). While some of these variables and influences can be controlled under experimental conditions, the notion of using such a sensitive measure in isolation as a diagnostic tool is not realistic. This being said, one potentially valuable strategy in the characterization of clinical populations is the use of PPI in combination with multiple other measures of forebrain inhibitory function, such as P50 event-related potential (ERP) suppression (“P50 gating”; Adler et al. 1982) and antisaccade deficits (Radant et al. 2007), to identify multiple measures and patterns of normal vs. deficient function (Cadenhead et al. 2002; Braff et al. 2008; Sugar et al. 2007). PPI and P50 gating are both deficient but correlate weakly, if at all, in schizophrenia patients (Braff et al. 2007b); similarly, PPI and antisaccade performance are both deficient but do not correlate significantly in schizophrenia patients (Kumari et al. 2005b). Thus, these measures apparently assess forebrain inhibitory processes that are dissociable and nonredundant. More importantly, there are patients who exhibit normal levels of some but not other gating measures (and presumably normal function within brain circuitry regulating some but not other measures), and subpopulations of patients who exhibit different profiles in these deficits (Kumari et al. 2005b; Swerdlow et al. 2006f; Braff et al. 2007b). These subpopulations may reflect different patterns of brain dysfunction and conceivably distinct genetic substrates and treatment sensitivities (Braff et al. 2007a).

Symptoms, course, and outcome

Can we predict the clinical course or even clinical features of schizophrenia based on PPI levels? There is no compelling data to suggest that among schizophrenia patients, levels of PPI predict clinical course, nor are there consistent robust relationships between lower levels of PPI and higher levels of specific symptoms of schizophrenia, or cumulative positive or negative symptoms scores (Table 1). Certainly, there is much interest in determining whether, with repeated or longitudinal measures, a change in PPI predicts or accompanies clinical deterioration or improvement, including the prediction of illness onset in prodromal subjects (Cadenhead 2002; Addington et al. 2007; Cannon et al. 2008). Very few studies have collected longitudinal measures of PPI in schizophrenia populations with adequate sample size and duration to be informative, although some are in progress. One might predict a relationship between PPI and psychosis in extreme conditions, such as the shift from euthymic to manic bipolar disorder, but even in this case, studies have been limited to cross-sectional comparisons, and results across studies have not been consistent (Perry et al. 2001; Rich et al. 2005; Barrett et al. 2005; Carroll et al. 2007). Duncan et al. (2006a, b) did detect an association between lower levels of PPI, and greater levels of psychotic symptoms and psychological discomfort among unmedicated schizophrenia patients.

Interestingly, while robust relationships between PPI and the most common clinical indices of schizophrenia have been hard to detect, reports have identified significant correlations between PPI and a number of relatively complex clinical measures, ranging from quantitative Rorschach ink blot indices of thought disturbance (Perry and Braff 1994) to scales of distractibility and attention (Karper et al. 1996). One report (Swerdlow et al. 2006f) identified a significant positive correlation between PPI and global functioning levels (GAF score) in schizophrenia patients, but this relationship was evident only among male patients, and the correlation—while highly significant (p < 0.005)—accounted for a relatively modest amount of the total PPI variance. In addition, PPI levels were associated with levels of independent living, also perhaps reflecting its relationship to global functioning. As a result, more sophisticated and sensitive analyses of PPI, related gating measures, and function in schizophrenia patients are being pursued (Light et al. 2007a; Braff et al. 2007a). Studies have detected modest but statistically significant relationships between PPI and measures of executive function in some patient groups [e.g., children with 22q11DS (Sobin et al. 2005a, b)]. A preliminary qualitative article by Butler et al. (1991) noted a nonsignificant trend toward greater tactile (but not acoustic) PPI among six (predominantly male) patients with schizophrenia and low levels of Wisconsin Card Sorting Test perseverative responses than among nine (predominantly female) patients distinguished by high levels of Wisconsin Card Sorting Test (WCST) perseverative responses. Kumari et al. (2007a) recently reported a significant (p < 0.03) correlation between tactile PPI and WCST perseverative responses in male schizophrenia patients. Significant positive relationships between acoustic PPI and working memory as well as other formal indices of neurocognitive function have been detected among clinically normal individuals (Bitsios et al. 2006; Light et al. 2007b, 2008; Csomor et al. 2008), although no such relationships have been reported for schizophrenia patients.

The relative insensitivity of PPI to clinical state speaks of the importance of trait features of this measure, which may reflect more “hard-wired” anatomical and genetic determinants. The fact that some relationships can be detected between PPI and relatively global measures of function in schizophrenia patients, but not between PPI and clinical state per se, is consistent with the hypothesis that the causal link between genes and functional outcome in schizophrenia reflects the impact of forebrain circuits that regulate basic gating mechanisms, more than those that control the expression of specific symptom states (Light et al. 2004; Braff and Light 2004; Light and Braff 2005). Thus, while diagnosis in schizophrenia will remain symptom-based for the foreseeable future, it could be argued that studies of the biology of schizophrenia and its relationship to functional outcome may be best advanced through quantitative measures of forebrain inhibitory function such as PPI.

Treatment

As PPI deficits in schizophrenia reflect dysfunction in forebrain circuitry and are linked to both cognitive and functional deficits in schizophrenia patients, can PPI or its potentiation by drugs in patients be used to predict individualized treatment for this disorder? Certainly, in terms of preclinical predictive models, PPI has been quite powerful, as discussed below. In schizophrenia patients, cross-sectional data and some longitudinal findings demonstrate that antipsychotic treatment is associated with elevated (i.e., “normalized”) PPI and that this association is most robust with atypical antipsychotics as a class, compared to first generation antipsychotics (Table 1). Of course, interpreting medication effects in most of these reports is difficult because patients are uniformly being treated with complex multidrug regimens across a range of doses, and medication compliance is known to be poor among schizophrenia outpatients (Lieberman et al. 2005). A recent controlled study with a multidrug cross-over design detected PPI-increasing effects of olanzapine (but not risperidone or haloperidol) in chronically ill schizophrenia patients (Wynn et al. 2007). Findings of PPI-increasing effects of both quetiapine and clozapine in clinically normal, “low-gating” subjects suggests that the PPI-increasing effects of these drugs in schizophrenia patients may not reflect disorder-specific processes (Swerdlow et al. 2006a; Vollenweider et al. 2006). We do not know if the PPI-enhancing effects of these drugs, and conceivably some of their clinical benefit, may reflect their ability to optimize function within spared (intact) gating mechanisms, rather than their ability to correct or normalize activity within dysfunctional mechanisms.

Still, it is reasonable to ask whether the ability of drugs to normalize PPI in patients, or to increase PPI in “low-gating” normals, might reflect their impact on brain processes and resulting cognitive abilities that ultimately would have clinical utility and perhaps cognitive-enhancing effects in schizophrenia. While clinically effective antipsychotics (particularly atypical antipsychotics) are associated with increased PPI in patients and low-gating normals (Table 1), PPI is also increased in non-patients by ketamine and methylenedioxymethamphetamine (MDMA; discussed below; Duncan et al. 2001; Abel et al. 2003; Vollenweider et al. 1999), neither of which would be on anyone’s list of likely antipsychotic agents. Nicotine is associated with increased PPI in schizophrenia patients (Kumari et al. 2001; Swerdlow et al. 2006f), but despite the hypothesis that smoking reflects a form of “self-medication” in schizophrenia patients, there is no clear evidence for either antipsychotic or cognitive-enhancing effects of nicotine in these patients. While there is an active quest by many groups to develop cognitively enhancing nicotinic receptor-specific agonists, based on the putative relationship between the alpha-7 nicotinic receptor subtype and schizophrenia (Freedman et al. 1997), there is presently no evidence that such compounds either increase PPI or enhance cognition in patients. Thus, screening compounds as effective antipsychotics based on their PPI-enhancing effects in clinical or special populations is likely to yield both true and false positives. At this point, there is an inferential, but not empirical, basis for using PPI enhancement as a basis for predicting the ability of a compound to enhance cognition and real-world daily functioning in schizophrenia. Clearly, this is an area of active investigation, and such empirical evidence might emerge based on these efforts.

A reliable, robust quantitative phenotype

While the realistic expectations for PPI as a clinically useful biomarker may be somewhat limited, it is very realistic to expect that PPI will continue to be a valuable tool for investigating brain functions relevant to several neuropsychiatric disorders, including schizophrenia. The many strengths of PPI as an experimental measure have been reviewed elsewhere (Braff et al. 2001b), and none of the realistic limitations described above detract from its attributes as an objective, quantifiable, reliable, robust, neurochemically and parametrically sensitive cross-species measure of a neurobiologically important process. Nonetheless, even in its use as an investigative experimental tool in humans, there should be a realistic assessment of what we can and cannot expect from PPI.

Two types of studies speak strongly to the general reliability of this quantitative phenotype. First, test–retest reliability has been established for PPI in normal comparison subjects (NCS), across days (Abel et al. 1998; Swerdlow et al. 2001c; Flaten 2002), weeks, and months (Cadenhead et al. 1999; Ludewig et al. 2002). More recently, 1-year retest data collected in 68 schizophrenia patients yielded intra-class correlations of 0.75 (30 ms)–0.89 (120 ms; Light et al. 2007a), suggesting a very high stability of this phenotype in patients. Second, a multisite study of PPI in NCS was conducted, using carefully standardized equipment, test methods, and inclusion/exclusion criteria. No significant differences in PPI were detected across seven geographically dispersed test sites, despite some modest methodological drift that was detected via rigorous quality assurance efforts (Swerdlow et al. 2007). Thus, within individuals, and across test samples, PPI appears to be a reliable phenotype.

While PPI is a reliable phenotype, at least among NCS, it is not reasonable to expect that every schizophrenia patient will exhibit a “deficient-PPI” phenotype. In fact, as noted above, there is no way to test this possibility because there is no absolute value that defines “deficient” PPI. Under commonly used test conditions, there is substantial overlap in the distribution of PPI values, between schizophrenia patients and community comparison subjects (cf. Braff et al. 2001b). Clearly, there are schizophrenia patients who have higher levels of PPI compared to many NCS. The overlapping group distributions with this measure likely reflect the many influences on PPI, other than schizophrenia-related pathology, such as sex, hormonal status, smoking, withdrawal from caffeine or nicotine, fatigue, and medications. There are also normal interindividual differences in activity within brain circuitry (e.g., in the pallidum, pons, or cerebellum) that regulates PPI, but is not primarily involved in schizophrenia. With typical testing parameters, NCS vs. unmedicated patients or patients receiving only typical antipsychotics, group separation in mean percent PPI might be reasonably expected to reach 1 SD (e.g., Kumari et al. 1999; Ludewig et al. 2003; Swerdlow et al. 2006f), which corresponds to 55% nonoverlap. However, when patients taking atypical antipsychotics are included, group separation drops dramatically, to about 0.3 SD (e.g. Swerdlow et al. 2006f)—or 21% nonoverlap. This latter fact is particularly important, given that upwards of 90% of schizophrenia patients in most current open-enrollment studies report taking atypical antipsychotic medications [although true compliance is likely lower (Dolder et al. 2002; Lacro et al. 2002)].

In addition to medication status, studies have reported many other variables in patient selection that influence group separation in comparisons of schizophrenia patients vs. NCS. One issue that may ultimately impact the utility of PPI as a quantitative phenotype is its potential sensitivity to ascertainment bias. As noted above, PPI correlates positively with global function in schizophrenia patients. Thus, on average, studies of lower functioning patients will detect greater separation vs. NCS, and those of higher functioning patients will detect less group separation. For this reason, investigators are considering the impact of study designs that select for higher- vs. lower-functioning schizophrenia patients, such as those that require a proband within an intact family structure (and who thus may be relatively higher functioning) vs. those utilizing patients without intact families, who are often homeless or medically indigent (Calkins et al. 2007).

Perhaps equally important as the selection of patients is the selection of NCS. Comparison samples differ substantially across studies and can range from generally healthy, young college students, to “professional controls”, who are often low-functioning and unemployed, beyond their activities as test subjects in biomedical research. The latter group is more likely to have histories of disorders that are associated with reduced PPI, such as anxiety disorders (OCD, panic disorder or post-traumatic stress disorder) or “cluster A” personality disorders; they may also be more likely to carry vulnerability genes for neuropsychiatric disorders, take psychotropic medications that influence PPI, and have histories of substance use or brain trauma that might impact PPI-regulatory brain circuitry. Much has been written about the considerations in selecting a “matched”, “representative”, “normal” or “supernormal” comparison group in biomedical research (e.g., Roy et al. 1997; Calkins et al. 2004), and without belaboring this point, these same considerations apply to studies of PPI and may greatly impact group separation in comparisons of control vs. schizophrenia populations.

As reviewed in Braff et al. (2001b) and elsewhere, the amount of separation between schizophrenia and NCS populations in PPI is highly dependent on testing conditions, and specifically, on stimulus parameters. Thus, if all else is equal, schizophrenia-linked PPI deficits are most pronounced under conditions in which prepulse salience, often based on its intensity over background, is within a “dynamic range”: not too high, but not too low. For example, most studies find this “sweet spot” of maximal schizophrenia vs. NCS separation using discrete white noise prepulses 8–16 dB over a 70-dB(A) background, with about 60 ms prepulse intervals [or stimulus onset asynchronies (SOAs; Table 1)]. Some studies failing to detect PPI deficits in schizophrenia samples have used prepulses in the absence of a background white noise, effectively creating very large prepulse intensities of 25–40 dB(A; Hazlett et al. 2003, Wynn et al. 2004, 2005). In addition to prepulse intensity relative to background, prepulse frequency (e.g., tone vs. white noise), duration (discrete vs. continuous) and other variables (including the use of binaural vs. mono-aural stimuli) may contribute to maximizing the group separation in PPI between schizophrenia and NCS populations (Braff et al. 2001a; Hsieh et al. 2006; Kumari et al. 2005b, 2007b).

As noted above, the temporal “sweet spot” for detecting automatic (uninstructed) PPI deficits in schizophrenia patients appears to occur with prepulse intervals between 30 and 240 ms, depending somewhat on other stimulus characteristics. The temporal range around 60 ms appears to be most sensitive in several studies (Braff et al. 1978, 1992, 2005; Weike et al. 2000; Leumann et al. 2002; Swerdlow et al. 2006f) and may be the range in which PPI deficits are most resistant to normalization by antipsychotic medications. Interestingly, this interval sits at the juncture between preconscious and conscious information processing, based on perceptual detection thresholds (Libet et al. 1979; Kanabus et al. 2002). The possibility that PPI in this temporal range may be most deficient in schizophrenia suggests that automatic inhibitory mechanisms may be most “porous” at a critical barrier between preconscious processing and conscious awareness. While clearly a point for more systematic analysis, such a notion suggests a biological mechanism that is syntonic with psychological models for the intrusion of unedited, preconscious content into conscious awareness in this disorder (Libet et al. 1979; Gray 1995; Swerdlow 1996; Grobstein 2005).

A useful tool for probing the neurobiology and genetics of gating deficits in schizophrenia

Perhaps the most realistic expectation is that PPI is and will remain a useful tool for studying the neurobiology of information processing abnormalities in schizophrenia. While the PPI deficit “signal” in genetic studies of schizophrenia has been blunted by the widespread use of atypical antipsychotics, investigators are increasingly well informed about the many other factors affecting the measurement of PPI and the detection of schizophrenia-associated deficits, and in this way are better positioned to study the basis for these deficits at the levels of their neurobiological and genetic substrates. These studies will be aided by special populations, including “low-gating” normals (Swerdlow et al. 2006a; Vollenweider et al. 2006) and asymptomatic relatives of schizophrenia probands (Kumari et al. 2005b), and by patients with related disorders, such as 22q11 deletion syndrome and unmedicated “prodromal” individuals (Sobin et al. 2005a, b).

As a relatively robust and reliable quantitative phenotype, PPI will be used to map genes associated with deficient sensorimotor gating in schizophrenia probands and families (Swerdlow et al. 2007; Greenwood et al. 2007). The strength of this “endophenotype” approach to understanding disease genetics has been described by many, including Gottesman and Gould (2003), Gould and Gottesman (2006), and Braff et al. (2007a), and largely reflects the fact that the quantitative laboratory measure (in this case, PPI), is closer to the underlying biology (i.e., aberrant neural circuits and their regulation by disease genes), compared to the more variable clinical phenotype (Braff et al. 2007a). There are a small but growing number of examples in which this strategy has proven successful, in identifying genes that confer risk for colon cancer (Leppert et al. 1990) and Type II diabetes (Scott et al. 2007). Whether this strategy can succeed in identifying vulnerability genes for more complex neuropsychiatric disorders is a question at the core of several large ongoing investigative efforts.

Gains will likely be made through the combined use of PPI with sophisticated neurocognitive, neuroimaging, and genetic/genomic tools in schizophrenia and normal populations. It is realistic to expect that these various applications will converge in a top‑down or bottom‑up fashion, i.e., to link: (1) genes with (2) brain substrates that cause (3) gating deficits responsible for (4) neurocognitive disturbances and (5) the resulting daily functional impairment in schizophrenia. Based on the genes and brain substrates identified in these studies, one might reasonably expect that novel treatments will be identified, perhaps acting on intracellular G-protein-coupled signal transduction mechanisms that have already been implicated in the regulation of PPI (van den Buuse et al. 2005a; Kelly et al. 2007; Swerdlow et al. 2006d; Culm et al. 2004; Svenningsson et al. 2003), and which may also be abnormal in some schizophrenia patients (cf. Catapano and Manji 2007). There are also mature lines of research suggesting that novel treatments may target neuropeptides, such as neurotensin (Kinkead et al. 2005; Feifel et al. 2004), that potently regulate PPI and its dopaminergic control, or may target specific dopamine receptors subtypes that regulate PPI via relatively localized effects within mesolimbic and limbic–fronto–striatal circuits (e.g., Zhang et al. 2006). At some stage, it is reasonable to expect that the development of any one of these or other novel treatments might be guided by their effects on PPI in control or clinical populations.

A surrogate measure for neural processes with wide-reaching psychological implications

The frontal, limbic, and mesolimbic circuitry that regulates PPI also regulates many higher-order psychological processes. Thus, PPI can be viewed as a simple surrogate “readout” of activity in this circuitry—an experimentally generated signal from the forebrain, detected through efferents descending through a “pontine portal”. Alternatively, PPI can be viewed as a measure of a fundamental psychological process—sensorimotor gating—with broad-reaching implications for the structure of complex behavior and thoughts. In truth, both views are at least partly accurate, under specific uses of the PPI paradigm.

“Gating” can be a very specific process when operationalized in the laboratory, but is less precisely defined when used as a psychological construct. How broadly can we extrapolate from the laboratory measure of one type of gating—sensorimotor gating—to other forms of automatic inhibition of sensory, cognitive, or motor information? There is credible evidence that PPI correlates significantly with a form of perceptual “gating”, measured by the degree to which the prepulse reduces the perceived intensity of the startling stimulus (Peak 1939; Swerdlow et al. 2005b). On the other hand, PPI does not correlate strongly with the most structurally similar form of “gating”—sensory gating—measured by suppression of the P50 auditory event-related potential (ERP; Light et al. 2006; Hong et al. 2007). Nor does PPI in normal humans correlate strongly with other measures thought to assess inhibitory processes that contribute to forms of “cognitive gating”, such as latent inhibition (Murphy et al. 2001; Leumann et al. 2002; Peleg-Raibstein et al. 2006a, b) or visuospatial or semantic priming (Swerdlow et al. 1995b). Certainly, there is little evidence that PPI assesses processes that are strong determinants of normal personality structure and dimensions (Swerdlow et al. 2003d). At the least, it is important to recognize that the construct of “gating” is applied to many different processes and that it is reasonable to expect PPI to be informative about some, but not all or even most of these processes.

Summary: human studies

Human studies of PPI will continue to provide one important level of information within a top‑down or bottom‑up understanding of the biology of schizophrenia. PPI offers great promise as a quantitative phenotype for genetic studies and will be used in combination with other measures to connect an aberrant physiological signal (impaired startle inhibition) with its underlying neural substrates (via neuroimaging studies) and with its consequences in terms of cognitive deficits (via neurocognitive measures) and real-life impairment (via functional measures). It is realistic to expect that as we gain a better understanding of its modulating variables and optimal experimental methods, PPI in humans will continue its evolution, started in 1978 (Braff et al. 1978) from an isolated laboratory-based psychophysiological phenomenon, into a productive clinical research tool for understanding psychopathology. As we learn more about PPI, our scientific approaches to its use will continue to become more sophisticated, and we will be better positioned to take full advantage of what it can tell us about normal and abnormal brain functions.

Animal studies: What can our field realistically expect to learn about schizophrenia based on studies of PPI in laboratory animals?

Etiology

Two general applications of animal studies of PPI will be considered here: (1) the use of PPI to evaluate models or model organisms relevant to the etiology of schizophrenia; and (2) the use of PPI to “map” the neural substrates of deficient PPI in schizophrenia.

Model organisms, created via genetic, developmental, surgical, pharmacological, or immune manipulations, have been a mainstay of studies of the etiology, pathophysiology, and treatment of schizophrenia. Of course, schizophrenia—as defined clinically—is a uniquely human disorder (least we ascribe to rats the ability to have “two or more voices conversing with one another or voices maintaining a running commentary on the [rat’s] thoughts or behavior,” or the ability to conceptualize that “alien thoughts have been put into his or her mind...”, or to have homologous complex social cognitive deficits; APA 2000). However, investigators can apply schizophrenia-linked constructs to these models and test whether the resulting animal reproduces laboratory-based phenotypes exhibited by schizophrenia patients. The degree to which these phenotypes are reproduced in the model organism provides a level of validity to the construct, even if it is specific to the laboratory-based phenotype, rather than the broader clinical disorder.

For example, given a particular schizophrenia candidate gene “X”, it is reasonable to ask whether manipulations of gene “X” produce an animal that exhibits reduced levels of PPI compared to a wild-type animal. If so, then the gene “X” mutant would be a valid model for PPI deficits in schizophrenia. Such an approach has been taken with many different animal models (Table 3). There are obvious limitations to the specificity and sensitivity of this approach, which could be deduced from the above discussions of the PPI findings in humans.

Because deficient PPI is not unique to schizophrenia populations, there is no a priori justification for claiming that such a mutant specifically models the PPI deficits in schizophrenia, rather than OCD (Swerdlow et al. 1993a; Hoenig et al. 2005), Tourette Syndrome (Smith and Lees 1989; Castellanos et al. 1996; Swerdlow et al. 2001b), Blepharospasm (Gomez-Wong et al. 1998), or a number of other conditions. The specificity of the linkage of the model with schizophrenia, and hence with PPI deficits in schizophrenia, must come from the construct. For example, the finding of PPI deficits in a murine model of 22q11 deletion syndrome (22q11DS) links this model to PPI deficits in schizophrenia (Paylor et al. 2006; Sobin et al. 2005a, b), on the basis of the clinical relationship between 22q11DS and schizophrenia. Without this clinical relationship, this would just be a mouse with low PPI, and the model would most likely be a “false positive” for the schizophrenia phenotype.

Certainly, it is unlikely that most genes associated with low vs. high levels of PPI will be related to reduced PPI in schizophrenia or any one other disease states. This is because the most potent influences regulating baseline PPI involve physiological substrates that are probably not relevant to schizophrenia. For example, a very potent determinant of acoustic PPI is hearing threshold, as an organism that cannot hear a prepulse will not exhibit PPI. Thus, many candidate “PPI genes” identified via gene inactivation or mapping strategies of drug-free PPI in inbred and recombinant rodents will likely be associated with hearing threshold. Beyond the level of sensory detection, the most potent neural control of baseline PPI is exerted by the pedunculopontine nucleus (PPTg) (Swerdlow and Geyer 1993a), which mediates PPI via its impact on the nucleus reticularis pontis caudalis (NRPC; Koch et al. 1993). For the same reasons noted for hearing threshold, genetic studies of PPI will likely be influenced strongly by genes coding for the normal function of the PPTg—a structure that does not play a central role in any model for the pathophysiology of schizophrenia. In contrast, the prefrontal cortex (PFC)—which is viewed as a critical substrate for some core symptoms of schizophrenia (e.g., cognitive disorganization, deficient working memory, executive functioning, abstract reasoning, cognitive flexibility and context processing, and negative symptoms)—is likely to be three or four synapses removed from the primary startle circuit; in a normal human or rodent, genes controlling the PFC will likely contribute only weakly to a genetic “signal” based on levels of baseline PPI.

One might argue that a finding of PPI deficits provides additional validation that a particular model reproduces one of the quantitative phenotypes associated with schizophrenia. But as noted above, there is no definitive evidence that PPI deficits—or the neural abnormalities that produce them—are necessary for the expression of the broader schizophrenia phenotype. Rather, it is almost certainly true that there are large numbers of functionally impaired, symptomatic schizophrenia patients who exhibit levels of PPI in the “normal” range. Thus, rejecting animal models on the basis of “normal” PPI levels would likely result in a number of “false-negative” models—i.e., ones in which some features of the model accurately recreate important aspects of the biology of schizophrenia, but do not result in reduced PPI.

Perhaps the most realistic expectation of PPI in the assessment of animal models of schizophrenia is that it can provide validation for specific existing constructs—i.e., that the construct can reproduce PPI deficits exhibited by a significant subgroup of the heterogeneous population of schizophrenia patients. On the other hand, “normal” or unaltered PPI should not be used as the basis for rejecting a model: even in the presence of “normal” (i.e., wild-type, sham lesioned or placebo-treated) PPI levels, it is very possible that a model might be highly informative about the biology of schizophrenia.

Animal studies are also used to explicate the neural regulation of PPI, as a means of understanding the neural basis of PPI deficits in schizophrenia and other disorders. In this case, the manipulations are selected not necessarily based on a “construct” of schizophrenia, but rather based on the extant PPI neural “map”, and the understanding of anatomical and neurochemical properties of that map. In general, the organism used in these studies is not a schizophrenia “model” per se, but is more akin to a canvas on which a neural map can be painted. A reasonably comprehensive understanding of this “map”, ca. 2000, is found in Swerdlow et al. (2001a), and an updated list of studies of “PPI anatomy” is found in Table 4.

Much can be gleaned about PPI and its broader context by considering two facts related to its anatomical substrates. First, PPI remains intact after acute trans-collicular decerebration in the rat (Davis et al. 1982). In other words, the expression of unimodal acoustic PPI in rats does not require any part of the forebrain, and therefore, it must be mediated at or below the pons. The prepulse does not (and by physical and temporal constraints, cannot) “travel” to the forebrain to generate its inhibitory impact on the simple startle reflex (see discussion in Swerdlow et al. 2001a). Second, PPI can be regulated, and even eliminated, by subtle pharmacological manipulations at the most rostral tip of the forebrain [e.g., D1 receptor blockade within the medial prefrontal cortex (Ellenbroek et al. 1996; Shoemaker et al. 2005; Swerdlow et al. 2005c)]. Thus, brain substrates at the furthest point from the PPI “mediating” circuitry in the pons are capable of potently regulating the amount of inhibition generated by the prepulse, presumably via tonic, “thermostat-like stimulus-independent changes in activity within descending circuitry.

These two facts lead to a simple conclusion: while PPI is mediated via the pons, it can be regulated by the forebrain. A relative loss of PPI in clinical populations, and in the animal models that are used to study them, can be a consequence of aberrant activity within this descending circuitry—somewhere “between” the cortex and pons—or within substrates that impinge upon it. The efforts to “map” this PPI-regulatory circuitry, point-to-point, from cortex to pons, are aimed to help investigators identify candidate substrates that contribute to the loss of PPI in patient populations and candidate targets for therapeutic interventions. Of the many words of caution related to this use of animals to “map PPI”, two will be noted here.

First, rodent brains and human brains are not the same. Thus, a map of neural circuitry regulating PPI in rodents cannot be expected to translate exactly to human brains. Indeed, it is surprising how much overlap is suggested across species, based on neuroimaging findings in humans (Kumari et al. 2003a, 2005, 2007a; Postma et al. 2006), and based on examples of localized neuropathology associated with PPI deficits in brain disorders such as HD and in rat and murine models of this disorder (Swerdlow et al. 1995a; Carter et al. 1999; Van Raamsdonk et al. 2005). These findings notwithstanding, it is clear that species differences will be most pronounced in phylogenetically newest regions, some of which—e.g., frontal cortex—may be of most relevance to schizophrenia. As we attempt to interpret these circuit maps at higher levels of resolution to guide drug development—i.e., beyond simple efferent/afferent patterns, and down to the receptor- and subcellular levels—these cross-species differences may become increasingly important. A number of these differences are already suggested based on simple pharmacological challenge studies, described below.

Second, all rodent brains are not the same. Strain differences in PPI, and in sensitivity to drug effects on PPI, are quite remarkable across inbred and outbred rat strains, and across inbred and outbred mouse strains. These differences must reflect differences in the PPI-regulatory brain circuitry, potentially at any level from the presence of different cell types within a larger circuit organization, down to differences in the activity of specific enzymes within signal transduction pathways. Inbred Brown Norway rats exhibit significantly more PPI at short prepulse intervals and significantly less PPI at long prepulse intervals, compared to outbred Sprague Dawley (SD) rats (Swerdlow et al. 2006a). These differences are heritable (Swerdlow et al. 2008), and must reflect genetically mediated differences in brain organization. Albino SD and hooded Long Evans (LE) rats differ significantly in their sensitivity to the PPI-disruptive effects of dopamine (DA) agonists (e.g., Swerdlow et al. 2004a, 2006d) and in the expression of DA-regulatory enzymes [e.g., catechol-o-methyl transferase (COMT)] and signal transduction enzymes (e.g., protein kinase) within the nucleus accumbens (Shilling et al. 2008). Which of these strains provides an anatomical/neurochemical “map” of PPI that is most informative about human PPI circuitry, and hence, about PPI circuit abnormalities in schizophrenia? The answer is likely to differ, based on the neural systems and levels of resolution being studied, and the models being applied.

Treatment

It is reasonable to expect that studies of PPI in laboratory animals will continue to play a major role in the discovery and development of novel therapeutics for schizophrenia. As noted above, there is no compelling empirically based reason to expect that increased PPI per se might be desirable or functionally enhancing, nor that the ability of a drug to increase PPI in schizophrenia patients should be necessary or sufficient for clinical benefit. Despite this caveat, there is clear empirical evidence that the ability of drugs to “normalize” PPI levels after they have been reduced experimentally by specific drugs or perhaps by other manipulations (e.g., developmental manipulations) strongly predicts clinical utility and even potency of antipsychotic agents (Swerdlow et al. 1994; Swerdlow and Geyer 1998; Fig. 2). Towards this end, PPI has been used in several different types of predictive models, which differ in their sensitivity, specificity, logistical complexity, and even in the types of antipsychotics that they appear to identify. These issues are reviewed in Geyer et al. (2001), and an update of studies using PPI for its predictive validity since 2000 are found in Table 2.
https://static-content.springer.com/image/art%3A10.1007%2Fs00213-008-1072-4/MediaObjects/213_2008_1072_Fig2_HTML.gif
Fig. 2

Evidence supporting the predictive validity of one “rapid-throughput” animal model of PPI deficits. In these studies (Swerdlow et al. 1994), PPI was disrupted in adult male Sprague–Dawley rats by the mixed D1/D2 agonist, apomorphine (0.5 mg/kg sc). The ED50 of a number of drugs to reverse this apomorphine effect correlated significantly with their clinical potency. Subsequent studies have identified many other clinically effective antipsychotic agents from different chemical classes that prevent the PPI-disruptive effects of apomorphine in rats [see Table 2 and Geyer et al. (2001)]. A small number of potential “false-positive” compounds have also been detected, primarily in other species or strains. Other predictive models have been developed using PPI as a dependent measure, as described in the text and Table 2, each with different sensitivity, specificity, and logistical complexities

The four most common variations of the PPI paradigm in models predictive of antipsychotic effects involve the use of (1) DA agonists (Fig. 2), (2) NMDA antagonists, (3) isolation rearing (IR), and (4) neonatal ventral hippocampal lesions (NVHLs). While each of these variations is based on a biological “construct” for the etiology of schizophrenia, i.e., hyperdopaminergia, hypoglutamatergia, and specific neurodevelopmental insults, they have all been applied towards predicting antipsychotic properties in novel compounds. In truth, only the former two variants are well suited to traditional “rapid throughput” drug screens, based on the amount of time and resources necessary for the developmental models, and the relatively small (and often strain- or sex-dependent) effects of isolation rearing on PPI (Weiss et al. 1999, 2000; Powell et al. 2002). In each of these variations, the ability of a drug to “normalize” PPI is interpreted as evidence for antipsychotic potential. Some second generation antipsychotics, such as clozapine, quetiapine, and olazapine, tend to increase PPI in otherwise intact animals (Swerdlow and Geyer 1993b; cf. Geyer et al. 2001), particularly in mice, adding some interpretative complexity to their ability to normalize PPI after pharmacological, developmental, or surgical manipulations. In fact, the ability to enhance baseline PPI is a signal that has been used as a predictor of antipsychotic potential in mice, in some normally “low-gating” mouse strains (cf. Ouagazzal et al. 2001a), rat strains (Feifel et al. 2001, 2004), and even in normal “low-gating” humans (Swerdlow et al. 2006a; Vollenweider et al. 2006).

Beyond the dopamine system, some new targets of antipsychotics have emerged in recent years, based in part on studies using variations of PPI paradigms as predictive models. Examples of these targets include (but are not limited to) selective 5-HT2C receptor agonists (Marquis et al. 2007), CB1 cannabinoid receptor antagonists (Nagai et al. 2006), neurotensin-1 receptor agonists (Shilling et al. 2003, 2004; Caceda et al. 2005), selective adenosine A(2A) receptor agonists (Wardas et al. 2003), alpha-7 nicotinic receptor agonists (Suemara et al. 2004), and selective histamine H3 receptor antagonists (Fox et al. 2005; Table 2). It should be emphasized that in some cases, these targets were identified based on PPI assays with less compelling predictive validity, such as the ability of compounds to increase basal PPI levels in mice, or to normalize PPI after its disruption by 5HT agonists or NMDA antagonists. These assays may have strong sensitivity, particularly for identifying compounds with potentially novel mechanisms, but they also may lack specificity for detecting antipsychotic properties, at least in comparison to assays based on the ability to block the PPI-disruptive effects of apomorphine and perhaps other DA agonists (Fig. 2). We will have to await clinical evidence to determine whether these reports reflect “false positives” of these models.

PPI has only more recently begun to be used in models for detecting preventative or neuroprotective interventions, to identify strategies that would prevent the neuropathological and clinical consequences of a vulnerability gene or developmental insult involved in the prodrome and onset of schizophrenia. Some studies are approaching such an application, using early neuroimmune challenges to yield PPI deficits during adulthood (e.g., Borrell et al. 2002), or using sustained early life antipsychotic exposure to blunt the PPI-disruptive effects of developmental insults (Powell et al. 2006a, b). Assuming that these models succeed, it remains to be determined how one would test or apply such interventions in a clinical setting.

A reliable, robust, quantitative phenotype

In any given rodent species and strain, both PPI and its drug sensitivity are quite robust and reliable phenotypes. Within a range of 30–120 ms prepulse intervals, and 2–16 dB noise prepulses over a 65- to 70-dB(A) noise background, and 105–120 dB(A) noise pulses, PPI in rats exhibits a magnitude and parametric sensitivity that are strikingly similar across a number of studies from different laboratories and, conveniently, are also quite similar to those exhibited by humans. Similarly, PPI-disruptive effects of a number of simple manipulations (e.g., administration of a direct DA agonist) have been replicated across laboratories to the point that they have become “standard assays”, in predictive models for antipsychotic development. The PPI-disruptive effects of more complex manipulations, including early developmental lesions or isolation rearing, tend to be more variable across laboratories (discussed above), perhaps due to the complexities (and hence variability) of the methods and uncontrolled sources of variance. Some differences in reports of PPI drug sensitivity and sensitivity to developmental manipulations clearly seem to result from differences in rat strain or even supplier (e.g., Swerdlow et al. 1998, 2000b, 2003a, 2004a), and these differences are being explicated at the levels of heritable differences in neural substrates regulating PPI.

Some disparities in reported drug or other manipulation effects on PPI may also reflect differences in the recording properties of a variety of “home built“ and commercially available startle response acquisition systems. While there is no “gold standard” for such an apparatus, there are a number of characteristics that should be evaluated in interpreting whether response measurements “obey the laws of physiology”, e.g., intensity- and interval-dependence of PPI, and relative insensitivity of PPI to weight differences across animals. These issues are reviewed in Geyer and Swerdlow (1998).

Startle and PPI data can be deceptively complex, and some disparities in reported effects on PPI in rodents undoubtedly reflect these complexities and resulting interpretative differences across studies. Despite the impressive degree of automation in laboratory measures of PPI, one cannot automatically enter startle data into an equation and reasonably expect the calculated percent PPI to be informative. For example, we have previously reviewed the importance of considering the impact of changes in startle magnitude on changes in PPI (Swerdlow et al. 2000a). Simply put, the only unambiguous changes in sensorimotor gating are ones that can be demonstrated in the absence of changes in startle magnitude. In this case, reduced sensorimotor gating reflects a diminished impact of the prepulse on startle magnitude and, hence, an increase in startle magnitude on prepulse + pulse trials only. Any other related pattern of results, involving significantly reduced or increased startle magnitude on pulse-alone trials, must be interpreted in the context of additional supportive evidence. Such evidence might come from the use of low and high pulse intensities or from subgroups of rats that are matched based on comparable levels of startle magnitude.

Another interpretative issue that has been discussed in several recent reports relates to the potential impact of prepulse-induced startle activity on PPI and its modification by drugs or other experimental manipulations (Yee et al. 2004; Swerdlow et al. 2004c). A stimulus is only considered a “prepulse” in relationship to a second stimulus. By any other metric, it is simply a stimulus and can elicit motor activity including a startle reflex, depending on its properties. If the prepulse intensity exceeds the startle threshold, a “prepulse + pulse” configuration is better described as a “paired-pulse” configuration, and the resulting decrement in the startle response elicited by the second pulse is described as “paired-pulse inhibition”, comparable to the phenomenon used to study “blink excitability” (e.g., Kimura and Harada 1976; Valls-Sole et al. 2004). The similarities and differences of PPI and paired-pulse inhibition have been described for a small number of drug effects (e.g. Swerdlow et al. 2002a), but relatively little is known about this relationship for the long list of manipulations that have been applied towards PPI studies.

The interpretative ambiguities created by “prepulse-elicited startle” are most relevant to conditions in which the prepulse exceeds startle threshold. In a rat, for 20 ms noise prepulses over a 70-dB(A) noise background, this threshold is generally between 12 and 15 dB, although the precise value varies with strain, sex, age, and other factors. Other prepulse characteristics, including frequency (pure tone vs. white noise), duration, and configuration (continuous vs. discrete) can impact its motor-inhibiting and activating properties. For the vast majority of published PPI studies, prepulses are used at levels that elicit no or little detectable motor activity; even relatively intense prepulses (e.g., 10–15 dB salience, based on the stimulus conditions described above) might elicit a motor “signal” that is <1% of the total startle signal (Swerdlow et al. 2004c). In fact, this signal is comparable to that detected on “NOSTIM” trials, i.e., when no motor activity is recorded in the absence of stimulus delivery, suggesting that this small signal reflects ongoing motor activity rather than a prepulse-elicited motor response (e.g. Swerdlow et al. 2004c; Weber and Swerdlow 2008). Importantly, only a small fraction of studies utilize prepulses with supra-threshold intensities, and among these, most also utilize much weaker prepulses as internal comparisons. PPI is used to assess many things, and in some cases, a range of prepulse intensities is used to create a complete parametric characterization for purposes unrelated to drug effects (e.g., QTL analyses). Clearly, in these cases, the use of intense prepulses is not a “confound”, but simply a way to fully characterize a phenotype.

It is argued that potentially confounding effects might arise if a drug or other manipulation lowers startle threshold and, hence, transforms a non-startling prepulse into one that elicits a motor response (Yee et al. 2004). Specifically, a potentially confounding interaction might arise if increases in prepulse-evoked motor responses diminished the prepulse’s inhibitory effects on a subsequent startle response. In fact, there is no reason to predict such an effect: full startle responses elicited by an S1 in a paired-pulse paradigm do not interfere with the inhibitory impact of S1 on the startle response to S2 (e.g., Swerdlow et al. 2002a), so there is no credible reason to predict that such interference would result from a prepulse-evoked response that is 100-fold less intense. Nonetheless, under drug conditions, a number of control comparisons can be conducted—analogous to those used to understand the impact on PPI of drug-induced changes in startle magnitude—to determine whether drug effects on prepulse-evoked motor activity and PPI can be “dissociated”. We might predict that a common drug receptor (e.g., D1 or D2) might mediate two processes (reduced PPI and increased prepulse-induced motor activity), via effects within different brain substrates. Similar to changes in startle magnitude, a given drug might elicit either increases, decreases, or no change in prepulse-induced motor responses, yet have a consistent effect on PPI (e.g., Weber and Swerdlow 2008); even in cases where drug-induced changes in prepulse-induced activity are detected, they amount to shifts of less than 1% of the total “signal” of the startle response and, as noted above, are comparable to changes observed in “NOSTIM” activity. Thus, while it is a reasonable precaution to consider measuring prepulse-elicited motor activity to ascertain whether it is significantly greater than ongoing background motor activity, and whether it might potentially interact with the startling effects of the startle pulse, in our experience, such an exercise amounts to “much ado about [almost] nothing” (Swerdlow 2005).

A useful tool for modeling the neurobiology and gating and its deficits in humans

The most compelling contribution of animal studies of PPI towards the understanding of the basis for PPI deficits in schizophrenia comes in the ability to directly manipulate neural and genetic substrates and test hypotheses in a controlled experimental setting. The challenges of extrapolating such findings across species are not trivial, as discussed above in relationship to neural circuit maps. Still, for understanding the contribution to PPI deficits in schizophrenia of pathology in medial prefrontal cortex, hippocampus, amygdala or ventral striatum, or of specific candidate genes or early developmental insults, cross-species studies are a unique, powerful tool.

PPI studies have also identified neurobiological bridges across species that may reveal potential limitations of these studies and, perhaps, more generally of animal models of schizophrenia. For example, several drugs potently disrupt PPI in rats and yet increase PPI in normal humans. This is most notable because the drugs in question—ketamine (Abel et al. 2003; Duncan et al. 2001), MDMA (Vollenweider et al. 1999) and under some conditions, DA agonists (Bitsios et al. 2005)—have pharmacological and clinical properties that are central to models for the pathophysiology of schizophrenia. These findings raise both experimental and conceptual issues.

At an experimental level, drug doses, routes of administration, and pharmacokinetic/dynamic properties differ substantially across species. As one example, amphetamine reliably decreases PPI in rats only at doses above 2 mg/kg administered subcutaneously (Mansbach et al. 1988; Sills 1999; Swerdlow et al. 2006d), while the oral dose of amphetamine given to normal humans in PPI studies rarely exceeds 0.29 mg/kg (20 mg total; e.g., Hutchison and Swift 1999; Swerdlow et al. 2003b). Species differences in drug effects might also reflect contextual differences in the test setting. Humans volunteer and are paid for study participation, have the test conditions explained by a supportive research assistant, swallow a pill, and sit in a comfortable chair during testing; by contrast, rats are removed from a cage, injected with a drug, and then placed alone in a plastic tube inside an unfamiliar box where they are exposed to loud, unexpected noises. One might imagine that drug effects on a fight-or-flight reflex (startle) might differ in these two conditions, independent of species. Furthermore, while the parametric properties of PPI (e.g., sensitivity to prepulse intensity and interval) are strikingly similar across species, drug effects might reveal some cross-species differences in these parametric effects. For example, at 120 ms prepulse intervals, ketamine has opposite effects on PPI in rats (disrupts PPI; Mansbach and Geyer 1989) and humans (increases PPI; Abel et al. 2003; Duncan et al. 2001); on the other hand, ketamine can increase PPI in rats at shorter prepulse intervals (e.g., 30 ms; Mansbach and Geyer 1989). Our group has detected similar species- and interval-dependent effects with the NMDA antagonist, memantine (Swerdlow et al. 2003c, 2005a). Conceivably, NMDA-related mechanisms of drug effects on gating at 30 ms in rats might best approximate those at 120 ms in humans.

However, this explanation does not address the conceptual dilemma created by the fact that psychotomimetic drugs increase PPI in normal humans, while schizophrenia is associated with reduced PPI. While PPI deficits in schizophrenia might possibly reflect the consequences of sustained deficiencies in glutamatergic activity in the context of developmentally aberrant neural connections, it does not follow that such effects would be reproduced by an acute challenge of an NMDA antagonist to a normal individual with normal neural connectivity. Furthermore, one might easily imagine that acute drug effects on an intact brain might enhance sensorimotor gating via a mechanism that is very distinct from (e.g., “upstream” or “downstream” from) those responsible for reduced gating in the brain of a schizophrenia patient. Nonetheless, faced with these discrepant effects of psychotomimetic drugs on PPI, it is difficult to know whether the failings lie in the cross-species translation of the PPI model, in the validity of the acute ketamine/glutamate antagonist model of schizophrenia, or both.

An additional challenge in building neurobiological bridges of PPI studies across species comes from the human side of the bridge—from the observations that drug effects on PPI in humans can differ significantly, depending on basal levels of PPI. A number of drugs—including amphetamine (Swerdlow et al. 2003b), pergolide, amantadine (Bitsios et al. 2005), quetiapine (Swerdlow et al. 2006a), and clozapine (Vollenweider et al. 2006)—have been demonstrated to have effects that differ significantly (and in some cases, are arithmetically opposite) in normal humans with low vs. high PPI levels, relative to the overall test population. Similar findings may be emerging from animal studies, e.g., among inbred strains with low basal levels of PPI (cf. Ouagazzal et al. 2001a). How we interpret this “rate dependency” of drug effects on PPI in humans and laboratory animals and what it means about the many reported drug effects on PPI that have not considered or tested the impact of basal PPI levels, are issues that remain to be resolved.

While this discussion has focused primarily on cross-species comparisons between rodents and humans, and we discussed earlier the strain differences in PPI that have been detected in both rats and mice, it is also worth noting that there are also a number of important cross-species differences in PPI and its parametric and pharmacological sensitivity between rats and mice. Just as one example, while PPI is disrupted by DA agonists in both rats and mice, there is some evidence that this effect primarily reflects activation of D2 receptors in rats (Swerdlow et al. 1994; cf. Geyer et al. 2001), but of D1 receptors in mice (Ralph-Williams et al. 2003a; Ralph and Caine 2005). Within a restricted set of stimulus parameters (particularly prepulse intervals), infusion of D2 agonists into the nucleus accumbens decreases PPI in rats and increases PPI in mice (Mohr et al. 2007). This issue is not yet settled, as mice lacking D2 receptors are insensitive to the PPI-disruptive effects of d-amphetamine (Ralph et al. 1999), and some mouse strains exhibit “rat-like” PPI sensitivity to D2 agonists (Ralph and Caine 2007). Nonetheless, enough data exists that we can be fairly confident that a similar drug effect on PPI in rats and mice does not necessarily reflect a common underlying brain substrate. This raises the dilemma that when modeling the loss of PPI in schizophrenia, we are almost certainly studying very different neurobiological substrates, depending on the model species; this makes it very difficult to identify a clear, a priori rationale for selecting one species over another.

A surrogate measure for neural processes with wide-reaching psychological implications

Models of higher cognitive processes are only now being developed in rodents. Given the limited size and processing capacity of the frontal cortex in mice and rats vs. primates, and its relatively weaker contribution to the organization of behavior, there is reason to be skeptical that rodent models of higher cognitive processes will provide meaningful homology to human cognition. Nonetheless, mice and rats are amenable to complex conditioning schedules and are capable of performing choices and sophisticated behavioral sequences, and it is certain that studies will assess the potential relationship of PPI to these processes (e.g., Roegge et al. 2007; Depoortere et al. 2007a, b; Garner et al. 2007; Paine et al. 2007). Extrapolating these findings to humans will present many challenges. In general, the farther forward one moves in the brain, the greater the anatomical and functional differences between rodents and humans. For example, one might imagine a scenario in which “cognitive” control in rodents involves a prominent role for subcortical (e.g., basal ganglia) functions that overlap with PPI-regulatory circuitry, while in humans, higher cognitive control is “encephalized” to discrete frontal circuits that participate less in the regulation of startle gating.

There is already some evidence for both convergence and divergence of PPI and other operational animal models of “gating”, in terms of their underlying neural substrates. For example, contemporaneous measures of PPI and N40 gating—an animal model of P50 ERP gating in humans—revealed that apomorphine, phencyclidine, and DOI each disrupt PPI and reduce ERP responsivity to the S1 stimulus in the N40-gating paradigm, but do not specifically disrupt N40 gating per se (Swerdlow et al. 2006b). Some overlap has been reported in the pharmacological sensitivity of PPI and [some of the various forms of] latent inhibition to DA agonists and NMDA antagonists (Mansbach and Geyer 1989; Bakshi et al. 1995; Razoux et al. 2007), although many conditions lead to a loss of PPI in rats but leave latent inhibition intact (e.g., amphetamine withdrawal (Peleg-Raibstein et al. 2006a, b) and D2 blockade in the basolateral amygdala (Stevenson and Gratton 2004)). Thus, neurobiological mechanisms of PPI cannot be assumed to be common to experimental measures of either sensory or cognitive gating in rats. The potential overlap in the neurobiology of PPI and higher-order functions in rats, such as working memory, is an area of ongoing investigation. At present, there is no compelling evidence that such an overlap exists or that PPI is informative about higher cognitive functions in rodents.

Summary: animal studies

Animal models will remain an important tool in developing and testing hypotheses for the pathogenesis of brain disorders. As a reliable, quantitative “read out” of relatively well-defined neural circuitry, measures of PPI in laboratory animals will continue to be used to test and validate these hypotheses and to generate important new hypotheses regarding cellular mechanisms and therapeutic strategies. PPI models provide predictive validity in drug discovery and development, both as rapid through-put screens and as components of more biologically sophisticated models involving developmental, immunologic, and genetic manipulations. Areas of convergence and divergence are being identified in the cross-species pharmacology of PPI; areas of convergence will be exploited so that human drug effects can be predicted and understood based on PPI drug effects in rodents and their underlying cellular and molecular substrates. Finally, the relationship of PPI to higher-order learning processes is being explored in rodents, and the findings will be used to generate and test hypotheses regarding the interplay of sensorimotor gating and cognition in normal and disordered humans.

Conclusions

The construct of gating deficits in neuropsychiatric disorders has empirical support and intuitive appeal, and serves as a unifying heuristic for understanding the psychological and neural substrates shared by otherwise apparently unrelated disorders. PPI is an operational measure of basic, brain-based gating processes. It is robust, reliable, easily quantified, and versatile as an experimental tool, and is abnormal in several brain disorders including schizophrenia, that are characterized by clinical evidence of impaired gating of sensory, cognitive, motor of affective information. PPI can be measured across species and is regulated in laboratory animals by neurochemical, anatomical, developmental, and genetic substrates that can be systematically studied and used as the basis for developing and testing hypotheses for the biological basis of PPI deficits in patients.

For all of these reasons, studies of PPI in humans and laboratory animals have multiplied and expanded, and this measure is being used to explore many new questions at many different levels of analysis. While our field does not yet face the floods of the “Sorcerer’s Apprentice” (von Goethe 1779), it is clear that findings have amassed at an exponential rate and are testing our collective ability to critically integrate results, to identify areas of consistency, redundancy, and disagreement. Based on a review of the present literature, we reached several conclusions: (1) in humans, PPI is not “diagnostic”; levels of PPI do not predict clinical course, specific symptoms, or individual medication responses; (2) in preclinical studies, PPI is valuable for evaluating models or model organisms relevant to schizophrenia, “mapping” neural substrates of deficient PPI in schizophrenia, and advancing the discovery and development of novel therapeutics; (3) across species, PPI is a reliable, robust quantitative phenotype that is useful for probing the neurobiology and genetics of gating deficits in schizophrenia. In this review, we also identify some realistic expectations of this paradigm, describing its considerable strengths but also limitations, and stress some interpretative issues for consideration as we move forward with this powerful tool for translational neuropsychiatric research.

Acknowledgements

The authors of this study were supported by grants from the NIMH (NRS, DLB, GAL: MH 42228, MH 65571; NRS: MH 68366, MH 53484, MH 58903, MH 69589; GAL: MH 79777) and the VISN 22 MIRECC (DLB, GAL). DLB also was supported by a NARSAD Distinguished Investigator Award. The authors have also served as paid consultants to pharmaceutical companies or have had research supported by these companies (NRS, DLB, GAL: Allergan Pharmaceuticals, Pfizer Pharmaceuticals; DLB: Acadia Pharmaceuticals; GAL: Memory Pharmaceuticals, Sepacor and Astra-Zeneca). No funding entity provided any input to, oversight of, or influence over the contents of this review. The authors thank Ms. Maria Bongiovanni and Mr. David Ko for their expert assistance in manuscript preparation.

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© Springer-Verlag 2008