Brain Topography

, Volume 30, Issue 6, pp 822–831 | Cite as

Alpha/Theta Neurofeedback Increases Mentalization and Default Mode Network Connectivity in a Non-Clinical Sample

  • Claudio ImperatoriEmail author
  • Giacomo Della Marca
  • Noemi Amoroso
  • Giulia Maestoso
  • Enrico Maria Valenti
  • Chiara Massullo
  • Giuseppe Alessio Carbone
  • Anna Contardi
  • Benedetto Farina
Original Paper


Several studies showed the effectiveness of alpha/theta (A/T) neurofeedback training in treating some psychiatric conditions. Despite the evidence of A/T effectiveness, the psychological and neurobiological bases of its effects is still unclear. The aim of the present study was to explore the usefulness of the A/T training in increasing mentalization in a non-clinical sample. The modifications of electroencephalographic (EEG) functional connectivity in Default Mode Network (DMN) associated with A/T training were also investigated. Forty-four subjects were enrolled in the study and randomly assigned to receive ten sessions of A/T training [neurofeedback group (NFG) = 22], or to act as controls [waiting list group (WLG) = 22]. All participants were administered the mentalization questionnaire (MZQ) and the Symptom Checklist-90-Revised (SCL-90-R). In the post training assessment, compared to WLG, NFG showed a significant increase of MZQ total scores (3.94 ± 0.73 vs. 3.53 ± 0.77; F1;43 = 8.19; p = 0.007; d = 0.863). Furthermore, A/T training was also associated with a significant increase of EEG functional connectivity in several DMN brain areas (e.g. Posterior Cingulate Cortex). Taken together our results support the usefulness of the A/T training in enhancing mentalization and DMN connectivity.


EEG-neurofeedback Alpha/theta training Mentalization Default mode network EEG functional connectivity eLORETA 



This study was performed without any financial support

Compliance with Ethical Standards

Conflict of interest

The authors have no conflicts of interest.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed Consent

Informed consent was obtained from all patients for being included in the study.


  1. Arani FD, Rostami R, Nostratabadi M (2010) Effectiveness of neurofeedback training as a treatment for opioid-dependent patients. Clin EEG Neurosci 41:170–177. doi: 10.1177/155005941004100313 CrossRefPubMedGoogle Scholar
  2. Bowyer SM (2016) Coherence a measure of the brain networks: past and present. Neuropsychiatr Electrophysiol 2:1–12. doi: 10.1186/s40810-015-0015-7 CrossRefGoogle Scholar
  3. Boynton T (2001) Applied research using alpha/theta training for enhancing creativity and well-being. J Neurother 5:5–18CrossRefGoogle Scholar
  4. Burns ST (2015) Neurofeedback in hereditary angioedema: a single case study of symptom reduction. Appl Psychophysiol Biofeedback 40:251–256. doi: 10.1007/s10484-015-9288-7 CrossRefPubMedGoogle Scholar
  5. Canuet L et al (2011) Resting-state EEG source localization and functional connectivity in schizophrenia-like psychosis of epilepsy. PLoS ONE 6:e27863. doi: 10.1371/journal.pone.0027863 CrossRefPubMedPubMedCentralGoogle Scholar
  6. Canuet L et al (2012) Resting-state network disruption and APOE genotype in Alzheimer’s disease: a lagged functional connectivity study. PLoS ONE 7:e46289. doi: 10.1371/journal.pone.0046289 CrossRefPubMedPubMedCentralGoogle Scholar
  7. Ciaramidaro A, Adenzato M, Enrici I, Erk S, Pia L, Bara BG, Walter H (2007) The intentional network: how the brain reads varieties of intentions. Neuropsychologia 45:3105–3113. doi: 10.1016/j.neuropsychologia.2007.05.011 CrossRefPubMedGoogle Scholar
  8. Cohen J (1988) Statistical power analysis for the behavioral sciences, 2nd edn. Erlbaum, HillsdaleGoogle Scholar
  9. Dehghani-Arani F, Rostami R, Nadali H (2013) Neurofeedback training for opiate addiction: improvement of mental health and craving. Appl Psychophysiol Biofeedback 38:133–141. doi: 10.1007/s10484-013-9218-5 CrossRefPubMedPubMedCentralGoogle Scholar
  10. Denny BT, Kober H, Wager TD, Ochsner KN (2012) A meta-analysis of functional neuroimaging studies of self- and other judgments reveals a spatial gradient for mentalizing in medial prefrontal cortex. J Cogn Neurosci 24:1742–1752. doi: 10.1162/jocn_a_00233 CrossRefPubMedPubMedCentralGoogle Scholar
  11. Derogatis L (1977) The SCL-90-R Manual. Clinical Psychometric Research Unit. Johns Hopkins University School of Medicine, Baltimore, MDGoogle Scholar
  12. Egner T, Strawson E, Gruzelier JH (2002) EEG signature and phenomenology of alpha/theta neurofeedback training versus mock feedback. Appl Psychophysiol Biofeedback 27:261–270. doi: 10.1023/A:1021063416558 CrossRefPubMedGoogle Scholar
  13. Fahrion SL, Walters ED, Coyne L, Allen T (1992) Alterations in EEG amplitude, personality factors, and brain electrical mapping after alpha-theta brainwave training: a controlled case study of an alcoholic in recovery. Alcohol Clin Exp Res 16:547–552CrossRefPubMedGoogle Scholar
  14. Fonagy P, Bateman A (2008) The development of borderline personality disorder—A mentalizing model. J Pers Disord 22:4–21. doi: 10.1521/pedi.2008.22.1.4 CrossRefPubMedGoogle Scholar
  15. Fonagy P, Gergely G, Jurist EL, Target M (2002) Affect regulation, mentalization, and the development of the self. Other Press, New YorkGoogle Scholar
  16. Friston KJ, Frith CD, Liddle PF, Frackowiak RS (1991) Comparing functional (PET) images: the assessment of significant change. J Cereb Blood Flow Metab 11:690–699. doi: 10.1038/jcbfm.1991.122 CrossRefPubMedGoogle Scholar
  17. Gaillard R et al (2009) Converging intracranial markers of conscious access. PLoS Biol 7:e61. doi: 10.1371/journal.pbio.1000061 CrossRefPubMedGoogle Scholar
  18. Gevensleben H et al (2014) Neurofeedback in ADHD: further pieces of the puzzle. Brain Topogr 27:20–32. doi: 10.1007/s10548-013-0285-y CrossRefPubMedGoogle Scholar
  19. Gruzelier J (2009) A theory of alpha/theta neurofeedback, creative performance enhancement, long distance functional connectivity and psychological integration. Cogn Process 10(Suppl 1):S101–S109 doi: 10.1007/s10339-008-0248-5 CrossRefPubMedGoogle Scholar
  20. Gruzelier JH (2014) EEG-neurofeedback for optimising performance. II: creativity, the performing arts and ecological validity. Neurosci Biobehav Rev 44:142–158. doi: 10.1016/j.neubiorev.2013.11.004 CrossRefPubMedGoogle Scholar
  21. Hausberg MC et al (2012) Is a self-rated instrument appropriate to assess mentalization in patients with mental disorders? Development and first validation of the mentalization questionnaire (MZQ). Psychother Res 22:699–709. doi: 10.1080/10503307.2012.709325 CrossRefPubMedGoogle Scholar
  22. Immordino-Yang MH, Singh V (2013) Hippocampal contributions to the processing of social emotions. Hum Brain Mapp 34:945–955. doi: 10.1002/hbm.21485 CrossRefPubMedGoogle Scholar
  23. Imperatori C et al (2013) Modifications of EEG power spectra in mesial temporal lobe during n-back tasks of increasing difficulty. A sLORETA study. Front Hum Neurosci 7:109. doi: 10.3389/fnhum.2013.00109 CrossRefPubMedPubMedCentralGoogle Scholar
  24. Imperatori C et al (2014) Aberrant EEG functional connectivity and EEG power spectra in resting state post-traumatic stress disorder: A sLORETA study. Biol Psychol 102C:10–17. doi: 10.1016/j.biopsycho.2014.07.011 CrossRefGoogle Scholar
  25. Imperatori C et al (2016) Default Mode Network alterations in alexithymia: an EEG power spectra and connectivity study. Sci Rep 6:36653. doi: 10.1038/srep36653 CrossRefPubMedPubMedCentralGoogle Scholar
  26. Imperatori C et al (2017) Coping food craving with neurofeedback. Evaluation of the usefulness of alpha/theta training in a non-clinical sample. Int J Psychophysiol 112:89–97 doi: 10.1016/j.ijpsycho.2016.11.010 CrossRefPubMedGoogle Scholar
  27. Innamorati M et al (2015) Emotion regulation and mentalization in people at risk for food addiction. Behav Med:1–10 doi: 10.1080/08964289.2015.1036831
  28. Knyazev GG (2013) EEG correlates of self-referential processing. Front Hum Neurosci 7:264. doi: 10.3389/fnhum.2013.00264 CrossRefPubMedPubMedCentralGoogle Scholar
  29. Leech R, Kamourieh S, Beckmann CF, Sharp DJ (2011) Fractionating the default mode network: distinct contributions of the ventral and dorsal posterior cingulate cortex to cognitive control. J Neurosci 31:3217–3224. doi: 10.1523/JNEUROSCI.5626-10.2011 CrossRefPubMedGoogle Scholar
  30. Linden W (2007) The Autogenic Training Method of J. H. Schultz. Guilford Press, New YorkGoogle Scholar
  31. Lombardo MV, Chakrabarti B, Bullmore ET, Wheelwright SJ, Sadek SA, Suckling J, Baron-Cohen S (2010) Shared neural circuits for mentalizing about the self and others. J Cogn Neurosci 22:1623–1635. doi: 10.1162/jocn.2009.21287 CrossRefPubMedGoogle Scholar
  32. Luyten P, Fonagy P (2015) The neurobiology of mentalizing. Personal Disord 6:366–379. doi: 10.1037/per0000117 CrossRefPubMedGoogle Scholar
  33. Mars RB, Neubert FX, Noonan MP, Sallet J, Toni I, Rushworth MF (2012) On the relationship between the “default mode network” and the “social brain”. Front Hum Neurosci 6:189. doi: 10.3389/fnhum.2012.00189 CrossRefPubMedPubMedCentralGoogle Scholar
  34. Nichols TE, Holmes AP (2002) Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum Brain Mapp 15:1–25CrossRefPubMedGoogle Scholar
  35. Pascual-Marqui RD (2007) Coherence and phase synchronization: generalization to pairs of multivariate time series, and removal of zero-lag contributions. arXiv:07061776v3 [statME] 12 July 2007.
  36. Pascual-Marqui RD, Michel CM, Lehmann D (1994) Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. Int J Psychophysiol 18:49–65. doi: 10.1016/0167-8760(84)90014 CrossRefPubMedGoogle Scholar
  37. Pascual-Marqui RD, Michel CM, Lehmann D (1995) Segmentation of brain electrical activity into microstates: model estimation and validation. IEEE Trans Biomed Eng 42:658–665. doi: 10.1109/10.391164 CrossRefPubMedGoogle Scholar
  38. Pascual-Marqui RD et al (2011) Assessing interactions in the brain with exact low-resolution electromagnetic tomography. Philos Trans A Math Phys Eng Sci 369:3768–3784. doi: 10.1098/rsta.2011.0081 CrossRefPubMedGoogle Scholar
  39. Peniston EG, Kulkosky PJ (1989) Alpha-theta brainwave training and beta-endorphin levels in alcoholics. Alcohol Clin Exp Res 13:271–279CrossRefPubMedGoogle Scholar
  40. Peniston EG, Kulkosky PJ (1991) Alpha-theta brainwave neurofeedback therapy for Vietnam veterans with combat-related posttraumatic stress disorder. Medical Psychotherapy 4:47–60Google Scholar
  41. Raymond J, Varney C, Parkinson LA, Gruzelier JH (2005) The effects of alpha/theta neurofeedback on personality and mood. Cogn Brain Res 23:287–292. doi: 10.1016/j.cogbrainres.2004.10.023 CrossRefGoogle Scholar
  42. Rostami R, Dehghani-Arani F (2015) Neurofeedback training as a new method in treatment of crystal methamphetamine dependent patients: a preliminary study. Appl Psychophysiol Biofeedback 40:151–161. doi: 10.1007/s10484-015-9281-1 CrossRefPubMedGoogle Scholar
  43. Sarno I, Preti E, Prunas A, Madeddu F (2011) SCL-90-R: symptom checklist 90 R. Versione Italiana Validata e Standardizzata. Giunti O.S, FirenzeGoogle Scholar
  44. Saxby E, Peniston EG (1995) Alpha-theta brainwave neurofeedback training: an effective treatment for male and female alcoholics with depressive symptoms. J Clin Psychol 51:685–693CrossRefPubMedGoogle Scholar
  45. Schmidt J, Martin A (2015) Neurofeedback reduces overeating episodes in female restrained eaters: a randomized controlled pilot-study. Appl Psychophysiol Biofeedback 40:283–295. doi: 10.1007/s10484-015-9297-6 CrossRefPubMedGoogle Scholar
  46. Scott WC, Kaiser D, Othmer S, Sideroff SI (2005) Effects of an EEG biofeedback protocol on a mixed substance abusing population. Am J Drug Alcohol Abuse 31:455–469. doi: 10.1081/ADA200056807 CrossRefPubMedGoogle Scholar
  47. Senn S (2006) Change from baseline and analysis of covariance revisited. Stat Med 25:4334–4344. doi: 10.1002/sim.2682 CrossRefPubMedGoogle Scholar
  48. Sokhadze TM, Cannon RL, Trudeau DL (2008) EEG biofeedback as a treatment for substance use disorders: review, rating of efficacy, and recommendations for further research. Appl Psychophysiol Biofeedback 33:1–28. doi: 10.1007/s10484-007-9047-5 CrossRefPubMedPubMedCentralGoogle Scholar
  49. Takahashi HK, Kitada R, Sasaki AT, Kawamichi H, Okazaki S, Kochiyama T, Sadato N (2015) Brain networks of affective mentalizing revealed by the tear effect: the integrative role of the medial prefrontal cortex and precuneus. Neurosci Res 101:32–43. doi: 10.1016/j.neures.2015.07.005 CrossRefPubMedGoogle Scholar
  50. Thatcher RW, North DM, Biver CJ (2014) LORETA EEG phase reset of the default mode network. Front Hum Neurosci 8:529. doi: 10.3389/fnhum.2014.00529 CrossRefPubMedPubMedCentralGoogle Scholar
  51. Tononi G, Koch C (2008) The neural correlates of consciousness: an update. Ann N Y Acad Sci:239–261Google Scholar
  52. Trudeau DL (2005) EEG biofeedback for addictive disorders—The State of the Art in 2004. J Adult Dev 12:139–146CrossRefGoogle Scholar
  53. Tsuchiya N, Adolphs R (2007) Emotion and consciousness. Trends Cogn Sci 11:158–167. doi: 10.1016/j.tics.2007.01.005 CrossRefPubMedGoogle Scholar
  54. Vernon DJ (2005) Can neurofeedback training enhance performance? An evaluation of the evidence with implications for future research. Appl Psychophysiol Biofeedback 30:347–364. doi: 10.1007/s10484-005-8421-4 CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Claudio Imperatori
    • 1
    Email author
  • Giacomo Della Marca
    • 2
  • Noemi Amoroso
    • 1
  • Giulia Maestoso
    • 1
  • Enrico Maria Valenti
    • 1
  • Chiara Massullo
    • 1
  • Giuseppe Alessio Carbone
    • 1
  • Anna Contardi
    • 1
  • Benedetto Farina
    • 1
  1. 1.Department of Human SciencesEuropean University of RomeRomeItaly
  2. 2.Sleep Disorders Unit, Institute of NeurologyCatholic UniversityRomeItaly

Personalised recommendations