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Age-related hearing loss increases full-brain connectivity while reversing directed signaling within the dorsal–ventral pathway for speech

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Abstract

Speech comprehension difficulties are ubiquitous to aging and hearing loss, particularly in noisy environments. Older adults’ poorer speech-in-noise (SIN) comprehension has been related to abnormal neural representations within various nodes (regions) of the speech network, but how senescent changes in hearing alter the transmission of brain signals remains unspecified. We measured electroencephalograms in older adults with and without mild hearing loss during a SIN identification task. Using functional connectivity and graph-theoretic analyses, we show that hearing-impaired (HI) listeners have more extended (less integrated) communication pathways and less efficient information exchange among widespread brain regions (larger network eccentricity) than their normal-hearing (NH) peers. Parameter optimized support vector machine classifiers applied to EEG connectivity data showed hearing status could be decoded (> 85% accuracy) solely using network-level descriptions of brain activity, but classification was particularly robust using left hemisphere connections. Notably, we found a reversal in directed neural signaling in left hemisphere dependent on hearing status among specific connections within the dorsal–ventral speech pathways. NH listeners showed an overall net “bottom-up” signaling directed from auditory cortex (A1) to inferior frontal gyrus (IFG; Broca’s area), whereas the HI group showed the reverse signal (i.e., “top-down” Broca’s → A1). A similar flow reversal was noted between left IFG and motor cortex. Our full-brain connectivity results demonstrate that even mild forms of hearing loss alter how the brain routes information within the auditory–linguistic–motor loop.

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Notes

  1. An array of 32 ch was used since our dataset included recording of brainstem potentials (Bidelman et al. 2019), which require a very high sample rate that taxes available throughput of our EEG system. Estimates indicate that the accuracy of LORETA for 32 ch is ~ 1.5 × less accurate than 64 ch (Michel et al. 2004). Still, inverse methods were applied uniformly across all listeners/groups so while overall localization precision might be underestimated, this would not account for group differences.

  2. BRAPH does not implement directed measures of connectivity (Mijalkov et al. 2017) so our full-brain (global) analysis used undirected measures. As such, our full-brain analysis offers a somewhat qualitative view of hearing-related changes in brain connectivity. Consequently, we used directed connectivity metrics (PTE) for specific hypothesis testing and to evaluate hearing-related changes in specific connections with the auditory–linguistic-motor loop (e.g., Fig. 7). Together, our undirected and directed analyses at the full-brain and circuit level offer two complementary approaches that provide different, yet converging evidence for hearing-related changes in brain connectivity.

  3. Our connectivity matrices were derived from source signals, which yield the most veridical estimate of functional brain connectivity (Bastos and Schoffelen 2016; Lai et al. 2018). Nevertheless, effects of field spread can never be fully abolished in EEG, even at the source level (Schoffelen and Gross 2009; Zhang et al. 2016) and correlated activity of adjacent sources reduces the accuracy of functional connectivity analysis (for an excellent review of this tradeoff, see Schoffelen and Gross 2009). However, proper interpretation of source connectivity results can be achieved by analyzing the relative changes in connectivity caused by experimental manipulations (Schoffelen and Gross 2009). Thus, because field spread effects are identical across our experimental conditions (i.e., groups; noise levels) they subtract out and are unlikely to account for group differences. Moreover, our characterizations of topographic connectivity patterns (Figs. 2, 3, 4, 56) reflect the organizational properties of the connectome at the full-brain level and these measures show good reliability in the face of residual correlated activity (Hardmeier et al. 2014).

  4. This differs from Bidelman et al. (2019), where PTE values were not normalized between ± 0.5.

References

  • Abdala C, Dhar S (2012) Maturation and aging of the human cochlea: a view through the DPOAE looking glass. J Assoc Res Otolaryngol 13(3):403–421

    PubMed  PubMed Central  Google Scholar 

  • Alain C, Snyder JS (2008) Age-related differences in auditory evoked responses during rapid perceptual learning. Clin Neurophysiol 119(2):356–366

    PubMed  Google Scholar 

  • Alain C, McDonald K, Van Roon P (2012) Effects of age and background noise on processing a mistuned harmonic in an otherwise periodic complex sound. Hear Res 283:126–135

    PubMed  Google Scholar 

  • Alain C, Roye A, Salloum C (2014) Effects of age-related hearing loss and background noise on neuromagnetic activity from auditory cortex. Front Syst Neurosci 8:8

    PubMed  PubMed Central  Google Scholar 

  • Alain C, Arsenault JS, Garami L, Bidelman GM, Snyder JS (2017) Neural correlates of speech segregation based on formant frequencies of adjacent vowels. Sci Rep 7(40790):1–11

    Google Scholar 

  • Alain C, Du Y, Bernstein LJ, Barten T, Banai K (2018) Listening under difficult conditions: an activation likelihood estimation meta-analysis. Hum Brain Mapp 39(7):2695–2709

    PubMed  PubMed Central  Google Scholar 

  • Anderson S, Skoe E, Chandrasekaran B, Kraus N (2010) Neural timing is linked to speech perception in noise. J Neurosci 30(14):4922–4926

    PubMed  PubMed Central  CAS  Google Scholar 

  • Anderson S, Parbery-Clark A, White-Schwoch T, Kraus N (2012) Aging affects neural precision of speech encoding. J Neurosci 32(41):14156–14164

    PubMed  PubMed Central  CAS  Google Scholar 

  • Anderson S, White-Schwoch T, Choi HJ, Kraus N (2013a) Training changes processing of speech cues in older adults with hearing loss. Front Syst Neurosci 7(97):1–9

    Google Scholar 

  • Anderson S, White-Schwoch T, Parbery-Clark A, Kraus N (2013b) A dynamic auditory-cognitive system supports speech-in-noise perception in older adults. Hear Res 300C:18–32

    Google Scholar 

  • Bashivan P, Bidelman GM, Yeasin M (2014) Modulation of brain connectivity by cognitive load in the working memory network. In: Proceedings on the IEEE symposium series on computational intelligence (IEEE SSCI), Orlando, FL, December 9–12

  • Bashivan P, Yeasin M, Bidelman GM (2017) Temporal progression in functional connectivity determines individual differences in working memory capacity. In: Proceedings of the international joint conference on neural networks (IJCNN 2017) (Anchorage, AK, May 14–19). pp 2943–2949

  • Bassett DS, Bullmore E (2006) Small-world brain networks. Neuroscientist 12(6):512–523

    PubMed  Google Scholar 

  • Bastos AM, Schoffelen J-M (2016) A tutorial review of functional connectivity analysis methods and their interpretational pitfalls. Front Syst Neurosci 9:175

    PubMed  PubMed Central  Google Scholar 

  • Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B (Methodol) 57(1):289–300

    Google Scholar 

  • Betlejewski S (2006) Age connected hearing disorders (presbyacusis) as a social problem. Otolaryngol Pol 60(6):883–886

    PubMed  Google Scholar 

  • Bidelman GM, Dexter L (2015) Bilinguals at the “cocktail party”: dissociable neural activity in auditory-linguistic brain regions reveals neurobiological basis for nonnative listeners’ speech-in-noise recognition deficits. Brain Lang 143:32–41

    PubMed  Google Scholar 

  • Bidelman GM, Howell M (2016) Functional changes in inter- and intra-hemispheric auditory cortical processing underlying degraded speech perception. Neuroimage 124:581–590

    PubMed  Google Scholar 

  • Bidelman GM, Villafuerte JW, Moreno S, Alain C (2014) Age-related changes in the subcortical-cortical encoding and categorical perception of speech. Neurobiol Aging 35(11):2526–2540

    PubMed  Google Scholar 

  • Bidelman GM, Lowther JE, Tak SH, Alain C (2017) Mild cognitive impairment is characterized by deficient hierarchical speech coding between auditory brainstem and cortex. J Neurosci 37(13):3610–3620

    PubMed  PubMed Central  CAS  Google Scholar 

  • Bidelman GM, Davis MK, Pridgen MH (2018) Brainstem-cortical functional connectivity for speech is differentially challenged by noise and reverberation. Hear Res 367:149–160

    PubMed  PubMed Central  Google Scholar 

  • Bidelman GM, Price CN, Shen D, Arnott S, Alain C (2019) Afferent-efferent connectivity between auditory brainstem and cortex accounts for poorer speech-in-noise comprehension in older adults. bioRxiv [preprint]: https://doi.org/10.1101/568840

  • Bilodeau-Mercure M, Lortie CL, Sato M, Guitton MJ, Tremblay P (2015) The neurobiology of speech perception decline in aging. Brain Struct Funct 220(2):979–997

    PubMed  Google Scholar 

  • Boyen K, de Kleine E, van Dijk P, Langers DRM (2014) Tinnitus-related dissociation between cortical and subcortical neural activity in humans with mild to moderate sensorineural hearing loss. Hear Res 312:48–59

    PubMed  Google Scholar 

  • Brent GA, Smith DBD, Michalewski HJ, Thompson LW (1976) Differences in the evoked potential in young and old subjects during habituation and dishabituation procedures. Psychophysiology 14:96–97

    Google Scholar 

  • Caspary DM, Ling L, Turner JG, Hughes LF (2008) Inhibitory neurotransmission, plasticity and aging in the mammalian central auditory system. J Exp Biol Med 211:1781–1791

    CAS  Google Scholar 

  • Chang Y, Lee SH, Lee YJ, Hwang MJ, Bae SJ, Kim MN, Lee J, Woo S, Lee H, Kang DS (2004) Auditory neural pathway evaluation on sensorineural hearing loss using diffusion tensor imaging. NeuroReport 15(11):1699–1703

    PubMed  Google Scholar 

  • Christensen H, Mackinnon AJ, Korten A, Jorm AF (2001) The “common cause hypothesis” of cognitive aging: evidence for not only a common factor but also specific associations of age with vision and grip strength in a cross-sectional analysis. Psychol Aging 16(4):588–599

    PubMed  CAS  Google Scholar 

  • Cohen G (1979) Language comprehension in old age. Cognit Psychol 11(4):412–429

    PubMed  CAS  Google Scholar 

  • Cruickshanks KJ, Wiley TL, Tweed TS, Klein BE, Klein R, Mares-Perlman JA, Nondahl DM (1998) Prevalence of hearing loss in older adults in Beaver Dam, Wisconsin: the epidemiology of hearing loss study. Am J Epidemiol 148(9):879–886

    PubMed  CAS  Google Scholar 

  • de Haan W, Pijnenburg YAL, Strijers RLM, van der Made Y, van der Flier WM, Scheltens P, Stam CJ (2009) Functional neural network analysis in frontotemporal dementia and Alzheimer’s disease using EEG and graph theory. BMC Neurosci 10(1):101

    PubMed  PubMed Central  Google Scholar 

  • Desikan RS, Segonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, Buckner RL, Dale AM, Maguire RP, Hyman BT, Albert MS, Killiany RJ (2006) An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31(3):968–980

    PubMed  Google Scholar 

  • Du Y, Buchsbaum BR, Grady CL, Alain C (2014) Noise differentially impacts phoneme representations in the auditory and speech motor systems. Proc Natl Acad Sci USA 111(19):1–6

    Google Scholar 

  • Du Y, Buchsbaum BR, Grady CL, Alain C (2016) Increased activity in frontal motor cortex compensates impaired speech perception in older adults. Nat Commun 7(12241):1–12

    Google Scholar 

  • Dubno JR, Schaefer AB (1992) Comparison of frequency selectivity and consonant recognition among hearing-impaired and masked normal-hearing listeners. J Acoust Soc Am 91(4 Pt 1):2110–2121

    PubMed  CAS  Google Scholar 

  • Friston KJ (2011) Functional and effective connectivity: a review. Brain Connect 1(1):13–36

    PubMed  Google Scholar 

  • Fuchs M, Drenckhahn R, Wischmann H-A, Wagner M (1998) An improved boundary element method for realistic volume-conductor modeling. IEEE Trans Biomed Eng 45(8):980–997

    PubMed  CAS  Google Scholar 

  • Fuchs M, Kastner J, Wagner M, Hawes S, Ebersole J (2002) A standardized boundary element method volume conductor model. Clin Neurophysiol 113(5):702–712

    PubMed  Google Scholar 

  • Garrett DD, Samanez-Larkinc GR, MacDonaldd SWS, Lindenberger U, McIntosh AR, Grady CL (2013) Moment-to-moment brain signal variability: a next frontier in human brain mapping? Neurosci Biobehav Rev 37:610–624

    PubMed  PubMed Central  Google Scholar 

  • Goodin DS, Squires KC, Henderson BH, Starr A (1978) Age-related variations in evoked potentials to auditory stimuli in normal human subjects. Electroencephalogr Clin Neurophysiol 44(4):447–458

    PubMed  CAS  Google Scholar 

  • Gordon-Salant S, Fitzgibbons PJ (1993) Temporal factors and speech recognition performance in young and elderly listeners. J Speech Hear Res 36:1276–1285

    PubMed  CAS  Google Scholar 

  • Gozzo Y, Vohr B, Lacadie C, Hampson M, Katz KH, Maller-Kesselman J, Schneider KC, Peterson BS, Rajeevan N, Makuch RW, Constable RT, Ment LR (2009) Alterations in neural connectivity in preterm children at school age. Neuroimage 48(2):458–463

    PubMed  Google Scholar 

  • Grady CL, Maisog JM, Horwitz B, Ungerleider LG, Mentis MJ, Salerno JA, Pietrini P, Wagner E, Haxby JV (1994) Age-related changes in cortical blood flow activation during visual processing of faces and location. J Neurosci 14(3 Pt 2):1450–1462

    PubMed  CAS  PubMed Central  Google Scholar 

  • Gramfort A, Papadopoulo T, Olivi E, Clerc M (2010) OpenMEEG: Opensource software for quasistatic bioelectromagnetics. Biomed Eng Online 9(1):45

    PubMed  PubMed Central  Google Scholar 

  • Hardmeier M, Hatz F, Bousleiman H, Schindler C, Stam CJ, Fuhr P (2014) Reproducibility of functional connectivity and graph measures based on the phase lag index (PLI) and weighted phase lag index (wPLI) derived from high resolution EEG. PLoS One 9(10):e108648–e108648

    PubMed  PubMed Central  Google Scholar 

  • Harris JM, Hirst JL, Mossinghoff MJ (2008) Combinatorics and graph theory, vol 2. Springer, New York

    Google Scholar 

  • He W, Sowman PF, Brock J, Etchell AC, Stam CJ, Hillebrand A (2018) Topological segregation of functional networks increases in developing brains. bioRxiv [preprint]:378562

  • Humes LE, Busey TA, Craig J, Kewley-Port D (2013) Are age-related changes in cognitive function driven by age-related changes in sensory processing? Atten Percept Psychophys 75:508–524

    PubMed  Google Scholar 

  • Hutka S, Alain C, Binns M, Bidelman GM (2013) Age-related differences in the sequential organization of speech sounds. J Acoust Soc Am 133(6):4177–4187

    PubMed  Google Scholar 

  • Javad F, Warren JD, Micallef C, Thornton JS, Golay X, Yousry T, Mancini L (2014) Auditory tracts identified with combined fMRI and diffusion tractography. Neuroimage 84(Supplement C):562–574

    PubMed  Google Scholar 

  • Kaiser M (2011) A tutorial in connectome analysis: topological and spatial features of brain networks. Neuroimage 57(3):892–907

    PubMed  Google Scholar 

  • Khatun S, Morshed BI, Bidelman GM (2019) A single-channel EEG-based approach to detect mild cognitive impairment via speech-evoked brain responses. IEEE Trans Neural Syst Rehabilit Eng 27(5):1063–1070

    Google Scholar 

  • Killion MC, Niquette PA, Gudmundsen GI, Revit LJ, Banerjee S (2004) Development of a quick speech-in-noise test for measuring signal-to-noise ratio loss in normal-hearing and hearing-impaired listeners. J Acoust Soc Am 116(4 Pt 1):2395–2405

    PubMed  Google Scholar 

  • Konkle DF, Beasley DS, Bess FH (1977) Intelligibility of time-altered speech in relation to chronological aging. J Speech Hear Res 20:108–115

    PubMed  CAS  Google Scholar 

  • Kral A, Kronenberger WG, Pisoni DB, O’Donoghue GM (2016) Neurocognitive factors in sensory restoration of early deafness: a connectome model. Lancet Neurolol 15(6):610–621

    Google Scholar 

  • Kujawa SG, Liberman MC (2006) Acceleration of age-related hearing loss by early noise exposure: evidence of a misspent youth. J Neurosci 26(7):2115–2123

    PubMed  PubMed Central  CAS  Google Scholar 

  • Lai M, Demuru M, Hillebrand A, Fraschini M (2018) A comparison between scalp- and source-reconstructed EEG networks. Sci Rep 8(1):12269

    PubMed  PubMed Central  Google Scholar 

  • Li S-C, Lindenberger U (1999) Cross-level unification: a computational exploration of the link between deterioration of neurotransmitter systems and dedifferentiation of cognitive abilities in old age. In: Nilsson LG, Markowitsch HJ (eds) Cognitive neuroscience of memory. Hogrefe & Huber, Kirkland, pp 103–146

    Google Scholar 

  • Lin Y, Wang J, Wu C, Wai Y, Yu J, Ng S (2008) Diffusion tensor imaging of the auditory pathway in sensorineural hearing loss: changes in radial diffusivity and diffusion anisotropy. J Magn Reson Imaging 28(3):598–603

    PubMed  Google Scholar 

  • Lin FR, Metter EJ, O’Brien RJ, Resnick SM, Zonderman AB, Ferrucci L (2011) Hearing loss and incident dementia. Arch Neurol 68(2):214–220

    PubMed  PubMed Central  Google Scholar 

  • Lin FR, Yaffe K, Xia J, Xue QL, Harris TB, Purchase-Helzner E, Satterfield S, Ayonayon HN, Ferrucci L, Simonsick EM (2013) Hearing loss and cognitive decline in older adults. JAMA Intern Med 173(4):293–299

    PubMed  Google Scholar 

  • Liu B, Feng Y, Yang M, Chen JY, Li J, Huang ZC, Zhang LL (2015) Functional connectivity in patients with sensorineural hearing loss using resting-state mri. Am J Audiol 24(2):145–152

    PubMed  Google Scholar 

  • Lobier M, Siebenhuhner F, Palva S, Palva JM (2014) Phase transfer entropy: a novel phase-based measure for directed connectivity in networks coupled by oscillatory interactions. Neuroimage 85(Pt 2):853–872

    PubMed  Google Scholar 

  • Lopez ME, Aurtenetxe S, Pereda E, Cuesta P, Castellanos NP, Bruna R, Niso G, Maestu F, Bajo R (2014) Cognitive reserve is associated with the functional organization of the brain in healthy aging: a MEG study. Front Aging Neurosci 6:125

    PubMed  PubMed Central  Google Scholar 

  • Lutz J, Hemminger F, Stahl R, Dietrich O, Hempel M, Reiser M, Jager L (2007) Evidence of subcortical and cortical aging of the acoustic pathway: a diffusion tensor imaging (DTI) study. Acad Radiol 14(6):692–700

    PubMed  Google Scholar 

  • Mahmud MS, Yeasin M, Shen D, Arnott S, Alain C, Bidelman GM (2018) What brain connectivity patterns from EEG tell us about hearing loss: a graph theoretic approach. In: Proceedings of the 10th international conference on electrical and computer engineering (ICECE 2018), Dhaka, Bangladesh, Dec. 20–22. pp 205–208

  • Makary CA, Shin J, Kujawa SG, Liberman MC, Merchant SN (2011) Age-related primary cochlear neuronal degeneration in human temporal bones. J Assoc Res Otolaryngol 12(6):711–717

    PubMed  PubMed Central  Google Scholar 

  • Martin JS, Jerger JF (2005) Some effects of aging on central auditory processing. J Rehabilit Res Dev 42(4 Suppl 2):25–44

    Google Scholar 

  • Mazziotta JC, Toga AW, Evans A, Lancaster JL, Fox PT (1995) A probabilistic atlas of the human brain: theory and rationale for its development. Neuroimage 2:89–101

    PubMed  CAS  Google Scholar 

  • Michel CM, Murray MM, Lantz G, Gonzalez S, Spinelli L, Grave de Peralta R (2004) EEG source imaging. Clin Neurophysiol 115(10):2195–2222

    PubMed  Google Scholar 

  • Mijalkov M, Kakaei E, Pereira JB, Westman E, Volpe G (2017) BRAPH: a graph theory software for the analysis of brain connectivity. PLoS One 12(8):e0178798

    PubMed  PubMed Central  Google Scholar 

  • Oostenveld R, Praamstra P (2001) The five percent electrode system for high-resolution EEG and ERP measurements. Clin Neurophysiol 112:713–719

    PubMed  CAS  Google Scholar 

  • Park Y, Luo L, Parhi KK, Netoff T (2011) Seizure prediction with spectral power of EEG using cost-sensitive support vector machines. Epilepsia 52(10):1761–1770

    PubMed  Google Scholar 

  • Parthasarathy A, Bartlett E (2011) Age-related auditory deficits in temporal processing in F-344 rats. Neuroscience 192:619–630

    PubMed  CAS  Google Scholar 

  • Parthasarathy A, Datta J, Torres JA, Hopkins C, Bartlett EL (2014) Age-related changes in the relationship between auditory brainstem responses and envelope-following responses. J Assoc Res Otolaryngol 15(4):649–661

    PubMed  PubMed Central  Google Scholar 

  • Pascual-Marqui RD, Esslen M, Kochi K, Lehmann D (2002) Functional imaging with low-resolution brain electromagnetic tomography (LORETA): a review. Methods Find Exp Clin Pharmacol 24(Suppl C):91–95

    PubMed  Google Scholar 

  • Pearson JD, Morrell CH, Gordon-Salant S, Brant LJ, Metter EJ, Klein LL, Fozard JL (1995) Gender differences in a longitudinal study of age-associated hearing loss. J Acoust Soc Am 97:1196–1205

    PubMed  CAS  Google Scholar 

  • Peelle JE, Wingfield A (2016) The neural consequences of age-related hearing loss. Trends Neurosci 39(7):486–497

    PubMed  PubMed Central  CAS  Google Scholar 

  • Peelle JE, Troiani V, Wingfield A, Grossman M (2010) Neural processing during older adults’ comprehension of spoken sentences: age differences in resource allocation and connectivity. Cereb Cortex 20(4):773–782

    PubMed  Google Scholar 

  • Peelle JE, Troiani V, Grossman M, Wingfield A (2011) Hearing loss in older adults affects neural systems supporting speech comprehension. J Neurosci 31(35):12638–12643

    PubMed  PubMed Central  CAS  Google Scholar 

  • Pfefferbaum A, Ford JM, Roth WT, Kopell BS (1980) Age-related changes in auditory event-related potentials. Electroencephalogr Clin Neurophysiol 49(3–4):266–276

    PubMed  CAS  Google Scholar 

  • Pichora-Fuller KM, Alain C, Schneider B (2017) Older adults at the cocktail party. In: Middlebrook JC, Simon JZ, Popper AN, Fay RF (eds) Springer handbook of auditory research: the auditory system at the cocktail party. Springer, Berlin, pp 227–259

    Google Scholar 

  • Picton TW, Alain C, Woods DL, John MS, Scherg M, Valdes-Sosa P, Bosch-Bayard J, Trujillo NJ (1999) Intracerebral sources of human auditory-evoked potentials. Audiol Neurootol 4(2):64–79

    PubMed  CAS  Google Scholar 

  • Picton TW, van Roon P, Armilio ML, Berg P, Ille N, Scherg M (2000) The correction of ocular artifacts: a topographic perspective. Clin Neurophysiol 111(1):53–65

    PubMed  CAS  Google Scholar 

  • Presacco A, Simon JZ, Anderson S (2016) Evidence of degraded representation of speech in noise, in the aging midbrain and cortex. J Neurophysiol 116(5):2346–2355

    PubMed  PubMed Central  Google Scholar 

  • Presacco A, Simon JZ, Anderson S (2019) Speech-in-noise representation in the aging midbrain and cortex: effects of hearing loss. PLoS One 14(3):e0213899

    PubMed  PubMed Central  CAS  Google Scholar 

  • Propst EJ, Greinwald JH, Schmithorst V (2010) Neuroanatomic differences in children with unilateral sensorineural hearing loss detected using functional magnetic resonance imaging. Arch Otolaryngol Head Neck Surg 136(1):22–26

    PubMed  Google Scholar 

  • Rauschecker JP, Scott SK (2009) Maps and streams in the auditory cortex: nonhuman primates illuminate human speech processing. Nat Neurosci 12(6):718–724

    PubMed  PubMed Central  CAS  Google Scholar 

  • Reuter-Lorenz PA, Cappell KA (2008) Neurocognitive aging and the compensation hypothesis. Curr Dir Psychol Sci 17(3):177–182

    Google Scholar 

  • Ricketts TA, Hornsby B (2005) Sound quality measures for speech in noise through a commercial hearing aid implementing “digital noise reduction”. J Am Acad Audiol 16:272–279

    Google Scholar 

  • Rubinov M, Sporns O (2010) Complex network measures of brain connectivity: uses and interpretations. Neuroimage 52(3):1059–1069

    PubMed  Google Scholar 

  • Saito T, Rehmsmeier M (2015) The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets. PLoS One 10(3):e0118432

    PubMed  PubMed Central  Google Scholar 

  • Salat DH, Buckner RL, Snyder AZ, Greve DN, Desikan RS, Busa E, Morris JC, Dale AM, Fischl B (2004) Thinning of the cerebral cortex in aging. Cereb Cortex 14(7):721–730

    PubMed  Google Scholar 

  • Salthouse TA, Lichty W (1985) Tests of the neural noise hypothesis of age-related cognitive change. J Gerontol 40(4):443–450

    PubMed  CAS  Google Scholar 

  • Schlee W, Weisz N, Bertrand O, Hartmann T, Elbert T (2008) Using auditory steady state responses to outline the functional connectivity in the tinnitus brain. PLoS One 3(11):e3720

    PubMed  PubMed Central  Google Scholar 

  • Schmidt SA, Akrofi K, Carpenter-Thompson JR, Husain FT (2013) Default mode, dorsal attention and auditory resting state networks exhibit differential functional connectivity in tinnitus and hearing loss. PLoS One 8(10):e76488

    PubMed  PubMed Central  CAS  Google Scholar 

  • Schneider BA, Daneman M, Pichora-Fuller MK (2002) Listening in aging adults: from discourse comprehension to psychoacoustics. Can J Exp Psychol 56(3):139–152

    PubMed  Google Scholar 

  • Schneider BA, Daneman M, Murphy DR (2005) Speech comprehension difficulties in older adults: cognitive slowing or age-related changes in hearing? Psychol Aging 20(2):261–271

    PubMed  Google Scholar 

  • Schoffelen JM, Gross J (2009) Source connectivity analysis with MEG and EEG. Hum Brain Mapp 30(6):1857–1865

    PubMed  PubMed Central  Google Scholar 

  • Scott SK, Johnsrude IS (2003) The neuroanatomical and functional organization of speech perception. Trends Neurosci 26(2):100–107

    PubMed  CAS  Google Scholar 

  • Song J, Davey C, Poulsen C, Luu P, Turovets S, Anderson E, Li K, Tucker D (2015) EEG source localization: sensor density and head surface coverage. J Neurosci Meth 256:9–21

    Google Scholar 

  • Strouse A, Ashmead DH, Ohde RN, Grantham DW (1998) Temporal processing in the aging auditory system. J Acoust Soc Am 104(4):2385–2399

    PubMed  CAS  Google Scholar 

  • Tadel F, Baillet S, Mosher JC, Pantazis D, Leahy RM (2011) Brainstorm: a user-friendly application for MEG/EEG analysis. Comput Intell Neurosci 2011:1–13

    Google Scholar 

  • Tay T, Wang JJ, Kifley A, Lindley R, Newall P, Mitchell P (2006) Sensory and cognitive association in older persons: findings from an older Australian population. Gerontology 52(6):386–394

    PubMed  Google Scholar 

  • Thompson EC, Woodruff Carr K, White-Schwoch T, Tierney A, Nicol T, Kraus N (2016) Hemispheric asymmetry of endogenous neural oscillations in young children: implications for hearing speech in noise. Sci Rep 6:19737

    PubMed  PubMed Central  CAS  Google Scholar 

  • Tremblay K, Piskosz M, Souza P (2003a) Effects of age and age-related hearing loss on the neural representation of speech cues. Clin Neurophysiol 114:1332–1343

    PubMed  Google Scholar 

  • Tremblay KL, Piskosz M, Souza P (2003b) Effects of age and age-related hearing loss on the neural representation of speech cues. Clin Neurophysiol 114(7):1332–1343

    PubMed  Google Scholar 

  • van Lutterveld R, van Dellen E, Pal P, Yang H, Stam CJ, Brewer J (2017) Meditation is associated with increased brain network integration. Neuroimage 158:18–25

    PubMed  Google Scholar 

  • van Rooij J, Plomp R (1992) Auditive and cognitive factors in speech perception by elderly listeners. III. Additional data and final discussion. J Acoust Soc Am 91:1028–1033

    PubMed  Google Scholar 

  • West RL (1996) An application of prefrontal cortex function theory to cognitive aging. Psychol Bull 120(2):272–292

    PubMed  CAS  Google Scholar 

  • Wong PCM, Jin JX, Gunasekera GM, Abel R, Lee ER, Dhar S (2009) Aging and cortical mechanisms of speech perception in noise. Neuropsychologia 47:693–703

    PubMed  Google Scholar 

  • Wong PC, Ettlinger M, Sheppard JP, Gunasekera GM, Dhar S (2010) Neuroanatomical characteristics and speech perception in noise in older adults. Ear Hear 31(4):471–479

    PubMed  PubMed Central  Google Scholar 

  • Woods DL, Clayworth CC (1986) Age-related changes in human middle latency auditory evoked potentials. Electroencephalogr Clin Neurophysiol 65(4):297–303

    PubMed  CAS  Google Scholar 

  • Zhang J, Cui Y, Deng L, He L, Zhang J, Zhang J, Zhou Q, Liu Q, Zhang Z (2016) Closely spaced MEG source localization and functional connectivity analysis using a new prewhitening invariance of noise space algorithm. Neural Plas 2016:4890497

    Google Scholar 

  • Zhang H, Lee A, Qiu A (2017) A posterior-to-anterior shift of brain functional dynamics in aging. Brain Struct Funct 222(8):3665–3676

    PubMed  Google Scholar 

  • Zhang Y, Mao Z, Feng S, Liu X, Lan L, Zhang J, Yu X (2018) Altered functional networks in long-term unilateral hearing loss: a connectome analysis. Brain Behav 8(2):e00912

    PubMed  PubMed Central  Google Scholar 

  • Zhiwei L, Minfen S (2007) Classification of mental task EEG signals using wavelet packet entropy and SVM. In: 2007 8th international conference on electronic measurement and instruments, 16–18 Aug. 2007. pp 3-906-903-909

  • Zhuravleva TY, Alperin BR, Haring AE, Rentz DM, Holcomb PJ, Daffner KR (2014) Age-related decline in bottom-up processing and selective attention in the very old. J Clin Neurophysiol 31(3):261–271

    PubMed  PubMed Central  Google Scholar 

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Funding

This work was funded by Grants from the Canadian Institutes of Health Research (MOP 106619) and the Natural Sciences and Engineering Research Council of Canada (NSERC, 194536) awarded to C.A, and The Hearing Research Foundation awarded to S.R.A, and the National Institute on Deafness and Other Communication Disorders of the National Institutes of Health under award number NIH/NIDCD R01DC016267 (G.M.B.).

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Authors and Affiliations

  1. Institute for Intelligent Systems, University of Memphis, Memphis, TN, USA

    Gavin M. Bidelman

  2. School of Communication Sciences and Disorders, University of Memphis, 4055 North Park Loop, Memphis, TN, 38152, USA

    Gavin M. Bidelman

  3. Department of Anatomy and Neurobiology, University of Tennessee Health Sciences Center, Memphis, TN, USA

    Gavin M. Bidelman

  4. Department of Electrical and Computer Engineering, University of Memphis, Memphis, TN, USA

    Md Sultan Mahmud & Mohammed Yeasin

  5. Rotman Research Institute–Baycrest Centre for Geriatric Care, Toronto, ON, Canada

    Dawei Shen, Stephen R. Arnott & Claude Alain

  6. Department of Psychology, University of Toronto, Toronto, ON, Canada

    Claude Alain

  7. Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada

    Claude Alain

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  1. Gavin M. Bidelman
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  2. Md Sultan Mahmud
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  3. Mohammed Yeasin
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  4. Dawei Shen
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  5. Stephen R. Arnott
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  6. Claude Alain
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Correspondence to Gavin M. Bidelman.

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The authors declare they have no conflict of interest.

Ethical approval

Research involving human subjects for this study was approved by the Baycrest Hospital Human Subject Review Committee and participants gave written informed consent in accordance with protocol REB# 06-31.

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Bidelman, G.M., Mahmud, M.S., Yeasin, M. et al. Age-related hearing loss increases full-brain connectivity while reversing directed signaling within the dorsal–ventral pathway for speech. Brain Struct Funct 224, 2661–2676 (2019). https://doi.org/10.1007/s00429-019-01922-9

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  • DOI: https://doi.org/10.1007/s00429-019-01922-9

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