Musicians at the Cocktail Party: Neural Substrates of Musical Training During Selective Listening in Multispeaker Situations.

Musical training has been demonstrated to benefit speech-in-noise perception. It is however unknown whether this effect translates to selective listening in cocktail party situations, and if so what its neural basis might be. We investigated this question using magnetoencephalography-based speech envelope reconstruction and a sustained selective listening task, in which participants with varying amounts of musical training attended to 1 of 2 speech streams while detecting rare target words. Cortical frequency-following responses (FFR) and auditory working memory were additionally measured to dissociate musical training-related effects on low-level auditory processing versus higher cognitive function. Results show that the duration of musical training is associated with a reduced distracting effect of competing speech on target detection accuracy. Remarkably, more musical training was related to a robust neural tracking of both the to-be-attended and the to-be-ignored speech stream, up until late cortical processing stages. Musical training-related increases in FFR power were associated with a robust speech tracking in auditory sensory areas, whereas training-related differences in auditory working memory were linked to an increased representation of the to-be-ignored stream beyond auditory cortex. Our findings suggest that musically trained persons can use additional information about the distracting stream to limit interference by competing speech.

[1]  E. C. Cmm,et al.  on the Recognition of Speech, with , 2008 .

[2]  Virginia Best,et al.  Listening to every other word: examining the strength of linkage variables in forming streams of speech. , 2008, The Journal of the Acoustical Society of America.

[3]  Jerker Rönnberg,et al.  The effects of working memory capacity and semantic cues on the intelligibility of speech in noise. , 2013, The Journal of the Acoustical Society of America.

[4]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[5]  Jayaganesh Swaminathan,et al.  Executive Function, Visual Attention and the Cocktail Party Problem in Musicians and Non-Musicians , 2016, PloS one.

[6]  Richard M. Leahy,et al.  Brainstorm: A User-Friendly Application for MEG/EEG Analysis , 2011, Comput. Intell. Neurosci..

[7]  S. Soli,et al.  Development of the Hearing in Noise Test for the measurement of speech reception thresholds in quiet and in noise. , 1994, The Journal of the Acoustical Society of America.

[8]  Ananthanarayan Krishnan,et al.  Enhanced brainstem encoding predicts musicians’ perceptual advantages with pitch , 2011, The European journal of neuroscience.

[9]  Jonathan Z. Simon,et al.  Adaptive Temporal Encoding Leads to a Background-Insensitive Cortical Representation of Speech , 2013, The Journal of Neuroscience.

[10]  J. Simon,et al.  Emergence of neural encoding of auditory objects while listening to competing speakers , 2012, Proceedings of the National Academy of Sciences.

[11]  S. David,et al.  Auditory attention : focusing the searchlight on sound , 2007 .

[12]  J. Simon,et al.  Neural coding of continuous speech in auditory cortex during monaural and dichotic listening. , 2012, Journal of neurophysiology.

[13]  Nikos Makris,et al.  Automatically parcellating the human cerebral cortex. , 2004, Cerebral cortex.

[14]  Hari M. Bharadwaj,et al.  Individual Differences Reveal Correlates of Hidden Hearing Deficits , 2015, The Journal of Neuroscience.

[15]  S. Koelsch,et al.  Working memory for speech and music , 2012, Annals of the New York Academy of Sciences.

[16]  Jonathan Z Simon,et al.  Cortical Representations of Speech in a Multitalker Auditory Scene , 2017, The Journal of Neuroscience.

[17]  Robert J. Zatorre,et al.  Musical Training as a Framework for Brain Plasticity: Behavior, Function, and Structure , 2012, Neuron.

[18]  Michael W. Weiss,et al.  Coordinated plasticity in brainstem and auditory cortex contributes to enhanced categorical speech perception in musicians , 2014, The European journal of neuroscience.

[19]  Barbara G. Shinn-Cunningham,et al.  Measuring auditory selective attention using frequency tagging , 2014, Front. Integr. Neurosci..

[20]  Hari M. Bharadwaj,et al.  Individual Differences in Temporal Perception and Their Implications for Everyday Listening , 2017 .

[21]  Deniz Başkent,et al.  Musician advantage for speech-on-speech perception. , 2016, The Journal of the Acoustical Society of America.

[22]  N. Kraus,et al.  Musicians' enhanced neural differentiation of speech sounds arises early in life: developmental evidence from ages 3 to 30. , 2014, Cerebral cortex.

[23]  Robin A. A. Ince,et al.  Frontal Top-Down Signals Increase Coupling of Auditory Low-Frequency Oscillations to Continuous Speech in Human Listeners , 2015, Current Biology.

[24]  Martin Cooke,et al.  A glimpsing model of speech perception in noise. , 2006, The Journal of the Acoustical Society of America.

[25]  Sylvain Baillet,et al.  Motor origin of temporal predictions in auditory attention , 2017, Proceedings of the National Academy of Sciences.

[26]  Stefan Koelsch,et al.  Neuroarchitecture of verbal and tonal working memory in nonmusicians and musicians , 2011, Human brain mapping.

[27]  N. Kraus,et al.  The Frequency-Following Response: A Window into Human Communication , 2017 .

[28]  Anders M. Dale,et al.  Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.

[29]  Jayaganesh Swaminathan,et al.  Musical training, individual differences and the cocktail party problem , 2015, Scientific Reports.

[30]  D. Poeppel,et al.  Mechanisms Underlying Selective Neuronal Tracking of Attended Speech at a “Cocktail Party” , 2013, Neuron.

[31]  Claude Alain,et al.  Concurrent Sound Segregation Is Enhanced in Musicians , 2009, Journal of Cognitive Neuroscience.

[32]  Charles Spence,et al.  The role of working memory in auditory selective attention , 2009, Quarterly journal of experimental psychology.

[33]  Robert J. Zatorre,et al.  Speech-in-noise perception in musicians: A review , 2017, Hearing Research.

[34]  R. Näätänen,et al.  Selection of speech messages in free-field listening. , 1993, Neuroreport.

[35]  Stefan Debener,et al.  Target Speaker Detection with Concealed EEG Around the Ear , 2016, Front. Neurosci..

[36]  R. Zatorre,et al.  Selective Entrainment of Theta Oscillations in the Dorsal Stream Causally Enhances Auditory Working Memory Performance , 2017, Neuron.

[37]  Ruth Y Litovsky,et al.  Role of masker predictability in the cocktail party problem. , 2008, The Journal of the Acoustical Society of America.

[38]  T. Lunner,et al.  The Ease of Language Understanding (ELU) model: theoretical, empirical, and clinical advances , 2013, Front. Syst. Neurosci..

[39]  Mounya Elhilali,et al.  A cocktail party with a cortical twist: how cortical mechanisms contribute to sound segregation. , 2008, The Journal of the Acoustical Society of America.

[40]  H. Murohashi,et al.  Working memory capacity affects the interference control of distractors at auditory gating , 2012, Neuroscience Letters.

[41]  A. Dale,et al.  Cortical Surface-Based Analysis II: Inflation, Flattening, and a Surface-Based Coordinate System , 1999, NeuroImage.

[42]  Alexander Dekhtyar,et al.  Information Retrieval , 2018, Lecture Notes in Computer Science.

[43]  C. Lam,et al.  Musician Enhancement for Speech-In-Noise , 2009, Ear and hearing.

[44]  Tom Manly,et al.  Musicians and non-musicians are equally adept at perceiving masked speech. , 2015, The Journal of the Acoustical Society of America.

[45]  Joachim Gross,et al.  Auditory cortical delta-entrainment interacts with oscillatory power in multiple fronto-parietal networks , 2017, NeuroImage.

[46]  T. Houtgast,et al.  A review of the MTF concept in room acoustics and its use for estimating speech intelligibility in auditoria , 1985 .

[47]  Joachim Gross,et al.  Good practice for conducting and reporting MEG research , 2013, NeuroImage.

[48]  Barbara Tillmann,et al.  Does tonality boost short-term memory in congenital amusia? , 2013, Brain Research.

[49]  N. Kraus,et al.  Musical Experience Limits the Degradative Effects of Background Noise on the Neural Processing of Sound , 2009, The Journal of Neuroscience.

[50]  T. Picton,et al.  Human auditory steady-state responses: Respuestas auditivas de estado estable en humanos , 2003, International journal of audiology.

[51]  Terence W Picton,et al.  Human temporal auditory acuity as assessed by envelope following responses. , 2004, The Journal of the Acoustical Society of America.

[52]  R Schoonhoven,et al.  A whole head MEG study of the amplitude-modulation-following response: phase coherence, group delay and dipole source analysis , 2003, Clinical Neurophysiology.

[53]  Nina Kraus,et al.  Musical training during early childhood enhances the neural encoding of speech in noise , 2012, Brain and Language.

[54]  T. Lunner,et al.  Working memory capacity may influence perceived effort during aided speech recognition in noise. , 2012, Journal of the American Academy of Audiology.

[55]  Marc Schönwiesner,et al.  Selective Attention Modulates Human Auditory Brainstem Responses: Relative Contributions of Frequency and Spatial Cues , 2014, PloS one.

[56]  E. C. Cherry Some Experiments on the Recognition of Speech, with One and with Two Ears , 1953 .

[57]  Christian Brodbeck,et al.  Neural source dynamics of brain responses to continuous stimuli: Speech processing from acoustics to comprehension , 2017, NeuroImage.

[58]  David Poeppel,et al.  Cortical oscillations and speech processing: emerging computational principles and operations , 2012, Nature Neuroscience.

[59]  John J. Foxe,et al.  Attentional Selection in a Cocktail Party Environment Can Be Decoded from Single-Trial EEG. , 2015, Cerebral cortex.

[60]  D. Mackinnon,et al.  A Simulation Study of Mediated Effect Measures. , 1995, Multivariate behavioral research.

[61]  Nina Kraus,et al.  Biological impact of auditory expertise across the life span: Musicians as a model of auditory learning , 2014, Hearing Research.

[62]  N. Mesgarani,et al.  Selective cortical representation of attended speaker in multi-talker speech perception , 2012, Nature.

[63]  Robert J. Zatorre,et al.  Musical training sharpens and bonds ears and tongue to hear speech better , 2017, Proceedings of the National Academy of Sciences.

[64]  David Poeppel,et al.  The Tracking of Speech Envelope in the Human Cortex , 2013, PloS one.

[65]  Aniruddh D. Patel Why would Musical Training Benefit the Neural Encoding of Speech? The OPERA Hypothesis , 2011, Front. Psychology.

[66]  Robert J. Zatorre,et al.  Neural Correlates of Early Sound Encoding and their Relationship to Speech-in-Noise Perception , 2017, Front. Neurosci..

[67]  Nina Kraus,et al.  Annals of the New York Academy of Sciences Cognitive Factors Shape Brain Networks for Auditory Skills: Spotlight on Auditory Working Memory , 2022 .

[68]  Robert J. Zatorre,et al.  Common parietal activation in musical mental transformations across pitch and time , 2013, NeuroImage.

[69]  Anders M. Dale,et al.  An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest , 2006, NeuroImage.

[70]  Michael A. Cohen,et al.  Auditory and visual memory in musicians and nonmusicians , 2011, Psychonomic bulletin & review.

[71]  M. Sobel Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models , 1982 .

[72]  Stefan Debener,et al.  The Right Temporoparietal Junction Supports Speech Tracking During Selective Listening: Evidence from Concurrent EEG-fMRI , 2017, The Journal of Neuroscience.

[73]  Patrik Sörqvist,et al.  A sub-process view of working memory capacity: Evidence from effects of speech on prose memory , 2010, Memory.

[74]  Sylvain Baillet,et al.  Cortical contributions to the auditory frequency-following response revealed by MEG , 2016, Nature Communications.

[75]  Giancarlo Valente,et al.  Assessing Top-Down and Bottom-Up Contributions to Auditory Stream Segregation and Integration With Polyphonic Music , 2018, Front. Neurosci..

[76]  Edmund C. Lalor,et al.  The Multivariate Temporal Response Function (mTRF) Toolbox: A MATLAB Toolbox for Relating Neural Signals to Continuous Stimuli , 2016, Front. Hum. Neurosci..