Brain responses in humans reveal ideal observer-like sensitivity to complex acoustic patterns
Open accessAbstract
Significance: We reveal the temporal dynamics and underlying neural sources of the process by which the brain discovers complex temporal patterns in rapidly unfolding sound sequences. We demonstrate that the auditory system, supported by a network of auditory cortical, hippocampal, and frontal sources, continually scans the environment, efficiently represents complex stimulus statistics, and rapidly (close to the bounds implied by an ideal observer model) responds to emergence of regular patterns, even when these are not behaviorally relevant. Neuronal activity correlated with the predictability of ongoing auditory input, both in terms of deterministic structure and the entropy of random sequences, providing clear neurophysiological evidence of the brain's capacity to automatically encode high-order statistics in sensory input.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
A series of studies reports that the transition from random to regular sequences of auditory stimuli is accompanied by a sustained increase in neural activity measured with MEG, EEG, and fMRI, in stark contrast to ES studies showing dampened neural responses to predictable stimuli.
“a series of studies reporting that the transition from random to regular sequences of auditory stimuli is accompanied by a sustained increase in neural activity measured with MEG, EEG, and fMRI, 144 , 154 , 155 in stark contrast to ES studies showing dampened neural responses to predictable stimuli.”
From Evaluating the neurophysiological evidence for predictive processing as a model of perception (2020) · cites this paper as [144]
Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measuredOverall, the evidence is consistent with PP's contention that the brain constructs dynamic representations of regularities in the sensory stream and that these representations are intimately involved in subsequent sensory processing.
“Overall, this evidence is consistent with PP's contention that the brain constructs dynamic representations of regularities in the sensory stream and that these representations are intimately involved in subsequent sensory processing.”
From Evaluating the neurophysiological evidence for predictive processing as a model of perception (2020) · cites this paper as [144]
Humans are capable of rapidly extracting regularities from the sensory environment, and there is strong evidence that the resultant expectations influence sensory processing.
“Humans are capable of rapidly extracting regularities from the sensory environment 144 , 158 , 160 , 161 and there is strong evidence that the resultant expectations influence sensory processing.”
From Evaluating the neurophysiological evidence for predictive processing as a model of perception (2020) · cites this paper as [144]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1994) · doi:10.1201/9780429246593 · Cited by 40,500 · see citing works
The assessment and analysis of handedness: The Edinburgh inventory
Oldfield, R. C. (1971) · Neuropsychologia · doi:10.1016/0028-3932(71)90067-4 · Cited by 35,900 · see citing works
An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1993) · doi:10.1007/978-1-4899-4541-9 · Cited by 21,230 · see citing works
Statistical parametric maps in functional imaging: A general linear approach
Friston, K. J., Holmes, A. P., Worsley, K. J., Poline, J. ‐., Frith, C. D., & Frackowiak, R. S. J. (1994) · Human Brain Mapping · doi:10.1002/hbm.460020402 · Cited by 9,688 · see citing works
Self-citationWhatever next? Predictive brains, situated agents, and the future of cognitive science
Clark, A. (2013) · Behavioral and Brain Sciences · doi:10.1017/s0140525x12000477 · Cited by 5,924 · cited 1× · see citing works
“However, a crucial link (19), missing in much of the sensory processing and statistical learning literature, is an understanding of the processes through which patterns within ongoing sensory input are recognized or instantiated in the first instance.”
BackgroundA theory of cortical responses.
Friston, K. (2005) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2005.1622 · Cited by 4,578 · see citing works
Self-citationSpatial registration and normalization of images
Friston, K. J., Ashburner, J., Frith, C., Poline, J.-B., Heather, J. D., & Frackowiak, R. S. J. (1995) · Human Brain Mapping · doi:10.1002/hbm.460030303 · Cited by 3,744 · see citing works
Self-citationThe mismatch negativity (MMN) in basic research of central auditory processing: A review
Näätänen, R., Paavilainen, P., Rinne, T., & Alho, K. (2007) · Clinical Neurophysiology · doi:10.1016/j.clinph.2007.04.026 · Cited by 2,644 · see citing works
Frackowiak, R. S. J. (1997) · Cited by 1,713 · see citing works
The mismatch negativity: a review of underlying mechanisms
Garrido, M. I., Kilner, J. M., Stephan, K. E., & Friston, K. J. (2009) · Clinical Neurophysiology · doi:10.1016/j.clinph.2008.11.029 · Cited by 1,441 · cited 1× · see citing works
“Activations in IFG and AC are commonly reported in the context of the MMN oddball paradigm (27, 28) and interpreted (29) as suggesting that the MMN arises from an interaction between bottom-up and reentrant effects (9, 11, 30).”
BackgroundSelf-citationTop-down modulation: bridging selective attention and working memory
Gazzaley, A., & Nobre, A. C. (2012) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2011.11.014 · Cited by 1,404 · see citing works
Attention, uncertainty, and free-energy
Feldman, H., & Friston, K. J. (2010) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2010.00215 · Cited by 1,365 · see citing works
Self-citationCoupling Between Neuronal Firing, Field Potentials, and fMRI in Human Auditory Cortex
Mukamel, R., Gelbard, H., Arieli, A., Hasson, U., Fried, I., & Malach, R. (2005) · Science · doi:10.1126/science.1110913 · Cited by 1,042 · see citing works
Neural mechanisms underlying melodic perception and memory for pitch
Zatorre, R. J., Evans, A. C., & Meyer, E. (1994) · Journal of Neuroscience · doi:10.1523/jneurosci.14-04-01908.1994 · Cited by 875 · see citing works
Fraisse, P. (1963) · Medical Entomology and Zoology · Cited by 777 · see citing works
Multiple Time Scales of Adaptation in Auditory Cortex Neurons
Ulanovsky, N., Las, L., Farkas, D., & Nelken, I. (2004) · Journal of Neuroscience · doi:10.1523/jneurosci.1905-04.2004 · Cited by 711 · see citing works
Smith, E. C., & Lewicki, M. S. (2006) · Nature · doi:10.1038/nature04485 · Cited by 625 · see citing works
Modeling the auditory scene: predictive regularity representations and perceptual objects
Winkler, I., Denham, S. L., & Nelken, I. (2009) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2009.09.003 · Cited by 562 · see citing works
Evidence for a hierarchy of predictions and prediction errors in human cortex
Wacongne, C., Labyt, E., van Wassenhove, V., Bekinschtein, T., Naccache, L., & Dehaene, S. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1117807108 · Cited by 560 · see citing works
A neuronal model of predictive coding accounting for the mismatch negativity.
Wacongne, C., Changeux, J.-P., & Dehaene, S. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.5003-11.2012 · Cited by 542 · see citing works
Turk-Browne, N. B., Scholl, B. J., Chun, M. M., & Johnson, M. K. (2009) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2009.21131 · Cited by 523 · see citing works
Opitz, B., Rinne, T., Mecklinger, A., von Cramon, D. Y., & Schröger, E. (2002) · NeuroImage · doi:10.1006/nimg.2001.0970 · Cited by 513 · see citing works
Attention reverses the effect of prediction in silencing sensory signals
Kok, P., Rahnev, D., Jehee, J. F. M., Lau, H. C., & de Lange, F. P. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhr310 · Cited by 430 · see citing works
Molholm, S., Martı́nez, A., Ritter, W., Javitt, D. C., & Foxe, J. J. (2004) · Cerebral Cortex · doi:10.1093/cercor/bhh155 · Cited by 397 · see citing works
Segregating the core computational faculty of human language from working memory
Makuuchi, M., Bahlmann, J., Anwander, A., & Friederici, A. D. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0810928106 · Cited by 364 · see citing works
Early electrophysiological indicators for predictive processing in audition: A review
Bendixen, A., SanMiguel, I., & Schröger, E. (2011) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2011.08.003 · Cited by 331 · see citing works
Yonelinas, A. P. (2013) · Behavioural Brain Research · doi:10.1016/j.bbr.2013.05.030 · Cited by 328 · see citing works
Todorovic, A., & de Lange, F. P. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.2227-12.2012 · Cited by 326 · see citing works
The Necessity of the Medial Temporal Lobe for Statistical Learning
Schapiro, A. C., Gregory, E., Landau, B., McCloskey, M. E., & Turk‐Browne, N. B. (2014) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00578 · Cited by 315 · see citing works
Free Energy, Precision and Learning: The Role of Cholinergic Neuromodulation
Moran, R. J., Campo, P., Symmonds, M., Stephan, K. E., Dolan, R. J., & Friston, K. J. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.4255-12.2013 · Cited by 312 · see citing works
Self-citationBuchsbaum, B. R., Olsen, R. K., Koch, P. F., & Berman, K. F. (2005) · Neuron · doi:10.1016/j.neuron.2005.09.029 · Cited by 304 · see citing works
Expectation in Melody: The Influence of Context and Learning
Pearce, M. T., & Wiggins, G. A. (2006) · Music Perception An Interdisciplinary Journal · doi:10.1525/mp.2006.23.5.377 · Cited by 297 · see citing works
Self-citationPearce, M. T. (2005) · City Research Online (City University London) · Cited by 267 · see citing works
Self-citationAttention Is Spontaneously Biased Toward Regularities
Zhao, J., Al-Aidroos, N., & Turk-Browne, N. B. (2013) · Psychological Science · doi:10.1177/0956797612460407 · Cited by 266 · see citing works
Denoising based on spatial filtering
de Cheveigné, A., & Simon, J. Z. (2008) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2008.03.015 · Cited by 258 · see citing works
Pearce, M. T., Ruiz, M. H., Kapasi, S., Wiggins, G. A., & Bhattacharya, J. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.019 · Cited by 248 · see citing works
Self-citationPaavilainen, P. (2013) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2013.03.015 · Cited by 236 · see citing works
Repetition effects to sounds: evidence for predictive coding in the auditory system
Baldeweg, T. (2006) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2006.01.010 · Cited by 223 · see citing works
An Evaluation of the Use of Magnetic Field Maps to Undistort Echo-Planar Images
Cusack, R., Brett, M., & Osswald, K. (2002) · NeuroImage · doi:10.1006/nimg.2002.1281 · Cited by 219 · see citing works
Bendixen, A., Schroger, E., & Winkler, I. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.1493-09.2009 · Cited by 218 · see citing works
Electrical Stimulation of Broca's Area Enhances Implicit Learning of an Artificial Grammar
de Vries, M. D., Barth, A. C. R., Maiworm, S., Knecht, S., Zwitserlood, P., & Flöel, A. (2010) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2009.21385 · Cited by 214 · see citing works
Dynamic Causal Modeling of the Response to Frequency Deviants
Garrido, M. I., Kilner, J. M., Kiebel, S. J., & Friston, K. J. (2009) · Journal of Neurophysiology · doi:10.1152/jn.90291.2008 · Cited by 208 · see citing works
Self-citationCharan Ranganath, A., DeGutis, J., & D’Esposito, M. (2004) · Cognitive Brain Research · doi:10.1016/j.cogbrainres.2003.11.017 · Cited by 206 · see citing works
Attal, Y., & Schwartz, D. (2013) · PLoS ONE · doi:10.1371/journal.pone.0059856 · Cited by 200 · see citing works
Joint decorrelation, a versatile tool for multichannel data analysis
Alain De Cheveigné, A., & Parra, L. C. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.05.068 · Cited by 192 · see citing works
Adaptation in the auditory system: an overview
Pérez‐González, D., & Malmierca, M. S. (2014) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2014.00019 · Cited by 174 · see citing works
Modelling trial-by-trial changes in the mismatch negativity
Lieder, F., Daunizeau, J., Garrido, M. I., Friston, K. J., & Stephan, K. E. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002911 · Cited by 168 · see citing works
Sensitivity to Complex Statistical Regularities in Rat Auditory Cortex
Yaron, A., Hershenhoren, I., & Nelken, I. (2012) · Neuron · doi:10.1016/j.neuron.2012.08.025 · Cited by 162 · see citing works
Artificial syntactic violations activate Broca's region
Petersson, K. M., Forkstam, C., & Ingvar, M. (2004) · Cognitive Science · doi:10.1207/s15516709cog2803_4 · Cited by 141 · see citing works
Outlier Responses Reflect Sensitivity to Statistical Structure in the Human Brain
Garrido, M. I., Sahani, M., & Dolan, R. J. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002999 · Cited by 137 · see citing works
Detecting Changes in Scenes: The Hippocampus Is Critical for Strength-Based Perception
Aly, M., Charan Ranganath, A., & Yonelinas, A. P. (2013) · Neuron · doi:10.1016/j.neuron.2013.04.018 · Cited by 124 · see citing works
Quraan, M. A., Moses, S. N., Hung, Y., et al. (2010) · Human Brain Mapping · doi:10.1002/hbm.21068 · Cited by 118 · see citing works
Identification of temporal order within auditory sequences
Warren, R. M., & Obusek, C. J. (1972) · Perception & Psychophysics · doi:10.3758/bf03212848 · Cited by 116 · see citing works
Preattentive detection of nonsalient contingencies between auditory features
Paavilainen, P., Arajärvi, P., & Takegata, R. (2007) · Neuroreport · doi:10.1097/wnr.0b013e328010e2ac · Cited by 113 · see citing works
Recovering sound sources from embedded repetition
McDermott, J. H., Wrobleski, D. M., & Oxenham, A. J. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1004765108 · Cited by 106 · see citing works
Schröger, E., Bendixen, A., Denham, S. L., Mill, R. W., Bõhm, T. M., & Winkler, I. (2013) · Brain Topography · doi:10.1007/s10548-013-0334-6 · Cited by 85 · see citing works
Melodic and Nonmelodic Sequences of Tones: Effects of Duration on Perception
Warren, R. M., Gardner, D. A., Brubaker, B. S., et al. (1991) · Music Perception An Interdisciplinary Journal · doi:10.2307/40285503 · Cited by 77 · see citing works
Garrido, M. I., Barnes, G. R., Kumaran, D., Maguire, E. A., & Dolan, R. J. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.07.016 · Cited by 72 · see citing works
Two types of auditory sequence perception
Warren, B. M., & Ackroff, J. M. (1976) · Perception & Psychophysics · doi:10.3758/bf03199420 · Cited by 71 · see citing works
Auditory pattern recognition by untrained listeners
Warren, R. M. (1974) · Perception & Psychophysics · doi:10.3758/bf03199291 · Cited by 62 · see citing works
Warren, R. M. (2008) · Cambridge University Press eBooks · doi:10.1017/cbo9780511754777 · Cited by 43 · see citing works
Auditory temporal edge detection in human auditory cortex
Maria Chait, A., Poeppel, D., & Simon, J. Z. (2008) · Brain Research · doi:10.1016/j.brainres.2008.03.050 · Cited by 40 · see citing works
Elfman, K. W., Aly, M., & Yonelinas, A. (2014) · Hippocampus · doi:10.1002/hipo.22345 · Cited by 36 · see citing works
Auditory perception : an analysis and synthesis
Warren, R. M. (2008) · Cited by 34 · see citing works
When acoustic sequences are not perceptual sequences: The global perception of auditory patterns
Warren, R. M., & Bashford, J. A. (1993) · Perception & Psychophysics · doi:10.3758/bf03206943 · Cited by 27 · see citing works
Sound segregation via embedded repetition is robust to inattention.
Masutomi, K., Barascud, N., Kashino, M., McDermott, J. H., & Maria Chait, A. (2015) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/xhp0000147 · Cited by 26 · see citing works
Self-citationGeiser, E., Walker, K. M. M., & Bendor, D. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.00159 · Cited by 26 · see citing works
Combining Magnetoencephalography and Functional Magnetic Resonance Imaging
Mathiak, K., & Fallgatter, A. J. (2005) · International review of neurobiology · doi:10.1016/s0074-7742(05)68005-1 · Cited by 13 · see citing works
“Change Deafness” Arising from Inter-feature Masking within a Single Auditory Object
Barascud, N., Griffiths, T. D., McAlpine, D., & Maria Chait, A. (2013) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00481 · Cited by 9 · see citing works
Self-citationRetroactive adjustment of perceived time
Patel, M., & Maria Chait, A. (2010) · Cognition · doi:10.1016/j.cognition.2010.10.011 · Cited by 6 · see citing works
The Timing of Change Detection and Change Perception in Complex Acoustic Scenes
Jaunmahomed, Z., & Chait, M. (2012) · Frontiers in Psychology · doi:10.3389/fpsyg.2012.00396 · Cited by 6 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 1
- [59]59. Hari R (1990) The neuromagnetic method in the study of the human auditory cortex. Auditory Evoked Magnetic Fields and Potentials Advances in Audiology, eds Grandori F, Hoke M, Romani G (Karger, Basel).
Cited by
Sorted by citations
How Do Expectations Shape Perception?
de Lange, F. P., Heilbron, M., & Kok, P. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.06.002 · Cited by 975 · see citing works
A New Unifying Account of the Roles of Neuronal Entrainment
Lakatos, P., Gross, J., & Thut, G. (2019) · Current Biology · doi:10.1016/j.cub.2019.07.075 · Cited by 508 · see citing works
Great Expectations: Is there Evidence for Predictive Coding in Auditory Cortex?
Heilbron, M., & Chait, M. (2018) · Neuroscience · doi:10.1016/j.neuroscience.2017.07.061 · Cited by 428 · see citing works
Self-citationEvaluating the neurophysiological evidence for predictive processing as a model of perception
Walsh, K. S., McGovern, D. P., Clark, A., & O'Connell, R. G. (2020) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.14321 · Cited by 333 · see citing works
Enhanced deviant responses in patterned relative to random sound sequences
Southwell, R., & Chait, M. (2018) · Cortex · doi:10.1016/j.cortex.2018.08.032 · Cited by 80 · see citing works
Self-citationThe Cumulative Effects of Predictability on Synaptic Gain in the Auditory Processing Stream
Auksztulewicz, R., Barascud, N., Cooray, G., Nobre, A. C., Chait, M., & Friston, K. (2017) · The Journal of Neuroscience · doi:10.1523/jneurosci.0291-17.2017 · Cited by 55 · see citing works
Self-citationFunctional neuroanatomy of speech signal decoding in primary progressive aphasias
Hardy, C. J. D., Agustus, J. L., Marshall, C. R., Clark, C. N., Russell, L. L., Brotherhood, E. V., Bond, R. L., Fiford, C. M., Ondobaka, S., Thomas, D. L., et al. (2017) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2017.04.026 · Cited by 47 · see citing works
Gendron, M., Mesquita, B., & Barrett, L. F. (2020) · Culture, Mind, and Brain · doi:10.1017/9781108695374.010 · Cited by 20 · see citing works
- Authors
- Barascud, N., Pearce, M. T., Griffiths, T. D., Friston, K. J., & Chait, M.
- Affiliations
- Wellcome Centre for Human Neuroimaging (GB)
- Queen Mary University of London (GB)
- Ear Institute, University College London, London WC1X 8EE, United Kingdom;
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2016-01-19
- Volume
- 113
- Issue
- 5
- Pages
- E616-25
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC4747708
- OpenAlex
- W2255122597
- Cited by
- 296
- References
- 71
- Citations by year
- 2026: 21 · 2025: 44 · 2024: 25 · 2023: 24 · 2022: 25 · 2021: 23 · 2020: 66 · 2019: 21 · 2018: 21 · 2017: 20 · 2016: 4 · 2014: 2
- FWCI
- 13.86
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Queen Mary Research Online (Queen Mary University of London) (submittedVersion)
- Newcastle University ePrints (Newcastle Univesity)
- Funders
- Wellcome Trust (093292/Z/10/Z)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neuroscience and Music Perception
- Life Sciences › Neuroscience › Cognitive Neuroscience › Tactile and Sensory Interactions
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- statistical learning, ideal observer, predictive coding, evidence accumulation, temporal structure of sound, predictability, entropy (information theory), primary auditory cortex, hippocampus, inferior frontal gyrus, perceptual inference
- MeSH terms
- Acoustics, Brain, Humans, Magnetic Resonance Imaging, Psychophysics, Magnetoencephalography
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
