The relationship between the temporal structure of magnetoencephalography recorded brain activity and capacity to form discrete auditory representations

A function of oscillatory brain activity may be to align activity relative to threshold potentials and in doing so provide limited opportunities for representational neuronal assemblies to form. This low‐level function could apply across frequency bands and potentially affect the temporal dynamics of experience. To test these possibilities, a magnetoencephalography protocol was developed where capacity to form discrete auditory representations over time was assessed relative to oscillatory brain activity. Three sets of preregistered analyses were conducted. First, the capacity to form representations correlated with the prevalence and durations of activity localised to the auditory cortex. Second, brain oscillations became entrained to stimuli over a broad range of frequencies. Finally, a sequence of gamma (γ) band events predicted successful discrete representation, where previous research had indicated similar individuation‐related differences within the alpha (α) range. Together, these findings indicate that a low‐level function of cortical oscillations, which may apply across a range of frequency bands, is periodically to set conditions in which representational neuronal assemblies can manifest, limiting and so affecting the flow of experience.

[1]  Robert T. Knight,et al.  Parameterizing neural power spectra , 2018, bioRxiv.

[2]  R. VanRullen Perceptual Cycles , 2016, Trends in Cognitive Sciences.

[3]  Zhongming Liu,et al.  Broadband Electrophysiological Dynamics Contribute to Global Resting-State fMRI Signal , 2016, The Journal of Neuroscience.

[4]  Christopher W. Pleydell-Pearce,et al.  The phase of pre-stimulus alpha oscillations influences the visual perception of stimulus timing , 2016, NeuroImage.

[5]  Joachim Lange,et al.  Beta oscillations define discrete perceptual cycles in the somatosensory domain , 2015, Proceedings of the National Academy of Sciences.

[6]  Rufin VanRullen,et al.  On the cyclic nature of perception in vision versus audition , 2014, Philosophical Transactions of the Royal Society B: Biological Sciences.

[7]  Rajesh P. N. Rao,et al.  Broadband changes in the cortical surface potential track activation of functionally diverse neuronal populations , 2014, NeuroImage.

[8]  P. Schyns,et al.  Speech Rhythms and Multiplexed Oscillatory Sensory Coding in the Human Brain , 2013, PLoS biology.

[9]  Karl J. Friston,et al.  Broadband Cortical Desynchronization Underlies the Human Psychedelic State , 2013, The Journal of Neuroscience.

[10]  C. Schroeder,et al.  The Spectrotemporal Filter Mechanism of Auditory Selective Attention , 2013, Neuron.

[11]  K. Linkenkaer-Hansen,et al.  Neuronal long-range temporal correlations and avalanche dynamics are correlated with behavioral scaling laws , 2013, Proceedings of the National Academy of Sciences.

[12]  Joachim Gross,et al.  Phase-Locked Responses to Speech in Human Auditory Cortex are Enhanced During Comprehension , 2012, Cerebral cortex.

[13]  David M. Groppe,et al.  Mass univariate analysis of event-related brain potentials/fields I: a critical tutorial review. , 2011, Psychophysiology.

[14]  Biyu J. He Scale-Free Properties of the Functional Magnetic Resonance Imaging Signal during Rest and Task , 2011, The Journal of Neuroscience.

[15]  V. Menon,et al.  Decoding temporal structure in music and speech relies on shared brain resources but elicits different fine-scale spatial patterns. , 2011, Cerebral cortex.

[16]  E. Maris,et al.  Prior Expectation Mediates Neural Adaptation to Repeated Sounds in the Auditory Cortex: An MEG Study , 2011, The Journal of Neuroscience.

[17]  R. VanRullen,et al.  Spontaneous EEG oscillations reveal periodic sampling of visual attention , 2010, Proceedings of the National Academy of Sciences.

[18]  Christopher T. Kello,et al.  Scaling laws in cognitive sciences , 2010, Trends in Cognitive Sciences.

[19]  Karl J. Friston The free-energy principle: a unified brain theory? , 2010, Nature Reviews Neuroscience.

[20]  Jeremy R. Manning,et al.  Broadband Shifts in Local Field Potential Power Spectra Are Correlated with Single-Neuron Spiking in Humans , 2009, The Journal of Neuroscience.

[21]  R. VanRullen,et al.  The Phase of Ongoing EEG Oscillations Predicts Visual Perception , 2009, The Journal of Neuroscience.

[22]  Jeffrey N. Rouder,et al.  Bayesian t tests for accepting and rejecting the null hypothesis , 2009, Psychonomic bulletin & review.

[23]  Á. Pascual-Leone,et al.  Spontaneous fluctuations in posterior alpha-band EEG activity reflect variability in excitability of human visual areas. , 2008, Cerebral cortex.

[24]  G. Karmos,et al.  Entrainment of Neuronal Oscillations as a Mechanism of Attentional Selection , 2008, Science.

[25]  R. Oostenveld,et al.  Nonparametric statistical testing of EEG- and MEG-data , 2007, Journal of Neuroscience Methods.

[26]  R. Ratcliff,et al.  1/f noise in human cognition: Is it ubiquitous, and what does it mean? , 2006, Psychonomic bulletin & review.

[27]  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.

[28]  R. Desimone,et al.  Gamma-band synchronization in visual cortex predicts speed of change detection , 2006, Nature.

[29]  C. Koch,et al.  The Continuous Wagon Wheel Illusion Is Associated with Changes in Electroencephalogram Power at ∼13 Hz , 2006, The Journal of Neuroscience.

[30]  C. Koch,et al.  Attention-driven discrete sampling of motion perception. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[31]  William A. Simpson,et al.  Illusory percepts of moving patterns due to discrete temporal sampling , 2005, Neuroscience Letters.

[32]  G. Buzsáki,et al.  Neuronal Oscillations in Cortical Networks , 2004, Science.

[33]  G. V. van Orden,et al.  Self-organization of cognitive performance. , 2003, Journal of experimental psychology. General.

[34]  Michael E. Hasselmo,et al.  A Proposed Function for Hippocampal Theta Rhythm: Separate Phases of Encoding and Retrieval Enhance Reversal of Prior Learning , 2002, Neural Computation.

[35]  Thomas E. Nichols,et al.  Nonparametric permutation tests for functional neuroimaging: A primer with examples , 2002, Human brain mapping.

[36]  J. Vrba,et al.  Signal processing in magnetoencephalography. , 2001, Methods.

[37]  C. Herrmann Human EEG responses to 1–100 Hz flicker: resonance phenomena in visual cortex and their potential correlation to cognitive phenomena , 2001, Experimental Brain Research.

[38]  J. Martinerie,et al.  The brainweb: Phase synchronization and large-scale integration , 2001, Nature Reviews Neuroscience.

[39]  Christa Neuper,et al.  Do brain oscillations of different frequencies indicate interaction between cortical areas in humans? , 2000, Neuroscience Letters.

[40]  F. Varela,et al.  Perception's shadow: long-distance synchronization of human brain activity , 1999, Nature.

[41]  D. Altman,et al.  Calculating correlation coefficients with repeated observations: Part 2—correlation between subjects , 1995, BMJ.

[42]  D. Altman,et al.  Statistics notes: Calculating correlation coefficients with repeated observations: Part 1—correlation within subjects , 1995 .

[43]  Ehud Zohary,et al.  Correlated neuronal discharge rate and its implications for psychophysical performance , 1994, Nature.

[44]  E. John,et al.  Perceptual framing and cortical alpha rhythm , 1981, Neuropsychologia.

[45]  J. M. Stroud THE FINE STRUCTURE OF PSYCHOLOGICAL TIME , 1967 .

[46]  I. Mészáros THE PHENOMENOLOGY OF INTERNAL TIME‐CONSCIOUSNESS , 1965 .

[47]  J. Ford,et al.  Relationships between pre-stimulus γ power and subsequent P300 and reaction time breakdown in schizophrenia. , 2011, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[48]  F. Varela,et al.  Measuring phase synchrony in brain signals , 1999, Human brain mapping.

[49]  F. H. Lopes da Silva,et al.  Computer-assisted EEG diagnosis: pattern recognition and brain mapping , 1998 .

[50]  D H Brainard,et al.  The Psychophysics Toolbox. , 1997, Spatial vision.

[51]  J. Bland,et al.  Calculating correlation coefficients with repeated observations: Part 1--Correlation within subjects. , 1995, BMJ.

[52]  William Chauvenet,et al.  A manual of spherical and practical astronomy , 1891 .