Brain noise estimation from MEG response to flickering visual stimulation

Abstract We consider the brain as an autonomous stochastic system, whose fundamental frequencies are locked to an external periodic stimulation. Taking into account that phase synchronization between brain response and stimulating signal is affected by noise, we propose a novel method for experimental estimation of brain noise by analyzing neurophysiological activity during perception of flickering visual stimuli. Using magnetoencephalography (MEG) we evaluate steady-state visual evoked fields (SSVEF) in the occipital cortex when subjects observe a square image with modulated brightness. Then, we calculate the probability distribution of the SSVEF phase fluctuations and compute its kurtosis. The higher kurtosis, the better the phase synchronization. Since kurtosis characterizes the distribution’s sharpness, we associate inverse kurtosis with brain noise which broadens this distribution. We found that the majority of subjects exhibited leptokurtic kurtosis (K > 3) with tails approaching zero more slowly than Gaussian. The results of this work may be useful for the development of efficient and accurate brain-computer interfaces to be adapted to individual features of every subject in accordance with his/her brain noise.

[1]  Massimo Riani,et al.  Visual Perception of Stochastic Resonance , 1997 .

[2]  Leslie G. Ungerleider,et al.  The neural systems that mediate human perceptual decision making , 2008, Nature Reviews Neuroscience.

[3]  Lauri Parkkonen,et al.  Early visual brain areas reflect the percept of an ambiguous scene , 2008, Proceedings of the National Academy of Sciences.

[4]  Alexander N. Pisarchik,et al.  Critical slowing down and noise-induced intermittency in bistable perception: bifurcation analysis , 2014, Biological Cybernetics.

[5]  W. Singer,et al.  Temporal binding and the neural correlates of sensory awareness , 2001, Trends in Cognitive Sciences.

[6]  P. Szendrő,et al.  Pink-noise behaviour of biosystems , 2001, European Biophysics Journal.

[7]  R Jaimes-Reátegui,et al.  Deterministic coherence resonance in coupled chaotic oscillators with frequency mismatch. , 2015, Physical review. E, Statistical, nonlinear, and soft matter physics.

[8]  Alexander E. Hramov,et al.  Coherence resonance in stimulated neuronal network , 2018 .

[9]  Philip L. Smith,et al.  A comparison of sequential sampling models for two-choice reaction time. , 2004, Psychological review.

[10]  G. Wilson,et al.  Steady state evoked responses: correlations with human cognition. , 1986, Psychophysiology.

[11]  R Jaimes-Reátegui,et al.  Experimental evidence of deterministic coherence resonance in coupled chaotic systems with frequency mismatch. , 2016, Physical review. E.

[12]  Alexander S. Ecker,et al.  On the Structure of Neuronal Population Activity under Fluctuations in Attentional State , 2015, The Journal of Neuroscience.

[13]  Xiaorong Gao,et al.  Frequency and Phase Mixed Coding in SSVEP-Based Brain--Computer Interface , 2011, IEEE Transactions on Biomedical Engineering.

[14]  Joseph Ciorciari,et al.  Steady-State Visually Evoked Potential topography associated with a visual vigilance task , 2005, Brain Topography.

[15]  R Jaimes-Reátegui,et al.  Synchronization of chaotic systems with coexisting attractors. , 2006, Physical review letters.

[16]  Vladimir Nedayvozov,et al.  Visual perception affected by motivation and alertness controlled by a noninvasive brain-computer interface , 2017, PloS one.

[17]  Alexander N. Pisarchik,et al.  Stochastic sensitivity of a bistable energy model for visual perception , 2017 .

[18]  John J. Foxe,et al.  Visual spatial attention tracking using high-density SSVEP data for independent brain-computer communication , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[19]  Philip L. Smith,et al.  Psychology and neurobiology of simple decisions , 2004, Trends in Neurosciences.

[20]  I. Merk,et al.  A stochastic model of multistable visual perception , 2002, Biological Cybernetics.

[21]  Matthias M. Müller,et al.  The time course of cortical facilitation during cued shifts of spatial attention , 1998, Nature Neuroscience.

[22]  Lauri Parkkonen,et al.  Human Neuromagnetic Steady-State Responses to Amplitude-Modulated Tones, Speech, and Music , 2014, Ear and hearing.

[23]  Steven A. Hillyard,et al.  Steady-State VEP and Attentional Visual Processing , 2003 .

[24]  Alexander S. Ecker,et al.  Attentional fluctuations induce shared variability in macaque primary visual cortex , 2017, Nature Communications.

[25]  Christian Keitel,et al.  Flicker-Driven Responses in Visual Cortex Change during Matched-Frequency Transcranial Alternating Current Stimulation , 2016, Front. Hum. Neurosci..

[26]  Fernando Maestú,et al.  Artificial neural network detects human uncertainty. , 2018, Chaos.

[27]  J. Maunsell,et al.  A Neuronal Population Measure of Attention Predicts Behavioral Performance on Individual Trials , 2010, The Journal of Neuroscience.

[28]  Vladimir A. Maksimenko,et al.  Increasing Human Performance by Sharing Cognitive Load Using Brain-to-Brain Interface , 2018, Front. Neurosci..

[29]  Christof Koch,et al.  Subthreshold voltage noise of rat neocortical pyramidal neurones , 2005, The Journal of physiology.

[30]  Michael N. Shadlen,et al.  Synchrony Unbound A Critical Evaluation of the Temporal Binding Hypothesis , 1999, Neuron.

[31]  J. Rinzel,et al.  Noise-induced alternations in an attractor network model of perceptual bistability. , 2007, Journal of neurophysiology.

[32]  Jasna Martinovic,et al.  High frequency oscillations as a correlate of visual perception. , 2011, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[33]  M. O. Zhuravlev,et al.  Experimental measurements of human brain noise intensity in perception of ambiguous images , 2016 .

[34]  Keiichi Kitajo,et al.  Behavioral stochastic resonance within the human brain. , 2003, Physical review letters.

[35]  Markus Bauer,et al.  No evidence for widespread synchronized networks in binocular rivalry: MEG frequency tagging entrains primarily early visual cortex. , 2008, Journal of vision.

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

[37]  Eero P. Simoncelli,et al.  Attention stabilizes the shared gain of V4 populations , 2015, eLife.

[38]  J J Vidal,et al.  Toward direct brain-computer communication. , 1973, Annual review of biophysics and bioengineering.

[39]  D. P. Russell,et al.  Investigating neural correlates of conscious perception by frequency-tagged neuromagnetic responses. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[40]  Y. Ejima,et al.  Estimation of the Timing of Human Visual Perception from Magnetoencephalography , 2006, The Journal of Neuroscience.

[41]  Xiao-Jing Wang.  Neural dynamics and circuit mechanisms of decision-making , 2012, Current Opinion in Neurobiology.

[42]  J. Lorenceau,et al.  Magnetoencephalographic signatures of visual form and motion binding , 2011, Brain Research.

[43]  Klaus Lehnertz,et al.  Stochastic qualifiers of epileptic brain dynamics. , 2007, Physical review letters.

[44]  G Calhoun,et al.  Brain-computer interfaces based on the steady-state visual-evoked response. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[45]  J. Maunsell,et al.  Using Neuronal Populations to Study the Mechanisms Underlying Spatial and Feature Attention , 2011, Neuron.

[46]  John Rinzel,et al.  Noise and adaptation in multistable perception: noise drives when to switch, adaptation determines percept choice. , 2014, Journal of vision.

[47]  U. Feudel,et al.  Control of multistability , 2014 .

[48]  Marc M. Van Hulle,et al.  Multichannel Decoding for Phase-Coded SSVEP Brain-Computer Interface , 2012, Int. J. Neural Syst..

[49]  Olivier David,et al.  Waves of consciousness: ongoing cortical patterns during binocular rivalry , 2004, NeuroImage.

[50]  Mahmut Ozer,et al.  Autapse-induced multiple coherence resonance in single neurons and neuronal networks , 2016, Scientific Reports.

[51]  Gustavo Deco,et al.  Stochastic dynamics as a principle of brain function , 2009, Progress in Neurobiology.

[52]  V Di Lollo,et al.  Inverse-intensity effect in duration of visible persistence. , 1995, Psychological bulletin.

[53]  Carney Landis,et al.  Something about Flicker-Fusion , 1951 .

[54]  C. Mirasso,et al.  System size coherence resonance in coupled FitzHugh-Nagumo models , 2003 .

[55]  Anastasiya E. Runnova,et al.  Classifying the Perceptual Interpretations of a Bistable Image Using EEG and Artificial Neural Networks , 2017, Front. Neurosci..

[56]  Jochen Braun,et al.  Bistable Perception Modeled as Competing Stochastic Integrations at Two Levels , 2009, PLoS Comput. Biol..