Harmonic Amplitude Summation for Frequency-tagging Analysis

Abstract In the approach of frequency tagging, stimuli that are presented periodically generate periodic responses of the brain. Following a transformation into the frequency domain, the brain's response is often evident at the frequency of stimulation, F, and its higher harmonics (2F, 3F, etc.). This approach is increasingly used in neuroscience, as it affords objective measures to characterize brain function. However, whether these specific harmonic frequency responses should be combined for analysis—and if so, how—remains an outstanding issue. In most studies, higher harmonic responses have not been described or were described only individually; in other studies, harmonics have been combined with various approaches, for example, averaging and root-mean-square summation. A rationale for these approaches in the context of frequency-based analysis principles and an understanding of how they relate to the brain's response amplitudes in the time domain have been missing. Here, with these elements addressed, the summation of (baseline-corrected) harmonic amplitude is recommended.

[1]  A. R. Rodrigues,et al.  Flicker ERGs representing chromaticity and luminance signals. , 2010, Investigative ophthalmology & visual science.

[2]  J. Masdeu,et al.  Human Cerebral Activation during Steady-State Visual-Evoked Responses , 2003, The Journal of Neuroscience.

[3]  Naotsugu Tsuchiya,et al.  From intermodulation components to visual perception and cognition-a review , 2019, NeuroImage.

[4]  D. P. Russell,et al.  Increased Synchronization of Neuromagnetic Responses during Conscious Perception , 1999, The Journal of Neuroscience.

[5]  B. Chemin,et al.  EEG time-warping to study non-strictly-periodic EEG signals related to the production of rhythmic movements , 2018, Journal of Neuroscience Methods.

[6]  I J Murray,et al.  Amplitude and phase variations of harmonic components in human achromatic and chromatic visual evoked potentials , 1996, Visual Neuroscience.

[7]  Arnaud Delorme,et al.  EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis , 2004, Journal of Neuroscience Methods.

[8]  P. Sieving,et al.  Submicrovolt flicker electroretinogram: cycle-by-cycle recording of multiple harmonics with statistical estimation of measurement uncertainty. , 1998, Investigative ophthalmology & visual science.

[9]  Alexandre Gramfort,et al.  Encoding of event timing in the phase of neural oscillations , 2014, NeuroImage.

[10]  N. Kazanina,et al.  Fast Periodic Visual Stimulation indexes preserved semantic memory in healthy ageing , 2020, Scientific Reports.

[11]  A. Norcia,et al.  Spatial frequency masking with the sweep-VEP , 1997, Vision Research.

[12]  André Mouraux,et al.  Fast periodic visual stimulation to study tool-selective processing in the human brain , 2018, Experimental Brain Research.

[13]  Matthias M. Müller,et al.  The neural signature of extracting emotional content from rapid visual streams at multiple presentation rates: A cross-laboratory study. , 2018, Psychophysiology.

[14]  Klaus-Robert Müller,et al.  Decoding of top-down cognitive processing for SSVEP-controlled BMI , 2016, Scientific Reports.

[15]  Jonathan Winawer,et al.  Asynchronous Broadband Signals Are the Principal Source of the BOLD Response in Human Visual Cortex , 2013, Current Biology.

[16]  Mark W Pettet,et al.  Abnormalities of coherent motion processing in strabismic amblyopia: Visual-evoked potential measurements. , 2008, Journal of vision.

[17]  Reinhold Scherer,et al.  Steady-state visual evoked potential (SSVEP)-based communication: impact of harmonic frequency components , 2005, Journal of neural engineering.

[18]  Mario Cebulla,et al.  Objective detection of auditory steady-state responses: comparison of one-sample and q-sample tests. , 2006, Journal of the American Academy of Audiology.

[19]  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.

[20]  Arjan Hillebrand,et al.  The temporal frequency tuning of human visual cortex investigated using synthetic aperture magnetometry , 2004, NeuroImage.

[21]  Barrie W. Jervis,et al.  A Fundamental Investigation of the Composition of Auditory Evoked Potentials , 1983, IEEE Transactions on Biomedical Engineering.

[22]  Bruno Rossion,et al.  Fast periodic stimulation (FPS): a highly effective approach in fMRI brain mapping , 2017, bioRxiv.

[23]  Matthias M. Müller,et al.  Effects of spatial selective attention on the steady-state visual evoked potential in the 20-28 Hz range. , 1998, Brain research. Cognitive brain research.

[24]  D. Spinelli,et al.  Spatiotemporal analysis of the cortical sources of the steady‐state visual evoked potential , 2007, Human brain mapping.

[25]  J. Fourier Théorie analytique de la chaleur , 2009 .

[26]  Bruno Rossion,et al.  Understanding individual face discrimination by means of fast periodic visual stimulation , 2014, Experimental Brain Research.

[27]  B. Rossion,et al.  Supra-additive contribution of shape and surface information to individual face discrimination as revealed by fast periodic visual stimulation. , 2014, Journal of vision.

[28]  Chris Daniel. Geisler,et al.  Average responses to clicks in man recorded by scalp electrodes , 1960 .

[29]  Michael A. Webster,et al.  Directional Visual Motion Is Represented in the Auditory and Association Cortices of Early Deaf Individuals , 2019, Journal of Cognitive Neuroscience.

[30]  T. Allison,et al.  Face-sensitive regions in human extrastriate cortex studied by functional MRI. , 1995, Journal of neurophysiology.

[31]  Chad S Duncan,et al.  Physiological correlates of watercolor effect. , 2014, Journal of the Optical Society of America. A, Optics, image science, and vision.

[32]  Talia L. Retter,et al.  Visual adaptation provides objective electrophysiological evidence of facial identity discrimination , 2016, Cortex.

[33]  Bruno Rossion,et al.  An objective electrophysiological marker of face individualisation impairment in acquired prosopagnosia with fast periodic visual stimulation , 2016, Neuropsychologia.

[34]  Marc M. Van Hulle,et al.  Decoding Steady-State Visual Evoked Potentials From Electrocorticography , 2018, Front. Neuroinform..

[35]  A. Elsner,et al.  Analysis of nonlinearities in the flicker ERG. , 1992, Optometry and vision science : official publication of the American Academy of Optometry.

[36]  Talia L. Retter,et al.  Understanding human individuation of unfamiliar faces with oddball fast periodic visual stimulation and electroencephalography , 2020, The European journal of neuroscience.

[37]  B. Rossion,et al.  Fast Periodic Visual Stimulation EEG Reveals Reduced Neural Sensitivity to Fearful Faces in Children with Autism , 2019, Journal of Autism and Developmental Disorders.

[38]  D. Regan,et al.  Colour coding of pattern responses in man investigated by evoked potential feedback and direct plot techniques , 1975, Vision Research.

[39]  Christian Keitel,et al.  Stimulus-Driven Brain Oscillations in the Alpha Range: Entrainment of Intrinsic Rhythms or Frequency-Following Response? , 2014, The Journal of Neuroscience.

[40]  Joonkoo Park,et al.  A neural basis for the visual sense of number and its development: A steady-state visual evoked potential study in children and adults , 2017, Developmental Cognitive Neuroscience.

[41]  Robert Burkard,et al.  The Auditory Steady-State Response: Generation, Recording, and Clinical Applications , 2009 .

[42]  A. Norcia,et al.  Methods for the identification of evoked response components in the frequency and combined time/frequency domains. , 1986, Electroencephalography and clinical neurophysiology.

[43]  Andreas Keil,et al.  Perceiving Threat In the Face of Safety: Excitation and Inhibition of Conditioned Fear in Human Visual Cortex , 2013, The Journal of Neuroscience.

[44]  Gilbert Strang,et al.  Computational Science and Engineering , 2007 .

[45]  T. Sejnowski,et al.  Dynamic Brain Sources of Visual Evoked Responses , 2002, Science.

[46]  Bruno Rossion,et al.  An objective method for measuring face detection thresholds using the sweep steady-state visual evoked response. , 2012, Journal of vision.

[47]  S. Heinrich,et al.  Frequency-domain analysis of fast oddball responses to visual stimuli: a feasibility study. , 2009, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[48]  C. Baker,et al.  Linear and nonlinear components of human electroretinogram. , 1984, Journal of neurophysiology.

[49]  Angelique C Paulk,et al.  Closed-Loop Behavioral Control Increases Coherence in the Fly Brain , 2015, The Journal of Neuroscience.

[50]  Bruno Rossion,et al.  Figures and figure supplements , 2014 .

[51]  D. Regan,et al.  Nonlinearity in human visual responses to two-dimensional patterns, and a limitation of fourier methods , 1987, Vision Research.

[52]  Steven W. Smith,et al.  The Scientist and Engineer's Guide to Digital Signal Processing , 1997 .

[53]  Bruno Rossion,et al.  A single glance at natural face images generate larger and qualitatively different category-selective spatio-temporal signatures than other ecologically-relevant categories in the human brain , 2016, NeuroImage.

[54]  Alex R. Wade,et al.  Evidence for an Optimal Algorithm Underlying Signal Combination in Human Visual Cortex , 2016, Cerebral cortex.

[55]  Jonathan D. Victor,et al.  The human visual evoked potential: Analysis of components due to elementary and complex aspects of form , 1985, Vision Research.

[56]  Bruno Rossion,et al.  A robust index of lexical representation in the left occipito-temporal cortex as evidenced by EEG responses to fast periodic visual stimulation , 2015, Neuropsychologia.

[57]  Peng Zhang,et al.  Binocular Rivalry Requires Visual Attention , 2011, Neuron.

[58]  Erol Basar,et al.  Functional aspects of evoked alpha and theta responses in humans and cats , 1994, Biological Cybernetics.

[59]  A. Troelstra Harmonic distortion in the frog's ERG and its possible relation to differences in latencies. , 1971, Vision research.

[60]  M CLYNES,et al.  DYNAMICS AND SPATIAL BEHAVIOR OF LIGHT EVOKED POTENTIALS, THEIR MODIFICATION UNDER HYPNOSIS, AND ON‐LINE CORRELATION IN RELATION TO RHYTHMIC COMPONENTS * , 1964, Annals of the New York Academy of Sciences.

[61]  S. Andersen,et al.  Behavioral performance follows the time course of neural facilitation and suppression during cued shifts of feature-selective attention , 2010, Proceedings of the National Academy of Sciences.

[62]  M. Carandini,et al.  Local Origin of Field Potentials in Visual Cortex , 2009, Neuron.

[63]  Jean-Yves Baudouin,et al.  Expertise for conspecific face individuation in the human brain , 2020, NeuroImage.

[64]  B. Rossion,et al.  The right hemispheric dominance for face perception in preschool children depends on the visual discrimination level , 2019, Developmental science.

[65]  W. Cobb,et al.  Cerebral Potentials evoked by Pattern Reversal and their Suppression in Visual Rivalry , 1967, Nature.

[66]  Tzyy-Ping Jung,et al.  High-speed spelling with a noninvasive brain–computer interface , 2015, Proceedings of the National Academy of Sciences.

[67]  Bruno Rossion,et al.  Tuning functions for automatic detection of brief changes of facial expression in the human brain , 2018, NeuroImage.

[68]  J. Atkinson,et al.  Reorganization of Global Form and Motion Processing during Human Visual Development , 2010, Current Biology.

[69]  C. Herrmann,et al.  Time–Frequency Analysis of Event-Related Potentials: A Brief Tutorial , 2013, Brain Topography.

[70]  B. Rossion,et al.  An objective neural signature of rapid perspective taking , 2017, Social cognitive and affective neuroscience.

[71]  C. Tyler,et al.  Movement adaptation in the visual evoked response , 1977, Experimental Brain Research.

[72]  Bruno Rossion,et al.  Uncovering the neural magnitude and spatio-temporal dynamics of natural image categorization in a fast visual stream , 2016, Neuropsychologia.

[73]  Justin M. Ales,et al.  The steady-state visual evoked potential in vision research: A review. , 2015, Journal of vision.

[74]  M. Bach,et al.  On the statistical significance of electrophysiological steady-state responses , 2004, Documenta Ophthalmologica.

[75]  D. Donker Harmonic composition and topographic distribution of responses to sine wave modulated light (SML), their reproducibility and their interhemispheric relationship. , 1975, Electroencephalography and clinical neurophysiology.

[76]  Jean-Louis Thonnard,et al.  EEG frequency tagging to explore the cortical activity related to the tactile exploration of natural textures , 2016, Scientific Reports.

[77]  J. Atkinson,et al.  Motion- and orientation-specific cortical responses in infancy , 2005, Vision Research.

[78]  C. Jacques,et al.  High test-retest reliability of a neural index of rapid automatic discrimination of unfamiliar individual faces , 2019, Journal of Vision.

[79]  Andrzej Cichocki,et al.  Steady State Visual Evoked Potentials in the Delta Range (0.5-5 Hz) , 2008, ICONIP.

[80]  A. Norcia,et al.  An objective signature for visual binding of face parts in the human brain. , 2013, Journal of vision.

[81]  Smith-Kettlewell Neural correlates of object-based attention , 2002 .

[82]  D. Regan Some characteristics of average steady-state and transient responses evoked by modulated light. , 1966, Electroencephalography and clinical neurophysiology.

[83]  M. Bach,et al.  Do's and don'ts in Fourier analysis of steady-state potentials , 2004, Documenta Ophthalmologica.

[84]  P. Suffczynski,et al.  On the Quantification of SSVEP Frequency Responses in Human EEG in Realistic BCI Conditions , 2013, PloS one.

[85]  B. Rossion,et al.  The effect of parametric stimulus size variation on individual face discrimination indexed by fast periodic visual stimulation , 2014, BMC Neuroscience.

[86]  Sven P. Heinrich,et al.  Permutation-Based Significance Tests for Multiharmonic Steady-State Evoked Potentials , 2009, IEEE Transactions on Biomedical Engineering.

[87]  G. Glover,et al.  Retinotopic organization in human visual cortex and the spatial precision of functional MRI. , 1997, Cerebral cortex.

[88]  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.

[89]  Matthias M. Müller,et al.  Human Neuroscience , 2022 .

[90]  B. Rossion,et al.  Maternal odor shapes rapid face categorization in the infant brain. , 2020, Developmental science.

[91]  A. Mouraux,et al.  Nociceptive Steady-State Evoked Potentials Elicited by Rapid Periodic Thermal Stimulation of Cutaneous Nociceptors , 2011, The Journal of Neuroscience.

[92]  Marcia Grabowecky,et al.  Attention induces synchronization-based response gain in steady-state visual evoked potentials , 2007, Nature Neuroscience.

[93]  Anil K. Seth,et al.  The power of human brain magnetoencephalographic signals can be modulated up or down by changes in an attentive visual task , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[94]  M. Eimer,et al.  Neural responses in a fast periodic visual stimulation paradigm reveal domain-general visual discrimination deficits in developmental prosopagnosia , 2020, Cortex.

[95]  Barry B. Lee,et al.  Simultaneous chromatic and luminance human electroretinogram responses , 2012, The Journal of physiology.

[96]  Marcia Grabowecky,et al.  Differential Roles of Frequency-following and Frequency-doubling Visual Responses Revealed by Evoked Neural Harmonics , 2011, Journal of Cognitive Neuroscience.

[97]  O. Gwinn,et al.  Hemispheric Asymmetries in Deaf and Hearing During Sustained Peripheral Selective Attention. , 2019, Journal of deaf studies and deaf education.

[98]  A. Cichocki,et al.  Steady-state visually evoked potentials: Focus on essential paradigms and future perspectives , 2010, Progress in Neurobiology.

[99]  Marina Schmid,et al.  An Introduction To The Event Related Potential Technique , 2016 .

[100]  Bruno Rossion,et al.  A rapid, objective and implicit measure of visual quantity discrimination , 2018, Neuropsychologia.

[101]  David Regan,et al.  A frequency domain technique for characterizing nonlinearities in biological systems , 1988 .

[102]  D. Regan Human brain electrophysiology: Evoked potentials and evoked magnetic fields in science and medicine , 1989 .

[103]  Christian Keysers,et al.  Visual masking and RSVP reveal neural competition , 2002, Trends in Cognitive Sciences.

[104]  Robert Shapley,et al.  Linear and nonlinear systems analysis of the visual system: Why does it seem so linear? A review dedicated to the memory of Henk Spekreijse , 2009, Vision Research.

[105]  Mark W Pettet,et al.  Development of the Spatial Organization and Dynamics of Lateral Interactions in the Human Visual System , 2003, The Journal of Neuroscience.

[106]  C Pantev,et al.  A high-precision magnetoencephalographic study of human auditory steady-state responses to amplitude-modulated tones. , 2000, The Journal of the Acoustical Society of America.

[107]  Susan L. Travis,et al.  Neural Responses to Target Features outside a Search Array Are Enhanced during Conjunction but Not Unique-Feature Search , 2014, The Journal of Neuroscience.

[108]  Floyd Ratliff,et al.  Intermodulation components of the visual evoked potential: Responses to lateral and superimposed stimuli , 2004, Biological cybernetics.

[109]  Bruno Rossion,et al.  A face-selective ventral occipito-temporal map of the human brain with intracerebral potentials , 2016, Proceedings of the National Academy of Sciences.

[110]  J. Tanaka,et al.  Investigating the perception of face identity in adults on the autism spectrum using behavioural and electrophysiological measures , 2019, Vision Research.

[111]  Anthony M. Norcia,et al.  Measurement of spatial contrast sensitivity with the swept contrast VEP , 1989, Vision Research.

[112]  Sven P. Heinrich,et al.  Some thoughts on the interpretation of steady-state evoked potentials , 2010, Documenta Ophthalmologica.

[113]  B. Rossion,et al.  Robust sensitivity to facial identity in the right human occipito-temporal cortex as revealed by steady-state visual-evoked potentials. , 2011, Journal of vision.

[114]  Yijun Wang,et al.  Brain-Computer Interfaces Based on Visual Evoked Potentials , 2008, IEEE Engineering in Medicine and Biology Magazine.

[115]  Gérard Dreyfus,et al.  Transient brain activity explains the spectral content of steady-state visual evoked potentials , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[116]  Serhat Ozekes,et al.  Harmonic analysis of steady-state visual evoked potentials in brain computer interfaces , 2020, Biomed. Signal Process. Control..

[117]  E. Adrian,et al.  Brain Rhythms , 1944, Nature.

[118]  David Poeppel,et al.  Interpretations of Frequency Domain Analyses of Neural Entrainment: Periodicity, Fundamental Frequency, and Harmonics , 2016, Front. Hum. Neurosci..

[119]  Mukund Patel Introduction to Electrical Power and Power Electronics , 2012 .

[120]  P. Sauseng,et al.  Neural correlates of visuo-spatial working memory encoding—An EEG study , 2011, Neuroscience Letters.

[121]  Uwe Hassler,et al.  Steady-state visually evoked potential correlates of object recognition memory , 2003 .

[122]  H Spekreijse,et al.  Rectification in the goldfish retina: analysis by sinusoidal and auxiliary stimulation. , 1969, Vision research.

[123]  Hans Strasburger,et al.  THE ANALYSIS OF STEADY STATE EVOKED POTENTIALS REVISITED , 1987 .

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

[125]  A. Compston The Berger rhythm: potential changes from the occipital lobes in man. , 2010, Brain : a journal of neurology.

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

[127]  L. H. Van Der Tweel,et al.  HUMAN VISUAL RESPONSES TO SINUSOIDALLY MODULATED LIGHT. , 1965, Electroencephalography and clinical neurophysiology.

[128]  J. Movshon,et al.  Receptive field organization of complex cells in the cat's striate cortex. , 1978, The Journal of physiology.

[129]  C.E. Davila,et al.  Optimal detection of visual evoked potentials , 1998, IEEE Transactions on Biomedical Engineering.

[130]  Bruno Rossion,et al.  Individual Differences in Face Identity Processing with Fast Periodic Visual Stimulation , 2017, Journal of Cognitive Neuroscience.

[131]  J. G. Dijk Human brain electrophysiology: Evoked potentials and evoked magnetic fields in science and medicine By D. Regan, Elsevier Science Publishing Co., New York, 1988, 672 pages, US $140.00 , 1990, Journal of the Neurological Sciences.

[132]  Bruno Rossion,et al.  Visual adaptation reveals an objective electrophysiological measure of high-level individual face discrimination , 2017, Scientific Reports.

[133]  Sven P. Heinrich,et al.  Adaptation dynamics in pattern-reversal visual evoked potentials , 2001, Documenta Ophthalmologica.

[134]  Bruno Rossion,et al.  Fast periodic presentation of natural images reveals a robust face-selective electrophysiological response in the human brain. , 2015, Journal of vision.

[135]  S. Makeig,et al.  A 40-Hz auditory potential recorded from the human scalp. , 1981, Proceedings of the National Academy of Sciences of the United States of America.

[136]  Bruno Rossion,et al.  Left cortical specialization for visual letter strings predicts rudimentary knowledge of letter-sound association in preschoolers , 2016, Proceedings of the National Academy of Sciences.

[137]  D Regan,et al.  Clinical investigation of lesions of the visual pathway: a new objective technique. , 1969, Journal of neurology, neurosurgery, and psychiatry.

[138]  J. Gross,et al.  Steady-State Visual Evoked Potentials Can Be Explained by Temporal Superposition of Transient Event-Related Responses , 2011, PloS one.

[139]  A. Norcia,et al.  An objective index of individual face discrimination in the right occipito-temporal cortex by means of fast periodic oddball stimulation , 2014, Neuropsychologia.

[140]  Donald C. Rojas,et al.  Test-Retest Reliability of the 40 Hz EEG Auditory Steady-State Response , 2014, PloS one.

[141]  Andreas Keil,et al.  Face-Evoked Steady-State Visual Potentials: Effects of Presentation Rate and Face Inversion , 2012, Front. Hum. Neurosci..

[142]  A. Norcia,et al.  An adaptive filter for steady-state evoked responses. , 1995, Electroencephalography and clinical neurophysiology.

[143]  Andreas Keil,et al.  Sleepless and desynchronized: Impaired inter trial phase coherence of steady-state potentials following sleep deprivation , 2019, NeuroImage.

[144]  E C Wong,et al.  Processing strategies for time‐course data sets in functional mri of the human brain , 1993, Magnetic resonance in medicine.

[145]  E. Peli,et al.  Signal to noise ratio considerations in the analysis of sweep visual-evoked potentials. , 1988, Applied Optics.

[146]  M. Webster,et al.  Asymmetric neural responses for facial expressions and anti-expressions , 2018, Neuropsychologia.

[147]  Talia L. Retter,et al.  All-or-none visual categorization in the human brain , 2019, bioRxiv.

[148]  L. H. van der Tweel,et al.  Relation between psychophysics and electrophysiology of flicker , 2004, Documenta Ophthalmologica.

[149]  J. Kremers,et al.  Rod-/L-cone and rod-/M-cone interactions in electroretinograms at different temporal frequencies , 2001, Visual Neuroscience.

[150]  Julio Artieda,et al.  Activation of Human Cerebral and Cerebellar Cortex by Auditory Stimulation at 40 Hz , 2002, The Journal of Neuroscience.

[151]  C. Lanczos,et al.  Some improvements in practical Fourier analysis and their application to x-ray scattering from liquids , 1942 .

[152]  L. Scullica,et al.  The fundamental and second harmonic of the photopic flicker electroretinogram: temporal frequency-dependent abnormalities in retinitis pigmentosa , 1999, Clinical Neurophysiology.

[153]  BsnNr C. Srorn,et al.  CLASSIFYING SIMPLE AND COMPLEX CELLS ON THE BASIS OF RESPONSE MODULATION , 2002 .

[154]  S A Hillyard,et al.  Feature-selective attention enhances color signals in early visual areas of the human brain , 2006, Proceedings of the National Academy of Sciences.

[155]  Benedikt Zoefel,et al.  The Involvement of Endogenous Neural Oscillations in the Processing of Rhythmic Input: More Than a Regular Repetition of Evoked Neural Responses , 2018, Front. Neurosci..

[156]  Xiaorong Gao,et al.  Design and implementation of a brain-computer interface with high transfer rates , 2002, IEEE Transactions on Biomedical Engineering.

[157]  G. Eaton Rapid processing. , 1961, Medical & biological illustration.

[158]  G. Sperling,et al.  Attentional modulation of SSVEP power depends on the network tagged by the flicker frequency. , 2006, Cerebral cortex.

[159]  R. Delgado,et al.  Steady-state analysis of auditory evoked potentials over a wide range of stimulus repetition rates: Profile in adults , 2011, International journal of audiology.

[160]  J Artieda,et al.  Topography of cortical activation differs for fundamental and harmonic frequencies of the steady-state visual-evoked responses. An EEG and PET H215O study. , 2007, Cerebral cortex.

[161]  Matthew J. Davidson,et al.  The SSVEP tracks attention, not consciousness, during perceptual filling-in , 2020, eLife.

[162]  S. Hillyard,et al.  Selective attention to stimulus location modulates the steady-state visual evoked potential. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[163]  Bruno Rossion,et al.  A steady-state visual evoked potential approach to individual face perception: Effect of inversion, contrast-reversal and temporal dynamics , 2012, NeuroImage.

[164]  E. Chadnova,et al.  Interocular interaction of contrast and luminance signals in human primary visual cortex , 2018, NeuroImage.

[165]  J D Victor,et al.  Two-frequency analysis of interactions elicited by Vernier stimuli , 2000, Visual Neuroscience.

[166]  Bruno Rossion,et al.  At a Single Glance: Fast Periodic Visual Stimulation Uncovers the Spatio-Temporal Dynamics of Brief Facial Expression Changes in the Human Brain , 2016, Cerebral cortex.

[167]  Bertrand Thirion,et al.  Phase delays within visual cortex shape the response to steady-state visual stimulation , 2011, NeuroImage.

[168]  J. Peirce,et al.  Measuring nonlinear signal combination using EEG. , 2017, Journal of vision.

[169]  Matthias M. Müller,et al.  Rapid processing of neutral and angry expressions within ongoing facial stimulus streams: Is it all about isolated facial features? , 2020, PloS one.

[170]  Sven P. Heinrich,et al.  Relating the steady-state visual evoked potential to single-stimulus responses derived from m-sequence stimulation , 2015, Documenta Ophthalmologica.

[171]  A. Norcia,et al.  Configural specificity of the lateral occipital cortex , 2010, Neuropsychologia.

[172]  Matthias M. Müller,et al.  Magnetoencephalographic recording of steadystate visual evoked cortical activity , 2005, Brain Topography.

[173]  Alex R. Wade,et al.  Cue-Invariant Networks for Figure and Background Processing in Human Visual Cortex , 2006, The Journal of Neuroscience.

[174]  James Gordon,et al.  Quantification and statistical analysis of the transient visual evoked potential to a contrast‐reversing pattern: A frequency‐domain approach , 2018, The European journal of neuroscience.