Alpha and alpha-beta phase synchronization mediate the recruitment of the visuospatial attention network through the Superior Longitudinal Fasciculus

ABSTRACT It is well known that attentional selection of relevant information relies on local synchronization of alpha band neuronal oscillations in visual cortices for inhibition of distracting inputs. Additionally, evidence for long‐range coupling of neuronal oscillations between visual cortices and regions engaged in the anticipation of upcoming stimuli has been more recently provided. Nevertheless, on the one hand the relation between long‐range functional coupling and anatomical connections is still to be assessed, and, on the other hand, the specific role of the alpha and beta frequency bands in the different processes underlying visuo‐spatial attention still needs further clarification. We address these questions using measures of linear (frequency‐specific) and nonlinear (cross‐frequency) phase‐synchronization in a cohort of 28 healthy subjects using magnetoencephalography. We show that alpha band phase‐synchronization is modulated by the orienting of attention according to a parieto‐occipital top‐down mechanism reflecting behavior, and its hemispheric asymmetry is predicted by volume's asymmetry of specific tracts of the Superior‐Longitudinal‐Fasciculus. We also show that a network comprising parietal regions and the right putative Frontal‐Eye‐Field, but not the left, is recruited in the deployment of spatial attention through an alpha‐beta cross‐frequency coupling. Overall, we demonstrate that the visuospatial attention network features subsystems indexed by characteristic spectral fingerprints, playing different functional roles in the anticipation of upcoming stimuli and with diverse relation to fiber tracts. HIGHLIGHTSOrienting visuo‐spatial attention modulates parieto‐occipital alpha synchronization.Hemispheric asymmetry of alpha connectivity is predicted by asymmetry of SLF.Hemispheric asymmetry of alpha connectivity reflects subject's performance.Alpha‐beta cross‐frequency coupling indexes attention deployment but not orienting.

[1]  G. V. Simpson,et al.  Anticipatory Biasing of Visuospatial Attention Indexed by Retinotopically Specific α-Bank Electroencephalography Increases over Occipital Cortex , 2000, The Journal of Neuroscience.

[2]  M. Corbetta,et al.  Frontoparietal Cortex Controls Spatial Attention through Modulation of Anticipatory Alpha Rhythms , 2009, The Journal of Neuroscience.

[3]  Guido Nolte,et al.  Perceptual Integration Deficits in Autism Spectrum Disorders Are Associated with Reduced Interhemispheric Gamma-Band Coherence , 2015, The Journal of Neuroscience.

[4]  H. Kennedy,et al.  Visual Areas Exert Feedforward and Feedback Influences through Distinct Frequency Channels , 2014, Neuron.

[5]  Kostas I. Nikolopoulos,et al.  The Multivariate θ-method , 2019, Forecasting with the Theta Method.

[6]  M. Raichle,et al.  On the role of the corpus callosum in interhemispheric functional connectivity in humans , 2017, Proceedings of the National Academy of Sciences.

[7]  Heiner Deubel,et al.  Deployment of visual attention before sequences of goal-directed hand movements , 2006, Vision Research.

[8]  K. Müller,et al.  Robustly estimating the flow direction of information in complex physical systems. , 2007, Physical review letters.

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

[10]  T. Sejnowski,et al.  Correlated neuronal activity and the flow of neural information , 2001, Nature Reviews Neuroscience.

[11]  A. Engel,et al.  Intrinsic Coupling Modes: Multiscale Interactions in Ongoing Brain Activity , 2013, Neuron.

[12]  S. Kastner,et al.  FEF-Controlled Alpha Delay Activity Precedes Stimulus-Induced Gamma-Band Activity in Visual Cortex , 2017, The Journal of Neuroscience.

[13]  Guido Nolte,et al.  Resting-state theta-band connectivity and verbal memory in schizophrenia and in the high-risk state , 2015, Schizophrenia Research.

[14]  T. Klingberg,et al.  Combined analysis of DTI and fMRI data reveals a joint maturation of white and grey matter in a fronto-parietal network. , 2003, Brain research. Cognitive brain research.

[15]  A. Engel,et al.  Neuronal Synchronization along the Dorsal Visual Pathway Reflects the Focus of Spatial Attention , 2008, Neuron.

[16]  Guanyu Liu,et al.  Frontal eye field involvement in sustaining visual attention: Evidence from transcranial magnetic stimulation , 2015, NeuroImage.

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

[18]  P. Fries Rhythms for Cognition: Communication through Coherence , 2015, Neuron.

[19]  Seungjin Choi,et al.  Independent Component Analysis , 2009, Handbook of Natural Computing.

[20]  M. Catani,et al.  A lateralized brain network for visuospatial attention , 2011, Nature Neuroscience.

[21]  Robert Oostenveld,et al.  Online and offline tools for head movement compensation in MEG , 2013, NeuroImage.

[22]  Á. Pascual-Leone,et al.  α-Band Electroencephalographic Activity over Occipital Cortex Indexes Visuospatial Attention Bias and Predicts Visual Target Detection , 2006, The Journal of Neuroscience.

[23]  Manuel Schabus,et al.  A shift of visual spatial attention is selectively associated with human EEG alpha activity , 2005, The European journal of neuroscience.

[24]  Jon Driver,et al.  Visual Selection and the Human Frontal Eye Fields: Effects of Frontal Transcranial Magnetic Stimulation on Partial Report Analyzed by Bundesen's Theory of Visual Attention , 2011, The Journal of Neuroscience.

[25]  L. M. Ward,et al.  From local inhibition to long-range integration: A functional dissociation of alpha-band synchronization across cortical scales in visuospatial attention , 2009, Brain Research.

[26]  W. Singer,et al.  Dynamic predictions: Oscillations and synchrony in top–down processing , 2001, Nature Reviews Neuroscience.

[27]  J Gross,et al.  REPRINTS , 1962, The Lancet.

[28]  G. Nolte The magnetic lead field theorem in the quasi-static approximation and its use for magnetoencephalography forward calculation in realistic volume conductors. , 2003, Physics in medicine and biology.

[29]  J. Palva,et al.  Discovering oscillatory interaction networks with M/EEG: challenges and breakthroughs , 2012, Trends in Cognitive Sciences.

[30]  P. Fries A mechanism for cognitive dynamics: neuronal communication through neuronal coherence , 2005, Trends in Cognitive Sciences.

[31]  Tzyy-Ping Jung,et al.  Independent Component Analysis of Electroencephalographic Data , 1995, NIPS.

[32]  Karl J. Friston,et al.  Multisubject fMRI Studies and Conjunction Analyses , 1999, NeuroImage.

[33]  G. V. Simpson,et al.  Dynamic Activation of Frontal, Parietal, and Sensory Regions Underlying Anticipatory Visual Spatial Attention , 2011, The Journal of Neuroscience.

[34]  Robert Desimone,et al.  Pulvinar-Cortex Interactions in Vision and Attention , 2016, Neuron.

[35]  W. Drongelen,et al.  Localization of brain electrical activity via linearly constrained minimum variance spatial filtering , 1997, IEEE Transactions on Biomedical Engineering.

[36]  Juha Silvanto,et al.  Stimulation of the human frontal eye fields modulates sensitivity of extrastriate visual cortex. , 2006, Journal of neurophysiology.

[37]  Y. Saalmann,et al.  The Pulvinar Regulates Information Transmission Between Cortical Areas Based on Attention Demands , 2012, Science.

[38]  A. Walden,et al.  Spectral analysis for physical applications : multitaper and conventional univariate techniques , 1996 .

[39]  Robert Oostenveld,et al.  Visual areas exert feedforward and feedback influences through distinct frequency channels , 2014 .

[40]  D. Louis Collins,et al.  Unbiased average age-appropriate atlases for pediatric studies , 2011, NeuroImage.

[41]  J. Schoffelen,et al.  Source connectivity analysis with MEG and EEG , 2009, Human brain mapping.

[42]  D. Robinson,et al.  Behavioral enhancement of visual responses in monkey cerebral cortex. I. Modulation in posterior parietal cortex related to selective visual attention. , 1981, Journal of neurophysiology.

[43]  J. Matias Palva,et al.  High-alpha band synchronization across frontal, parietal and visual cortex mediates behavioral and neuronal effects of visuospatial attention , 2017, NeuroImage.

[44]  Nicholas A. Steinmetz,et al.  Frontal eye field , 2012, Scholarpedia.

[45]  Leslie G. Ungerleider,et al.  Mechanisms of visual attention in the human cortex. , 2000, Annual review of neuroscience.

[46]  H H Donaldson,et al.  LOCALIZATION IN THE BRAIN. , 1884, Science.

[47]  Guido Nolte,et al.  Estimating true brain connectivity from EEG/MEG data invariant to linear and static transformations in sensor space , 2012, NeuroImage.

[48]  Timothy Edward John Behrens,et al.  Frontoparietal Structural Connectivity Mediates the Top-Down Control of Neuronal Synchronization Associated with Selective Attention , 2015, PLoS biology.

[49]  Adrian K. C. Lee,et al.  Attention Drives Synchronization of Alpha and Beta Rhythms between Right Inferior Frontal and Primary Sensory Neocortex , 2015, The Journal of Neuroscience.

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

[51]  Abraham Z. Snyder,et al.  Frequency specific interactions of MEG resting state activity within and across brain networks as revealed by the multivariate interaction measure , 2013, NeuroImage.

[52]  Robert Oostenveld,et al.  FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data , 2010, Comput. Intell. Neurosci..

[53]  Filippo Zappasodi,et al.  Resilience and cross-network connectivity: A neural model for post-trauma survival , 2017, Progress in Neuro-Psychopharmacology and Biological Psychiatry.

[54]  Jörn M. Horschig,et al.  Directed Communication between Nucleus Accumbens and Neocortex in Humans Is Differentially Supported by Synchronization in the Theta and Alpha Band , 2015, PloS one.

[55]  Tomás Paus,et al.  Transcranial Magnetic Stimulation of the Human Frontal Eye ®eld Facilitates Visual Awareness , 2022 .

[56]  Mark W. Woolrich,et al.  A symmetric multivariate leakage correction for MEG connectomes , 2015, NeuroImage.

[57]  E. Miller,et al.  Response to Comment on "Top-Down Versus Bottom-Up Control of Attention in the Prefrontal and Posterior Parietal Cortices" , 2007, Science.

[58]  M. Corbetta,et al.  Control of goal-directed and stimulus-driven attention in the brain , 2002, Nature Reviews Neuroscience.

[59]  Juan L. P. Soto,et al.  A multivariate method for estimating cross-frequency neuronal interactions and correcting linear mixing in MEG data, using canonical correlations , 2016, Journal of Neuroscience Methods.

[60]  O. Jensen,et al.  Shaping Functional Architecture by Oscillatory Alpha Activity: Gating by Inhibition , 2010, Front. Hum. Neurosci..

[61]  C. L. Nikias,et al.  Higher-order spectra analysis : a nonlinear signal processing framework , 1993 .

[62]  Terrence J. Sejnowski,et al.  An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.

[63]  Guido Nolte,et al.  Univariate normalization of bispectrum using Hölder's inequality , 2014, Journal of Neuroscience Methods.

[64]  N. Tzourio-Mazoyer,et al.  Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain , 2002, NeuroImage.

[65]  M. Hallett,et al.  Identifying true brain interaction from EEG data using the imaginary part of coherency , 2004, Clinical Neurophysiology.

[66]  Paul Tiesinga,et al.  Oscillatory mechanisms of feedforward and feedback visual processing , 2015, Trends in Neurosciences.

[67]  C. Tallon-Baudry,et al.  Neural Dissociation between Visual Awareness and Spatial Attention , 2008, The Journal of Neuroscience.

[68]  C. Almli,et al.  Unbiased nonlinear average age-appropriate brain templates from birth to adulthood , 2009, NeuroImage.

[69]  V. V. Nikulin,et al.  Phase synchronization between alpha and beta oscillations in the human electroencephalogram , 2006, Neuroscience.

[70]  Guido Nolte,et al.  Third order spectral analysis robust to mixing artifacts for mapping cross-frequency interactions in EEG/MEG , 2014, NeuroImage.

[71]  Guido Nolte,et al.  Disclosing large-scale directed functional connections in MEG with the multivariate phase slope index , 2018, NeuroImage.

[72]  Guido Nolte,et al.  Bispectral pairwise interacting source analysis for identifying systems of cross-frequency interacting brain sources from electroencephalographic or magnetoencephalographic signals. , 2016, Physical review. E.