A physical neural mass model framework for the analysis of oscillatory generators from laminar electrophysiological recordings
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A. Bastos | G. Deco | G. Ruffini | R. Sanchez-Todo | E. Santarnecchi | Borja Mercadal | E. L. Sola | E. Miller
[1] F. Wendling,et al. Towards a mesoscale physical modeling framework for stereotactic-EEG recordings , 2022, bioRxiv.
[2] J. García-Ojalvo,et al. Comparison between an exact and a heuristic neural mass model with second-order synapses , 2022, bioRxiv.
[3] F. Wendling,et al. A personalizable autonomous neural mass model of epileptic seizures , 2021, bioRxiv.
[4] Rick A Adams,et al. Computational Modeling of Electroencephalography and Functional Magnetic Resonance Imaging Paradigms Indicates a Consistent Loss of Pyramidal Cell Synaptic Gain in Schizophrenia , 2021, Biological Psychiatry.
[5] Andreas Daffertshofer,et al. On the Validity of Neural Mass Models , 2021, Frontiers in Computational Neuroscience.
[6] A. Thiele,et al. Stimulus dependence of directed information exchange between cortical layers in macaque V1 , 2020, bioRxiv.
[7] Emiliano Santarnecchi,et al. EEG spectral power abnormalities and their relationship with cognitive dysfunction in patients with Alzheimer's disease and type 2 diabetes , 2019, Neurobiology of Aging.
[8] Johannes L. Schönberger,et al. SciPy 1.0: fundamental algorithms for scientific computing in Python , 2019, Nature Methods.
[9] Fabrice Wendling,et al. COALIA: A Computational Model of Human EEG for Consciousness Research , 2019, bioRxiv.
[10] Stefan Everling,et al. Alpha Oscillations Modulate Preparatory Activity in Marmoset Area 8Ad , 2019, The Journal of Neuroscience.
[11] Gustavo Deco,et al. Personalization of hybrid brain models from neuroimaging and electrophysiology data , 2018, bioRxiv.
[12] Holly Rossiter,et al. Lamina-specific cortical dynamics in human visual and sensorimotor cortices , 2018, eLife.
[13] Earl K. Miller,et al. Working Memory 2.0 , 2018, Neuron.
[14] Xiao-Jing Wang,et al. Engagement of Pulvino-cortical Feedforward and Feedback Pathways in Cognitive Computations , 2018, Neuron.
[15] Bradley Voytek,et al. Cycle-by-cycle analysis of neural oscillations , 2018, bioRxiv.
[16] Daniel Soudry,et al. Bifurcation analysis of two coupled Jansen-Rit neural mass models , 2018, PloS one.
[17] Gaute T. Einevoll,et al. Multimodal Modeling of Neural Network Activity: Computing LFP, ECoG, EEG, and MEG Signals With LFPy 2.0 , 2018, bioRxiv.
[18] Sarah Feldt Muldoon,et al. Personalized brain network models for assessing structure–function relationships , 2018, Current Opinion in Neurobiology.
[19] Earl K. Miller,et al. Laminar recordings in frontal cortex suggest distinct layers for maintenance and control of working memory , 2018, Proceedings of the National Academy of Sciences.
[20] O. Sporns,et al. Network neuroscience , 2017, Nature Neuroscience.
[21] Karl J. Friston,et al. Linking canonical microcircuits and neuronal activity: Dynamic causal modelling of laminar recordings , 2017, NeuroImage.
[22] Wim Fias,et al. Brain networks under attack: robustness properties and the impact of lesions. , 2016, Brain : a journal of neurology.
[23] L. Mucke,et al. Network abnormalities and interneuron dysfunction in Alzheimer disease , 2016, Nature Reviews Neuroscience.
[24] Viktor K. Jirsa,et al. Transcranial direct current stimulation changes resting state functional connectivity: A large-scale brain network modeling study , 2016, NeuroImage.
[25] Xiao-Jing Wang,et al. Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex , 2016, Science Advances.
[26] Roberto C. Sotero,et al. Topology, Cross-Frequency, and Same-Frequency Band Interactions Shape the Generation of Phase-Amplitude Coupling in a Neural Mass Model of a Cortical Column , 2016, bioRxiv.
[27] Sarah Feldt Muldoon,et al. Stimulation-Based Control of Dynamic Brain Networks , 2016, PLoS Comput. Biol..
[28] C. Schroeder,et al. Laminar Profile and Physiology of the α Rhythm in Primary Visual, Auditory, and Somatosensory Regions of Neocortex , 2015, The Journal of Neuroscience.
[29] Ernest Montbri'o,et al. Macroscopic description for networks of spiking neurons , 2015, 1506.06581.
[30] J. Schall,et al. Microcircuitry of agranular frontal cortex: contrasting laminar connectivity between occipital and frontal areas. , 2015, Journal of neurophysiology.
[31] P. Roelfsema,et al. Alpha and gamma oscillations characterize feedback and feedforward processing in monkey visual cortex , 2014, Proceedings of the National Academy of Sciences.
[32] H. Kennedy,et al. Visual Areas Exert Feedforward and Feedback Influences through Distinct Frequency Channels , 2014, Neuron.
[33] G. Woodman,et al. Microcircuitry of Agranular Frontal Cortex: Testing the Generality of the Canonical Cortical Microcircuit , 2014, The Journal of Neuroscience.
[34] S. Jones,et al. Distinguishing mechanisms of gamma frequency oscillations in human current source signals using a computational model of a laminar neocortical network , 2013, Front. Hum. Neurosci..
[35] Nikola T. Markov,et al. Cortical High-Density Counterstream Architectures , 2013, Science.
[36] Giulio Ruffini,et al. The electric field in the cortex during transcranial current stimulation , 2013, NeuroImage.
[37] F. Wendling,et al. From Oscillatory Transcranial Current Stimulation to Scalp EEG Changes: A Biophysical and Physiological Modeling Study , 2013, PloS one.
[38] Adam Kohn,et al. Laminar dependence of neuronal correlations in visual cortex. , 2013, Journal of neurophysiology.
[39] D. Leopold,et al. Layer-Specific Entrainment of Gamma-Band Neural Activity by the Alpha Rhythm in Monkey Visual Cortex , 2012, Current Biology.
[40] Karl J. Friston,et al. Canonical Microcircuits for Predictive Coding , 2012, Neuron.
[41] Chun-I Yeh,et al. Laminar analysis of visually evoked activity in the primary visual cortex , 2012, Proceedings of the National Academy of Sciences.
[42] C. Koch,et al. The origin of extracellular fields and currents — EEG, ECoG, LFP and spikes , 2012, Nature Reviews Neuroscience.
[43] M. Goodfellow. Spatio-temporal Modelling and Analysis of Epileptiform EEG , 2011 .
[44] Pierre Mégevand,et al. Functional Development of Large-Scale Sensorimotor Cortical Networks in the Brain , 2011, The Journal of Neuroscience.
[45] R. Desimone,et al. Laminar differences in gamma and alpha coherence in the ventral stream , 2011, Proceedings of the National Academy of Sciences.
[46] C. Schroeder,et al. Neuronal Mechanisms and Attentional Modulation of Corticothalamic Alpha Oscillations , 2011, The Journal of Neuroscience.
[47] Gaute T. Einevoll,et al. Inverse Current Source Density Method in Two Dimensions: Inferring Neural Activation from Multielectrode Recordings , 2011, Neuroinformatics.
[48] Amir Shmuel,et al. Anatomically-constrained effective connectivity among layers in a cortical column modeled and estimated from local field potentials. , 2010, Journal of integrative neuroscience.
[49] P. Benquet,et al. Computational modeling of high-frequency oscillations at the onset of neocortical partial seizures: From ‘altered structure’ to ‘dysfunction’ , 2010, NeuroImage.
[50] Ying Zheng,et al. A Dynamic Causal Model of the Coupling Between Pulse Stimulation and Neural Activity , 2009, Neural Computation.
[51] P. Lefèbvre,et al. Dynamic Labour Supply Effects of Childcare Subsidies: Evidence from a Canadian Natural Experiment on Low-Fee Universal Child Care , 2009 .
[52] Anders M. Dale,et al. Estimation of Thalamocortical and Intracortical Network Models from Joint Thalamic Single-Electrode and Cortical Laminar-Electrode Recordings in the Rat Barrel System , 2009, PLoS Comput. Biol..
[53] S. Epstein,et al. Gamma oscillations mediate stimulus competition and attentional selection in a cortical network model , 2008, Proceedings of the National Academy of Sciences.
[54] C. Schroeder,et al. Neuronal Mechanisms of Cortical Alpha Oscillations in Awake-Behaving Macaques , 2008, The Journal of Neuroscience.
[55] A Constructive Mean-Field Analysis of Multi-Population Neural Networks with Random Synaptic Weights and Stochastic Inputs , 2008, Front. Comput. Neurosci..
[56] Karl J. Friston,et al. Bayesian estimation of synaptic physiology from the spectral responses of neural masses , 2008, NeuroImage.
[57] Karl J. Friston,et al. A neural mass model for MEG/EEG: coupling and neuronal dynamics , 2003, NeuroImage.
[58] A. Draguhn,et al. Cellular and Network Mechanisms Underlying Spontaneous Sharp Wave–Ripple Complexes in Mouse Hippocampal Slices , 2003, The Journal of physiology.
[59] R. Guillery,et al. On the actions that one nerve cell can have on another: distinguishing "drivers" from "modulators". , 1998, Proceedings of the National Academy of Sciences of the United States of America.
[60] Ben H. Jansen,et al. Electroencephalogram and visual evoked potential generation in a mathematical model of coupled cortical columns , 1995, Biological Cybernetics.
[61] J. Fermaglich. Electric Fields of the Brain: The Neurophysics of EEG , 1982 .
[62] F. H. Lopes da Silva,et al. Model of brain rhythmic activity , 1974, Kybernetik.
[63] Cessac Bruno,et al. A constructive mean-field analysis of multi population neural networks with random synaptic weights , 2009 .
[64] Olivier Faugeras,et al. Analysis of Jansen's model of a single cortical column , 2006 .
[65] Ben H. Jansen,et al. A neurophysiologically-based mathematical model of flash visual evoked potentials , 2004, Biological Cybernetics.
[66] U. Mitzdorf. Current source-density method and application in cat cerebral cortex: investigation of evoked potentials and EEG phenomena. , 1985, Physiological reviews.
[67] A. J. Hermans,et al. A model of the spatial-temporal characteristics of the alpha rhythm , 1982 .
[68] A. J. Hermans,et al. A model of the spatial-temporal characteristics of the alpha rhythm. , 1982, Bulletin of mathematical biology.
[69] F. H. Lopes da Silva,et al. Models of neuronal populations: the basic mechanisms of rhythmicity. , 1976, Progress in brain research.
[70] David A. Leopold,et al. Frontiers in Systems Neuroscience Systems Neuroscience , 2022 .