Neurological disease and cognitive dynamics (II): Neural oscillations and cognitive dynamics

HAN Fang; FAN Denggui; ZHANG Liyuan; WANG Qingyun; GU Xiaochun; WANG Zhijie

doi:10.6052/1000-0992-21-065

Volume 52 Issue 3

Sep. 2022

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Article Navigation > Advances in Mechanics > 2022 > 52(3): 587-622

Han F, Fan D G, Zhang L Y, Wang Q Y, Gu X C, Wang Z J. Neurological disease and cognitive dynamics (II): Neural oscillations and cognitive dynamics. Advances in Mechanics, 2022, 52(3): 587-622 doi: 10.6052/1000-0992-21-065

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Han F, Fan D G, Zhang L Y, Wang Q Y, Gu X C, Wang Z J. Neurological disease and cognitive dynamics (II): Neural oscillations and cognitive dynamics. Advances in Mechanics, 2022, 52(3): 587-622 doi: 10.6052/1000-0992-21-065

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Neurological disease and cognitive dynamics (II): Neural oscillations and cognitive dynamics

doi: 10.6052/1000-0992-21-065

1.
College of Information Science and Technology, Donghua University, Shanghai 201620, China
2.
School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China
3.
Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
4.
School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China
5.
Shanghai Dianji University, Shanghai, 200245, China

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Corresponding author: nmqingyun@163.com
Received Date: 2021-12-13
Accepted Date: 2022-01-19

Available Online: 2022-01-19

Publish Date: 2022-09-25

Abstract

Abstract

The brain nervous system has various oscillatory rhythms, from slow to fast. These rhythmic oscillations are believed to be involved in the realization of various brain functions. The high-frequency Gamma synchronous oscillations are considered to be most related to the cognitive functions of the brain. In this review paper, the research progress of Gamma oscillations and their functions in biological experiments is expounded. Then, concerning the biological observation that the frequency of Gamma oscillations sensitively depends on the characteristics of external stimuli, the dynamical modeling work on the variable-frequency Gamma oscillations and the cognitive functions based on neural network models is also expounded. In this paper, the generation mechanisms of variable-frequency Gamma oscillation dynamics regulated by visual stimuli are explained, and a neurocognitive mechanism of global enhancement of firing rate contrast based on synchronous inhibition is proposed. The research results are helpful to understand the generation mechanisms of synchronous oscillations of nervous system and the cognitive functions and lay a foundation for the study of brain working mechanisms of cognitive activities and brain-like intelligence.
- neural oscillations,
- Gamma oscillations dynamics,
- cognitive mechanisms,
- stimulus regulation,
- variable frequency,
- neural network model

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References(143)

References

Adjamian P, Hadjipapas A, Barnes G R, et al. 2008. Induced Gamma activity in primary visual cortex is related to luminance and not color contrast: an MEG study. Journal of Vision, 8: 1-7. doi: 10.1167/8.7.1

Adrian E D. 1935. Discharge frequencies in the cerebral and cerebellar cortex. Proceedings of the Physical Society, 83: 32-33.

Adrian E D. 1942. Olfactory reactions in the brain of the hedgehog. The Journal of Physiology, 100: 459-473. doi: 10.1113/jphysiol.1942.sp003955

Aoyagi T, Kang Y, Terada N, et al. 2002. The role of Ca²⁺ dependent cationic current in generating Gamma frequency rhythmic bursts: modeling study. Neuroscience, 115: 1127-1138. doi: 10.1016/S0306-4522(02)00537-7

Bastos A M, Briggs F, Alitto H J, et al. 2014. Simultaneous recordings from the primary visual cortex and lateral geniculate nucleus reveal rhythmic interactions and a cortical source for Gamma-band. Journal of Neuroscience, 34: 7639-7644. doi: 10.1523/JNEUROSCI.4216-13.2014

Bartos M, Vida I, Frotscher M, et al. 2002. Fast synaptic inhibition promotes synchronized Gamma oscillations in hippocampal interneuron networks. Proceedings of the National Academy of Sciences of the United States of America, 99: 13222-13227. doi: 10.1073/pnas.192233099

Bartos M, Vida I, Jonas P. 2007. Synaptic mechanisms of synchronized Gamma oscillations in inhibitory interneuron networks. Nature Reviews Neuroscience, 8: 45-56. doi: 10.1038/nrn2044

Bathellier B, Lagier S, Faure P, et al. 2006. Circuit properties generating Gamma oscillations in a network model of the olfactory bulb. Journal of Neurophysiology, 95: 2678-2691. doi: 10.1152/jn.01141.2005

Bathellier B, Carleton A, Gerstner W. 2008. Gamma oscillations in a nonlinear regime: a minimal model approach using heterogeneous Integrate-and-Fire networks. Neural Computation, 20: 2973-3002. doi: 10.1162/neco.2008.11-07-636

Bauer M, Stenner M-P, Friston K J, Dolan R J. 2014. Attentional modulation of Alpha/Beta and Gamma oscillations reflect functionally distinct processes. Journal of Neuroscience, 34: 16117-16125. doi: 10.1523/JNEUROSCI.3474-13.2014

Bear M F, Connors B W, Paradiso M A. 2004. Neuroscience: Exploring the Brain. Beijing: High Education Press

Bitzenhofer S H, Popplau J A, Hanganu-Opatz I. 2020. Gamma activity accelerates during prefrontal development. Elife, 9: e56795. doi: 10.7554/eLife.56795

Bland B, Brian H. 1986. The physiology and pharmacology of hippocampal formation Theta rhythms. Progrss in Neurobiology, 26: 1-54. doi: 10.1016/0301-0082(86)90019-5

Borgers C, Kopell N J. 2008. Gamma oscillations and stimulus selection. Neural Computation, 20: 383-414. doi: 10.1162/neco.2007.07-06-289

Borgers C, Epstein S, Kopell N J. 2008. Gamma oscillations mediate stimulus competition and attentional selection in a cortical network model. Proceedings of the National Academy of Sciences of the United States of America, 105: 18023-18028. doi: 10.1073/pnas.0809511105

Bouyer J, Montaron M, Rougeul A. 1981. Fast fronto-parietal rhythms during combined focused attentive behaviour and immobility in cat: Cortical and thalamic localizations. Electroencephalography and Clinical Neurophysiology, 51: 244-252. doi: 10.1016/0013-4694(81)90138-3

Bragin A, Jandó G, Nádasdy Z, et al. 1995. Gamma (40-100 Hz) oscillation in the hippocampus of the behaving rat. Journal of Neuroscience, 15: 47-60. doi: 10.1523/JNEUROSCI.15-01-00047.1995

Bremer F. 1958. Cerebral and cerebellar potential. Physiological Reviews, 58: 357-388.

Brette R, Rudolph M, Carnevale T, et al. 2007. Simulation of networks of spiking neurons: a review of tools and strategies. Journal of Computational Neuroscience, 23: 349-398. doi: 10.1007/s10827-007-0038-6

Brunet N M, Bosman C A, Vinck M, et al. 2014. Stimulus repetition modulates Gamma-band synchronization in primate visual cortex. Proceedings of the National Academy of Sciences, 111: 3626-3631. doi: 10.1073/pnas.1309714111

Buzsáki G. 2006. Rhythms of the Brain. Oxford University Press

Buzsáki G, Draguhn A. 2004. Neuronal oscillations in cortical networks. Science, 304: 1926-1929. doi: 10.1126/science.1099745

Buzsáki G, Horváth Z, Urioste R, et al. 1992. High-frequency network oscillation in the hippocampus. Science, 256: 1025-1027. doi: 10.1126/science.1589772

Buzśaki G, Wang X J. 2012. Mechanisms of Gamma oscillations. Annual Review of Neuroscience, 35: 203-225. doi: 10.1146/annurev-neuro-062111-150444

Canolty R T, Edwards E, Dalal S S, et al. 2006. High Gamma power is phase-locked to Theta oscillations in human neocortex. Science, 313: 1626-1628. doi: 10.1126/science.1128115

César, Rennó-Costa, Garcia D, et al. 2019. Regulation of Gamma-frequency oscillation by feedforward inhibition: A computational modeling study. Hippocampus, 29: 957-970. doi: 10.1002/hipo.23093

Chapeau-Blondeau F, Chambet N. 1995. Synapse models for neural networks: From ion channel kinetics to multiplicative coefficient w_ij. Neural Computation, 7: 713-734. doi: 10.1162/neco.1995.7.4.713

Cole S R, Voytek B. 2017. Brain oscillations and the importance of waveform shape. Trends in Cognitive Sciences, 21: 137-149. doi: 10.1016/j.tics.2016.12.008

Dayan P, Abbott L F. 2001. Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. Mit Press

Demiralp T, Bayraktaroglu Z, Lenz D, et al. 2007. Gamma amplitudes are coupled to Theta phase in human EEG during visual perception. International Journal of Psychophysiology, 64: 24-30. doi: 10.1016/j.ijpsycho.2006.07.005

Destexhe A, Mainen Z F, Sejnowski T J. 1998. Kinetic models of synaptic transmission. Methods in Neuronal Modeling, 2: 1-25.

Doesburg S M, Roggeveen A B, Kitajo K, et al. 2008. Large-scale Gamma-band phase synchronization and selective attention. Cerebral Cortex, 18: 386-396. doi: 10.1093/cercor/bhm073

Fan J, Byrne J, Worden M S, et al. 2007. The relation of brain oscillations to attentional networks. Journal of Neuroscience, 27: 6197-6206. doi: 10.1523/JNEUROSCI.1833-07.2007

Fitzgerald P J, Watson B O. 2018. Gamma oscillations as a biomarker for major depression: an emerging topic. Translational Psychiatry, 8: 177. doi: 10.1038/s41398-018-0239-y

FitzHugh R. 1961. Impulses and physiological states in theoretical models of nerve membrane. Biophysical Journal, 1: 445-466. doi: 10.1016/S0006-3495(61)86902-6

Freeman W J. 1975. Mass Action in the Nervous System. Academic Press

Frien A, Eckhorn R, Bauer R, et al. 1994. Stimulus-specific fast oscillations at zero phase between visual areas V1 and V2 of awake monkey. NeuroReport, 5: 2273-2277. doi: 10.1097/00001756-199411000-00017

Fries P. 2005. A mechanism for cognitive dynamics: Neuronal communication through neuronal coherence. Trends in Cognitive Sciences, 9: 474-480. doi: 10.1016/j.tics.2005.08.011

Fries P. 2015. Rhythms for cognition: Communication through coherence. Neuron, 88: 220-235. doi: 10.1016/j.neuron.2015.09.034

Fries P, Nikolić D, Singer W. 2007. The Gamma cycle. Trends in Neurosciences, 30: 309-316. doi: 10.1016/j.tins.2007.05.005

Fries P, Reynolds J H, Rorie A E, et al. 2001. Modulation of oscillatory neuronal synchronization by selective visual attention. Science, 291: 1560-1563. doi: 10.1126/science.1055465

Gazit T, Friedman A, Lax E, et al. 2015. Programmed deep brain stimulation synchronizes VTA gamma band field potential and alleviates depressive-like behavior in rats. Neuropharmacology, 91: 135-141. doi: 10.1016/j.neuropharm.2014.12.003

Glass L. 2001. Synchronization and rhythmic processes in physiology. Nature, 410: 277-284. doi: 10.1038/35065745

Gieselmann M A, Thiele A. 2008. Comparison of spatial integration and surround suppression characteristics in spiking activity and the local field potential in macaque V1. European Journal of Neuroscience, 28: 447-459. doi: 10.1111/j.1460-9568.2008.06358.x

Gray C M, Knig P, Engel A K, et al. 1989. Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties. Nature, 338: 334-337. doi: 10.1038/338334a0

Gregory S, Fusca M, Rees G, et al. 2016. Gamma frequency and the spatial tuning of primary visual cortex. PLoS One, 11: e0157374. doi: 10.1371/journal.pone.0157374

Grossberg S, Versace M. 2008. Spikes, synchrony, and attentive learning by laminar thalamocortical circuits. Brain Research, 1218: 278-312. doi: 10.1016/j.brainres.2008.04.024

Gruber T, Müller M M, Keil A, et al. 1999. Selective visual-spatial attention alters induced Gamma band responses in the human EEG. Clinical Neurophysiology, 110: 2074-2085. doi: 10.1016/S1388-2457(99)00176-5

Gu X C, Han F, Wang Z J, et al. 2019. Dependency of Gamma oscillations in E/I neuronal network on illumination contrast of external stimulus. Theoretical & Applied Mechanics Letters, 9: 21-27.

Gu X C, Han F, Wang Z J. 2021a. Dependency analysis of frequency and strength of Gamma oscillations on input difference between excitatory and inhibitory neurons. Cognitive Neurodynamics, 15: 501-515. doi: 10.1007/s11571-020-09622-5

Gu X C, Han F, Wang Z J, Kashif K, et al. 2021b. Enhancement of Gamma oscillations in E/I neural networks by increase of difference between external inputs. Electronic Research Archive, 29: 3227-3241. doi: 10.3934/era.2021035

Han F, Gu X, Wang Z J, et al. 2018. Global firing rate contrast enhancement in E/I neuronal networks by recurrent synchronized inhibition. Chaos, 28: 106324. doi: 10.1063/1.5037207

Han F, Wang Z J, Fan H, et al. 2020. High-frequency synchronization improves firing rate contrast and information transmission efficiency in E/I neuronal networks. Neural Plasticity, 2020: 8823111.

Han F, Wang Z J, Fan H. 2017. Determine neuronal tuning curves by exploring optimum firing rate distribution for information efficiency. Frontiers in Computational Neuroscience, 11: 10.

Hauck M, Lorenz J, Engel A K. 2007. Attention to painful stimulation enhances γ-band activity and synchronization in human sensorimotor cortex. Journal of Neuroscience, 27: 9270-9277. doi: 10.1523/JNEUROSCI.2283-07.2007

Henrie J A, Kang K, Shapley R. 2005. Stimulus size affects the LFP spectral contents in primate V1. Society for Neuroscience, 35: 18.

Henrie J A, Shapley R. 2005. LFP power spectra in v1 cortex: The graded effect of stimulus contrast. Journal of Neurophysiology, 94: 479-490. doi: 10.1152/jn.00919.2004

Herrmann C S, Murray M M, Ionta S, et al. 2016. Shaping intrinsic neural oscillations with periodic stimulation. Journal of Neuroscience, 36: 5328-5337. doi: 10.1523/JNEUROSCI.0236-16.2016

Hindmarsh J L, Rose R M. 1982. A model of the nerve impulse using two first-order differential equations. Nature, 296: 162-164. doi: 10.1038/296162a0

Hipp J F, Engel A K, Siegel M. 2011. Oscillatory synchronization in large-scale cortical networks predicts perception. Neuron, 69: 387-396. doi: 10.1016/j.neuron.2010.12.027

Hodgkin A L, Huxley A F. 1952. Currents carried by sodium and potassium ions through the membrane of the giant axon of Loligo. Journal of Physiology, 116: 449. doi: 10.1113/jphysiol.1952.sp004717

Howard M W, Rizzuto D S, Caplan J B, et al. 2003. Gamma oscillations correlate with working memory load in humans. Cerebral Cortex, 13: 1369-1374. doi: 10.1093/cercor/bhg084

Hutt A, Mierau A, Lefebvre J. 2016. Dynamic control of synchronous activity in networks of spiking neurons. PLoS ONE, 11: e0161488. doi: 10.1371/journal.pone.0161488

Huxter J, Burgess N, O’Keefe1 J. 2003. Independent rate and temporal coding in hippocampal pyramidal cells. Nature, 425: 828-832. doi: 10.1038/nature02058

Izhikevich E M. 2003. Simple model of spiking neurons. IEEE Transactions on Neural Networks and Learning Systems, 14: 1569-1572. doi: 10.1109/TNN.2003.820440

Jadi M P, Behrens M M, Sejnowski T J. 2016. Abnormal Gamma oscillations in N-methyl-D-aspartate receptor hypofunction models of schizophrenia. Biological Psychiatry, 79: 716-726. doi: 10.1016/j.biopsych.2015.07.005

Jadi M P, Sejnowski T J. 2014a. Cortical oscillations arise from contextual interactions that regulate sparse coding. Proceedings of the National Academy of Sciences of the United States of America, 111: 6780-6785. doi: 10.1073/pnas.1405300111

Jadi M P, Sejnowski T J. 2014b. Regulating cortical oscillations in an inhibition-stabilized network. Proceedings of the IEEE, 102: 830-842. doi: 10.1109/JPROC.2014.2313113

Jasper H, Penfield W. 1949. Electrocorticograms in man: Effect of voluntary movement upon the electrical activity of the precentral gyrus. European Archives of Psychiatry and Clinical Neuroscience, 183: 163-174.

Jensen O, Tesche C D. 2010. Frontal Theta activity in humans increases with memory load in a working memory task. European Journal of Neuroscience, 15: 1395-1399.

Jerbi K, Hamamé C M, Ossandón T, et al. 2008. Role of posterior parietal Gamma activity in planning prosaccades and antisaccades. Journal of Neuroscience, 28: 13713-13715. doi: 10.1523/JNEUROSCI.4896-08.2008

Jia X, Tanabe S, KohnA. 2013a. Gamma and the coordination of spiking activity in early visual cortex. Neuron, 77: 762-774. doi: 10.1016/j.neuron.2012.12.036

Jia X, Xing D, Kohn A. 2013b. No consistent relationship between Gamma power and peak frequency in macaque primary visual cortex. Journal of Neuroscience, 33: 17-25. doi: 10.1523/JNEUROSCI.1687-12.2013

Kahana M J, Sekuler R, Caplan J B, et al. 1999. Human Theta oscillations exhibit task dependence during virtual maze navigation. Nature, 399: 781-784. doi: 10.1038/21645

Kaiser J, Bühler M, Lutzenberger W. 2004. Magnetoencephalographic Gamma-band responses to illusory triangles in humans. NeuroImage, 23: 551-560. doi: 10.1016/j.neuroimage.2004.06.033

Kang K, Shelley M, Henrie J A, et al. 2010. LFP Spectral peaks in V1 cortex: network resonance and cortico-cortical feedback. Journal of Computational Neuroscience, 29: 495-507. doi: 10.1007/s10827-009-0190-2

Khalid A, Kim BS, Seo BA, et al. 2016. Gamma oscillation in functional brain networks is involved in the spontaneous remission of depressive behavior induced by chronic restraint stress in mice. BMC Neurosci, 17: 4.

Kim J, Bertalmio M. 2015. Investigating the effect of lateral inhibition in the retinal circuitry on lightness contrast and assimilation: a model study. Journal of Vision, 15: 633. doi: 10.1167/15.12.633

Koch S P, Werner P, Steinbrink J, et al. 2009. Stimulus-induced and state-dependent sustained Gamma activity is tightly coupled to the hemodynamic response in humans. Journal of Neuroscience, 29: 13962-13970. doi: 10.1523/JNEUROSCI.1402-09.2009

Kopell N J, Gritton H J, Whittington M A, Kramer M A. 2014. Beyond the connectome: the dynome. Neuron, 83: 1319-1328. doi: 10.1016/j.neuron.2014.08.016

Kostal L, Lansky P. 2013. Information capacity and its approximations under metabolic cost in a simple homogeneous population of neurons. Biosystems, 112: 265-275. doi: 10.1016/j.biosystems.2013.03.019

Kropotov J D. 2009. Quantitative EEG, Event-Related Potentials and Neurotherapy. Academic Press.

Lapicque L. 1907. Recherches quantitatives sur l'excitation electrique des nerfs traitée comme une polarization. Journal of Physiology and Pathology General, 9: 620-635.

Lefebvre J, Hutt A, Knebel J F, et al. 2015. Stimulus statistics shape oscillations in nonlinear recurrent neural networks. Journal of Neuroscience, 35: 2895-2903. doi: 10.1523/JNEUROSCI.3609-14.2015

Li K T, Liang J, Zhou C. 2021. Gamma oscillations facilitate effective learning in excitatory-inhibitory balanced neural circuits. Neural Plasticity, 7: 1-18.

Lu Y, Sarter M, Zochowski M, et al. 2020. Phasic cholinergic signaling promotes emergence of local Gamma rhythms in excitatory–inhibitory networks. European Journal of Neuroscience, 52: 3545-3560. doi: 10.1111/ejn.14744

Magazzini L, Singh K D. 2018. Spatial attention modulates visual Gamma oscillations across the human ventral stream. NeuroImage, 166: 219-229. doi: 10.1016/j.neuroimage.2017.10.069

Masuda N. 2009. Selective population rate coding: A possible computational role of Gamma oscillations in selective attention. Neural Computation, 21: 3335-3362. doi: 10.1162/neco.2009.09-08-857

Mcclelland J L, Rumelhard D E. 1986. Exploration in Parallel Distributed Processing, A Handbook of Models, Programs, and Exercises. Cambridge: MIT Press

McCulloch W S, Pitts W. 1943. A logical calculus of the ideas immanent in neurons activity. Bulletin of Mathematical Biophysics, 5: 115-133. doi: 10.1007/BF02478259

Morrison A, Aertsen A, Diesmann M. 2007. Spike-timing dependent plasticity in balanced random networks thanks. Neural Computation, 19: 1437-1467. doi: 10.1162/neco.2007.19.6.1437

Moujahid A, d'Anjou A, Torrealdea F J, Torrealdea F. 2011. Energy and information in Hodgkin-Huxley neurons. Physical Review E, 83: 031912. doi: 10.1103/PhysRevE.83.031912

Mountcastle V B. 1997. The columnar organization of the neocortex. Brain, 120: 701-722. doi: 10.1093/brain/120.4.701

Muthukumaraswamy S D, Singh K D. 2013. Visual Gamma oscillations: the effects of stimulus type, visual field coverage and stimulus motion on meg and EEG recordings. NeuroImage, 69: 223-230. doi: 10.1016/j.neuroimage.2012.12.038

Neymotin S A, Lee H, Park E, et al. 2011. Emergence of physiological oscillation frequencies in a computer model of neocortex. Frontiers in Computational Neuroscience, 5: 19.

Oliveira L D R, Gomes R M, Santos B A, et al. 2019. Effects of the parameters on the oscillation frequency of Izhikevich spiking neural networks. Neurocomputing, 337: 251-261. doi: 10.1016/j.neucom.2019.01.071

Onslow A C E, Jones M W, Bogacz R. 2014. A canonical circuit for generating phase-amplitude coupling. PLoS ONE, 9: e102591. doi: 10.1371/journal.pone.0102591

Orekhova E V, Butorina A V, Sysoeva O V, et al. 2015. Frequency of Gamma oscillations in humans is modulated by velocity of visual motion. Journal of Neurophysiology, 114: 244-255. doi: 10.1152/jn.00232.2015

Osipova D, Takashima A, Oostenveld R, et al. 2006. Theta and Gamma oscillations predict encoding and retrieval of declarative memory. Journal of Neuroscience, 26: 7523-7531. doi: 10.1523/JNEUROSCI.1948-06.2006

Panzeri S, Brunel N, Logothetis N K, et al. 2010. Sensory neural codes using multiplexed temporal scales. Trends in Neurosciences, 33: 111-120. doi: 10.1016/j.tins.2009.12.001

Peng X, Wang Z, Han F, et al. 2018. A novel time-event-driven algorithm for simulating spiking neural networks based on circular array. Neurocomputing, 292: 121-129. doi: 10.1016/j.neucom.2018.02.085

Perry G, Randle J M, Koelewijn L, et al. 2015. Linear tuning of Gamma amplitude and frequency to luminance contrast: evidence from a continuous mapping paradigm. PLoS One, 10: e0124798. doi: 10.1371/journal.pone.0124798

Peter A, Stauch B J, Shapcott K, et al. 2021. Stimulus-specific plasticity of macaque V1 spike rates and Gamma. Cell Reports, 37: 110086. doi: 10.1016/j.celrep.2021.110086

Petersen C C H, Sakmann B. 2013. Functionally independent columns of rat somatosensory barrel cortex revealed with voltage-sensitive dye imaging. Journal of Neuroscience, 21: 8435-8446.

Pesaran B, Pezaris J, Sahani M, et al. 2002. Temporal structure in neuronal activity during working memory in macaque parietal cortex. Nature Neuroscience, 5: 805-811. doi: 10.1038/nn890

Rall W. 1967. Distinguishing theoretical synaptic potentials computed for different soma-dendritic distributions of synaptic input. Journal of Neurophysiology, 30: 1138-1168. doi: 10.1152/jn.1967.30.5.1138

Ray S, Maunsell J H R. 2010. Differences in Gamma frequencies across visual cortex restrict their possible use in computation. Neuron, 67: 885-896. doi: 10.1016/j.neuron.2010.08.004

Ray S, Maunsell J H R. 2011. Different origins of Gamma rhythm and high-Gamma activity in macaque visual cortex. PLoS Biology, 9: e1000610. doi: 10.1371/journal.pbio.1000610

Richard A Y. 1987. The gaussian derivative model for spatial vision: i. retinal mechanisms. Spatial Vision, 2: 273-293. doi: 10.1163/156856887X00222

Rodieck R W. 1965. Quantitative analysis of cat retinal ganglion cell response to visual stimuli. Vision Research, 5: 583-601. doi: 10.1016/0042-6989(65)90033-7

Rodieck R W. 1975. Analysis of receptive fields of cat retinal ganglion cells. Journal of Neurophysiology, 28: 833-849.

Sacerdote L, Giraudo M T. 2013. Stochastic integrate and fire models: a review on mathematical methods and their applications. Quantitative Biology, 2058: 99-148.

Saleem A B, Lien A D, Krumin M, et al. 2017. Subcortical source and modulation of the narrowband Gamma oscillation in mouse visual cortex. Neuron, 93: 315-322. doi: 10.1016/j.neuron.2016.12.028

Sato Y, Ochi A, Mizutani T, Otsubo H. 2019. Low entropy of interictal Gamma oscillations is a biomarker of the seizure onset zone in focal cortical dysplasia type II. Epilepsy & Behavior, 96: 155-159.

Schnitzler A, Gross J. 2005. Normal and pathological oscillatory communication in the brain. Nature Reviews Neuroscience, 6: 285-296. doi: 10.1038/nrn1650

Schroeder C E, Lakatos P. 2009. Low-frequency neuronal oscillations as instruments of sensory selection. Trends in Neurosciences, 32: 9-18. doi: 10.1016/j.tins.2008.09.012

Schwarzkopf D S, Robertson D J, Song C, et al. 2012. The Frequency of visually induced Gamma-band oscillations depends on the size of early human visual cortex. Journal of Neuroscience, 32: 1507-1512. doi: 10.1523/JNEUROSCI.4771-11.2012

Sengupta B, Laughlin S B, Niven J E. 2014. Consequences of converting graded to action potentials upon neural information coding and energy efficiency. PLoS Computational Biology, 10: e1003439. doi: 10.1371/journal.pcbi.1003439

Senkowski D, Schneider T R, Foxe J J, Engel A K. 2008. Crossmodal binding through neural coherence: implications for multisensory processing. Trends in Neurosciences, 31: 401-409. doi: 10.1016/j.tins.2008.05.002

Sherfey J, Ardid S, Miller E K, et al. 2020. Prefrontal oscillations modulate the propagation of neuronal activity required for working memory. Neurobiology of Learning and Memory, 173: 107228. doi: 10.1016/j.nlm.2020.107228

Siegel M, Donner T H, Engel A K. 2012. Spectral fingerprints of large-scale neuronal interactions. Nature Reviews Neuroscience, 13: 121-134. doi: 10.1038/nrn3137

Siegel M, Donner T H, Oostenveld R, et al. 2008. Neuronal synchronization along the dorsal visual pathway reflects the focus of spatial attention. Neuron, 60: 709-719. doi: 10.1016/j.neuron.2008.09.010

Singer W, Gray C M. 1995. Visual feature integration and the temporal correlation hypothesis. Annual Review of Neuroscience, 18: 555-586. doi: 10.1146/annurev.ne.18.030195.003011

Sokolov A, Lutzenberger W, Pavlova M, et al. 1999. Gamma-band meg activity to coherent motion depends on task-driven attention. NeuroReport, 10: 1997-2000. doi: 10.1097/00001756-199907130-00001

Storchi R, Bedford R A, Martial F P, et al. 2017. Modulation of fast narrowband oscillations in the mouse retina and dLGN according to background light intensity. Neuron, 93: 299-307. doi: 10.1016/j.neuron.2016.12.027

Swettenham J B, Muthukumaraswamy S D, Singh K D. 2009. Spectral properties of induced and evoked Gamma oscillations in human early visual cortex to moving and stationary stimuli. Journal of Neurophysiology, 102: 1241-1253. doi: 10.1152/jn.91044.2008

Tan L L, Oswald M J, Kuner B, 2021. Neurobiology of brain oscillations in acute and chronic pain. Trends in Neurosciences, 44: 629-642.

Tiesinga P, Sejnowski T J. 2009. Cortical enlightenment: are attentional Gamma oscillations driven by ING or PING. Neuron, 63: 727-732. doi: 10.1016/j.neuron.2009.09.009

Trujillo C A, Gao R, Negraes P D. et al. 2019. Complex oscillatory waves emerging from cortical organoids model early human brain network development. Cell Stem Cell, 25: 1-12.

Valley M T, Firestein S A, 2008. Lateral look at olfactory bulb lateral inhibition. Neuron, 59: 682-684.

Vanderwolf C H. 1969. Hippocampal electrical activity and voluntary movement in the rat. Electroencephalography and Clinical Neurophysiology, 26: 407-418. doi: 10.1016/0013-4694(69)90092-3

Vida I, Bartos M, Jonas P. 2006. Shunting inhibition improves robustness of Gamma oscillations in hippocampal interneuron networks by homogenizing firing rates. Neuron, 49: 107-117. doi: 10.1016/j.neuron.2005.11.036

Vinck M, Batista-Brito R, Knoblich U, et al. 2015. Arousal and locomotion make distinct contributions to cortical activity patterns and visual encoding. Neuron, 86: 740-754. doi: 10.1016/j.neuron.2015.03.028

Wallace E, Benayoun M, Van Drongelen W, et al. 2011. Emergent oscillations in networks of stochastic spiking neurons. PLoS ONE, 6: e14804. doi: 10.1371/journal.pone.0014804

Wang X J. 2010. Neurophysiological and computational principles of cortical rhythms in cognition. Physiological Reviews, 90: 1195-1268. doi: 10.1152/physrev.00035.2008

Wang X J, Buzsáki G. 1996. Gamma oscillation by synaptic inhibition in a hippocampal interneuronal network model. Journal of Neuroscience, 16: 6402-6413. doi: 10.1523/JNEUROSCI.16-20-06402.1996

Wang Y H, Wang R B, Xu X Y. 2017. Neural energy supply-consumption properties based on Hodgkin-Huxley model. Neural Plasticity, 2017: 6207141.

Wang Z J, Han F, Aihara K. 2011. Three synaptic components contributing to robust network synchronization. Physical Review E, 83: 051905. doi: 10.1103/PhysRevE.83.051905

Wang Z J, Peng X, Han F, et al. 2020. A novel parallel clock-driven algorithm for simulation of neuronal networks based on virtual synapse. Simulation:Transactions of the Society for Modeling and Simulation International, 96: 415-427. doi: 10.1177/0037549720903804

Whittington M A, Traub R D, Jefferys J G R. 1995. Synchronized oscillations in interneuron networks driven by metabotropic glutamate receptor activation. Nature, 373: 612-615. doi: 10.1038/373612a0

Wildie M, Shanahan M. 2012. Establishing communication between neuronal populations through competitive entrainment. Frontiers in Computational Neuroscience, 5: 62.

Xing D, Yeh C, Burns S, et al. 2012. Laminar analysis of visually evoked activity in the primary visual cortex. Proceedings of the National Academy of Sciences of the United States of America, 109: 13871-13876.

Zhu Z, Wang R, Zhu F. 2018. The energy coding of a structural neural network based on the Hodgkin-Huxley model. Frontiers in Neuroscience, 12: 122. doi: 10.3389/fnins.2018.00122

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