The neurogenesis of P1 and N1: a concurrent EEG/LFP studyBruyns-Haylett, M., Luo, J., Bruyns-Haylett, A. J., Harris, S., Boorman, L., Milne, E., Vautrelle, N., Hayashi, Y., Whalley, B. J., Jones, M., Berwick, J., Riera, J. and Zheng, Y. ORCID: https://orcid.org/0000-0001-7472-6427 (2017) The neurogenesis of P1 and N1: a concurrent EEG/LFP study. NeuroImage, 146. pp. 575-588. ISSN 1053-8119
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1016/j.neuroimage.2016.09.034 Abstract/SummaryIt is generally recognised that event related potentials (ERPs) of electroencephalogram (EEG) primarily reflect summed post-synaptic activity of the local pyramidal neural population(s). However, it is still not understood how the positive and negative deflections (e.g. P1, N1 etc) observed in ERP recordings are related to the underlying excitatory and inhibitory post-synaptic activity. We investigated the neurogenesis of P1 and N1 in ERPs by pharmacologically manipulating inhibitory post-synaptic activity in the somatosensory cortex of rodent, and concurrently recording EEG and local field potentials (LFPs). We found that the P1 wave in the ERP and LFP of the supragranular layers is determined solely by the excitatory post-synaptic activity of the local pyramidal neural population, as is the initial segment of the N1 wave across cortical depth. The later part of the N1 wave was modulated by inhibitory post-synaptic activity, with its peak and the pulse width increasing as inhibition was reduced. These findings suggest that the temporal delay of inhibition with respect to excitation observed in intracellular recordings is also reflected in extracellular field potentials (FPs), resulting in a temporal window during which only excitatory post-synaptic activity and leak channel activity are recorded in the ERP and evoked LFP time series. Based on these findings, we provide clarification on the interpretation of P1 and N1 in terms of the excitatory and inhibitory post-synaptic activities of the local pyramidal neural population(s).
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Acar, Z.A., Acar, C.E., Makeig, S., 2016. Simultaneous head tissue conductivity and EEG source location estimation. Neuroimage 124, 168-180.
Allison, T., Hume, A.L., 1981. A comparative analysis of short-latency somatosensory evoked potentials in man, monkey, cat, and rat. Experimental neurology 72, 592-611.
Allison, T., McCarthy, G., Wood, C.C., Darcey, T.M., Spencer, D.D., Williamson, P.D., 1989. Human cortical potentials evoked by stimulation of the median nerve. II. Cytoarchitectonic areas generating short-latency activity. Journal of Neurophysiology 62, 694-710.
Anderson, J.S., Carandini, M., Ferster, D., 2000. Orientation tuning of input conductance, excitation, and inhibition in cat primary visual cortex. Journal of Neurophysiology 84, 909-926.
Arezzo, J., Legatt, A., Vaughan, V., 1979. Topography and intracranial sources of somatosensory evoked potentials in the monkey. I. Early components. Electroencephalography and clinical neurophysiology 46, 155-172.
Arezzo, J.C., Vaughan, H., Legatt, A.D., 1981. Topography and intracranial sources of somatosensory evoked potentials in the monkey. II. Cortical components. Electroencephalography and clinical neurophysiology 51, 1-18.
Armstrong-James, M., Fox, K., Das-Gupta, A., 1992. Flow of excitation within rat barrel cortex on striking a single vibrissa. Journal of Neurophysiology 68, 1345-1358.
Arthurs, O., Williams, E., Carpenter, T., Pickard, J., Boniface, S., 2000. Linear coupling between functional magnetic resonance imaging and evoked potential amplitude in human somatosensory cortex. Neuroscience 101, 803-806.
Atallah, B.V., Scanziani, M., 2009. Instantaneous modulation of gamma oscillation frequency by balancing excitation with inhibition. Neuron 62, 566-577.
Bannister, A.P., 2005. Inter-and intra-laminar connections of pyramidal cells in the neocortex. Neuroscience research 53, 95-103.
Benarroch, E.E., 2012. GABAB receptors Structure, functions, and clinical implications. Neurology 78, 578-584.
Bojak, I., Oostendorp, T.F., Reid, A.T., Kötter, R., 2010. Connecting mean field models of neural activity to EEG and fMRI data. Brain topography 23, 139-149.
Boorman, L., Harris, S., Bruyns-Haylett, M., Kennerley, A., Zheng, Y., Martin, C., Jones, M., Redgrave, P., Berwick, J., 2015. Long-latency reductions in gamma power predict hemodynamic changes that underlie the negative BOLD signal. The Journal of Neuroscience 35, 4641-4656.
Boorman, L., Kennerley, A.J., Johnston, D., Jones, M., Zheng, Y., Redgrave, P., Berwick, J., 2010. Negative blood oxygen level dependence in the rat: a model for investigating the role of suppression in neurovascular coupling. The Journal of Neuroscience 30, 4285-4294.
Bruno, R.M., Sakmann, B., 2006. Cortex is driven by weak but synchronously active thalamocortical synapses. Science 312, 1622-1627.
Bruyns‐Haylett, M., Harris, S., Boorman, L., Zheng, Y., Berwick, J., Jones, M., 2013. The resting‐state neurovascular coupling relationship: rapid changes in spontaneous neural activity in the somatosensory cortex are associated with haemodynamic fluctuations that resemble stimulus‐evoked haemodynamics. European Journal of Neuroscience 38, 2902-2916.
Bureau, I., von Saint Paul, F., Svoboda, K., 2006. Interdigitated paralemniscal and lemniscal pathways in the mouse barrel cortex. PLoS Biol 4, e382.
Buzsaki, G., 2006. Rhythms of the Brain. Oxford University Press.
Buzsáki, G., Anastassiou, C.A., Koch, C., 2012. The origin of extracellular fields and currents—EEG, ECoG, LFP and spikes. Nature Reviews Neuroscience 13, 407-420.
Carandini, M., Heeger, D.J., Senn, W., 2002. A synaptic explanation of suppression in visual cortex. The Journal of Neuroscience 22, 10053-10065.
Castro-Alamancos, M.A., 2004. Dynamics of sensory thalamocortical synaptic networks during information processing states. Progress in neurobiology 74, 213-247.
Castro‐Alamancos, M.A., Oldford, E., 2002. Cortical sensory suppression during arousal is due to the activity‐dependent depression of thalamocortical synapses. The Journal of physiology 541, 319-331.
Constantinople, C.M., Bruno, R.M., 2013. Deep cortical layers are activated directly by thalamus. Science 340, 1591-1594.
Coombes, S., 2010. Large-scale neural dynamics: simple and complex. Neuroimage 52, 731-739.
Csicsvari, J., Hirase, H., Czurko, A., Mamiya, A., Buzsáki, G., 1999. Fast network oscillations in the hippocampal CA1 region of the behaving rat. J Neurosci 19, RC20.
De Kock, C., Bruno, R.M., Spors, H., Sakmann, B., 2007. Layer‐and cell‐type‐specific suprathreshold stimulus representation in rat primary somatosensory cortex. The Journal of physiology 581, 139-154.
Debarbieux, F., Brunton, J., Charpak, S., 1998. Effect of bicuculline on thalamic activity: a direct blockade of I AHP in reticularis neurons. Journal of Neurophysiology 79, 2911-2918.
Deco, G., Jirsa, V.K., Robinson, P.A., Breakspear, M., Friston, K., 2008. The dynamic brain: from spiking neurons to neural masses and cortical fields. PLoS Comput Biol 4, e1000092.
Devor, A., Ulbert, I., Dunn, A.K., Narayanan, S.N., Jones, S.R., Andermann, M.L., Boas, D.A., Dale, A.M., 2005. Coupling of the cortical hemodynamic response to cortical and thalamic neuronal activity. Proceedings of the National Academy of Sciences of the United States of America 102, 3822-3827.
Di Russo, F., Martínez, A., Sereno, M.I., Pitzalis, S., Hillyard, S.A., 2002. Cortical sources of the early components of the visual evoked potential. Human brain mapping 15, 95-111.
Di, S., Barth, D.S., 1991. Topographic analysis of field potentials in rat vibrissa/barrel cortex. Brain research 546, 106-112.
Di, S., Baumgartner, C., Barth, D.S., 1990. Laminar analysis of extracellular field potentials in rat vibrissa/barrel cortex. Journal of Neurophysiology 63, 832-840.
Ebersole, J.S., Chatt, A.B., 1984. Laminar interactions during neocortical epileptogenesis. Brain research 298, 253-271.
Einevoll, G.T., Kayser, C., Logothetis, N.K., Panzeri, S., 2013. Modelling and analysis of local field potentials for studying the function of cortical circuits. Nature Reviews Neuroscience 14, 770-785.
Einevoll, G.T., Pettersen, K.H., Devor, A., Ulbert, I., Halgren, E., Dale, A.M., 2007. Laminar population analysis: estimating firing rates and evoked synaptic activity from multielectrode recordings in rat barrel cortex. Journal of Neurophysiology 97, 2174-2190.
Feldmeyer, D., 2012. Excitatory neuronal connectivity in the barrel cortex. Front Neuroanat 6, 24.
Feldmeyer, D., Lübke, J., Silver, R.A., Sakmann, B., 2002. Synaptic connections between layer 4 spiny neurone‐layer 2/3 pyramidal cell pairs in juvenile rat barrel cortex: physiology and anatomy of interlaminar signalling within a cortical column. The Journal of physiology 538, 803-822.
Franceschini, M.A., Nissilä, I., Wu, W., Diamond, S.G., Bonmassar, G., Boas, D.A., 2008. Coupling between somatosensory evoked potentials and hemodynamic response in the rat. Neuroimage 41, 189-203.
Freeman, S., Sohmer, H., 1996. A comparison of forepaw and vibrissae somatosensory cortical evoked potentials in the rat. Electroencephalography and Clinical Neurophysiology/Evoked Potentials Section 100, 362-369.
Freeman, T.C., Durand, S., Kiper, D.C., Carandini, M., 2002. Suppression without inhibition in visual cortex. Neuron 35, 759-771.
Freunberger, R., Klimesch, W., Griesmayr, B., Sauseng, P., Gruber, W., 2008. Alpha phase coupling reflects object recognition. Neuroimage 42, 928-935.
Fu, Y., Tucciarone, J.M., Espinosa, J.S., Sheng, N., Darcy, D.P., Nicoll, R.A., Huang, Z.J., Stryker, M.P., 2014. A cortical circuit for gain control by behavioral state. Cell 156, 1139-1152.
Gabernet, L., Jadhav, S.P., Feldman, D.E., Carandini, M., Scanziani, M., 2005. Somatosensory integration controlled by dynamic thalamocortical feed-forward inhibition. Neuron 48, 315-327.
Gentet, L.J., Avermann, M., Matyas, F., Staiger, J.F., Petersen, C.C., 2010. Membrane potential dynamics of GABAergic neurons in the barrel cortex of behaving mice. Neuron 65, 422-435.
Haider, B., Krause, M.R., Duque, A., Yu, Y., Touryan, J., Mazer, J.A., McCormick, D.A., 2010. Synaptic and network mechanisms of sparse and reliable visual cortical activity during nonclassical receptive field stimulation. Neuron 65, 107-121.
Heiss, J.E., Katz, Y., Ganmor, E., Lampl, I., 2008. Shift in the balance between excitation and inhibition during sensory adaptation of S1 neurons. The Journal of Neuroscience 28, 13320-13330.
Hewson-Stoate, N., Jones, M., Martindale, J., Berwick, J., Mayhew, J., 2005. Further nonlinearities in neurovascular coupling in rodent barrel cortex. Neuroimage 24, 565-574.
Higley, M.J., Contreras, D., 2006. Balanced excitation and inhibition determine spike timing during frequency adaptation. The Journal of Neuroscience 26, 448-457.
Higley, M.J., Contreras, D., 2007. Frequency adaptation modulates spatial integration of sensory responses in the rat whisker system. Journal of Neurophysiology 97, 3819-3824.
Isaacson, J.S., Scanziani, M., 2011. How inhibition shapes cortical activity. Neuron 72, 231-243.
Iurilli, G., Ghezzi, D., Olcese, U., Lassi, G., Nazzaro, C., Tonini, R., Tucci, V., Benfenati, F., Medini, P., 2012. Sound-driven synaptic inhibition in primary visual cortex. Neuron 73, 814-828.
Jansen, B.H., Zouridakis, G., Brandt, M.E., 1993. A neurophysiologically-based mathematical model of flash visual evoked potentials. Biological cybernetics 68, 275-283.
Jellema, T., Brunia, C., Wadman, W., 2004. Sequential activation of microcircuits underlying somatosensory-evoked potentials in rat neocortex. Neuroscience 129, 283-295.
Johnston, G.A., 2013. Advantages of an antagonist: bicuculline and other GABA antagonists. British journal of pharmacology 169, 328-336.
Jones, M., Hewson-Stoate, N., Martindale, J., Redgrave, P., Mayhew, J., 2004. Nonlinear coupling of neural activity and CBF in rodent barrel cortex. Neuroimage 22, 956-965.
Jones, M.S., Barth, D.S., 2002. Effects of bicuculline methiodide on fast (> 200 Hz) electrical oscillations in rat somatosensory cortex. Journal of Neurophysiology 88, 1016-1025.
Katzner, S., Busse, L., Carandini, M., 2011. GABAA inhibition controls response gain in visual cortex. The Journal of Neuroscience 31, 5931-5941.
Kennerley, A.J., Harris, S., Bruyns-Haylett, M., Boorman, L., Zheng, Y., Jones, M., Berwick, J., 2012. Early and late stimulus-evoked cortical hemodynamic responses provide insight into the neurogenic nature of neurovascular coupling. Journal of Cerebral Blood Flow & Metabolism 32, 468-480.
Klausberger, T., Magill, P.J., Márton, L.F., Roberts, J.D.B., Cobden, P.M., Buzsáki, G., Somogyi, P., 2003. Brain-state-and cell-type-specific firing of hippocampal interneurons in vivo. Nature 421, 844-848.
Klimesch, W., 2011. Evoked alpha and early access to the knowledge system: the P1 inhibition timing hypothesis. Brain research 1408, 52-71.
Klimesch, W., 2013. An algorithm for the EEG frequency architecture of consciousness and brain body coupling. Frontiers in human neuroscience 7.
Klimesch, W., Sauseng, P., Hanslmayr, S., 2007. EEG alpha oscillations: the inhibition–timing hypothesis. Brain research reviews 53, 63-88.
Krishek, B., Moss, S., Smart, T., 1996. A functional comparison of the antagonists bicuculline and picrotoxin at recombinant GABA A receptors. Neuropharmacology 35, 1289-1298.
Kublik, E., 2004. Contextual impact on sensory processing at the barrel cortex of awake rat. Acta neurobiologiae experimentalis 64, 229-238.
Kulics, A., Cauller, L., 1986. Cerebral cortical somatosensory evoked responses, multiple unit activity and current source-densities: their interrelationships and significance to somatic sensation as revealed by stimulation of the awake monkey's hand. Experimental brain research 62, 46-60.
Kurt, S., Crook, J.M., Ohl, F.W., Scheich, H., Schulze, H., 2006. Differential effects of iontophoretic in vivo application of the GABA A-antagonists bicuculline and gabazine in sensory cortex. Hearing research 212, 224-235.
Lee, A.K., Rajaram, S., Xia, J., Bharadwaj, H., Larson, E., Hämäläinen, M., Shinn-Cunningham, B.G., 2013. Auditory selective attention reveals preparatory activity in different cortical regions for selection based on source location and source pitch. Frontiers in neuroscience 6, 190.
Łęski, S., Lindén, H., Tetzlaff, T., Pettersen, K.H., Einevoll, G.T., 2013. Frequency dependence of signal power and spatial reach of the local field potential. PLoS Comput Biol 9, e1003137.
Lester, R.A., Clements, J.D., Westbrook, G.L., Jahr, C.E., 1990. Channel kinetics determine the time course of NM DA receptor-mediated synaptic currents. Nature 346, 565.
Li, J., Bravo, D.S., Louise Upton, A., Gilmour, G., Tricklebank, M.D., Fillenz, M., Martin, C., Lowry, J.P., Bannerman, D.M., McHugh, S.B., 2011. Close temporal coupling of neuronal activity and tissue oxygen responses in rodent whisker barrel cortex. European Journal of Neuroscience 34, 1983-1996.
Lindén, H., Pettersen, K.H., Einevoll, G.T., 2010. Intrinsic dendritic filtering gives low-pass power spectra of local field potentials. Journal of computational neuroscience 29, 423-444.
Lindén, H., Tetzlaff, T., Potjans, T.C., Pettersen, K.H., Grün, S., Diesmann, M., Einevoll, G.T., 2011. Modeling the spatial reach of the LFP. Neuron 72, 859-872.
Logothetis, N.K., 2002. The neural basis of the blood–oxygen–level–dependent functional magnetic resonance imaging signal. Philosophical Transactions of the Royal Society B: Biological Sciences 357, 1003-1037.
Logothetis, N.K., 2003. The underpinnings of the BOLD functional magnetic resonance imaging signal. The Journal of Neuroscience 23, 3963-3971.
Logothetis, N.K., Wandell, B.A., 2004. Interpreting the BOLD signal. Annu. Rev. Physiol. 66, 735-769.
Luck, S., 2005. An Introduction to Event-Related Potentials and their Neural Origins (Chapter 1). Cambridge: MIT Press.
Lucka, F., Pursiainen, S., Burger, M., Wolters, C.H., 2012. Hierarchical Bayesian inference for the EEG inverse problem using realistic FE head models: depth localization and source separation for focal primary currents. Neuroimage 61, 1364-1382.
Ma, H., Zhao, M., Suh, M., Schwartz, T.H., 2009. Hemodynamic surrogates for excitatory membrane potential change during interictal epileptiform events in rat neocortex. Journal of Neurophysiology 101, 2550-2562.
Makeig, S., Debener, S., Onton, J., Delorme, A., 2004. Mining event-related brain dynamics. Trends in cognitive sciences 8, 204-210.
Makeig, S., Onton, J., 2009. ERP features and EEG dynamics: an ICA perspective. Oxford Handbook of Event-Related Potential Components. New York, NY: Oxford.
Martin, C., Martindale, J., Berwick, J., Mayhew, J., 2006. Investigating neural–hemodynamic coupling and the hemodynamic response function in the awake rat. Neuroimage 32, 33-48.
Martindale, J., Mayhew, J., Berwick, J., Jones, M., Martin, C., Johnston, D., Redgrave, P., Zheng, Y., 2003. The hemodynamic impulse response to a single neural event. Journal of Cerebral Blood Flow & Metabolism 23, 546-555.
Mitzdorf, U., 1985. Current source-density method and application in cat cerebral cortex: investigation of evoked potentials and EEG phenomena. Physiological reviews 65, 37-100.
Moser, E., Mathiesen, I., Andersen, P., 1993. Association between brain temperature and dentate field potentials in exploring and swimming rats. Science 259, 1324-1326.
Muniak, M.A., Ray, S., Hsiao, S.S., Dammann, J.F., Bensmaia, S.J., 2007. The neural coding of stimulus intensity: linking the population response of mechanoreceptive afferents with psychophysical behavior. The Journal of Neuroscience 27, 11687-11699.
Musall, S., von Pföstl, V., Rauch, A., Logothetis, N.K., Whittingstall, K., 2014. Effects of neural synchrony on surface EEG. Cerebral Cortex 24, 1045-1053.
Nunez, P.L., Srinivasan, R., 2006. Electric fields of the brain: the neurophysics of EEG. Oxford university press.
Oberlaender, M., de Kock, C.P., Bruno, R.M., Ramirez, A., Meyer, H.S., Dercksen, V.J., Helmstaedter, M., Sakmann, B., 2012. Cell type–specific three-dimensional structure of thalamocortical circuits in a column of rat vibrissal cortex. Cerebral Cortex 22, 2375-2391.
Ohl, F.W., Scheich, H., Freeman, W.J., 2000. Topographic Analysis of Epidural Pure-Tone–Evoked Potentials in Gerbil Auditory Cortex. Journal of Neurophysiology 83, 3123-3132.
Okun, M., Lampl, I., 2008. Instantaneous correlation of excitation and inhibition during ongoing and sensory-evoked activities. Nature neuroscience 11, 535-537.
Olcese, U., Iurilli, G., Medini, P., 2013. Cellular and synaptic architecture of multisensory integration in the mouse neocortex. Neuron 79, 579-593.
Ozeki, H., Finn, I.M., Schaffer, E.S., Miller, K.D., Ferster, D., 2009. Inhibitory stabilization of the cortical network underlies visual surround suppression. Neuron 62, 578-592.
Paxinos Gand Watson, C., 1986. The rat brain in stereotaxic coordinates. San Diego, CA: Academic.
Pettersen, K.H., Devor, A., Ulbert, I., Dale, A.M., Einevoll, G.T., 2006. Current-source density estimation based on inversion of electrostatic forward solution: effects of finite extent of neuronal activity and conductivity discontinuities. Journal of neuroscience methods 154, 116-133.
Pinotsis, D.A., Friston, K.J., 2011. Neural fields, spectral responses and lateral connections. Neuroimage 55, 39-48.
Raizada, R.D., Grossberg, S., 2003. Towards a theory of the laminar architecture of cerebral cortex: Computational clues from the visual system. Cerebral Cortex 13, 100-113.
Ray, S., Crone, N.E., Niebur, E., Franaszczuk, P.J., Hsiao, S.S., 2008. Neural correlates of high-gamma oscillations (60–200 Hz) in macaque local field potentials and their potential implications in electrocorticography. The Journal of Neuroscience 28, 11526-11536.
Reinhold, K., Lien, A.D., Scanziani, M., 2015. Distinct recurrent versus afferent dynamics in cortical visual processing. Nature neuroscience.
Riera, J.J., Ogawa, T., Goto, T., Sumiyoshi, A., Nonaka, H., Evans, A., Miyakawa, H., Kawashima, R., 2012. Pitfalls in the dipolar model for the neocortical EEG sources. Journal of Neurophysiology 108, 956-975.
Roy, N.C., Bessaih, T., Contreras, D., 2011. Comprehensive mapping of whisker-evoked responses reveals broad, sharply tuned thalamocortical input to layer 4 of barrel cortex. Journal of Neurophysiology 105, 2421-2437.
Rubio-Garrido, P., Pérez-de-Manzo, F., Porrero, C., Galazo, M.J., Clascá, F., 2009. Thalamic input to distal apical dendrites in neocortical layer 1 is massive and highly convergent. Cerebral Cortex, bhn259.
Sachdev, R.N., Krause, M.R., Mazer, J.A., 2012. Surround suppression and sparse coding in visual and barrel cortices. Front Neural Circuits 6, 43.
Schwartzkroin, P.A., Prince, D.A., 1980. Changes in excitatory and inhibitory synaptic potentials leading to epileptogenic activity. Brain research 183, 61-77.
Slack, R., Boorman, L., Patel, P., Harris, S., Bruyns-Haylett, M., Kennerley, A., Jones, M., Berwick, J., 2016. A novel method for classifying cortical state to identify the accompanying changes in cerebral hemodynamics. Journal of neuroscience methods.
Sotero, R.C., Bortel, A., Martinez-Cancino, R., Neupane, S., O'CONNOR, P., Carbonell, F., Shmuel, A., 2010. Anatomically-constrained effective connectivity among layers in a cortical column modeled and estimated from local field potentials. Journal of integrative neuroscience 9, 355-379.
Sun, Y.J., Wu, G.K., Liu, B.-h., Li, P., Zhou, M., Xiao, Z., Tao, H.W., Zhang, L.I., 2010. Fine-tuning of pre-balanced excitation and inhibition during auditory cortical development. Nature 465, 927-931.
Sur, S., Sinha, V., 2009. Event-related potential: An overview. Industrial psychiatry journal 18, 70.
Teplan, M., 2002. Fundamentals of EEG measurement. Measurement science review 2, 1-11.
Thomson, D.J., 2000. Multitaper analysis of nonstationary and nonlinear time series data. Nonlinear and nonstationary signal processing, 317-394.
Turrigiano, G.G., 2008. The self-tuning neuron: synaptic scaling of excitatory synapses. Cell 135, 422-435.
Ueno, S., Bracamontes, J., Zorumski, C., Weiss, D.S., Steinbach, J.H., 1997. Bicuculline and gabazine are allosteric inhibitors of channel opening of the GABAA receptor. The Journal of Neuroscience 17, 625-634.
Valdes, P., Jiménez, J.C., Riera, J., Biscay, R., Ozaki, T., 1999. Nonlinear EEG analysis based on a neural mass model. Biological cybernetics 81, 415-424.
Vyazovskiy, V.V., Cirelli, C., Pfister-Genskow, M., Faraguna, U., Tononi, G., 2008. Molecular and electrophysiological evidence for net synaptic potentiation in wake and depression in sleep. Nature neuroscience 11, 200-208.
Wehr, M., Zador, A.M., 2003. Balanced inhibition underlies tuning and sharpens spike timing in auditory cortex. Nature 426, 442-446.
Wilent, W.B., Contreras, D., 2005. Dynamics of excitation and inhibition underlying stimulus selectivity in rat somatosensory cortex. Nature neuroscience 8, 1364-1370.
Xue, M., Atallah, B.V., Scanziani, M., 2014. Equalizing excitation-inhibition ratios across visual cortical neurons. Nature 511, 596-600.
Yang, W., Carrasquillo, Y., Hooks, B.M., Nerbonne, J.M., Burkhalter, A., 2013. Distinct balance of excitation and inhibition in an interareal feedforward and feedback circuit of mouse visual cortex. The Journal of Neuroscience 33, 17373-17384.
Yu, H., Chen, X., Sun, C., Shou, T., 2008. Global evaluation of contributions of GABA A, AMPA and NMDA receptors to orientation maps in cat's visual cortex. Neuroimage 40, 776-787.
Zhang, L.I., Tan, A.Y., Schreiner, C.E., Merzenich, M.M., 2003. Topography and synaptic shaping of direction selectivity in primary auditory cortex. Nature 424, 201-205.
Zhang, S., Xu, M., Kamigaki, T., Do, J.P.H., Chang, W.-C., Jenvay, S., Miyamichi, K., Luo, L., Dan, Y., 2014. Long-range and local circuits for top-down modulation of visual cortex processing. Science 345, 660-665.
Zheng, Y., Luo, J.J., Harris, S., Kennerley, A., Berwick, J., Billings, S.A., Mayhew, J., 2012. Balanced excitation and inhibition: Model based analysis of local field potentials. Neuroimage 63, 81-94. University Staff: Request a correction | Centaur Editors: Update this record |