Knowledge integration based on the relationship between structure and function of the neural substrate is one of the main targets of neuroinformatics and data-driven computational modeling. However, the multiplicity of data sources, the diversity of benchmarks, the mixing of observables of different natures, and the necessity of a long-term, systematic approach make such a task challenging. Here we present a first snapshot of a long-term integrative modeling program designed to address this issue in the domain of the visual system: a comprehensive spiking model of cat primary visual cortex. The presented model satisfies an extensive range of anatomical, statistical and functional constraints under a wide range of visual input statistics. In the presence of physiological levels of tonic stochastic bombardment by spontaneous thalamic activity, the modeled cortical reverberations self-generate a sparse asynchronous ongoing activity that quantitatively matches a range of experimentally measured statistics. When integrating feed-forward drive elicited by a high diversity of visual contexts, the simulated network produces a realistic, quantitatively accurate interplay between visually evoked excitatory and inhibitory conductances; contrast-invariant orientation-tuning width; center surround interactions; and stimulus-dependent changes in the precision of the neural code. This integrative model offers insights into how the studied properties interact, contributing to a better understanding of visual cortical dynamics. It provides a basis for future development towards a comprehensive model of low-level perception.

Faculty of Mathematics and Physics Charles University Malostranské nám 25 Prague 1 Czechia

INSERM UMRI S 968; Sorbonne Université UPMC Univ Paris 06 UMR S 968; CNRS UMR 7210 Institut de la Vision Paris France

Institut des neurosciences Paris Saclay Université Paris Saclay CNRS Saclay France

Unit of Neuroscience Information and Complexity CNRS FRE 3693 Gif sur Yvette France

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Olshausen BA. 20 years of learning about vision: Questions answered, questions unanswered, and questions not yet asked. In: 20 Years of Computational Neuroscience. Springer; 2013. p. 243–270.

Potjans TC, Diesmann M. The cell-type specific cortical microcircuit: Relating structure and activity in a full-scale spiking network model. Cerebral Cortex. 2014;24(3):785–806. doi: 10.1093/cercor/bhs358 PubMed DOI PMC

Bonin V, Mante V, Carandini M. The suppressive field of neurons in lateral geniculate nucleus. Journal of Neuroscience. 2005;25(47):10844–10856. doi: 10.1523/JNEUROSCI.3562-05.2005 PubMed DOI PMC

Carandini M, Heeger DJ. Summation and division by neurons in primate visual cortex. Science. 1994;264(5163):1333–1336. doi: 10.1126/science.8191289 PubMed DOI

Troyer TW, Krukowski aE, Priebe NJ, Miller KD. Contrast-invariant orientation tuning in cat visual cortex: thalamocortical input tuning and correlation-based intracortical connectivity. The Journal of Neuroscience. 1998;18(15):5908–5927. doi: 10.1523/JNEUROSCI.18-15-05908.1998 PubMed DOI PMC

Lauritzen TZ, Miller KD. Different roles for simple-cell and complex-cell inhibition in V1. Journal of Neuroscience. 2003;23(32):10201–10213. doi: 10.1523/JNEUROSCI.23-32-10201.2003 PubMed DOI PMC

Teich AF, Qian N. Comparison among some models of orientation selectivity. Journal of Neurophysiology. 2006;96(1):404–419. doi: 10.1152/jn.00015.2005 PubMed DOI

Finn IM, Priebe NJ, Ferster D. The emergence of contrast-invariant orientation tuning in simple cells of cat visual cortex. Neuron. 2007;54(1):137–52. doi: 10.1016/j.neuron.2007.02.029 PubMed DOI PMC

Olshausen BA, Field DJ. Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature. 1996;381(6583):607–609. doi: 10.1038/381607a0 PubMed DOI

Antolík J, Bednar JAJA. Development of Maps of Simple and Complex Cells in the Primary Visual Cortex. Frontiers in Computational Neuroscience. 2011;5(April):1–19. doi: 10.3389/fncom.2011.00017 PubMed DOI PMC

Zhu M, Rozell CJ. Visual Nonclassical Receptive Field Effects Emerge from Sparse Coding in a Dynamical System. PLoS Computational Biology. 2013;9(8):1–15. doi: 10.1371/journal.pcbi.1003191 PubMed DOI PMC

Somers DC, Todorov EV, Siapas AG, Toth LJ, Kim DS, Sur M. A local circuit approach to understanding integration of long-range inputs in primary visual cortex. Cerebral Cortex. 1998;8(3):204–217. doi: 10.1093/cercor/8.3.204 PubMed DOI

Rangan A, Tao L, Kovacic G, Cai D. Multiscale modeling of the primary visual cortex. IEEE Engineering in Medicine and Biology Magazine. 2009;28(3):19–24. doi: 10.1109/MEMB.2009.932803 PubMed DOI

Sejnowski TJ, Koch C, Churchland PS. Computational Neuroscience. Science. 1988;241(4871):1299–1306. doi: 10.1126/science.3045969 PubMed DOI

Einevoll GT, Destexhe A, Diesmann M, Grün S, Jirsa V, de Kamps M, et al.. The Scientific Case for Brain Simulations; 2019. PubMed

Markram H, Muller E, Ramaswamy S, Reimann MW, Abdellah M, Sanchez CA, et al.. Reconstruction and Simulation of Neocortical Microcircuitry. Cell. 2015;163(2):456–492. doi: 10.1016/j.cell.2015.09.029 PubMed DOI

Antolík J, Davison AP. Integrated workflows for spiking neuronal network simulations. Frontiers in Neuroinformatics. 2013;7(December):1–15. doi: 10.3389/fninf.2013.00034 PubMed DOI PMC

Buzás P, Kovács K, Ferecskó AS, Budd JML, Eysel UT, Kisvárday ZF. Model-based analysis of excitatory lateral connections in the visual cortex. Journal of Comparative Neurology. 2006;499(6):861–881. doi: 10.1002/cne.21134 PubMed DOI

Binzegger T, Douglas RJ, Martin KAC. A quantitative map of the circuit of cat primary visual cortex. Journal of Neuroscience. 2004;24(39):8441–8453. doi: 10.1523/JNEUROSCI.1400-04.2004 PubMed DOI PMC

Stepanyants A, Hirsch JA, Martinez LM, Kisvárday ZF, Ferecskó AS, Chklovskii DB. Local potential connectivity in cat primary visual cortex. Cerebral Cortex. 2008;18(1):13–28. doi: 10.1093/cercor/bhm027 PubMed DOI

Baudot P, Levy M, Marre O, Monier C, Pananceau M, Frégnac Y. Animation of natural scene by virtual eye-movements evokes high precision and low noise in V1 neurons. Frontiers in Neural Circuits. 2013;7(DEC):206. doi: 10.3389/fncir.2013.00206 PubMed DOI PMC

Papaioannou J, White A. Maintained activity of lateral geniculate nucleus neurons as a function of background luminance. Experimental Neurology. 1972;34(3):558–566. doi: 10.1016/0014-4886(72)90050-7 PubMed DOI

Cavaggioni A. The dark-discharge of the eye in the unrestrained cat. Pflügers Archiv European Journal of Physiology. 1968;304(1):75–80. doi: 10.1007/BF00586720 PubMed DOI

Levine MW. The distribution of the intervals between neural impulses in the maintained discharges of retinal ganglion cells. Biological Cybernetics. 1991;65(6):459–467. doi: 10.1007/BF00204659 PubMed DOI

Field GD, Rieke F. Mechanisms regulating variability of the single photon responses of mammalian rod photoreceptors. Neuron. 2002;35(4):733–747. doi: 10.1016/S0896-6273(02)00822-X PubMed DOI

Croner LJ, Purpura K, Kaplan E. Response variability in retinal ganglion cells of primates. Proceedings of the National Academy of Sciences of the United States of America. 1993;90(17):8128–8130. doi: 10.1073/pnas.90.17.8128 PubMed DOI PMC

Salari V, Scholkmann F, Bokkon I, Shahbazi F, Tuszynski J. The Physical Mechanism for Retinal Discrete Dark Noise: Thermal Activation or Cellular Ultraweak Photon Emission? PLoS ONE. 2016;11(3):1–16. doi: 10.1371/journal.pone.0148336 PubMed DOI PMC

Rogala J, Waleszczyk WJ, Wróbel A, Wójcik DK. Effect of cortex inactivation on spontaneous activity of cells in perigeniculate and dorsal lateral geniculate nuclei. BMC Neuroscience. 2013;14(S1):P418. doi: 10.1186/1471-2202-14-S1-P418 DOI

Da Costa NM, Martin KAC. How thalamus connects to spiny stellate cells in the cat’s visual cortex. Journal of Neuroscience. 2011;31(8):2925–2937. doi: 10.1523/JNEUROSCI.5961-10.2011 PubMed DOI PMC

Esposito F, Mulert C, Goebel R. Combined distributed source and single-trial EEG-fMRI modeling: Application to effortful decision making processes. NeuroImage. 2009;47(1):112–121. doi: 10.1016/j.neuroimage.2009.03.074 PubMed DOI

Lee AK, Manns ID, Sakmann B, Brecht M. Whole-Cell Recordings in Freely Moving Rats. Neuron. 2006;51(4):399–407. doi: 10.1016/j.neuron.2006.07.004 PubMed DOI

Destexhe A, Rudolph-Lilith M. Neuronal noise. Springer Series in Computational Neuroscience. Springer; US; 2012.

Le Van Quyen M, Muller LE, Telenczuk B, Halgren E, Cash S, Hatsopoulos NG, et al.. High-frequency oscillations in human and monkey neocortex during the wake–sleep cycle. Proceedings of the National Academy of Sciences. 2016;113(33):9363–9368. doi: 10.1073/pnas.1523583113 PubMed DOI PMC

Van Vreeswijk C, Sompolinsky H. Chaos in neuronal networks with balanced excitatory and inhibitory activity. Science. 1996;274(5293):1724–1726. doi: 10.1126/science.274.5293.1724 PubMed DOI

Brunel N. Dynamics of networks of randomly connected excitatory and inhibitory spiking neurons. Journal of Physiology-Paris. 2000;94(5-6):445–463. doi: 10.1016/S0928-4257(00)01084-6 PubMed DOI

Vogels TP, Abbott LF. Signal propagation and logic gating in networks of integrate-and-fire neurons. Journal of Neuroscience. 2005;25(46):10786–10795. doi: 10.1523/JNEUROSCI.3508-05.2005 PubMed DOI PMC

Bringuier V, Frégnac Y, Baranyi A, Debanne D, Shulz DE. Synaptic origin and stimulus dependency of neuronal oscillatory activity in the primary visual cortex of the cat. Journal of Physiology. 1997;500(3):751–774. doi: 10.1113/jphysiol.1997.sp022056 PubMed DOI PMC

Swadlow HA. Fast-spike Interneurons and Feedforward Inhibition in Awake Sensory Neocortex. Cerebral Cortex. 2003;13(1):25–32. doi: 10.1093/cercor/13.1.25 PubMed DOI

Monier C, Chavane F, Baudot P, Graham LJ, Frégnac Y. Orientation and direction selectivity of synaptic inputs in visual cortical neurons: a diversity of combinations produces spike tuning. Neuron. 2003;37(4):663–80. doi: 10.1016/S0896-6273(03)00064-3 PubMed DOI

Bardy C, Huang JY, Wang C, FitzGibbon T, Dreher B. ‘Simplification’ of responses of complex cells in cat striate cortex: Suppressive surrounds and’feedback’ inactivation. Journal of Physiology. 2006;574(3):731–750. doi: 10.1113/jphysiol.2006.110320 PubMed DOI PMC

Kim T, Freeman RD. Direction selectivity of neurons in the visual cortex is non-linear and lamina-dependent. European Journal of Neuroscience. 2016;43(10):1389–1399. doi: 10.1111/ejn.13223 PubMed DOI PMC

Hromadka T, DeWeese MR, Zador AM. Sparse Representation of Sounds in the Unanesthetized Auditory Cortex. PLoS biology. 2008;6(1):124–137. doi: 10.1371/journal.pbio.0060016 PubMed DOI PMC

Buzsáki G, Mizuseki K. The log-dynamic brain: how skewed distributions affect network operations. Nature Reviews Neuroscience. 2014;15(4):264–278. doi: 10.1038/nrn3687 PubMed DOI PMC

Monier C, Fournier J, Frégnac Y. In vitro and in vivo measures of evoked excitatory and inhibitory conductance dynamics in sensory cortices. Journal of Neuroscience Methods. 2008;169(2):323–365. doi: 10.1016/j.jneumeth.2007.11.008 PubMed DOI

Kumar A, Schrader S, Aertsen A, Rotter S. The high-conductance state of cortical networks. Neural Computation. 2008;20(1):1–43. doi: 10.1162/neco.2008.20.1.1 PubMed DOI

Carandini M, Ferster D. Membrane Potential and Firing Rate in Cat Primary Visual Cortex. The Journal of Neuroscience. 2000;20:470–484. doi: 10.1523/JNEUROSCI.20-01-00470.2000 PubMed DOI PMC

Contreras D, Palmer L. Response to Contrast of Electrophysiologically Defined Cell Classes in Primary Visual Cortex. The Journal of Neuroscience. 2003;23(17):6936–6945. doi: 10.1523/JNEUROSCI.23-17-06936.2003 PubMed DOI PMC

Nowak LG, Sanchez-Vives MV, McCormick DA. Lack of orientation and direction selectivity in a subgroup of fast-spiking inhibitory interneurons: Cellular and synaptic mechanisms and comparison with other electrophysiological cell types. Cerebral Cortex. 2008;18(5):1058–1078. doi: 10.1093/cercor/bhm137 PubMed DOI PMC

Cardin JA, Palmer LA, Contreras D. Stimulus feature selectivity in excitatory and inhibitory neurons in primary visual cortex. Journal of Neuroscience. 2007;27(39):10333–10344. doi: 10.1523/JNEUROSCI.1692-07.2007 PubMed DOI PMC

Chariker L, Shapley R, Young LS. Orientation selectivity from very sparse LGN inputs in a comprehensive model of macaque V1 cortex. Journal of Neuroscience. 2016;36(49):12368–12384. doi: 10.1523/JNEUROSCI.2603-16.2016 PubMed DOI PMC

Anderson JS, Carandini M, Ferster D. Orientation tuning of input conductance, excitation, and inhibition in cat primary visual cortex. Journal of Neurophysiology. 2000;84(2):909–926. doi: 10.1152/jn.2000.84.2.909 PubMed DOI

Schummers J, Mariño J, Sur M. Synaptic integration by V1 neurons depends on location within the orientation map. Neuron. 2002;36(5):969–978. doi: 10.1016/S0896-6273(02)01012-7 PubMed DOI

Hirsch JA, Martinez LM. Laminar processing in the visual cortical column. Current Opinion in Neurobiology. 2006;16(4):377–384. doi: 10.1016/j.conb.2006.06.014 PubMed DOI

Priebe NJ, Mechler F, Carandini M, Ferster D. The contribution of spike threshold to the dichotomy of cortical simple and complex cells. Nature Neuroscience. 2004;7(10):1113–1122. doi: 10.1038/nn1310 PubMed DOI PMC

Wang C, Bardy C, Huang JY, FitzGibbon T, Dreher B. Constrast dependence of center and surround integration in primary visual cortex of the cat. Journal of Vision. 2009;9(1):20.1–15. doi: 10.1167/9.1.20 PubMed DOI

Tailby C, Solomon SG, Peirce JW, Metha AB. Two expressions of “surround suppression” in V1 that arise independent of cortical mechanisms of suppression. Visual Neuroscience. 2007;24(1):99–109. doi: 10.1017/S0952523807070022 PubMed DOI

Okamoto M, Naito T, Sadakane O, Osaki H, Sato H. Surround suppression sharpens orientation tuning in the cat primary visual cortex. European Journal of Neuroscience. 2009;29(5):1035–1046. doi: 10.1111/j.1460-9568.2009.06645.x PubMed DOI

Akasaki T, Sato H, Yoshimura Y, Ozeki H, Shimegi S. Suppressive effects of receptive field surround on neuronal activity in the cat primary visual cortex. Neurosci Res. 2002;43(3):207–20. doi: 10.1016/S0168-0102(02)00038-X PubMed DOI

Nurminen L, Merlin S, Bijanzadeh M, Federer F, Angelucci A. Top-down feedback controls spatial summation and response amplitude in primate visual cortex. Nature Communications. 2018;9(1). doi: 10.1038/s41467-018-04500-5 PubMed DOI PMC

Jones HE, Andolina IM, Oakely NM, Murphy PC, Sillito AM. Spatial summation in lateral geniculate nucleus and visual cortex. Experimental Brain Research. 2000;135(2):279–284. doi: 10.1007/s002210000574 PubMed DOI

Wilson JR, Sherman SM. Receptive-field characteristics of neurons in cat striate cortex: Changes with visual field eccentricity. Journal of Neurophysiology. 1976;39(3):512–533. doi: 10.1152/jn.1976.39.3.512 PubMed DOI

Sengpiel F, Sen A, Blakemore C. Characteristics of surround inhibition in cat area 17. Experimental Brain Research. 1997;116(2):216–228. doi: 10.1007/PL00005751 PubMed DOI

Anderson JS, Lampl I, Gillespie DC, Ferster D. Membrane potential and conductance changes underlying length tuning of cells in cat primary visual cortex. Journal of Neuroscience. 2001;21(6):2104–2112. doi: 10.1523/JNEUROSCI.21-06-02104.2001 PubMed DOI PMC

Ozeki H, Finn IM, Schaffer ES, Miller KD, Ferster D. Inhibitory Stabilization of the Cortical Network Underlies Visual Surround Suppression. Neuron. 2009;62(4):578–592. doi: 10.1016/j.neuron.2009.03.028 PubMed DOI PMC

Kremkow J, Perrinet LU, Monier C, Alonso JM, Aertsen A, Frégnac Y, et al.. Push-pull receptive field organization and synaptic depression: Mechanisms for reliably encoding naturalistic stimuli in V1. Frontiers in Neural Circuits. 2016;10(MAY). doi: 10.3389/fncir.2016.00037 PubMed DOI PMC

Antolík J, Davison APA. Arkheia: Data Management and Communication for Open Computational Neuroscience. Frontiers in Neuroinformatics. 2018;12:6. doi: 10.3389/fninf.2018.00006 PubMed DOI PMC

Wielaard J, Sajda P. Circuitry and the classification of simple and complex cells in V1. Journal of Neurophysiology. 2006;96(5):2739–2749. doi: 10.1152/jn.00346.2006 PubMed DOI

Wielaard J, Sajda P. Extraclassical receptive field phenomena and short-range connectivity in V1. Cerebral Cortex. 2006;16(11):1531–1545. doi: 10.1093/cercor/bhj090 PubMed DOI

Hill S, Tononi G. Modeling sleep and wakefulness in the thalamocortical system. Journal of neurophysiology. 2005;93(3):1671–98. doi: 10.1152/jn.00915.2004 PubMed DOI

Lumer ED, Edelman GM, Tononi G. Neural dynamics in a model of the thalamocortical system. I. Layers, loops and the emergence of fast synchronous rhythms. Cerebral Cortex. 1997;7:207–27. doi: 10.1093/cercor/7.3.207 PubMed DOI

Lumer ED, Edelman GM, Tononi G. Neural dynamics in a model of the thalamocortical system. II. The role of neural synchrony tested through perturbations of spike timing. Cerebral Cortex. 1997;7:228–236. doi: 10.1093/cercor/7.3.228 PubMed DOI

Esser SK, Hill SL, Tononi G. Sleep homeostasis and cortical synchronization: I. Modeling the effects of synaptic strength on sleep slow waves. Sleep. 2007;30(12):1617–1630. doi: 10.1093/sleep/30.12.1617 PubMed DOI PMC

Cai D, Rangan AV, McLaughlin DW. Architectural and synaptic mechanisms underlying coherent spontaneous activity in V1. Proceedings of the National Academy of Sciences of the United States of America. 2005;102(16):5868–5873. doi: 10.1073/pnas.0501913102 PubMed DOI PMC

Tao L, Cai D, McLaughlin DW, Shelley MJ, Shapley R. Orientation selectivity in visual cortex by fluctuation-controlled criticality. Proceedings of the National Academy of Sciences of the United States of America. 2006;103(34):12911–12916. doi: 10.1073/pnas.0605415103 PubMed DOI PMC

Rangan AV, Cai D, McLaughlin DW. Modeling the spatiotemporal cortical activity associated with the line-motion illusion in primary visual cortex. Proceedings of the National Academy of Sciences of the United States of America. 2005;102(52):18793–18800. doi: 10.1073/pnas.0509481102 PubMed DOI PMC

Chariker L, Shapley R, Young LS. Rhythm and synchrony in a cortical network model. Journal of Neuroscience. 2018;38(40):8621–8634. doi: 10.1523/JNEUROSCI.0675-18.2018 PubMed DOI PMC

Chariker L, Shapley R, Young LS. Contrast response in a comprehensive network model of macaque V1. Journal of Vision. 2020;20(4):1–19. doi: 10.1167/jov.20.4.16 PubMed DOI PMC

Chariker L, Shapley R, Hawken M, Young LS. A Computational Model of Direction Selectivity in Macaque V1 Cortex Based on Dynamic Differences between On and Off Pathways. Journal of Neuroscience. 2022;42(16):3365–3380. doi: 10.1523/JNEUROSCI.2145-21.2022 PubMed DOI PMC

Nowak LG, Azouz R, Sanchez-Vives MV, Gray CM, McCormick Da. Electrophysiological classes of cat primary visual cortical neurons in vivo as revealed by quantitative analyses. Journal of Neurophysiology. 2003;89(3):1541–1566. doi: 10.1152/jn.00580.2002 PubMed DOI

Hubel DH, Wiesel TN. Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. The Journal of Physiology. 1962;160(1):106–154. doi: 10.1113/jphysiol.1962.sp006837 PubMed DOI PMC

Pugh M, Ringach D, Shapley R, Shelley M. Computational Modeling of Orientation Tuning Dynamics in V1 Neurons. J Comp Neuroscience. 2000;8:143–159. doi: 10.1023/A:1008921231855 PubMed DOI

Somers DC, Nelson SB, Sur M. An emergent model of orientation selectivity in cat visual cortical simple cells. Journal of Neuroscience. 1995;15(8):5448–5465. doi: 10.1523/JNEUROSCI.15-08-05448.1995 PubMed DOI PMC

Sillito AM, Kemp JA, Milson JA, Berardi N. A re-evaluation of the mechanisms underlying simple cell orientation selectivity. Brain Research. 1980;194:517–520. doi: 10.1016/0006-8993(80)91234-2 PubMed DOI

Creutzfeldt OD, Kuhnt U, Benevento LA. An intracellular analysis of visual cortical neurones to moving stimuli: Responses in a co-operative neuronal network. Experimental Brain Research. 1974;21(3):251–274. doi: 10.1007/BF00235746 PubMed DOI

Rubin DB, VanHooser SD, Miller KD. The stabilized supralinear network: A unifying circuit motif underlying multi-input integration in sensory cortex. Neuron. 2015;85(2):402–417. doi: 10.1016/j.neuron.2014.12.026 PubMed DOI PMC

Hirsch Ja, Alonso JM, Reid RC, Martinez LM. Synaptic Integration in Striate Cortical Simple Cells. Journal of Neuroscience. 1998;18(22):9517–9528. doi: 10.1523/JNEUROSCI.18-22-09517.1998 PubMed DOI PMC

Ferster D, Miller KD. Neural Mechanisms of Orientation Selectivity in the Visual Cortex. Annual Review of Neuroscience. 2000;23(1):441–471. doi: 10.1146/annurev.neuro.23.1.441 PubMed DOI

Ben-Yishai R, Lev Bar-Or R, Sompolinsky H. Theory of orientation tuning in visual cortex. Proceedings of the National Academy of Sciences of the United States of America. 1995;92(9):3844–3848. doi: 10.1073/pnas.92.9.3844 PubMed DOI PMC

Douglas R, Koch C, Mahowald M, Martin K, Suarez H. Recurrent excitation in neocortical circuits. Science. 1995;269(5226):981–985. doi: 10.1126/science.7638624 PubMed DOI

Ko H, Hofer SB, Pichler B, Buchanan KA, Sjöström PJ, Mrsic-Flogel TD. Functional specificity of local synaptic connections in neocortical networks. Nature. 2011;473(7345):87–91. doi: 10.1038/nature09880 PubMed DOI PMC

Arkhipov A, Gouwens NW, Billeh YN, Gratiy S, Iyer R, Wei Z, et al.. Visual physiology of the layer 4 cortical circuit in silico. PLOS Computational Biology. 2018;14(11):e1006535. doi: 10.1371/journal.pcbi.1006535 PubMed DOI PMC

Billeh YN, Cai B, Gratiy SL, Dai K, Iyer R, Gouwens NW, et al.. Systematic Integration of Structural and Functional Data into Multi-scale Models of Mouse Primary Visual Cortex. Neuron. 2020;106:388–403.e18. doi: 10.1016/j.neuron.2020.01.040 PubMed DOI

Fournier J, Monier C, Levy M, Marre O, Sari K, Kisvarday ZF, et al.. Hidden Complexity of Synaptic Receptive Fields in Cat V1. Journal of Neuroscience. 2014;34(16):5515–5528. doi: 10.1523/JNEUROSCI.0474-13.2014 PubMed DOI PMC

Frégnac Y, Bathellier B. Cortical Correlates of Low-Level Perception: From Neural Circuits to Percepts. Neuron. 2015;88:110–126. doi: 10.1016/j.neuron.2015.09.041 PubMed DOI

Gerard-Mercier F, Carelli PV, Pananceau M, Troncoso XG, Frégnac Y. Synaptic correlates of low-level perception in V1. Journal of Neuroscience. 2016;36(14):3925–3942. doi: 10.1523/JNEUROSCI.4492-15.2016 PubMed DOI PMC

Stepanyants A, Martinez LM, Ferecsko AS, Kisvarday ZF. The fractions of short- and long-range connections in the visual cortex. Proceedings of the National Academy of Sciences. 2009;106(9):3555–3560. doi: 10.1073/pnas.0810390106 PubMed DOI PMC

Martinez LM, Wang Q, Reid RC, Pillai C, Alonso JM, Sommer FT, et al.. Receptive field structure varies with layer in the primary visual cortex. Nature Neuroscience. 2005;8(3):372–379. doi: 10.1038/nn1404 PubMed DOI PMC

Allen Brain Observatory contributors. Allen Institute for Brain Science: Allen Brain Observatory; 2016. http://observatory.brain-map.org/visualcoding.

Thomson AM. Neocortical layer 6, a review. Frontiers in neuroanatomy. 2010;4(March):13. doi: 10.3389/fnana.2010.00013 PubMed DOI PMC

Thomson AM. Interlaminar Connections in the Neocortex. Cerebral Cortex. 2003;13(1):5–14. doi: 10.1093/cercor/13.1.5 PubMed DOI

Wang W, Jones HE, Andolina IM, Salt TE, Sillito AM. Functional alignment of feedback effects from visual cortex to thalamus. Nature Neuroscience. 2006;9(10):1330–1336. doi: 10.1038/nn1768 PubMed DOI

Sillito AM, Jones HE, Gerstein GL, West DC. Feature-linked synchronization of thalamic relay cell firing induced by feedback from the visual cortex. Nature. 1994;369(6480):479–482. doi: 10.1038/369479a0 PubMed DOI

Angelucci A, Bullier J. Reaching beyond the classical receptive field of V1 neurons: Horizontal or feedback axons? Journal of Physiology Paris. 2003;97(2-3):141–154. doi: 10.1016/j.jphysparis.2003.09.001 PubMed DOI

Budd JML. Extrastriate feedback to primary visual cortex in primates: A quantitative analysis of connectivity. Proceedings of the Royal Society B: Biological Sciences. 1998;265(1400):1037–1044. doi: 10.1098/rspb.1998.0396 PubMed DOI PMC

Xu X, Callaway EM. Laminar specificity of functional input to distinct types of inhibitory cortical neurons. Journal of Neuroscience. 2009;29(1):70–85. doi: 10.1523/JNEUROSCI.4104-08.2009 PubMed DOI PMC

Markov NT, Vezoli J, Chameau P, Falchier A, Quilodran R, Huissoud C, et al.. Anatomy of hierarchy: Feedforward and feedback pathways in macaque visual cortex. Journal of Comparative Neurology. 2014;522(1):225–259. doi: 10.1002/cne.23458 PubMed DOI PMC

Guarino DG, Davison AP, Frégnac Y, Antolík J. The cortico-thalamic loop attunes competitive lateral interactions across retinotopic and orientation preference maps. BioRxiv. 2022;.

Pfeffer CK, Xue M, He M, Huang ZJ, Scanziani M. Inhibition of inhibition in visual cortex: The logic of connections between molecularly distinct interneurons. Nature Neuroscience. 2013;16(8):1068–1076. doi: 10.1038/nn.3446 PubMed DOI PMC

Harris KD, Mrsic-Flogel TD. Cortical connectivity and sensory coding; 2013. PubMed

van Albada SJ, Helias M, Diesmann M. Scalability of Asynchronous Networks Is Limited by One-to-One Mapping between Effective Connectivity and Correlations. PLOS Computational Biology. 2015;11(9):1–37. doi: 10.1371/journal.pcbi.1004490 PubMed DOI PMC

Davis ZW, Benigno GB, Fletterman C, Desbordes T, Steward C, Sejnowski TJ, et al.. Spontaneous traveling waves naturally emerge from horizontal fiber time delays and travel through locally asynchronous-irregular states. Nature Communications. 2021;12(1). doi: 10.1038/s41467-021-26175-1 PubMed DOI PMC

Schmidt M, Bakker R, Shen K, Bezgin G, Diesmann M, Van Albada SJ. A multi-scale layer-resolved spiking network model of resting-state dynamics in macaque visual cortical areas. PLOS Computational Biology. 2018;14(10):e1006359. doi: 10.1371/journal.pcbi.1006359 PubMed DOI PMC

Fourcaud-Trocmé N, Hansel D, van Vreeswijk C, Brunel N. How spike generation mechanisms determine the neuronal response to fluctuating inputs. Journal of Neuroscience. 2003;23(37):11628–40. doi: 10.1523/JNEUROSCI.23-37-11628.2003 PubMed DOI PMC

Ascoli GA, Donohue DE, Halavi M. NeuroMorpho.Org: A Central Resource for Neuronal Morphologies. Journal of Neuroscience. 2007;27(35):9247–9251. doi: 10.1523/JNEUROSCI.2055-07.2007 PubMed DOI PMC

Kremkow J, Jin J, Komban SJ, Wang Y, Lashgari R, Li X, et al.. Neuronal nonlinearity explains greater visual spatial resolution for darks than lights. Proceedings of the National Academy of Sciences of the United States of America. 2014;111(8):3170–5. doi: 10.1073/pnas.1310442111 PubMed DOI PMC

Wang Y, Jin J, Kremkow J, Lashgari R, Komban SJ, Alonso JM. Columnar organization of spatial phase in visual cortex. Nature Neuroscience. 2014;18(1):97–103. doi: 10.1038/nn.3878 PubMed DOI PMC

Jones JP, Palmer LA. The two-dimensional spatial structure of simple receptive fields in cat striate cortex. Journal of Neurophysiology. 1987;58(6):1187–1211. doi: 10.1152/jn.1987.58.6.1187 PubMed DOI

Ringach DL. Mapping receptive fields in primary visual cortex. Journal of Physiology. 2004;558(3):717–728. doi: 10.1113/jphysiol.2004.065771 PubMed DOI PMC

Kayser AS, Miller KD. Opponent Inhibition: A Developmental Model of Layer 4 of the Neocortical Circuit. Neuron. 2002;33(1):131–142. doi: 10.1016/S0896-6273(01)00570-0 PubMed DOI

Sinha A, de Schepper R, Pronold J, Mitchell J, Mørk H, Nagendra Babu P, et al.. NEST 3.4; 2023.

Tusa RJ, Palmer La, Rosenquist aC. The retinotopic organization of area 17 (striate cortex) in the cat. The Journal of comparative neurology. 1978;177(2):213–35. doi: 10.1002/cne.901770204 PubMed DOI

Beaulieu C, Colonnier M. Number of neurons in individual laminae of areas 3B, 4γ, and 6aα of the cat cerebral cortex: A comparison with major visual areas. Journal of Comparative Neurology. 1989;279(2):228–234. doi: 10.1002/cne.902790206 PubMed DOI

Beaulieu C, Kisvarday Z, Somogyi P, Cynader M, Cowey A. Quantitative distribution of gaba-immunopositive and -immunonegative neurons and synapses in the monkey striate cortex (area 17). Cerebral Cortex. 1992;2(4):295–309. doi: 10.1093/cercor/2.4.295 PubMed DOI

Markram H, Toledo-Rodriguez M, Wang Y, Gupta A, Silberberg G, Wu C. Interneurons of the neocortical inhibitory system. Nature Reviews Neuroscience. 2004;5(10):793–807. doi: 10.1038/nrn1519 PubMed DOI

Angelucci A, Levitt JB, Walton EJS, Hupé JM, Bullier J, Lund JS. Circuits for local and global signal integration in primary visual cortex. Journal of Neuroscience. 2002;22(19):8633–8646. doi: 10.1523/JNEUROSCI.22-19-08633.2002 PubMed DOI PMC

Nordlie E, Gewaltig MO, Plesser HE. Towards reproducible descriptions of neuronal network models. PLoS Computational Biology. 2009;5(8):e1000456. doi: 10.1371/journal.pcbi.1000456 PubMed DOI PMC

McCormick DA, Connors BW, Lighthall JW, Prince DA. Comparative electrophysiology of pyramidal and sparsely spiny stellate neurons of the neocortex. Journal of Neurophysiology. 1985;54(4):782–806. doi: 10.1152/jn.1985.54.4.782 PubMed DOI

Naud R, Marcille N, Clopath C, Gerstner W. Firing patterns in the adaptive exponential integrate-and-fire model. Biological Cybernetics. 2008;99(4-5):335–347. doi: 10.1007/s00422-008-0264-7 PubMed DOI PMC

Antolík J. Rapid long-range disynaptic inhibition explains the formation of cortical orientation maps. Frontiers in Neural Circuits. 2017;11(March):1–15. doi: 10.3389/fncir.2017.00021 PubMed DOI PMC

Movshon JA, Thompson ID, Tolhurst DJ. Spatial and temporal contrast sensitivity of neurones in areas 17 and 18 of the cat’s visual cortex. The Journal of Physiology. 1978;283(1):101–120. doi: 10.1113/jphysiol.1978.sp012490 PubMed DOI PMC

Payne B, Peters A. The Cat Primary Visual Cortex. Elsevier Science; 2001.

Beaulieu C, Colonnier M. A laminar analysis of the number of round asymmetrical and flat symmetrical synapses on spines, dendritic trunks, and cell bodies in area 17 of the cat. Journal of Comparative Neurology. 1985;231(2):180–189. doi: 10.1002/cne.902310206 PubMed DOI

Stratford KJ, Tarczy-Hornoch K, Martin KAC, Bannister NJ, Jack JJB. Excitatory synaptic inputs to spiny stellate cells in cat visual cortex. Nature. 1996;382(6588):258–261. doi: 10.1038/382258a0 PubMed DOI

Allen C, Stevens CF. An evaluation of causes for unreliability of synaptic transmission. Proceedings of the National Academy of Sciences of the United States of America. 1994;91(October):10380–10383. doi: 10.1073/pnas.91.22.10380 PubMed DOI PMC

Izhikevich EM, Edelman GM. Large-scale model of mammalian thalamocortical systems. Proceedings of the National Academy of Sciences of the United States of America. 2008;105(9):3593–3598. doi: 10.1073/pnas.0712231105 PubMed DOI PMC

Budd JM, Kisvárday ZF. Local lateral connectivity of inhibitory clutch cells in layer 4 of cat visual cortex (area 17). Experimental Brain Research. 2001;140(2):245–250. doi: 10.1007/s002210100817 PubMed DOI

Lee WCA, Bonin V, Reed M, Graham BJ, Hood G, Glattfelder K, et al.. Anatomy and function of an excitatory network in the visual cortex. Nature. 2016;532(7599):370–374. doi: 10.1038/nature17192 PubMed DOI PMC

Hoffmann JHO, Meyer HS, Schmitt AC, Straehle J, Weitbrecht T, Sakmann B, et al.. Synaptic conductance estimates of the connection between local inhibitor interneurons and pyramidal neurons in layer 2/3 of a cortical column. Cerebral Cortex. 2015;25(11):4415–4429. doi: 10.1093/cercor/bhv039 PubMed DOI PMC

Cruikshank SJ, Lewis TJ, Connors BW. Synaptic basis for intense thalamocortical activation of feedforward inhibitory cells in neocortex. Nature Neuroscience. 2007;10(4):462–468. doi: 10.1038/nn1861 PubMed DOI

Abbott LF. Synaptic Depression and Cortical Gain Control. Science. 1997;275(5297):221–224. doi: 10.1126/science.275.5297.221 PubMed DOI

Markram H, Wang Y, Tsodyks M. Differential signaling via the same axon of neocortical pyramidal neurons. Proceedings of the National Academy of Sciences of the United States of America. 1998;95(9):5323–5328. doi: 10.1073/pnas.95.9.5323 PubMed DOI PMC

Banitt Y, Martin KAC, Segev I. A biologically realistic model of contrast invariant orientation tuning by thalamocortical synaptic depression. Journal of Neuroscience. 2007;27(38):10230–10239. doi: 10.1523/JNEUROSCI.1640-07.2007 PubMed DOI PMC

Beierlein M, Gibson JR, Connors BW. Two Dynamically Distinct Inhibitory Networks in Layer 4 of the Neocortex. Journal of Neurophysiology. 2003;90(5):2987–3000. doi: 10.1152/jn.00283.2003 PubMed DOI

Ma Y, Hu H, Agmon A. Short-term plasticity of unitary inhibitory-to-inhibitory synapses depends on the presynaptic interneuron subtype. Journal of Neuroscience. 2012;32(3):983–988. doi: 10.1523/JNEUROSCI.5007-11.2012 PubMed DOI PMC

Bringuier V, Chavane F, Glaeser L, Frégnac Y. Horizontal propagation of visual activity in the synaptic integration field of area 17 neurons. Science. 1999;283(5402):695–699. doi: 10.1126/science.283.5402.695 PubMed DOI

Frégnac Y. Reading Out the Synaptic Echoes of Low-Level Perception in V1. In: Fusiello A, Murino V, Cucchiara R, editors. Lecture Notes in Computer Science 1. vol. 7583 of Lecture Notes in Computer Science. Springer; 2012. p. 486–495.

Chavane F, Sharon D, Jancke D, Marre O, Frégnac Y, Grinvald A. Lateral spread of orientation selectivity in V1 is controlled by intracortical cooperativity. Frontiers in Systems Neuroscience. 2011;5(FEBRUARY 2011):1–26. doi: 10.3389/fnsys.2011.00004 PubMed DOI PMC

Ohana O, Portner H, Martin KAC. Fast Recruitment of Recurrent Inhibition in the Cat Visual Cortex. PLoS ONE. 2012;7(7):e40601. doi: 10.1371/journal.pone.0040601 PubMed DOI PMC

Cai D, DeAngelis GC, Freeman RD. Spatiotemporal receptive field organization in the lateral geniculate nucleus of cats and kittens. Journal of Neurophysiology. 1997;78(2):1045–1061. doi: 10.1152/jn.1997.78.2.1045 PubMed DOI

Alitto HJ, Usrey WM. Influence of contrast on orientation and temporal frequency tuning in ferret primary visual cortex. Journal of Neurophysiology. 2004;91(6):2797–2808. doi: 10.1152/jn.00943.2003 PubMed DOI

Skottun BC, De Valois RL, Grosof DH, Movshon JA, Albrecht DG, Bonds AB. Classifying simple and complex cells on the basis of response modulation. Vision Research. 1991;31(7-8):1078–1086. doi: 10.1016/0042-6989(91)90033-2 PubMed DOI

Assessment of optogenetically-driven strategies for prosthetic restoration of cortical vision in large-scale neural simulation of V1