Biological experiments targeting the mammalian primary visual cortex have shown that neuronal response to a preferred orientation grating is cross-inhibited by an orthogonal orientation mask grating. The plaid formed by the overlap of the two gratings not only causes a decrease in the neuronal firing rate but also shifts the gamma oscillation to a weaker oscillation at a higher frequency. The mechanism for the above phenomena is unclarified. In this paper, a large-scale cortical neuronal network model with biological details is constructed. In this model, two modes of connectivity that may contribute to cross-inhibition are considered: the thalamo-cortical feedforward pathway and the push-pull organization of cortical layer 4. Based on this model, the modulation of firing rate and gamma oscillation by a plaid stimulation are successfully reproduced, which is consistent with biological experiments and suggests that it is the thalamo-cortical feedforward pathway that leads to cross-inhibition. Furthermore, our analysis of the neuronal spike clusters and current fluctuations suggests that the push-pull organization leads to an increase in gamma frequency during the transition of visual stimuli from grating to plaid by modulating the source of synaptic inhibition in local neuronal populations. Such results will help to understand the visual processing under multi-input integration.
Citation: Hao Yang, Peihan Wang, Fang Han, Qingyun Wang. An interpretable mechanism for grating-induced cross-inhibition and gamma oscillation based on a visual cortical neuronal network model[J]. Electronic Research Archive, 2024, 32(4): 2936-2954. doi: 10.3934/era.2024134
Biological experiments targeting the mammalian primary visual cortex have shown that neuronal response to a preferred orientation grating is cross-inhibited by an orthogonal orientation mask grating. The plaid formed by the overlap of the two gratings not only causes a decrease in the neuronal firing rate but also shifts the gamma oscillation to a weaker oscillation at a higher frequency. The mechanism for the above phenomena is unclarified. In this paper, a large-scale cortical neuronal network model with biological details is constructed. In this model, two modes of connectivity that may contribute to cross-inhibition are considered: the thalamo-cortical feedforward pathway and the push-pull organization of cortical layer 4. Based on this model, the modulation of firing rate and gamma oscillation by a plaid stimulation are successfully reproduced, which is consistent with biological experiments and suggests that it is the thalamo-cortical feedforward pathway that leads to cross-inhibition. Furthermore, our analysis of the neuronal spike clusters and current fluctuations suggests that the push-pull organization leads to an increase in gamma frequency during the transition of visual stimuli from grating to plaid by modulating the source of synaptic inhibition in local neuronal populations. Such results will help to understand the visual processing under multi-input integration.
| [1] |
M. C. Morrone, D. C. Burr, L. Maffei, Functional implications of cross-orientation inhibition of cortical visual cells. Ⅰ. neurophysiological evidence, Proc. R. Soc. B, 216 (1982), 335–354, https://doi.org/10.1098/rspb.1982.0078 doi: 10.1098/rspb.1982.0078
|
| [2] |
G. C. DeAngelis, J. G. Robson, I. Ohzawa, R. D. Freeman, Organization of suppression in receptive fields of neurons in cat visual cortex, J. Neurophysiol., 68 (1992), 144–163. https://doi.org/10.1152/jn.1992.68.1.144 doi: 10.1152/jn.1992.68.1.144
|
| [3] |
N. J. Priebe, D. Ferster, Mechanisms underlying cross-orientation suppression in cat visual cortex, Nat. Neurosci., 9 (2006), 552–561. https://doi.org/10.1038/nn1660 doi: 10.1038/nn1660
|
| [4] |
M. Popović, A. K. Stacy, M. Kang, R. Nanu, C. E. Oettgen, D. L. Wise, et al., Development of cross-orientation suppression and size tuning and the role of experience, J. Neurosci., 38 (2018), 2656–2670. https://doi.org/10.1523/JNEUROSCI.2886-17.2018 doi: 10.1523/JNEUROSCI.2886-17.2018
|
| [5] |
H. E. Jones, W. Wang, A. M. Sillito, Spatial organization and magnitude of orientation contrast interactions in primate V1, J. Neurophysiol., 88 (2002), 2796–2808. https://doi.org/10.1152/jn.00403.2001 doi: 10.1152/jn.00403.2001
|
| [6] |
M. J. Bartolo, M. A. Gieselmann, V. Vuksanovic, D. Hunter, L. Sun, X. Chen, et al., Stimulus-induced dissociation of neuronal firing rates and local field potential gamma power and its relationship to the blood oxygen level-dependent signal in macaque primary visual cortex, Eur. J. Neurosci., 34 (2011), 1857–1870. https://doi.org/10.1111/j.1460-9568.2011.07877.x doi: 10.1111/j.1460-9568.2011.07877.x
|
| [7] |
D. L. Ringach, The geometry of masking in neural populations, Nat. Commun., 10 (2019), 4879. https://doi.org/10.1038/s41467-019-12881-4 doi: 10.1038/s41467-019-12881-4
|
| [8] |
D. R. Muir, P. Molina-Luna, M. M. Roth, F. Helmchen, B. M. Kampa, Specific excitatory connectivity for feature integration in mouse primary visual cortex, PLoS Comput. Biol., 13 (2017), 1–33. https://doi.org/10.1371/journal.pcbi.1005888 doi: 10.1371/journal.pcbi.1005888
|
| [9] |
S. C. Guan, S. H. Zhang, Y. C. Zhang, S. M. Tang, C. Yu, Plaid detectors in macaque V1 revealed by two-photon calcium imaging, Curr. Biol., 30 (2020), 934–940. https://doi.org/10.1016/j.cub.2020.01.005 doi: 10.1016/j.cub.2020.01.005
|
| [10] |
B. Lima, W. Singer, N. H. Chen, S. Neuenschwander, Synchronization dynamics in response to plaid stimuli in monkey V1, Cereb. Cortex, 20 (2009), 1556–1573. https://doi.org/10.1093/cercor/bhp218 doi: 10.1093/cercor/bhp218
|
| [11] |
G. Perry, The effects of cross-orientation masking on the visual gamma response in humans, Eur. J. Neurosci., 41 (2015), 1484–1495. https://doi.org/10.1111/ejn.12900 doi: 10.1111/ejn.12900
|
| [12] |
B. Wang, C. Han, T. Wang, W. Dai, Y. Li, Y. Yang, et al., Superimposed gratings induce diverse response patterns of gamma oscillations in primary visual cortex, Sci. Rep., 11 (2021), 4941. https://doi.org/10.1038/s41598-021-83923-5 doi: 10.1038/s41598-021-83923-5
|
| [13] |
C. M. Gray, P. König, A. K. Engel, W. Singer, Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties, Nature, 338 (1989), 334–337. https://doi.org/10.1038/338334a0 doi: 10.1038/338334a0
|
| [14] |
C. M. Gray, The temporal correlation hypothesis of visual feature integration: still alive and well, Neuron, 24 (1999), 31–47. https://doi.org/10.1016/S0896-6273(00)80820-X doi: 10.1016/S0896-6273(00)80820-X
|
| [15] |
P. Uhlhaas, W. Singer, Neuronal dynamics and neuropsychiatric disorders: toward a translational paradigm for dysfunctional large-scale networks, Neuron, 75 (2012), 963–980. https://doi.org/10.1016/j.neuron.2012.09.004 doi: 10.1016/j.neuron.2012.09.004
|
| [16] |
N. M. Brunet, C. A. Bosman, M. Vinck, M. Roberts, R. Oostenveld, R. Desimone, et al., Stimulus repetition modulates gamma-band synchronization in primate visual cortex, PNAS, 111 (2014), 3626–3631. https://doi.org/10.1073/pnas.1309714111 doi: 10.1073/pnas.1309714111
|
| [17] |
P. Fries, Rhythms for cognition: communication through coherence, Neuron, 88 (2015), 220–235. https://doi.org/10.1016/j.neuron.2015.09.034 doi: 10.1016/j.neuron.2015.09.034
|
| [18] |
C. E. Boudreau, D. Ferster, Short-term depression in thalamocortical synapses of cat primary visual cortex, J. Neurosci., 25 (2005), 7179–7190. https://doi.org/10.1523/JNEUROSCI.1445-05.2005 doi: 10.1523/JNEUROSCI.1445-05.2005
|
| [19] |
D. Rubin, S. Van Hooser, K. Miller, The stabilized supralinear network: a unifying circuit motif underlying multi-input integration in sensory cortex, Neuron, 85 (2015), 402–417. https://doi.org/10.1016/j.neuron.2014.12.026 doi: 10.1016/j.neuron.2014.12.026
|
| [20] |
D. Barbera, N. J. Priebe, L. L. Glickfeld, Feedforward mechanisms of cross-orientation interactions in mouse V1, Neuron, 110 (2022), 297–311. https://doi.org/10.1016/j.neuron.2021.10.017 doi: 10.1016/j.neuron.2021.10.017
|
| [21] |
M. A. Smith, W. Bair, J. A. Movshon, Dynamics of suppression in macaque primary visual cortex, J. Neurosci., 26 (2006), 4826–4834. https://doi.org/10.1523/JNEUROSCI.5542-06.2006 doi: 10.1523/JNEUROSCI.5542-06.2006
|
| [22] |
M. Koelling, R. Shapley, M. Shelley, Retinal and cortical nonlinearities combine to produce masking in V1 responses to plaids, J. Comput. Neurosci., 25 (2008), 390–400. https://doi.org/10.1007/s10827-008-0086-6 doi: 10.1007/s10827-008-0086-6
|
| [23] |
M. Carandini, D. J. Heeger, Normalization as a canonical neural computation, Nat. Rev. Neurosci., 13 (2012), 51–62. https://doi.org/10.1038/nrn3136 doi: 10.1038/nrn3136
|
| [24] |
D. J. Heeger, K. O. Zemlianova, A recurrent circuit implements normalization, simulating the dynamics of V1 activity, PNAS, 117 (2020), 22494–22505. https://doi.org/10.1073/pnas.2005417117 doi: 10.1073/pnas.2005417117
|
| [25] |
A. Das, S. Ray, Effect of cross-orientation normalization on different neural measures in macaque primary visual cortex, Cereb. Cortex Comm., 2 (2021), tgab009. https://doi.org/10.1093/texcom/tgab009 doi: 10.1093/texcom/tgab009
|
| [26] |
X. Jia, D. Xing, A. Kohn, No consistent relationship between gamma power and peak frequency in macaque primary visual cortex, J. Neurosci., 33 (2013), 17–25. https://doi.org/10.1523/JNEUROSCI.1687-12.2013 doi: 10.1523/JNEUROSCI.1687-12.2013
|
| [27] |
N. Meneghetti, C. Cerri, E. Tantillo, E. Vannini, M. Caleo, A. Mazzoni, Narrow and broad $\gamma$ bands process complementary visual information in mouse primary visual cortex, eNeuro, 8 (2021). https://doi.org/10.1523/ENEURO.0106-21.2021 doi: 10.1523/ENEURO.0106-21.2021
|
| [28] |
C. Han, T. Wang, Y. Wu, Y. Li, Y. Yang, L. Li, et al., The generation and modulation of distinct gamma oscillations with local, horizontal, and feedback connections in the primary visual cortex: a model study on large-scale networks, Neural Plast., 2021 (2021), 8874516. https://doi.org/10.1155/2021/8874516 doi: 10.1155/2021/8874516
|
| [29] |
X. Gu, F. Han, Z. Wang, K. Kashif, W. Lu, Enhancement of gamma oscillations in E/I neural networks by increase of difference between external inputs, Electron. Res. Arch., 29 (2021), 3227–3241. https://doi.org/10.3934/era.2021035 doi: 10.3934/era.2021035
|
| [30] |
O. J. A. Gonzalez, K. I. van Aerde, H. D. Mansvelder, J. van Pelt, A. van Ooyen, Inter-network interactions: impact of connections between oscillatory neuronal networks on oscillation frequency and pattern, PLOS ONE, 9 (2014), 1–16. https://doi.org/10.1371/journal.pone.0100899 doi: 10.1371/journal.pone.0100899
|
| [31] |
S. Keeley, A. A. Fenton, J. Rinzel, Modeling fast and slow gamma oscillations with interneurons of different subtype, J. Neurophysiol., 117 (2017), 950–965. https://doi.org/10.1152/jn.00490.2016 doi: 10.1152/jn.00490.2016
|
| [32] |
S. Makovkin, E. Kozinov, M. Ivanchenko, S. Gordleeva, Controlling synchronization of gamma oscillations by astrocytic modulation in a model hippocampal neural network, Sci. Rep., 12 (2022), 6970. https://doi.org/10.1038/s41598-022-10649-3 doi: 10.1038/s41598-022-10649-3
|
| [33] |
K. Wang, A. Wei, Y. Fu, T. Wang, X. Gao, B. Fu, et al., State-dependent modulation of thalamocortical oscillations by gamma light flicker with different frequencies, intensities, and duty cycles, Front. Neuroinf., 16 (2022). https://doi.org/10.3389/fninf.2022.968907 doi: 10.3389/fninf.2022.968907
|
| [34] |
T. W. Troyer, A. E. Krukowski, N. J. Priebe, K. D. Miller, Contrast-invariant orientation tuning in cat visual cortex: thalamocortical input tuning and correlation-based intracortical connectivity, J. Neurosci., 18 (1998), 5908–5927. https://doi.org/10.1523/JNEUROSCI.18-15-05908.1998 doi: 10.1523/JNEUROSCI.18-15-05908.1998
|
| [35] |
J. Kremkow, L. U. Perrinet, C. Monier, J. M. Alonso, A. Aertsen, Y. Frégnac, et al., Push-pull receptive field organization and synaptic depression: mechanisms for reliably encoding naturalistic stimuli in V1, Front. Neural Circuits, 10 (2016). https://doi.org/10.3389/fncir.2016.00037 doi: 10.3389/fncir.2016.00037
|
| [36] |
M. M. Taylor, D. Contreras, A. Destexhe, Y. Frégnac, J. Antolik, An anatomically constrained model of V1 simple cells predicts the coexistence of push–pull and broad inhibition, J. Neurosci., 41 (2021), 7797–7812. https://doi.org/10.1523/JNEUROSCI.0928-20.2021 doi: 10.1523/JNEUROSCI.0928-20.2021
|
| [37] |
E. A. Allen, R. D. Freeman, Dynamic spatial processing originates in early visual pathways, J. Neurosci., 26 (2006), 11763–11774. https://doi.org/10.1523/JNEUROSCI.3297-06.2006 doi: 10.1523/JNEUROSCI.3297-06.2006
|
| [38] | J. Antoĺık, R. Cagnol, T. Rozsa, C. Monier, Y. Frégnac, A. P. Davison, A comprehensive data-driven model of cat primary visual cortex, bioRxiv, 2023. https://doi.org/10.1101/416156 |
| [39] |
N. Fourcaud-Trocmé, D. Hansel, C. van Vreeswijk, N. Brunel, How spike generation mechanisms determine the neuronal response to fluctuating inputs, J. Neurosci., 23 (2003), 11628–11640. https://doi.org/10.1523/JNEUROSCI.23-37-11628.2003 doi: 10.1523/JNEUROSCI.23-37-11628.2003
|
| [40] |
J. Antolik, J. Bednar, Development of maps of simple and complex cells in the primary visual cortex, Front. Comput. Neurosci., 5 (2011). https://doi.org/10.3389/fncom.2011.00017 doi: 10.3389/fncom.2011.00017
|
| [41] |
T. Binzegger, R. J. Douglas, K. A. C. Martin, A quantitative map of the circuit of cat primary visual cortex, J. Neurosci., 24 (2004), 8441–8453. https://doi.org/10.1523/JNEUROSCI.1400-04.2004 doi: 10.1523/JNEUROSCI.1400-04.2004
|
| [42] |
A. Stepanyants, J. A. Hirsch, L. M. Martinez, Z. F. Kisvárday, A. S. Ferecskó, D. B. Chklovskii, Local potential connectivity in cat primary visual cortex, Cereb. Cortex, 18 (2007), 13–28. https://doi.org/10.1093/cercor/bhm027 doi: 10.1093/cercor/bhm027
|
| [43] |
L. Chariker, R. Shapley, L. S. Young, Orientation selectivity from very sparse lgn inputs in a comprehensive model of macaque V1 cortex, J. Neurosci., 36 (2016), 12368–12384. https://doi.org/10.1523/JNEUROSCI.2603-16.2016 doi: 10.1523/JNEUROSCI.2603-16.2016
|
| [44] |
L. Chariker, R. Shapley, L. S. Young, Rhythm and synchrony in a cortical network model, J. Neurosci., 38 (2018), 8621–8634. https://doi.org/10.1523/JNEUROSCI.0675-18.2018 doi: 10.1523/JNEUROSCI.0675-18.2018
|
| [45] |
J. A. Henrie, R. Shapley, Lfp power spectra in V1 cortex: the graded effect of stimulus contrast, J. Neurosci., 94 (2005), 479–490. https://doi.org/10.1152/jn.00919.2004 doi: 10.1152/jn.00919.2004
|
| [46] |
S. Katzner, I. Nauhaus, A. Benucci, V. Bonin, D. L. Ringach, M. Carandini, Local origin of field potentials in visual cortex, Neuron, 61 (2009), 35–41. https://doi.org/10.1016/j.neuron.2008.11.016 doi: 10.1016/j.neuron.2008.11.016
|
| [47] |
G. T. Einevoll, C. Kayser, N. K. Logothetis, S. Panzeri, Modelling and analysis of local field potentials for studying the function of cortical circuits, Nat. Rev. Neurosci., 14 (2013), 770–785. https://doi.org/10.1038/nrn3599 doi: 10.1038/nrn3599
|
| [48] |
T. V. Ness, M. W. H. Remme, G. T. Einevoll, Active subthreshold dendritic conductances shape the local field potential, J. Physiol., 594 (2016), 3809–3825. https://doi.org/10.1113/JP272022 doi: 10.1113/JP272022
|
| [49] |
A. Mazzoni, H. Lindén, H. Cuntz, A. Lansner, S. Panzeri, G. T. Einevoll, Computing the local field potential (lfp) from integrate-and-fire network models, PLoS Comput. Biol., 11 (2015), e1004584. https://doi.org/10.1371/journal.pcbi.1004584 doi: 10.1371/journal.pcbi.1004584
|
| [50] |
A. V. Rangan, L. S. Young, Emergent dynamics in a model of visual cortex, J. Comput. Neurosci., 35 (2013), 155–167. https://doi.org/10.1007/s10827-013-0445-9 doi: 10.1007/s10827-013-0445-9
|
| [51] |
L. Chariker, L. S. Young, Emergent spike patterns in neuronal populations, J. Comput. Neurosci., 38 (2015), 203–220. https://doi.org/10.1007/s10827-014-0534-4 doi: 10.1007/s10827-014-0534-4
|
| [52] |
G. Blasdel, Orientation selectivity, preference, and continuity in monkey striate cortex, J. Neurosci., 12 (1992), 3139–3161. https://doi.org/10.1523/JNEUROSCI.12-08-03139.1992 doi: 10.1523/JNEUROSCI.12-08-03139.1992
|
| [53] |
M. Whittington, R. Traub, N. Kopell, B. Ermentrout, E. Buhl, Inhibition-based rhythms: experimental and mathematical observations on network dynamics, Int. J. Psychophysiol., 38 (2000), 315–336. https://doi.org/10.1016/S0167-8760(00)00173-2 doi: 10.1016/S0167-8760(00)00173-2
|
| [54] |
C. Börgers, S. Epstein, N. J. Kopell, Background gamma rhythmicity and attention in cortical local circuits: a computational study, PNAS, 102 (2005), 7002–7007. https://doi.org/10.1073/pnas.0502366102 doi: 10.1073/pnas.0502366102
|
Figures(5)
Hao Yang, Peihan Wang, Fang Han, Qingyun Wang. An interpretable mechanism for grating-induced cross-inhibition and gamma oscillation based on a visual cortical neuronal network model[J]. Electronic Research Archive, 2024, 32(4): 2936-2954. doi: 10.3934/era.2024134
DownLoad: