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Stimulus-repetition Effects on Macaque V1 and V4 Microcircuits Explain Gamma-synchronization Increase

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Journal bioRxiv
Date 2024 Dec 23
PMID 39713348
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Abstract

Under natural conditions, animals repeatedly encounter the same visual scenes, objects or patterns repeatedly. These repetitions constitute statistical regularities, which the brain captures in an internal model through learning. A signature of such learning in primate visual areas V1 and V4 is the gradual strengthening of gamma synchronization. We used a V1-V4 Dynamic Causal Model (DCM) to explain visually induced responses in early and late epochs from a sequence of several hundred grating presentations. The DCM reproduced the empirical increase in local and inter-areal gamma synchronization, revealing specific intrinsic connectivity effects that could explain the phenomenon. In a sensitivity analysis, the isolated modulation of several connection strengths induced increased gamma. Comparison of alternative models showed that empirical gamma increases are better explained by (1) repetition effects in both V1 and V4 intrinsic connectivity (alone or together with extrinsic) than in extrinsic connectivity alone, and (2) repetition effects on V1 and V4 population input rather than output gain. The best input gain model included effects in V1 granular and superficial excitatory populations and in V4 granular and deep excitatory populations. Our findings are consistent with gamma reflecting bottom-up signal precision, which increases with repetition and, therefore, with predictability and learning.

References
1.
Brown H, Friston K . Dynamic causal modelling of precision and synaptic gain in visual perception - an EEG study. Neuroimage. 2012; 63(1):223-31. PMC: 3438451. DOI: 10.1016/j.neuroimage.2012.06.044. View

2.
Peter A, Stauch B, Shapcott K, Kouroupaki K, Schmiedt J, Klein L . Stimulus-specific plasticity of macaque V1 spike rates and gamma. Cell Rep. 2021; 37(10):110086. PMC: 8674536. DOI: 10.1016/j.celrep.2021.110086. View

3.
Zeidman P, Jafarian A, L Seghier M, Litvak V, Cagnan H, Price C . A guide to group effective connectivity analysis, part 2: Second level analysis with PEB. Neuroimage. 2019; 200:12-25. PMC: 6711451. DOI: 10.1016/j.neuroimage.2019.06.032. View

4.
Bazhenov M, Stopfer M, Sejnowski T, Laurent G . Fast odor learning improves reliability of odor responses in the locust antennal lobe. Neuron. 2005; 46(3):483-92. PMC: 2905210. DOI: 10.1016/j.neuron.2005.03.022. View

5.
Stauch B, Peter A, Schuler H, Fries P . Stimulus-specific plasticity in human visual gamma-band activity and functional connectivity. Elife. 2021; 10. PMC: 8412931. DOI: 10.7554/eLife.68240. View