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对猕猴初级视觉皮层和V4微电路的刺激重复效应解释了伽马同步的增加。

Stimulus-repetition effects on macaque V1 and V4 microcircuits explain gamma-synchronization increase.

作者信息

Katsanevaki Christini, Bosman Conrado A, Friston Karl J, Fries Pascal

机构信息

Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt 60528, Germany.

International Max Planck Research School for Neural Circuits, Frankfurt 60438, Germany.

出版信息

bioRxiv. 2024 Dec 11:2024.12.06.627165. doi: 10.1101/2024.12.06.627165.

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.

摘要

在自然条件下,动物会反复遇到相同的视觉场景、物体或图案。这些重复构成了统计规律,大脑通过学习在内部模型中捕捉到这些规律。在灵长类动物的视觉区域V1和V4中,这种学习的一个标志是γ同步的逐渐增强。我们使用V1 - V4动态因果模型(DCM)来解释在数百次光栅呈现序列的早期和晚期阶段视觉诱发的反应。DCM再现了局部和区域间γ同步的经验性增加,揭示了可以解释该现象的特定内在连接效应。在敏感性分析中,几个连接强度的单独调制会导致γ增加。替代模型的比较表明,经验性γ增加能更好地由以下因素解释:(1)V1和V4内在连接(单独或与外在连接一起)中的重复效应,而非仅外在连接中的重复效应;(2)对V1和V4群体输入而非输出增益的重复效应。最佳输入增益模型包括V1颗粒层和浅层兴奋性群体以及V4颗粒层和深层兴奋性群体中的效应。我们的研究结果与γ反映自下而上的信号精度一致,这种精度会随着重复以及可预测性和学习而增加。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/76dc/11661063/3318315c2e40/nihpp-2024.12.06.627165v1-f0001.jpg

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