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稳定的超线性网络解释了视觉皮层马振荡的对比依赖

Caleb J Holt¹, Kenneth D Miller², Yashar Ahmadian³

¹Department of Physics, Institute of Neuroscience, University of Oregon, Eugene, Oregon, United States of America.

PLoS computational biology

|June 27, 2024

概括

视觉皮层中的神经群体显示了随着刺激而变化的马带活动. 一个稳定超线性网络模型解释了这一点,它预测了V1中的特定水平连接结构用于视觉处理.

科学领域:

神经科学是一个神经科学.
计算神经科学是一种神经科学.
视觉皮层研究视觉皮层研究

背景情况:

视觉皮层中的神经群体表现出马波段活动 (30-80 Hz) 与刺激依赖的功率谱峰值.
在 V1 中,玛峰频率随着刺激对比度的增加而增加,并由受感场对比度局部控制.
现有的模型缺乏对这些对比度依赖的节的机械解释.

研究的目的:

为 V1.1 中的马峰频率对比度依赖提供一个机械解释.
研究V1中水平连接对于马振荡和上下文调制的作用.
在 V1.1. 预测水平连接的空间结构在 V1.1.

主要方法:

使用一个稳定超线性网络 (SSN) 模型的皮质电路.
开发了一个没有视网膜的减少SSN模型来捕捉对比度依赖.
将模型扩展到 retinotopic SSN 与水平连接,以研究周围抑制和局部对比效应.

主要成果:

一个减少的SSN模型成功地捕获了玛峰值频率的对比依赖性,将其归因于V1神经元的非和,超线性输入输出函数.
一个视网膜类SSN模型解释了围绕抑制和玛频率局部对比依赖.
该模型的成功需要具有明显的短距离和远距离空间组件的水平激发投影.

结论:

SSN模型为V1马振荡的对比依赖提供了一种机械解释.
在V1中,水平连接的特定空间结构对于整合局部对比信息和上下文调制至关重要.
这项研究预测 V1 的水平连接具有双组件结构,与皮层柱状组织保持一致.

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