Recurrent Circuit Model of Neural Response Dynamics in V1

项目摘要/摘要 初级视觉皮质(V1)是大脑皮层研究最多的区域之一，但缺乏理论依据 全面了解V1神经生理学的框架。通过拟议的研究，我们的目标是 来提供一个。一类电路模型，称为振荡递归门控神经积分器电路 (有机物)，模拟了许多关键的神经生理现象。我们的目标是发展一个完整的理论 V1中神经生理现象的范围，即具有生物物理真实性的单一预测模型 参数，并用以前发布的数据集来验证这一理论 方法论。 初步结果表明，理论的预测与V1的实验观测是相称的 响应动力学(包括起始瞬变和伽马振荡对刺激的依赖性)， 注意调节的动力学，反复放大和抑制的实验证据 稳定化，关于适应的实验观察，包括调谐变化和去相关，噪声 猝灭，噪声相关性对定向偏好和注意的相似性的依赖，以及 心理物理对比辨别。 目标1主要贡献：1)一种分析理论(即闭合形式的表达式)，它通过实验得出- 对与V1活动动力学有关的广泛现象的可测试性预测；2)封闭形式 从LFP功率谱理论推导出的表达式；3)一种新的对 视觉皮质。 目标2主要贡献：1)V1适应的分析性理论，使实验可检验 对与适应相关的广泛神经生理现象的预测；2)演示 这种适应在有限资源(电路中的全部活动)的情况下维持有效的神经编码， 尽管刺激统计数据在动态变化。 目标3主要贡献：1)一种分析理论，它对 神经反应的可变性和协变性；2)关于心理物理的实验可测预测 歧视。 这项拟议的研究具有变革性的潜力。我们将提供一组新的分析结果 以及用于表征广泛的神经电路模型的计算工具，这将具有重要的 对实验数据的分析和实验设计的影响，并将在实验上做出新的- 有机物和替代模型的可测试预测。我们将提供一个路线图，帮助您了解 潜在的电路机制(细胞类型、它们的互连和生物物理)，以及如何操纵 这些机制可能会改变电路功能，以纠正视觉感知和注意力障碍。

Project Summary/Abstract Primary visual cortex (V1) is one of the most studied areas of the cerebral cortex, but we lack a theoretical framework for a comprehensive understanding of V1 neurophysiology. Through the proposed research, we aim to provide one. A class of circuit models, called Oscillatory Recurrent Gated Neural Integrator Circuits (ORGaNICs), simulates many key neurophysiological phenomena. Our goal is to develop a theory for the full range of neurophysiological phenomena in V1, i.e., a single predictive model with biophysically-realistic parameters, and to test that theory with previously published datasets acquired with a wide range of methodologies. Preliminary results demonstrate predictions of the theory commensurate with experimental observations of V1 response dynamics (including onset transients and the stimulus-dependence of gamma oscillations), the dynamics of attentional modulation, experimental evidence for recurrent amplification and inhibitory stabilization, experimental observations about adaptation including tuning changes and decorrelation, noise quenching, the dependence of noise correlations on similarity in orientation preference and attention, and psychophysical contrast discrimination. Aim 1 key contributions: 1) an analytical theory (i.e., closed-form expressions) that makes experimentally- testable predictions about a wide range of phenomena related to the dynamics of V1 activity; 2) closed-form expressions derived from the theory for LFP power spectra; 3) a novel explanation for oscillatory activity in visual cortex. Aim 2 key contributions: 1) an analytical theory of adaptation in V1 that makes experimentally-testable predictions about a wide range of neurophysiological phenomena related to adaptation; 2) the demonstration that adaptation maintains an efficient neural code, subject to finite resources (overall activity in the circuit), despite dynamically changing stimulus statistics. Aim 3 key contributions: 1) an analytical theory that makes experimentally-testable predictions about the variability and covariability of neural responses; 2) experimentally-testable predictions about psychophysical discrimination. The proposed research has the potential to be transformative. We will provide a new set of analytical results and computational tools for characterizing a broad range of neural circuit models, which will have a significant impact on the analysis of experimental data and experimental design, and will make new experimentally- testable predictions for both ORGaNICs and alternative models. We will provide a roadmap for understanding the underlying circuit mechanisms (the cell types, their interconnections and biophysics), and how manipulating those mechanisms may change circuit function to correct disorders of visual perception and attention.