Nonlinear Dynamics of the Primary Visual Cortex

麦克劳克林0211655 研究人员和同事们一直在开发非生物约束的皮层视觉系统“前端”-初级视觉皮层（V1）的大规模计算模型。 到目前为止，他们的工作主要集中在大规模网络中单个细胞的局部性质上--例如方向选择性和简单与复杂动力学。 在这个项目中，他们将V1放大到一个更大的模型，达到足够大的尺度来研究心理学和心理物理学的一些基本视错觉。这涉及到几平方毫米的侧皮层区域，以及一个多层结构--重点是皮层动力学。 首先，一个“粗粒度的混合表示”是数学推导和测试数字-一个表示，结合空间粗粒度（本地）平均放电率，代表当地的背景皮质工作点，与一个理想化的表示子网络的个别点神经元嵌入在这个背景，并保留详细的放电模式individual神经元。 这两个组件相互作用-粗粒度的局部操作点影响单个神经元的响应，反之亦然。 第二，全局混合表征被用来研究视觉皮层处理中的特定动力学现象：（i）层特定的“方向选择性动力学”（通过逆时间相关方法测量）;以及（ii）“图形-背景分配中的双稳态”（在心理学和心理物理学实验中检测到）。 在这两种情况下，这种现象都涉及到V1的广泛的外侧区域，它的分层结构，以及（可能在图形-背景分配的情况下）其他皮层区域。 在这两种情况下，这项工作都与神经科学家罗伯特·沙普利的实验工作密切相关。 今天，通过新的生物实验结合现代科学计算的力量，科学家和应用数学家在理解人类大脑方面取得了重大进展。 视觉感知和视觉信息的皮层处理提供了重要的起点。 通过关注皮层视觉系统的“前端”，McLaughlin和他的同事们开发了视觉皮层的计算模型，这些模型受到生物实验的强烈约束。 在这个项目中，演示者开发了计算效率高的数值方法，将模型扩展到初级视觉皮层的全局表示-达到足够大的皮层尺度来研究心理学的一些基本视错觉。 这项工作需要应用数学家，计算科学家和神经科学家的直接互动-并涉及理论，计算和实验组件。

McLaughlin0211655 The investigator and colleagues have been developing abiologically constrained large-scale computational model of the"front-end" of the cortical visual system -- the primary visualcortex (V1). To date, their work has focused upon localproperties of individual cells within the large-scale network --properties such as orientation selectivity and simple vs complexcellular dynamics. In this project, they scale up to a moreglobal model of V1, reaching scales large enough to study someelementary optical illusions of psychology and psychophysics.This involves several square millimeters of lateral corticalarea, together with a multi-layered architecture -- with emphasisgiven to cortical dynamics. First, a "coarse-grained mixedrepresentation" is derived mathematically and tested numerically-- a representation that combines spatially coarse-grained(local) mean firing rates, representing local background corticaloperating points, with an idealized representation of asub-network of individual point neurons embedded within thisbackground and retaining the detailed firing patterns ofindividual neurons. These two components interact with eachother -- with the coarse-grained local operating pointsinfluencing the responses of the individual neurons, and viceversa. Second, the global mixed representation is used to studyspecific dynamical phenomena in visual cortical processing: (i)the layer-specific "dynamics of orientation selectivity" (asmeasured by reverse time correlation methods); and later (ii)"bistability in figure-ground assignments" (as detected inpsychology and psychophysics experiments). In both cases, thephenomena involve extensive lateral regions of V1, its layeredstructure, and (likely in the case of figure-ground assignment)other cortical regions. And in both cases the work involvesclose interaction with the experimental work of neural scientistRobert Shapley. Today, through new biological experiments combined with thepower of modern scientific computation, scientists and appliedmathematicians are making significant strides towardunderstanding the human brain. Visual perception and the corticalprocessing of visual information provide important startingpoints. By focusing upon the "front end" of the cortical visualsystem, McLaughlin and his colleagues develop computationalmodels of the visual cortex that are strongly constrained bybiological experiments. In this project the investigatorsdevelop computationally efficient numerical methods that permitscale-up of the models to global representations of the primaryvisual cortex -- reaching cortical scales large enough to studysome elementary optical illusions of psychology. This workrequires the direct interaction of applied mathematicians,computational scientists, and neural scientists -- and involvestheoretical, computational, and experimental components.