HEBB MARR NETWORKS THE HIPPOCAMPUS AND SPATIAL MEMORY

我们的目标是开发一个计算和经验框架，通过 以了解哺乳动物海马区的神经元动力学和 它的大脑皮层连接与空间表征和记忆有关。 这个系统对记忆的形成是至关重要的，它的功能障碍通过 伤害或疾病是人类记忆受损的主要原因。这个 该项目补充了正在进行的单细胞神经生理学研究 自由行为动物、自发突触和诱发性突触的活动 清醒动物的可塑性和调节，以及动物的微生理学 单次脉冲触发量子分析中的神经交互作用 体外培养的突触。这类研究产生的大量数据(来自我们的 Owner和其他集团)制造了一场“财富的尴尬”危机。我们 计划通过开发记录来自 用于从交互中获取数据的“立体电极”探头的并行阵列 在空间行为中，大约有50到100个海马神经元。 我们希望通过模拟来帮助缓解危机，包括 足够的已知网络、生物物理和单元活动参数 对几个重要的生理起源的有用见解 “系统级”现象可以从生理学的角度进行推导和测试。 实验。这些模拟的概念起点是 分布式联想记忆的Hebb-Marr形式。具体来说，我们 解决以下现象的起源和计算效用： 1)海马神经元对动物的位置有精确的选择性 以及在太空中的定向。这种选择性既不存在于 输入，也不是(令人惊讶的)系统的皮质输出。 此外，至少CA1区域可以重构空间表示 当从CA3传输到它的信息急剧降级时 (即，“模式补全”)。2)海马区颗粒细胞数量远多于 他们接受高度会聚的输入的皮质传入，但 他们开火的时间是1：10)。利用数值模拟的方法，我们将研究 假设该组织从属于正交化或 相关输入向量(c.f.Marr密码子形成)。3)。《筋膜》 Dentata还可以用于提取新的输入特征(c.f.这个 Kohonen的“新奇过滤器”)，这是一种基于我们观察到的假设 净突触效能增加，但净兴奋性因 在勘探过程中获取新信息。协助口译 并在今后的实验设计中，对这些现象进行模拟 颗粒细胞中的电诱发群子场电位 网络，理论推理所基于的网络，以及可能的 可能导致这些生理现象的细胞动力学， 以及对提议的新颖性提取效果的影响。

Our goal is to develop a computational and empirical framework through which to understand the neuronal dynamics of the mammalian hippocampus and its cortical connections, in relation to spatial representation and memory. This system is crucial for memory formation, and its dysfunction through injury or disease is the major cause of human memory impairment. The project complements ongoing neurophysiological studies of single cell activity in freely behaving animals, spontaneous and evoked synaptic plasticity and modulation in conscious animals, and the micro-physiology of neural interaction using spike-triggered quantal analysis at single synapses in vitro. The wealth of data generated by such studies (from our own and other groups) has created an "embarrassment of riches" crisis. We plan to exacerbate the crisis by developing methods for recording from parallel arrays of "stereotrode" probes to acquire data from interacting populations of about 50 to 100 hippocampal neurons during spatial behavior. We hope to help alleviate the crisis thorough simulations that incorporate enough of the known network, biophysical and unit activity parameters that useful insights into the physiological origins of several important "system-level" phenomena can be derived and tested in physiological experiments. The conceptual starting point for these simulations is the Hebb-Marr formalism for distributed associative memory. Specifically, we address the origins and computational utility of the following phenomena: 1) Hippocampal neurons are exquisitely selective for the animal's location and orientation in space. Such selectivity is present neither at the inputs, nor (surprisingly) at the cortical outputs of the system. Moreover, at least the CA1 region can reconstruct spatial representations when the information transmitted to it from CA3 is drastically degraded (i.e., "pattern completion"). 2) Hippocampal granule cells far outnumber the cortical afferents from which they receive highly convergent input, yet they fire 1:10). Using numerical simulation we will investigate the hypothesis that this organization subserves the orthogonalization or correlated input vectors (c.f. Marr's codon formation). 3). The fascia dentata may also serve in the extraction of novel input features (c.f. the "novelty filter" of Kohonen), an hypothesis based on our observation that net synaptic efficacy increases, yet net excitability is reduced by the acquisition of new information during exploration. To aid in interpreting these phenomena and in the design of future experiments, we will simulate electrically evoked population field potentials in the granule cell network, upon which the theoretical inferences are based, and the possible cellular dynamics that might lead both to these physiological phenomena, and to the proposed novelty extraction effect.