NETWORK ORGANIZATION OF MEMORY IN TRITONIA

当动物学习时，它们将记忆存储为解剖学分布 一系列的电路修改。 虽然这样的电路修改可以 精确地绘制了地图，生物物理和分子机制 每一个可塑性位点的基础都可以计算出来，事实证明， 很难调查在学习中获得信息的方式 与这些电路修改的位置相对应。 这样做的目的 项目是开发和应用这样做的技术，涉及 电生理学和计算机建模的交互式使用。 由于这 这种方法在脊椎动物中尚不可行，我们将专注于记忆 海洋软体动物Tritonia的潜在习惯化和致敏性。 基本程序是首先确定一个 通过生理学研究，然后评估他们的 信息内容通过将它们一次一个地插入到现实的 计算机模拟它们所在的神经回路。 该项目有三个具体目标：1）构建一个模拟的 逃避游泳神经回路在其休息状态，之前，它被修改， 2）表征电路修改的分布位置 3）构建模拟，将个人 通过训练产生的分布式电路修改的组件， 并利用它们来解决信息存储的几个问题。 了解记忆在神经系统中是如何组织的， 在理解脑损伤的后果和预测 某些外科手术的后果 还可能导致 在人工智能领域有用的设计思想。

When animals learn, they store their memories as anatomically distributed sets of circuit modifications. While such circuit modifications can be mapped with precision, and the biophysical and molecular mechanisms underlying each locus of plasticity can be worked out, it has proven very difficult to investigate the way that the information acquired in learning corresponds to these sites of circuit modification. The purpose of this project is to develop and apply a technique for doing this, involving the interactive use of electrophysiology and computer modeling. Since this approach is not yet feasible in vertebrates, we will focus on the memories underlying habituation and sensitization in the marine mollusc Tritonia. The basic procedure is to first identify the individual components of a distributed memory through physiological studies and then evaluate their information content by inserting them one at a time into a realistic computer simulation of the neural circuit in which they reside. The project has three specific aims: 1) Construct a simulation of the escape swim neural circuit in its resting state, before it is modified by training; 2) Characterize the distributed sites of circuit modification produced by training; 3) Construct simulations incorporating individual components of the distributed circuit modifications produced by training, and use them to address several issues of information storage. Knowledge of how memory is organized in nervous systems could be of great value in understanding the consequences of brain injury, and in forecasting the consequences of certain surgical procedures. It may also lead to useful design ideas in the area of artificial intelligence.