Models of behavior and spike timing in sequence memory

海马结构、内嗅皮层和前额叶皮层的计算模型将用于 模拟大鼠和人类行为任务中记忆引导行为。这些模拟将扩展 本实验室先前的建模工作（Hasselmo等人，2002 b; Fransen等人，2002; Koene等人，二○ ○三年; Hasselmo，2005 a; Koene and Hasselmo，2005; Hasselmo and Eichenbaum，2005）来生成预测 在一系列不同的记忆引导任务中的生理数据。行为动作的选择 模型依赖于输入刺激序列的编码和上下文相关检索（即， episodes）。这些模型将为中心的特定研究项目生成预测，包括： 1.）的人。产生关于神经元放电相对于刺激和海马θ的定时的预测 节奏在执行过程中的顺序识别任务的气味在大鼠，和 功能磁共振成像激活的幅度与顺序识别的正确与错误表现相关 人类的任务， 2.）的情况。产生关于上下文相关的特性和神经元放电的θ相位的预测， 气味序列歧义消除任务，以及功能磁共振成像激活的幅度 与人类在消除歧义任务中的选择有关， 3.）第三章产生关于T-迷宫中的延迟的位置不匹配（DNMP）任务的预测，涉及分裂细胞响应的时间和相对于θ节律的序列读出，以及 行为和在theta的不同阶段刺激引起的行为反应的中断， 不同的任务周期。 这些模拟将使用从阈值单元开始的神经元网络，并建立详细的 房室生物物理模拟，将网络动态与内在电流和 海马体和内嗅皮层内的神经元。从这项工作中获得的见解将提高我们的 了解海马和相关皮质的正常功能，可能有助于 治疗阿尔茨海默病或精神分裂症等疾病中的记忆障碍。

Computational models of the hippocampal formation, entorhinal cortex and prefrontal cortex will be used to simulate memory-guided behavior in both rat and human behavioral tasks. These simulations will extend previous modeling work in this laboratory (Hasselmo et al., 2002b; Fransen et al., 2002; Koene et al., 2003; Hasselmo, 2005a; Koene and Hasselmo, 2005; Hasselmo and Eichenbaum, 2005) to generate predictions about physiological data in a range of different memory-guided tasks. Selection of behavioral actions in the model depends on the encoding and context dependent retrieval of sequences of input stimuli (i.e. episodes). The models will generate predictions for specific research projects in the center, including: 1.) generation of predictions about the timing of neuron firing relative to stimuli and hippocampal theta rhythm during performance of the order recognition task with odors in rats, and the magnitude of fMRI activation associated with correct versus incorrect performance of an order recognition task in humans, 2.) generation of predictions about context-dependent properties and theta phase of neuronal firing in the odor sequence disambiguation task, and the magnitude of fMRI activation associated with choice in a disambiguation task in humans, 3.) generation of predictions about the delayed non-match to place (DNMP) task in the T-maze, concerning the timing of splitter cell responses and sequence readout relative to theta rhythm and behavior and the disruption of behavioral responses caused by stimulation at different phases of theta during different task periods. These simulations will use networks of neurons starting with threshold units and building to use of detailed compartmental biophysical simulations, to relate network dynamics to intrinsic currents and subclasses of neurons within the hippocampus and entorhinal cortex. The insights gained from this work will improve our understanding of the normal function of the hippocampus and associated cortex, potentially contributing to treatment of memory impairments in disorders such as Alzheimer's disease or schizophrenia.