Schmajuk N A
Department of Psychology, Northwestern University, Evanston, IL 60201.
Behav Brain Res. 1990 Aug 20;39(3):205-29. doi: 10.1016/0166-4328(90)90028-d.
The hippocampus has been proposed to participate in either spatial or temporal mapping. As an alternative to these seemingly conflicting views, we hypothesized that the hippocampus computes 'aggregate predictions' of environmental events that are used to control associative learning. Aggregate predictions forecast what event is going to occur, when in time, and where in space. The hypothesis assumes that activity of hippocampal pyramidal neurons is proportional to the instantaneous value of the aggregate prediction, and that the computation of the aggregate prediction is impaired by hippocampal lesions. In order to test the 'aggregate prediction' hypothesis in both spatial and temporal tasks, this paper presents a real-time neural network capable of describing temporal discrimination and spatial learning in a unified fashion. The neural network incorporates detectors that can be tuned to a particular value of continuous temporal or spatial variables. In the temporal domain, computer simulations were carried out for temporal discrimination in classical conditioning and instrumental learning, classical conditioning under different interstimulus intervals (ISIs), and classical conditioning with mixed ISIs. In the spatial domain, computer simulations were carried out for place and cue learning. The paper shows that under the 'aggregate prediction' hypothesis the network correctly describes activity of hippocampal pyramidal neurons and the effect of hippocampal lesions in temporal and spatial learning. These results suggest that, rather than either a temporal or spatial function, the hippocampus is involved in the computation of variables common to both temporal and spatial navigation.
海马体被认为参与空间或时间映射。作为这些看似相互矛盾观点的替代，我们假设海马体计算用于控制联想学习的环境事件的“综合预测”。综合预测预测事件将在何时何地发生。该假设认为海马体锥体细胞的活动与综合预测的瞬时值成正比，并且海马体损伤会损害综合预测的计算。为了在空间和时间任务中测试“综合预测”假设，本文提出了一种能够以统一方式描述时间辨别和空间学习的实时神经网络。该神经网络包含可以调整到连续时间或空间变量特定值的探测器。在时间领域，针对经典条件作用和工具性学习中的时间辨别、不同刺激间隔（ISI）下的经典条件作用以及混合ISI的经典条件作用进行了计算机模拟。在空间领域，针对位置和线索学习进行了计算机模拟。本文表明，在“综合预测”假设下，该网络正确描述了海马体锥体细胞的活动以及海马体损伤在时间和空间学习中的影响。这些结果表明，海马体并非参与时间或空间功能，而是参与时间和空间导航共有的变量计算。
