T-maze training of a recurrent CA3 model reveals the necessity of novelty-based modulation of LTP in hippocampal region CA3

Abstract

Abstract-The rat hippocampus has been shown to mediate a large set of spatial navigation tasks such as the simple T-maze. We investigated the performance of a minimal computational, but biologically based, model of CA3 on this task. For successful performance, the model needs to generate and maintain neuronal codes for each of the two arms of the T-maze. Moreover, each code must be distinctively recalled in a goal-dependent manner. The development of such neuronal codes is aided by the appearance of repetitively firing recurrent neurons -known as local context units, analogous to hippocampal place cells -which promote spatiotemporal association within the T-maze training sequences. The number, longevity, and connectivity of local context units exclusively coding for each arm of the maze grow with training. Although with too much training, the coding for one arm uncontrollably dominates over the other code, and goal appropriate choice-behavior is lost. That is, successful network codes can easily deteriorate with overtraining. The amount of training that produces this deterioration in performance depends on other network parameters. Rather than a failure of the model, we believe these results tell us something important about the biology of the hippocampal system. That is, this result provides support for the hypothesis of a hippocampal afferent system which down-regulates LTP once a task has been successfully learned. Modulatory systems (e.g., dopaminergic, generally D1/D5r) exist which are candidates for this functional role.

Spatial synchronization codes from coupled rate-phase neurons

“…Early theoretical models suggested that hippocampal sequences, learned via phase precession and/or temporally asymmetric synaptic plasticity, enabled context-dependent predictions of future positions [64–68]. Experimental studies revealed theta-rhythmic forward-sweeping sequences during active locomotion [69, 70] that mentally probed paths ahead of the animal’s current position to guide navigational decisions [71, 72].…”

The formation of neural codes in the hippocampus: trace conditioning as a prototypical paradigm for studying the random recoding hypothesis

“…Nevertheless, even if asymptotic stability does not obtain, the large number of training trials required to produce a collapse might be enough to ignore in practical situations; i.e., across training trials, there are many trials of correct prediction, and this run of successes would be biologically useful. Elsewhere we have discussed such an idea, that transient, successful prediction is useful if the hippocampus can be taken off-line (see Monaco and Levy (2003) for other observations and biological interpretations concerning unstable but transiently useful hippocampal encodings).…”

A Neural Mechanism for Reward Discounting: Insights from Modeling Hippocampal–Striatal Interactions

“…Studies show that when rats deliberate in a T-maze, neurons in their hippocampus fire as though they were exploring the two options in the maze (Johnson et al, 2007; Johnson & Redish, 2007). A simulation study of T-maze decision making using the present hippocampal model has demonstrated activity in both paths in the model (Monaco & Levy, 2003). Although it is clear that this delayed activation could be used to select actions based on eventual outcomes, it is not immediately obvious whether or how this mechanism might lead to discounting of those delayed rewards.…”