Abstract
We present a computational model of how memories can be contextually acquired and recalled in the hippocampus. Our adaptive contextual memory model comprises the lateral entorhinal cortex (LEC), the dentate gyrus (DG) and areas CA3 and CA1 in the hippocampus, and assumes external inputs about context that originate in the prefrontal cortex (PFC). Specifically, we propose that there is a top-down bias on the excitability of cells in the DG of the hippocampus that recruits a sub-population of cells to differentiate contexts, independent of experienced stimuli, expanding the “pattern separation” role typically attributed to the DG. It has been demonstrated in rats that if PFC is inactivated, both acquisition and recall of memory associations are impaired. However, PFC inactivation during acquisition of one set of memory associations surprisingly leads to subsequent facilitation of the acquisition of a conflicting set of memory associations in the same context under normal PFC operation. We provide here the first computational and algorithmic account of how the absence or presence of the top-down contextual biases on the excitability of DG cells during different learning phases of these experiments explains these data. Our model simulates PFC inactivation as the loss of inhibitory control on DG, which leads to full or partial activation of DG cells related to conflicting memory associations previously acquired in different contexts. This causes context-inappropriate memory traces to become active in the CA3 recurrent network and thereby the output CA1 area within the hippocampus. We show that these incongruous memory patterns proactively interfere with and slow the acquisition of new memory associations. Further, we demonstrate that pattern completion within CA3 in response to a partial cue for the recall of previously acquired memories is also impaired by PFC inactivation for the same reason. Pre-training the model with interfering memories in contexts different from those used in the experiments, simulating a lifetime of experiences, was crucial to reproduce the rat behavioral data. Finally, we made several testable predictions based on the model that suggest future experiments to deepen our understanding of brain-wide memory processes.
Highlights
A defining characteristic of our daily lives is our ability to recall memories of experiences that occurred in arbitrary places, even from the distant past
Our model is capable of forming and recalling contextual memories, because are the different contexts distinguished within the dentate gyrus (DG), and the mossy fiber projections from DG to CA3 are the strongest relative to other connections to CA3 cells; see Table 2
Simulated muscimol rats did continue learning for two additional blocks with the top-down contextual bias over DG in place, we suggest that the distributed projections from across various contextual DG ensembles to CA3 for the List 1 memory engrams were still sufficiently preserved by the time List 2 learning began
Summary
A defining characteristic of our daily lives is our ability to recall memories of experiences that occurred in arbitrary places, even from the distant past. Distributed regions beyond the medial temporal lobe, such as the prefrontal cortex (PFC), are known to be involved in memory processing, but their roles are computationally less clear. In this regard, the main goal of this article is to advance a computational account of how external contextual signals can modulate various aspects of associative memory encoding and recall in the entorhinal-hippocampal system. That data showed that memory associations can be impaired and facilitated by the inactivation of PFC under various conditions (Navawongse and Eichenbaum, 2013; Peters et al, 2013). The typical advantage for learning a conflicting set of memory associations in a different context is lost under PFC inactivation
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