Dataset Information

Dorsomedial prefrontal cortex and hippocampus represent strategic context even while simultaneously changing representation throughout a task session.

ABSTRACT: Dorsomedial prefrontal cortex (dmPFC) and hippocampus (HPC) are thought to play complementary roles in a spatial working memory and decision-making network, where spatial information from HPC informs representations in dmPFC, and contextual information from dmPFC biases how HPC recalls that information. We recorded simultaneously from neural ensembles in rodent dmPFC and HPC as rats performed a rule-switching task, and found that ensembles in dmPFC and HPC simultaneously encoded task contingencies and other time-varying information. While ensembles in HPC transitioned to represent new contingencies at the same time as rats updated their strategies to be consistent with the new contingency, dmPFC ensembles transitioned earlier. Neural representations of other time-varying information also changed faster in dmPFC than in HPC. Our results suggest that HPC and dmPFC represent contingencies while simultaneously representing other information which changes over time, and that this contextual information is integrated into hippocampal representations more slowly than in dmPFC.

SUBMITTER: Hasz BM

PROVIDER: S-EPMC7238283 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Dorsomedial prefrontal cortex and hippocampus represent strategic context even while simultaneously changing representation throughout a task session.

Hasz Brendan M BM Redish A David AD

Neurobiology of learning and memory 20200408

Dorsomedial prefrontal cortex (dmPFC) and hippocampus (HPC) are thought to play complementary roles in a spatial working memory and decision-making network, where spatial information from HPC informs representations in dmPFC, and contextual information from dmPFC biases how HPC recalls that information. We recorded simultaneously from neural ensembles in rodent dmPFC and HPC as rats performed a rule-switching task, and found that ensembles in dmPFC and HPC simultaneously encoded task contingenci ...[more]

PMID: 32276121

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Project description:BackgroundIn microsimulation models of diseases with an early, acute phase requiring short cycle lengths followed by a chronic phase, fixed short cycles may lead to computational inefficiency. Examples include epidemic or resource constraint models with early short cycles where long-term economic consequences are of interest for individuals surviving the epidemic or ultimately obtaining the resource. In this article, we demonstrate methods to improve efficiency in such scenarios. Furthermore, we show that care must be taken when applying these methods to epidemic or resource constraint models to avoid bias.MethodsTo demonstrate efficiency, we compared the model runtime among 3 versions of a microsimulation model: with short fixed cycles for all states (FCL), with dynamic cycle length (DCL) defined locally for each state, and with DCL features plus a discrete-event-like hybrid component. To demonstrate bias mitigation, we compared discounted lifetime costs for 3 versions of a resource constraint model: with a fixed horizon where simulation stops, with a fixed entry horizon beyond which new individuals could not enter the model, and with a fixed entry horizon plus a mechanism to maintain a constant level of competition for the resource after the horizon.ResultsThe 3 versions of the microsimulation model had average runtimes of 515 (95% credible interval [CI]: 477 to 545; FCL), 2.70 (95% CI: 1.48 to 2.92; DCL), and 1.45 (95% CI: 1.26 to 2.61; DCL-pseudo discrete event simulation) seconds, respectively. The first 2 resource constraint versions underestimated costs relative to the constant competition version: $20,055 (95% CI: $19,000 to $21,120), $27,030 (95% CI: $24,680 to $29,412), and $33,424 (95% CI: $27,510 to $44,484), respectively.LimitationsThe magnitude of improvements in efficiency and reduction in bias may be model specific.ConclusionChanging time representation in microsimulation may offer computational advantages.HighlightsShort cycle lengths may be required to model the acute phase of an illness but lead to computational inefficiency in a subsequent chronic phase in microsimulation models.A solution is to create state-specific cycle lengths so that cycle lengths change dynamically as the simulation progresses.Computational efficiency can be enhanced further by using a hybrid model containing discrete-event-simulation-like features.Hybrid models can efficiently handle events subsequent to exit from an epidemic or resource constraint model provided steps are taken to mitigate potential bias.

Dataset Information

Dorsomedial prefrontal cortex and hippocampus represent strategic context even while simultaneously changing representation throughout a task session.

Publications

Dorsomedial prefrontal cortex and hippocampus represent strategic context even while simultaneously changing representation throughout a task session.

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