Sharp-wave-ripple-associated activity in the medial prefrontal cortex supports spatial rule switching

Bakker, Hanna den; Dijck, Marie Van; Sun, Jyh-Jang; Kloosterman, Fabian

doi:10.1016/j.celrep.2023.112959

Cited by 6 publications

(2 citation statements)

References 49 publications

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“…Notably, the model accurately replicates the empirical finding that interrupting communication between the two hierarchical levels hampers rule switching and promotes perseverative behavior, in accordance with studies conducted by Ref. 49.…”

Section: Hierarchical Generative Model For Memory-guided Spatial Alte...supporting

confidence: 87%

Neural representation in active inference: Using generative models to interact with—and understand—the lived world

Pezzulo,

D'Amato,

Mannella

et al. 2024

Annals of the New York Academy of Sciences

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This paper considers neural representation through the lens of active inference, a normative framework for understanding brain function. It delves into how living organisms employ generative models to minimize the discrepancy between predictions and observations (as scored with variational free energy). The ensuing analysis suggests that the brain learns generative models to navigate the world adaptively, not (or not solely) to understand it. Different living organisms may possess an array of generative models, spanning from those that support action‐perception cycles to those that underwrite planning and imagination; namely, from explicit models that entail variables for predicting concurrent sensations, like objects, faces, or people—to action‐oriented models that predict action outcomes. It then elucidates how generative models and belief dynamics might link to neural representation and the implications of different types of generative models for understanding an agent's cognitive capabilities in relation to its ecological niche. The paper concludes with open questions regarding the evolution of generative models and the development of advanced cognitive abilities—and the gradual transition from pragmatic to detached neural representations. The analysis on offer foregrounds the diverse roles that generative models play in cognitive processes and the evolution of neural representation.

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Section: Hierarchical Generative Model For Memory-guided Spatial Alte...supporting

confidence: 87%

Neural representation in active inference: Using generative models to interact with—and understand—the lived world

Pezzulo,

D'Amato,

Mannella

et al. 2024

Annals of the New York Academy of Sciences

View full text Add to dashboard Cite

show abstract

“…Prefrontal cortex is thought to represent upcoming choice information and is required for flexible decision-making. In the context of spatial navigation, several studies have found evidence that prefrontal cortex acts in coordination with hippocampus to facilitate decision-making and planning for upcoming choices (Benchenane et al, 2010;den Bakker et al, 2023;Hyman et al, 2005;Jones & Wilson, 2005;O'Neill et al, 2013;Tamura et al, 2017). Prefrontal cortex neural activity in rodents has been observed to co-occur with hippocampal activity specifically when hippocampus encodes non-local spatial representations, suggesting prefrontal cortex may play a role in evaluating these non-local codes as potential choices (Berners-Lee et al, 2021;Hasz & Redish, 2020;Yu & Frank, 2021).…”

Section: Introductionmentioning

confidence: 99%

New information triggers prospective codes to adapt for flexible navigation

Prince,

Yassine,

Katragadda

et al. 2023

Preprint

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Navigating a dynamic world requires rapidly updating choices by integrating past experiences with new information. In hippocampus and prefrontal cortex, neural activity representing future goals is theorized to support planning. However, it remains unknown how prospective goal representations incorporate new, pivotal information. Accordingly, we designed a novel task that precisely introduces new information using virtual reality, and we recorded neural activity as mice flexibly adapted their planned destinations. We found that new information triggered increased hippocampal prospective representations of both possible goals; while in prefrontal cortex, new information caused prospective representations of choices to rapidly shift to the new choice. When mice did not flexibly adapt, prefrontal choice codes failed to switch, despite relatively intact hippocampal goal representations. Prospective code updating depended on the commitment to the initial choice and degree of adaptation needed. Thus, we show how prospective codes update with new information to flexibly adapt ongoing navigational plans.

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Neurons in the medial prefrontal cortex that are not modulated by hippocampal sharp-wave ripples are involved in spatial tuning and signaling upcoming choice

den Bakker,

Kloosterman

2024

Preprint

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The hippocampus is known to encode spatial information and reactivate experienced trajectories during sharp-wave ripple events. These events are thought to be key time-points at which information about learned trajectories is transferred to the neocortex for long-term storage. It is unclear, however, how this information may be transferred and integrated in downstream cortical regions. In this study, we performed high-density probe recordings across the full depth of the medial prefrontal cortex and in the hippocampus simultaneously in rats while they were performing a task of spatial navigation. We find that neurons in the medial prefrontal cortex encode spatial information and reliably predict upcoming choice on a maze, and we find that a subset of neurons in the mPFC is modulated by hippocampal sharp-wave ripples. However, the neurons that are involved in predicting upcoming choice are not the neurons that are modulated by hippocampal sharp-wave ripples. This indicates that the integration of spatial information requires the collaboration of different specialized populations of neurons.

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Sharp-wave-ripple-associated activity in the medial prefrontal cortex supports spatial rule switching

Cited by 6 publications

References 49 publications

Neural representation in active inference: Using generative models to interact with—and understand—the lived world

Neural representation in active inference: Using generative models to interact with—and understand—the lived world

New information triggers prospective codes to adapt for flexible navigation

Neurons in the medial prefrontal cortex that are not modulated by hippocampal sharp-wave ripples are involved in spatial tuning and signaling upcoming choice

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