Biology subjects

Kidder, K. S.

Publications and source records attributed to Kidder, K. S..

2 recordsLinked to original sources

bioRxiv2023

The medial prefrontal cortex during flexible decisions: Evidence for its role in distinct working memory processes

During decisions that involve working memory, task-related information must be encoded, maintained across delays, and retrieved. Few studies have attempted to causally disambiguate how different brain structures contribute to each of these components of working memory. In the present study, we used transient optogenetic disruptions of rat medial prefrontal cortex (mPFC) during a serial spatial reversal learning (SSRL) task to test its role in these specific working memory processes. By analyzing numerous performance metrics, we found: 1) mPFC disruption impaired performance during only the choice epoch of initial discrimination learning of the SSRL task, 2) mPFC disruption impaired performance in dissociable ways across all task epochs (delay, choice, return) during flexible decision-making, 3) mPFC disruption resulted in a reduction of the typical vicarious-trial-and-error (VTE) rate modulation that was related to changes in task demands. Taken together, these findings suggest that the mPFC plays an outsized role in working memory retrieval, becomes involved in encoding and maintenance when recent memories conflict with task demands, and enables animals to flexibly utilize working memory to update behavior as environments change.

neuroscience↗

bioRxiv2021

A machine learning approach for detecting vicarious trial and error behaviors

Vicarious trial and error behaviors (VTEs) indicate periods of indecision during decision-making, and have been proposed as a behavioral marker of deliberation. In order to understand the neural underpinnings of these putative bridges between behavior and neural dynamics, researchers need the ability to readily distinguish VTEs from non-VTEs. Here we utilize a small set of trajectory-based features and standard machine learning classifiers to identify VTEs from non-VTEs for rats performing a spatial delayed alternation task (SDA) on an elevated plus maze. We also show that previously reported features of the hippocampal field potential oscillation can be used in the same types of classifiers to separate VTEs from non-VTEs with above chance performance. However, we caution that the modest classifier success using hippocampal population dynamics is not sufficient for identifying trials where VTEs occur, and show that combining oscillation-based features with trajectory-based features degrades classifier performance compared to trajectory-based features alone. Overall, we propose a standard set of features useful for trajectory-based VTE classification and support previous suggestions that VTEs are supported by a network including, but likely extending beyond, the hippocampus.

neuroscience↗