Stable sequential dynamics in prefrontal cortex represents subjective estimation of time

Time estimation is an essential prerequisite underlying various cognitive functions. Previous studies identified ‘sequential firing’ and ‘activity ramps’ as the primary neuron activity patterns in the medial frontal cortex (mPFC) that could convey information regarding time. However, the relationship between these patterns and the timing behavior has not been fully understood. In this study, we utilized in vivo calcium imaging of mPFC in rats performing a timing task. We observed cells that showed selective activation at trial start, end, or during the timing interval. By aligning long-term time-lapse datasets, we discovered that sequential patterns of time coding were stable over weeks, while cells coding for trial start or end showed constant dynamism. Furthermore, with a novel behavior design that allowed the animal to determine individual trial interval, we were able to demonstrate that real-time adjustment in the sequence procession speed closely tracked the trial-to-trial interval variations. And errors in the rats’ timing behavior can be primarily attributed to the premature ending of the time sequence. Together, our data suggest that sequential activity maybe a stable neural substrate that represents time under physiological conditions. Furthermore, our results imply the existence of a unique cell type in the mPFC that participates in the time-related sequences. Future characterization of this cell type could provide important insights in the neural mechanism of timing and related cognitive functions.

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Publication Details

Journal
eLife
Published
2024-12-11
DOI
https://doi.org/10.7554/elife.96603.3
Primary Topic
Neuroscience and Music Perception
Type
article
Field-Weighted Citation Impact
0.00

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article

Stable sequential dynamics in prefrontal cortex represents subjective estimation of time

Shanglin Zhou, Peng Yuan, Baoming Li, Chaolin Ma et al.
eLife
Neuroscience and Music Perception
article

Stable sequential dynamics in prefrontal cortex represents subjective estimation of time

Shanglin Zhou, Peng Yuan, Baoming Li, Chaolin Ma, Jiawen Li, Wenqu Yin, Yiting Li, Xin Wang
article en

Abstract

Time estimation is an essential prerequisite underlying various cognitive functions. Previous studies identified ‘sequential firing’ and ‘activity ramps’ as the primary neuron activity patterns in the medial frontal cortex (mPFC) that could convey information regarding time. However, the relationship between these patterns and the timing behavior has not been fully understood. In this study, we utilized in vivo calcium imaging of mPFC in rats performing a timing task. We observed cells that showed selective activation at trial start, end, or during the timing interval. By aligning long-term time-lapse datasets, we discovered that sequential patterns of time coding were stable over weeks, while cells coding for trial start or end showed constant dynamism. Furthermore, with a novel behavior design that allowed the animal to determine individual trial interval, we were able to demonstrate that real-time adjustment in the sequence procession speed closely tracked the trial-to-trial interval variations. And errors in the rats’ timing behavior can be primarily attributed to the premature ending of the time sequence. Together, our data suggest that sequential activity maybe a stable neural substrate that represents time under physiological conditions. Furthermore, our results imply the existence of a unique cell type in the mPFC that participates in the time-related sequences. Future characterization of this cell type could provide important insights in the neural mechanism of timing and related cognitive functions.

eLifeVol. 13
Nanchang University (CN), Hangzhou Normal University (CN), Fudan University (CN), Second Affiliated Hospital of Nanchang University (CN), Huashan Hospital (CN), State Key Laboratory of Medical Neurobiology, Leibniz Institute for Neurobiology (DE)
National Natural Science Foundation of China
Openalex Percentile: Top 77%
Neuroscience and Music Perception
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