Neural Dynamics of Time Perception in the Ventral Premotor Cortex

Academic Background

Time perception is one of the central questions in neuroscience, particularly how the brain encodes time information as cognitive demands change. Time can be categorized as “long” or “short,” or it can be precisely represented as continuous intervals. The ventral premotor cortex (VPC) plays a crucial role in complex temporal processing, such as speech processing, but its specific role in time estimation remains underexplored. This study aims to investigate how the VPC processes time information in primates during a time interval comparison task (TICT) and a time categorization task (TCT).

Paper Source

This research was conducted by Héctor Díaz, Lucas Bayones, Manuel Álvarez, and other researchers from the Institute of Cellular Physiology at the National Autonomous University of Mexico (Universidad Nacional Autónoma de México). The paper, titled “Contextual neural dynamics during time perception in the primate ventral premotor cortex,” was published in the Proceedings of the National Academy of Sciences (PNAS) on February 6, 2025.

Research Process

Experimental Design

The study involved two main tasks: the time interval comparison task (TICT) and the time interval categorization task (TCT). In TICT, monkeys had to compare two consecutive time intervals (int1 and int2) and judge which one was longer after a fixed delay. In TCT, monkeys needed to categorize a single time interval as either “long” or “short.” Neuronal activity in the VPC was recorded during both tasks.

Subjects and Methods

Two monkeys were used as experimental subjects for both TICT and TCT tasks. During the experiments, mechanical probes stimulated the skin of the monkeys’ fingertips, and the monkeys responded by pressing buttons. Neuronal activity was recorded using electrodes placed in the VPC, with electrode positions precisely located using MRI scans.

Data Analysis

Researchers analyzed neuronal population activity using methods such as principal component analysis (PCA) and mutual information. Specifically, they developed an analysis method based on cosine similarity to quantify the similarity of neuronal population states at different time points.

Key Findings

Neuronal Activity in TICT

In TICT, VPC neurons exhibited highly heterogeneous responses. Most neurons showed activity during the presentation of time intervals, while a smaller subset retained this information during the working memory period. Population-level analysis revealed a linear relationship between neuronal activity and interval duration. This parametric encoding pattern persisted during the delay period.

Neuronal Activity in TCT

In TCT, neuronal activity displayed categorical characteristics. Neurons showed distinct dynamic patterns based on the category of the time interval (long or short). During the delay period, neuronal population activity clearly separated into two categories corresponding to “long” and “short” intervals.

Population Dynamic Analysis

Through PCA analysis, researchers found that VPC exhibits different population dynamics in TICT and TCT. In TICT, population activity showed a parametric linear relationship, whereas in TCT, it significantly diverged based on the category of the time interval. This dynamic switching indicates that VPC flexibly encodes time information according to task demands.

Conclusion

This study demonstrates that the VPC plays a critical role in encoding and maintaining time intervals. Neuronal populations exhibit parametric linear relationships in TICT, encoding time information, and distinctly separate categories in TCT. This flexible adaptive ability highlights the VPC’s importance in processing time information and reveals how the brain adjusts time perception mechanisms based on cognitive demands.

Research Highlights

1. Task-dependent Time Encoding: The study found that the VPC can flexibly adjust its time encoding mode based on task requirements (comparison or categorization).
2. Population Dynamic Analysis: Using PCA and cosine similarity analysis, researchers uncovered the evolving mechanisms of VPC dynamics during time perception.
3. Parametric Memory Maintenance: In TICT, the VPC can maintain parametric encoding of time information throughout the working memory period, providing new insights into time processing in working memory.
4. Dynamic Categorical Separation: In TCT, the VPC can clearly divide time intervals into “long” and “short” categories and retain this classification information throughout the delay period.

Value and Significance

This research not only expands our understanding of VPC function but also reveals the neural mechanisms of time information processing in the brain across different cognitive tasks. Specifically, the findings suggest that the VPC is involved not only in encoding time perception but also in maintaining this information in working memory, offering important clues about the relationship between time perception and cognitive control. Additionally, the methodological innovations, such as PCA-based population dynamic analysis, provide new tools for investigating neural mechanisms in complex cognitive tasks.

This study provides new insights into the neural basis of time perception and lays the foundation for exploring the neural mechanisms of other cognitive functions, such as decision-making and memory.