Understanding how the brain learns and applies rules is the key to unraveling the neural basis of flexible behavior. A new study from the University of Toyama, Japan, reveals that our ability to follow procedural rules is encoded in the evolving dynamics of neuronal activity in the medial prefrontal cortex (mPFC).
The research team, led by Assistant Professor Shuntaro Ohno at the Faculty of Medicine, University of Toyama, Japan, recorded neuronal activity in mice learning a Y-maze task. As learning progressed, distinct sequences of neural activation emerged in the mPFC that could predict whether the mouse succeeded or failed at obtaining a reward. Their findings were published in Molecular Brain on July 1, 2025.
The researchers placed the mice individually in a Y-shaped maze and allowed them to explore the maze without any restriction in the beginning. The branched arms were called the “Zone,” where each mouse had to wait and then respond to a light cue to navigate its way to the water container called the “Port,” and finally claim a water reward by licking within the predetermined time.
As their training progressed, the mice became faster and more successful in obtaining rewards, although the physical paths they took remained the same. Meanwhile, the scientists recorded hundreds of mPFC neurons through calcium imaging, capturing how neural populations changed during the learning process.
Decoding neural activity with iSeq
To comprehend this complex neural data, the team developed iSeq—a novel computational tool that applies convolutional non-negative matrix factorization to automatically detect neuronal sequences from imaging data without any prespecified behavioral labels. These sequences represent ordered patterns of neural activation spanning several seconds.
The analyses revealed that in the initial phases of training, the sequences were less predictive. However, by day 6, the dynamics of sequences differed significantly between successful and unsuccessful reward acquisition moments in mice that had mastered the task, even before the action occurred.
How learning reshapes brain activity
“The development of iSeq allowed us to observe the brain’s internal organization of behavior in unprecedented detail,” explained Dr. Ohno. “We found that as the animals learned, their prefrontal cortex dynamically restructured neural activity patterns to emphasize actions that reliably led to rewards.”
Furthermore, the researchers observed that the composition of neurons participating in each sequence changed across days of training. In other words, the set of cells that formed the sequence on day 1 was not the same as the one on day 6, indicating that the mPFC continually reorganized its neural circuits as the behavior became refined. This flexible reconfiguration, rather than the reuse of fixed neural assemblies, reflects the brain’s capacity to adapt its internal representations.
“These results suggest that the brain does not store a rule as a static template,” noted Dr. Ohno. “Instead, it continuously updates sequential activity patterns to link meaningful sensory cues, actions, and outcomes—essentially learning how to learn.”
Implications for neuroscience and beyond
These results bridge the gap between neural activity and behavioral rule execution. They suggest that a procedural rule—analogous to a cascade such as stimulus ? action ? reward—is represented in the brain as a chain of neural events.
This chain is not fixed but evolves as the animal becomes competent; the brain reorganizes neural sequences to align with successful behavior. Understanding the underlying mechanism offers new insight into how cognitive control, learning, and adaptation are instantiated in neural circuits.
The implications of this study extend beyond basic science. Insights into how rules are encoded and updated might inform rehabilitation strategies after a brain injury, or how artificial intelligence might mimic this flexibility. Moreover, the computational method iSeq could become a tool for investigating sequence-based neural dynamics in other areas of the brain and could be extended to other species
While the study was conducted in mice, it provides a foundational framework for understanding how the human brain learns to execute rules and adapt its behavior. The findings highlight the importance of temporal patterns in brain activity, and how they might form the basis of flexible, learned behavior rather than static connectivity alone.
More information:
Shuntaro Ohno et al, The medial prefrontal cortex encodes procedural rules as sequential neuronal activity dynamics, Molecular Brain (2025). DOI: 10.1186/s13041-025-01230-w
The content is provided for information purposes only.