Flexible clocks can sync up or drift apart across brain regions in mice

A study in mice suggests the brain does not rely on a single internal clock but can flexibly switch between shared and independent timing across regions, as reported by researchers from Science Tokyo. By recording thousands of neurons simultaneously in two brain areas during an alternating timing task, the team found that these areas sometimes tracked time together and sometimes separately. The findings, published in Nature Communications, provide a new framework for understanding how brain regions are coordinated.

The brain is constantly keeping track of time, even if one does not consciously notice it. This ability to sense elapsed time underlies many mental processes, such as movement, planning, working memory, decision-making and learning. Several brain regions can represent time in some way, especially areas in the frontal and parietal cortex involved in higher-order cognition. But if timing information shows up in many different areas of the brain at once, how do they stay in sync with each other?

Scientists have long wondered whether multiple brain regions all follow a single shared internal clock or whether each region can keep its own local clock when needed. Both possibilities could be useful; sometimes brain regions must stay aligned to a single event, while in other situations they may need to track different streams of information independently. However, testing this idea has proven difficult, as it requires recording the activity of large numbers of neurons at the same time while animals perform well-designed tasks.

Testing two clocks at once

To tackle this knowledge gap, a research team led by Associate Professor Riichiro Hira from the Department of Physiology and Cell Biology, Institute of Science Tokyo (Science Tokyo), Japan, investigated how two brain regions coordinate their sense of time. In their study, the researchers examined the secondary motor cortex and posterior parietal cortex in mice during an innovative time-tracking task.

The researchers first trained the mice to predict the timing of rewards as they alternated between 6-second and 12-second intervals. Over time, the mice learned this pattern and began to anticipate both the short and long reward intervals. The team then used wide-field two-photon calcium imaging to record the activity of thousands of neurons simultaneously in the two brain regions while the animals performed the task.

When timing drifted apart

In both areas, the team observed sequential patterns of activity, with different neurons becoming active at different moments, indicating that both regions were representing elapsed time. Through decoding analyses, the researchers then estimated what point in time each brain region was representing on a given trial. This approach revealed two kinds of errors: cases where both regions misjudged time similarly and cases where only one region drifted off. This suggests these regions are neither perfectly synchronized nor fully independent.

To explain this phenomenon, the team built a computational model consisting of twin connected recurrent neural networks. By analyzing neural activity in this model, the researchers gained insights into the brain’s timekeeping mechanisms.

Weak links, flexible coordination

As Hira explains, “We found sparse inter-regional connectivity promotes synchronization between the two regions, whereas widespread fluctuations prevent complete synchronization, allowing each region to preserve its own temporal representation.” In other words, the brain may use a combination of weak coupling and global activity patterns to balance stability with flexibility across regions.

Taken together, these findings provide a new framework for understanding how the brain can share information across regions without forcing every area into the same exact state. “In the future, our results may contribute to a better understanding of cognition, neurological disorders involving disrupted inter-regional coordination, and the development of brain-inspired artificial intelligence and robotic control systems that combine stability with flexibility,” Hira concludes.

Who’s behind this story?

See also  Outsmarting chemo-resistant ovarian cancer with nanoparticle treatment

Lisa Lock

BA art history, MA material culture. Former museum editor, paramedic, and transplant coordinator. Editing for Science X since 2021.

Full profile →

Advertisements

Robert Egan

Bachelor’s in mathematical biology, Master’s in creative writing. Well-traveled with unique perspectives on science and language.

Full profile →