Summary: The striatum and premotor cortex show altered patterns in neural activity when encoding time. The dynamics of the striatum were more sequential than those of the premotor cortex.
Tracking the passage of time to the second is critical for motor control, learning and cognition, including the ability to anticipate future events. While the brain depends on its circadian clock to measure hours and days, the circadian clock does not have a second hand.
Instead, the brain measures seconds through changing patterns of cellular activity. Much like a line of falling dominoes, each neuron activates the next, and time is marked by the neuron that is currently active. By analogy, if a sequence of falling dominoes takes 10 seconds from start to finish, one can deduce that 5 seconds has elapsed when the middle domino falls.
UCLA neuroscientists introduced mice to two different scents. The mice learned that one odor predicted the arrival of a sweet liquid reward after three seconds, while the other odor predicted a reward after six seconds. The mice started licking the spout earlier in anticipation of the reward after they sniffed the first scent than when they smelled the second.
Recordings in the striatum and premotor cortex of the brain revealed that changing patterns of neural activity in both regions encoded time–consistent with the notion that the brain has multiple clocks. But the pattern in the striatum was closer to the sequence of falling dominoes–a pattern referred to as a neural sequence–compared to the patterns in a motor area that provides input to the striatum.
Timing is a fundamental part of human behavior, learning and thought. By revealing how and where the brain counts and represents seconds, the UCLA discovery will deepen scientists’ understanding of normal and abnormal brain function.
Funding: Grants from the National Institute of Neurological Diseases and Stroke, the National Science Foundation and Marion Bowen Neurobiology Postdoctoral Grant Program at UCLA supported the research.
About this neuroscience research article
Elaine Schmidt – UCLA
The image is in the public domain.
Original Research: Closed access
“Neural Sequences as an Optimal Dynamical Regime for the Readout of Time” by Shanglin Zhou, Sotiris C. Masmanidis, Dean V. Buonomano. Neuron.
Neural Sequences as an Optimal Dynamical Regime for the Readout of Time
• Timing is critical to the brain’s ability to predict and prepare for future events
• During a two-interval task, time was encoded in both premotor cortex and striatum
• Dynamics in the striatum, however, was more sequential
• Neural sequences provide an ideal set of basis functions to read out time
Converging evidence suggests that the brain encodes time through dynamically changing patterns of neural activity, including neural sequences, ramping activity, and complex spatiotemporal dynamics. However, the potential computational significance and advantage of these different regimes have remained unaddressed. We combined large-scale recordings and modeling to compare population dynamics between premotor cortex and striatum in mice performing a two-interval timing task. Conventional decoders revealed that the dynamics within each area encoded time equally well; however, the dynamics in striatum exhibited a higher degree of sequentiality. Analysis of premotor and striatal dynamics, together with a large set of simulated prototypical dynamical regimes, revealed that regimes with higher sequentiality allowed a biologically constrained artificial downstream network to better read out time. These results suggest that, although different strategies exist for encoding time in the brain, neural sequences represent an ideal and flexible dynamical regime for enabling downstream areas to read out this information.