Public Release: 

Brain neurons help keep track of time

American Association for the Advancement of Science

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IMAGE: Time flows, time flies, time stands still. This material relates to a paper that appeared in the Dec. 9, 2016, issue of Science, published by AAAS. The paper, by S.... view more

Credit: Gil Costa

Turning the theory of how the human brain perceives time on its head, a novel analysis in mice reveals that dopamine neuron activity plays a key role in judgment of time, slowing down the internal clock. As Patrick Simen and Matthew Matell note in a related Perspective, "The results suggest the need to reassess the leading theory of dopamine function in timing--the dopamine clock hypothesis." Organisms' ability to accurately estimate periods of time is variable and depends on circumstances, including motivation, attention and emotions. Dopamine (DA) neurons residing in the midbrain have been implicated as regulators of this complex process. However, a direct link between the signals carried by DA neurons and timekeeping is lacking. What's more, current studies in which timing behavior is disrupted have demonstrated conflicting results - in some cases, increased DA release speeds up the subjective sense of time, while in other instances, it is slowed down or unaffected. To make sense of DA's involvement in time approximation, Sofia Soares and colleagues tracked DA activity in mice performing timed tasks. The mice were presented with two audible tones, and trained to classify the interval between each as shorter or longer. Soares et al. observed bursts of activity in mouse DA neurons that synchronized exclusively to the second noise, reflecting the rodents' anticipation of an upcoming reward, combined with their surprise about the arrival time of the sound. The authors discovered the transient activation or inhibition of dopamine neurons was sufficient to slow down or speed up time estimation, respectively. Simen and Matell emphasize the brain's fine-tuned ramping up and down of DA signals may prove essential in resolving previous experimental inconsistencies, and identifying novel DA functions that help shape behavior.

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