Neural and Behavioral Mechanisms of Interval Timing in the Striatum

• Main Author: Mello, Gustavo Borges Moreno e
• Publication Date: 2015
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: http://hdl.handle.net/10362/43665
• topic: Neuroscience; Basic Medicine; Neuroscience

To guide behavior and learn from its consequences, the brain must represent time over many scales. Yet, the neural signals used to encode time in the seconds to minute range are not known. The striatum is the major input area of the basal ganglia; it plays important roles in learning, motor function and normal timing behavior in the range of seconds to minutes. We investigated how striatal population activity might encode time. To do so, we recorded the electrical activity from striatal neurons in rats performing the serial fixed interval task, a dynamic version of the fixed Interval schedule of reinforcement. The animals performed in conformity with proportional timing, but did not strictly conform to scalar timing predictions, which might reflect a parallel strategy to optimize the adaptation to changes in temporal contingencies and consequently to improve reward rate over the session. Regarding the neural activity, we found that neurons fired at delays spanning tens of seconds and that this pattern of responding reflected the interaction between time and the animals’ ongoing sensorimotor state. Surprisingly, cells rescaled responses in time when intervals changed, indicating that striatal populations encoded relative time. Moreover, time estimates decoded from activity predicted trial-bytrial timing behavior as animals adjusted to new intervals, and disrupting striatal function with local infusion of muscimol led to a decrease in timing performance. Because of practical limitations in testing for sufficiency a biological system, we ran a simple simulation of the task; we have shown that neural responses similar to those we observe are conceptually sufficient to produce temporally adaptive behavior. Furthermore, we attempted to explain temporal processes on the basis of ongoing behavior by decoding temporal estimates from high-speed videos of the animals performing the task; we could not explain the temporal report solely on basis of ongoing behavior. These results suggest that striatal activity forms a scalable population firing rate code for time, providing timing signals that animals use to guide their actions.