Neurophysiology of timing in the hundreds of milliseconds: multiple layers of neuronal clocks in the medial premotor areas.

The precise quantification of time in the subsecond scale is critical for many complex behaviors including music and dance appreciation/execution, speech comprehension/articulation, and the performance of many sports. Nevertheless, its neural underpinnings are largely unknown. Recent neurophysiological experiments from our laboratory have shown that the cell activity in the medial premotor areas (MPC) of macaques can represent different aspects of temporal processing during a synchronization-continuation tapping task (SCT). In this task the rhythmic behavior of monkeys was synchronized to a metronome of isochronous stimuli in the hundreds of milliseconds range (synchronization phase), followed by a period where animals internally temporalized their movements (continuation phase). Overall, we found that the time-keeping mechanism in MPC is governed by different layers of neural clocks. Close to the temporal control of movements are two separate populations of ramping cells that code for elapsed or remaining time for a tapping movement during the SCT. Thus, the sensorimotor loops engaged during the task may depend on the cyclic interplay between two neuronal chronometers that quantify in their instantaneous discharge rate the time passed and the remaining time for an action. In addition, we found MPC neurons that are tuned to the duration of produced intervals during the rhythmic task, showing an orderly variation in the average discharge rate as a function of duration. All the tested durations in the subsecond scale were represented in the preferred intervals of the cell population. Most of the interval-tuned cells were also tuned to the ordinal structure of the six intervals produced sequentially in the SCT. Hence, this next level of temporal processing may work as the notes of a musical score, providing information to the timing network about what duration and ordinal element of the sequence are being executed. Finally, we describe how the timing circuit can use a dynamic neural representation of the passage of time and the context in which the intervals are executed by integrating the time-varying activity of populations of cells. These neural population clocks can be defined as distinct trajectories in the multidimensional cell response-space. We provide a hypothesis of how these different levels of neural clocks can interact to constitute a coherent timing machine that controls the rhythmic behavior during the SCT.