Peripheral sensory activity follows the temporal structure of input signals. Central sensory processing uses also rate coding, and motor outputs appear to be primarily encoded by rate. I propose here a simple, efficient structure, converting temporal coding to rate coding by neuronal phase-locked loops (PLL). The simplest form of a PLL includes a phase detector (that is, a neuronal-plausible version of an ideal coincidence detector) and a controllable local oscillator that are connected in a negative feedback loop. The phase detector compares the firing times of the local oscillator and the input and provides an output whose firing rate is monotonically related to the time difference. The output rate is fed back to the local oscillator and forces it to phase-lock to the input. Every temporal interval at the input is associated with a specific pair of output rate and time difference values; the higher the output rate, the further the local oscillator is driven from its intrinsic frequency. Sequences of input intervals, which by definition encode input information, are thus represented by sequences of firing rates at the PLL's output. The most plausible implementation of PLL circuits is by thalamocortical loops in which populations of thalamic “relay” neurons function as phase detectors that compare the timings of cortical oscillators and sensory signals. The output in this case is encoded by the thalamic population rate. This article presents and analyzes the algorithmic and the implementation levels of the proposed PLL model and describes the implementation of the PLL model to the primate tactile system.

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