Short-Term Synaptic Plasticity as a Mechanism for Sensory Timing

The ability to detect time intervals and temporal patterns is critical to some of the most fundamental computations the brain performs, including the ability to communicate and appraise a dynamically changing environment. Many of these computations take place on the scale of tens to hundreds of milliseconds. Electrophysiological evidence shows that some neurons respond selectively to duration, interval, rate, or order. Because the time constants of many time-varying neural and synaptic properties, including short-term synaptic plasticity (STP), are also in the range of tens to hundreds of milliseconds, they are strong candidates to underlie the formation of temporally selective neurons. Neurophysiological studies indicate that STP is indeed one of the mechanisms that contributes to temporal selectivity, and computational models demonstrate that neurons embedded in local microcircuits exhibit temporal selectivity if their synapses undergo STP. Converging evidence suggests that some forms of temporal selectivity emerge from the dynamic changes in the balance of excitation and inhibition imposed by STP. Animals have evolved mechanisms to track time and extract temporal information on the scale of tens to hundreds of milliseconds. It is within this range that animals and humans are not only able to identify simple temporal intervals but extract higher-order temporal patterns. Across species and modalities, researchers have identified neurons that selectively respond to temporal features including interval, duration, rate, and complex temporal structure. We propose that temporal selectivity is an intrinsic property of local neural circuits that relies on time-varying synaptic and neuronal properties; most notably STP. Computational models establish that temporally selective neurons emerge from neural microcircuits that incorporate STP.