Decoding temporally encoded sensory input by cortical oscillations and thalamic phase comparators

Abstract

The temporally encoded information obtained by vibrissal touch could be decoded "passively," involving only input-driven elements, or "actively," utilizing intrinsically driven oscillators. A previous study suggested that the trigeminal somatosensory system of rats does not obey the bottom-up order of activation predicted by passive decoding. Thus, we have tested whether this system obeys the predictions of active decoding. We have studied cortical single units in the somatosensory cortices of anesthetized rats and guinea pigs and found that about a quarter of them exhibit clear spontaneous oscillations, many of them around whisking frequencies (Ϸ10 Hz). The frequencies of these oscillations could be controlled locally by glutamate. These oscillations could be forced to track the frequency of induced rhythmic whisker movements at a stable, frequency-dependent, phase difference. During these stimulations, the response intensities of multiunits at the thalamic recipient layers of the cortex decreased, and their latencies increased, with increasing input frequency. These observations are consistent with thalamocortical loops implementing phase-locked loops, circuits that are most efficient in decoding temporally encoded information like that obtained by active vibrissal touch. According to this model, and consistent with our results, populations of thalamic "relay" neurons function as phase "comparators" that compare cortical timing expectations with the actual input timing and represent the difference by their population output rate.Rats, like other rodents, possess a specialized system for active touch. During tactile exploration, their whiskers scan the environment by rhythmic movements of 5-11 Hz (1, 2) to obtain sensory information about the location and texture of external objects (3, 4). Temporally, an object's location is encoded by the time interval between receptor firing at the onset of a whisking cycle and receptor firing due to perturbation of whisker motion by an external object [first-order vibrissal neurons respond strongly to these two events (5)]. This information could be decoded "passively;" that is, by feed-forward, bottom-up transformations utilizing neuronal temporal sensitivities (6) [axonal delay lines are not efficient at the millisecond range (7)]. Alternatively, temporal decoding could be obtained "actively," which involves top-down processes whereby intrinsic cortical oscillators track the input and provide a measure of its instantaneous frequency (8, 9).In passive decoding, sensory signals propagate in a feedforward manner to the cortex through thalamic "relay" neurons (Fig. 1A). Thus, whisker-locked activities of somatosensory thalamic neurons should lag brainstem but lead the cortical activities (Fig. 1B). In contrast, during whisker-locked oscillatory epochs in freely behaving rats, thalamic neurons phase-lag both brainstem and cortical neurons (10). Moreover, the oscillatory epochs are usually initiated at the cortex, further questioning the assumption of passive temporal d...

Imaging Spatiotemporal Dynamics of Surround Inhibition in the Barrels Somatosensory Cortex

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“…The utility of the oscillatory activity is supported by Ahissar and colleagues' work (41) showing that cortical neurons can entrain their oscillatory firing to the frequency of peripheral whisker stimulation, and thus set up a thalamic comparator that is ideal for detecting changes in incoming stimuli. The whisker twitchingrelated oscillations may serve to set up this comparator, which is highly sensitive to a novel stimulus.…”

Speech comprehension is correlated with temporal response patterns recorded from auditory cortex

“…The advantage of the latter mechanism is its online adaptivity, which allows tracking of continuous changes in the rate of speech. Recent evidence from the somatosensory system of the rat supports the implementation of phase-locked loops within thalamocortical loops (37,(49)(50)(51). Because the computational tasks, and frequency ranges, are similar, similar mechanisms could be useful for both somatosensory and auditory (and maybe even visual; see ref.…”