Hair-Cell Mechanotransduction Persists in TRP Channel Knockout Mice.

Members of the TRP superfamily of ion channels mediate mechanosensation in some organisms, and have been suggested as candidates for the mechanotransduction channel in vertebrate hair cells. Some TRP channels can be ruled out based on lack of an inner ear phenotype in knockout animals or pore properties not similar to the hair-cell channel. Such studies have excluded Trpv4, Trpa1, Trpml3, Trpm1, Trpm3, Trpc1, Trpc3, Trpc5, and Trpc6. However, others remain reasonable candidates. We used data from an RNA-seq analysis of gene expression in hair cells as well as data on TRP channel conductance to narrow the candidate group. We then characterized mice lacking functional Trpm2, Pkd2, Pkd2l1, Pkd2l2 and Pkd1l3, using scanning electron microscopy, auditory brainstem response, permeant dye accumulation, and single-cell electrophysiology. In all of these TRP-deficient mice, and in double and triple knockouts, mechanotransduction persisted. Together with published studies, these results argue against the participation of any of the 33 mouse TRP channels in hair cell transduction.

Thalamic synchrony and the adaptive gating of information flow to cortex.

Although it has long been posited that sensory adaptation serves to enhance information flow in sensory pathways, the neural basis remains elusive. Simultaneous single-unit recordings in the thalamus and cortex in anesthetized rats showed that adaptation differentially influenced thalamus and cortex in a manner that fundamentally changed the nature of information conveyed about vibrissa motion. Using an ideal observer of cortical activity, we found that performance in detecting vibrissal deflections degraded with adaptation while performance in discriminating among vibrissal deflections of different velocities was enhanced, a trend not observed in thalamus. Analysis of simultaneously recorded thalamic neurons did reveal, however, an analogous adaptive change in thalamic synchrony that mirrored the cortical response. An integrate-and-fire model using experimentally measured thalamic input reproduced the observed transformations. The results here suggest a shift in coding strategy with adaptation that directly controls information relayed to cortex, which could have implications for encoding velocity signatures of textures.

Transient and steady-state dynamics of cortical adaptation.

Adaptation is a ubiquitous property of all sensory pathways of the brain and thus likely critical in the encoding of behaviorally relevant sensory information. Despite evidence identifying specific biophysical mechanisms contributing to sensory adaptation, its functional role in sensory encoding is not well understood, particularly in the natural environment where transient rather than steady-state activity could dominate the neuronal representation. Here, we show that the heterogeneous transient and steady-state adaptation dynamics of single cortical neurons in the rat vibrissa system were well characterized by an underlying state variable. The state was directly predictable from temporal response properties that capture the time course of postexcitatory suppression following an isolated vibrissa deflection. Altering the initial state, by preceding the periodic stimulus with an additional vibrissa deflection, strongly influenced single-cell transient cortical adaptation responses. Despite the different transient activity, neurons reached the same steady-state adapted response with a time to steady state that was independent of the initial state. However, the differences in transient activity observed on small time scales were not present when activity was integrated over the longer time scale of a stimulus cycle. Taken together, the results here demonstrate that although adaptation can have significant effects on transient neuronal activity and direction selectivity, a simple measure of the time course of suppression following an isolated stimulus predicted a large portion of the observed adaptation dynamics.

Nonlinear encoding of tactile patterns in the barrel cortex.

Cells in the rodent barrel cortex respond to vibrissa deflection with a brief excitatory component and a longer suppressive component. The response to a given deflection is thus scaled because of suppression induced by a preceding deflection, causing the neuronal response to be linked to the temporal properties of the peripheral stimulus. A paired-deflection stimulus was used to characterize the postexcitatory suppression and a 3-deflection stimulus was used to investigate the nonlinear response to patterns of whisker deflections in barbiturate-anesthetized Sprague-Dawley rats. The postexcitatory suppression was not dependent on a sensory-evoked action potential to the first deflection, implying that it is likely a subthreshold property of the network. The suppression induced by a deflection served to suppress both the excitatory and suppressive components of a subsequent neuronal response, thus effectively disinhibiting it. Two different response properties were observed in the recorded cells. Approximately 65% responded to a vibrissa deflection with an excitatory component followed by a suppressive component and 35% responded with excitation, suppression, and a subsequent rebound in excitation. Based on these observations of postexcitatory dynamics, a prediction method was used to estimate neuronal responses to more complex stimulus trains. Using the 2nd-order representation obtained from the paired-deflection stimulus, responses to general periodic deflection patterns were well predicted. A higher cutoff frequency was predicted for rebound cells compared with cells not exhibiting rebound excitation, consistent with experimental observations. The method also predicted the response of neurons to a random aperiodic deflection pattern. Therefore the temporal structure of cortical dynamics after a single deflection dictates the response to complex temporal patterns, which are more representative of stimuli encountered under natural conditions.

A point process analysis of sensory encoding.

Nowhere is the sparse nature of neuronal coding more evident than in the sensory cortex, where neuronal response becomes increasingly tuned to specific features of the sensory environment. For such situations, where rate modulation schemes do not accurately describe the neuronal response to sensory stimuli, statistical descriptions based on point process events are particularly appropriate. Here, intensity measures derived from experimental data in the rat somatosensory cortex enable the direct analysis of statistical structure within spike trains, as well as inter-relationships between tactile stimuli and neuronal response. Intensity measures capture structure in spontaneous as well as driven activity, reflecting the interplay between excitatory and suppressive influences on neuronal firing. Second-order intensity estimates reveal strong dependencies upon patterns of tactile stimulation, which define the neuronal response characteristics to temporally structured stimuli.