Search

An important question in auditory neuroscience concerns how the neural representation of sound features changes from the periphery to the cortex. Here we focused on the encoding of sound onsets and we used a modeling approach to explore the degree to which auditory cortical neurons follow a similar envelope integration mechanism found at the auditory periphery. Our "forward" model was able to predict relatively accurately the timing of first spikes evoked by natural communication calls in the auditory cortex of awake, head-restrained mice, but only for a subset of cortical neurons. These neurons were systematically different in their encoding of the calls, exhibiting less call selectivity, shorter latency, greater precision, and more transient spiking compared with the same factors of their poorly predicted counterparts. Importantly, neurons that fell into this best-predicted group all had thin spike waveforms, suggestive of suspected interneurons conveying feedforward inhibition. Indeed, our population of call-excited thin spike neurons had significantly higher spontaneous rates and larger frequency tuning bandwidths than those of thick spike neurons. Thus the fidelity of our model's first spike predictions segregated neurons into one earlier responding subset, potentially dominated by suspected interneurons, which preserved a peripheral mechanism for encoding sound onsets and another longer latency subset that reflected higher, likely centrally constructed nonlinearities. These results therefore provide support for the hypothesis that physiologically distinct subclasses of neurons in the auditory cortex may contribute hierarchically to the representation of natural stimuli.

The mouse is a promising model system for auditory cortex research because of the powerful genetic tools available for manipulating its neural circuitry. Previous studies have identified two tonotopic auditory areas in the mouse-primary auditory cortex (AI) and anterior auditory field (AAF)- but auditory receptive fields in these areas have not yet been described. To establish a foundation for investigating auditory cortical circuitry and plasticity in the mouse, we characterized receptive-field structure in AI and AAF of anesthetized mice using spectrally complex and temporally dynamic stimuli as well as simple tonal stimuli. Spectrotemporal receptive fields (STRFs) were derived from extracellularly recorded responses to complex stimuli, and frequency-intensity tuning curves were constructed from responses to simple tonal stimuli. Both analyses revealed temporal differences between AI and AAF responses: peak latencies and receptive-field durations for STRFs and first-spike latencies for responses to tone bursts were significantly longer in AI than in AAF. Spectral properties of AI and AAF receptive fields were more similar, although STRF bandwidths were slightly broader in AI than in AAF. Finally, in both AI and AAF, a substantial minority of STRFs were spectrotemporally inseparable. The spectrotemporal interaction typically appeared in the form of clearly disjoint excitatory and inhibitory subfields or an obvious spectrotemporal slant in the STRF. These data provide the first detailed description of auditory receptive fields in the mouse and suggest that although neurons in areas AI and AAF share many response characteristics, area AAF may be specialized for faster temporal processing.

A central theme in neural coding concerns the role of response variability and noise in determining the information transmission of neurons. This issue was investigated in single cells of the lateral geniculate nucleus of barbiturate-anesthetized cats by quantifying the degree of precision in and the information transmission properties of individual spike train responses to full field, binary (bright or dark), flashing stimuli. We found that neuronal responses could be highly reproducible in their spike timing (approximately 1-2 ms standard deviation) and spike count (approximately 0.3 ratio of variance/mean, compared with 1.0 expected for a Poisson process). This degree of precision only became apparent when an adequate length of the stimulus sequence was specified to determine the neural response, emphasizing that the variables relevant to a cell's response must be controlled to observe the cell's intrinsic response precision. Responses could carry as much as 3.5 bits/spike of information about the stimulus, a rate that was within a factor of two of the limit the spike train could transmit. Moreover, there appeared to be little sign of redundancy in coding: on average, longer response sequences carried at least as much information about the stimulus as would be obtained by adding together the information carried by shorter response sequences considered independently. There also was no direct evidence found for synergy between response sequences. These results could largely, but not entirely, be explained by a simple model of the response in which one filters the stimulus by the cell's impulse response kernel, thresholds the result at a fairly high level, and incorporates a postspike refractory period.