Effects of spectral and temporal disruption on cortical encoding of gerbil vocalizations.

Animal communication sounds contain spectrotemporal fluctuations that provide powerful cues for detection and discrimination. Human perception of speech is influenced both by spectral and temporal acoustic features but is most critically dependent on envelope information. To investigate the neural coding principles underlying the perception of communication sounds, we explored the effect of disrupting the spectral or temporal content of five different gerbil call types on neural responses in the awake gerbil's primary auditory cortex (AI). The vocalizations were impoverished spectrally by reduction to 4 or 16 channels of band-passed noise. For this acoustic manipulation, an average firing rate of the neuron did not carry sufficient information to distinguish between call types. In contrast, the discharge patterns of individual AI neurons reliably categorized vocalizations composed of only four spectral bands with the appropriate natural token. The pooled responses of small populations of AI cells classified spectrally disrupted and natural calls with an accuracy that paralleled human performance on an analogous speech task. To assess whether discharge pattern was robust to temporal perturbations of an individual call, vocalizations were disrupted by time-reversing segments of variable duration. For this acoustic manipulation, cortical neurons were relatively insensitive to short reversal lengths. Consistent with human perception of speech, these results indicate that the stable representation of communication sounds in AI is more dependent on sensitivity to slow temporal envelopes than on spectral detail.

Transformation of temporal properties between auditory midbrain and cortex in the awake Mongolian gerbil.

The neural representation of meaningful stimulus features is thought to rely on precise discharge characteristics of the auditory cortex. Precisely timed onset spikes putatively carry the majority of stimulus-related information in auditory cortical neurons but make a small contribution to stimulus representation in the auditory midbrain. Because these conclusions derive primarily from anesthetized preparations, we reexamined temporal coding properties of single neurons in the awake gerbil inferior colliculus (IC) and compared them with primary auditory cortex (AI). Surprisingly, AI neurons displayed a reduction of temporal precision compared with those in the IC. Furthermore, this hierarchical transition from high to low temporal fidelity was observed for both static and dynamic stimuli. Because most of the data that support temporal precision were obtained under anesthesia, we also reexamined response properties of IC and AI neurons under these conditions. Our results show that anesthesia has profound effects on the trial-to-trial variability and reliability of discharge and significantly improves the temporal precision of AI neurons to both tones and amplitude-modulated stimuli. In contrast, IC temporal properties are only mildly affected by anesthesia. These results underscore the pitfalls of using anesthetized preparations to study temporal coding. Our findings in awake animals reveal that AI neurons combine faster adaptation kinetics and a longer temporal window than evident in IC to represent ongoing acoustic stimuli.

Computational estimation of the distribution of L-type Ca(2+) channels in motoneurons based on variable threshold of activation of persistent inward currents.

In the presence of neuromodulators such as serotonin and noradrenaline, motoneurons exhibit persistent inward currents (PICs) that serve to amplify synaptic inputs. A major component of these PICs is mediated by L-type Ca(2+) channels. Estimates based on electrophysiological studies indicate that these channels are located on the dendrites, but immunohistochemical studies of their precise distribution have yielded different results. Our goal was to determine the distribution of these channels using computational methods. A theoretical analysis of the activation of PICs by a somatic current injection in the absence or presence of synaptic activity suggests that L-type Ca(2+) channels may be segregated to discrete hot spots 25-200 microm long and centered 100-400 microm from the soma in the dendritic tree. Compartmental models based on detailed anatomical measurements of the structure of feline neck motoneurons with L-type Ca(2+) channels incorporated in these regions produced plateau potentials resulting from PIC activation. Furthermore, we replicated the experimental observation that the somatic threshold at which PICs were activated was depolarized by tonic activation of inhibitory synapses and hyperpolarized by tonic activation of excitatory synapses. Models with L-type Ca(2+) channels distributed uniformly were unable to replicate the change in somatic threshold of PIC activation. Therefore we conclude that the set of L-type Ca(2+) channels mediating plateau potentials is restricted to discrete regions in the dendritic tree. Furthermore, this distribution leads to the compartmentalization of the dendritic tree of motoneurons into subunits whose sequential activation lead to the graded amplification of synaptic inputs.