Sharad J. Shanbhag

Processing of communication calls in Guinea pig auditory cortex.

Vocal communication is an important aspect of guinea pig behaviour and a large contributor to their acoustic environment. We postulated that some cortical areas have distinctive roles in processing conspecific calls. In order to test this hypothesis we presented exemplars from all ten of their main adult vocalizations to urethane anesthetised animals while recording from each of the eight areas of the auditory cortex. We demonstrate that the primary area (AI) and three adjacent auditory belt areas contain many units that give isomorphic responses to vocalizations. These are the ventrorostral belt (VRB), the transitional belt area (T) that is ventral to AI and the small area (area S) that is rostral to AI. Area VRB has a denser representation of cells that are better at discriminating among calls by using either a rate code or a temporal code than any other area. Furthermore, 10% of VRB cells responded to communication calls but did not respond to stimuli such as clicks, broadband noise or pure tones. Area S has a sparse distribution of call responsive cells that showed excellent temporal locking, 31% of which selectively responded to a single call. AI responded well to all vocalizations and was much more responsive to vocalizations than the adjacent dorsocaudal core area. Areas VRB, AI and S contained units with the highest levels of mutual information about call stimuli. Area T also responded well to some calls but seems to be specialized for low sound levels. The two dorsal belt areas are comparatively unresponsive to vocalizations and contain little information about the calls. AI projects to areas S, VRB and T, so there may be both rostral and ventral pathways for processing vocalizations in the guinea pig.

A novel coding mechanism for social vocalizations in the lateral amygdala

The amygdala plays a central role in evaluating the significance of acoustic signals and coordinating the appropriate behavioral responses. To understand how amygdalar responses modulate auditory processing and drive emotional expression, we assessed how neurons respond to and encode information that is carried within complex acoustic stimuli. We characterized responses of single neurons in the lateral nucleus of the amygdala to social vocalizations and synthetic acoustic stimuli in awake big brown bats. Neurons typically responded to most of the social vocalizations presented (mean = nine of 11 vocalizations) but differentially modulated both firing rate and response duration. Surprisingly, response duration provided substantially more information about vocalizations than did spike rate. In most neurons, variation in response duration depended, in part, on persistent excitatory discharge that extended beyond stimulus duration. Information in persistent firing duration was significantly greater than in spike rate, and the majority of neurons displayed more information in persistent firing, which was more likely to be observed in response to aggressive vocalizations (64%) than appeasement vocalizations (25%), suggesting that persistent firing may relate to the behavioral context of vocalizations. These findings suggest that the amygdala uses a novel coding strategy for discriminating among vocalizations and underscore the importance of persistent firing in the general functioning of the amygdala.

Auditory Spatial Tuning at the Crossroads of the Midbrain and Forebrain

The barn owls midbrain and forebrain contain neurons tuned to sound direction. The spatial receptive fields of these neurons result from sensitivity to combinations of interaural time (ITD) and level (ILD) differences over a broad frequency range. While a map of auditory space has been described in the midbrain, no similar topographic representation has been found in the forebrain. The first nuclei that belong exclusively to the forebrain and midbrain pathways are the thalamic nucleus ovoidalis (Ov) and the external nucleus of the inferior colliculus (ICx), respectively. The midbrain projects to the auditory thalamus before sharp spatial receptive fields emerge; although Ov and ICx receive projections from the same midbrain nuclei, they are not directly connected. We compared the spatial tuning in Ov and ICx. Thalamic neurons respond to a broader frequency range and their ITD and ILD tuning varied more across frequency. However, neurons in Ov showed spatial receptive fields as selective as neurons in ICx. Thalamic spatial receptive fields were tuned to frontal and contralateral space and correlated with their tuning to ITD and ILD. Our results indicate that spatial tuning emerges in both pathways by similar combination selectivity to ITD and ILD. However, the midbrain and the thalamus do not appear to repeat exactly the same processing, as indicated by the difference in frequency range and the broader tuning to binaural cues. The differences observed at the initial stages of these sound-localization pathways may reflect diverse functions and coding schemes of midbrain and forebrain.

Population-wide bias of surround suppression in auditory spatial receptive fields of the owl’s midbrain

The physical arrangement of receptive fields (RFs) within neural structures is important for local computations. Nonuniform distribution of tuning within populations of neurons can influence emergent tuning properties, causing bias in local processing. This issue was studied in the auditory system of barn owls. The owls external nucleus of the inferior colliculus (ICx) contains a map of auditory space in which the frontal region is overrepresented. We measured spatiotemporal RFs of ICx neurons using spatial white noise. We found a population-wide bias in surround suppression such that suppression from frontal space was stronger. This asymmetry increased with laterality in spatial tuning. The bias could be explained by a model of lateral inhibition based on the overrepresentation of frontal space observed in ICx. The model predicted trends in surround suppression across ICx that matched the data. Thus, the uneven distribution of spatial tuning within the map could explain the topography of time-dependent tuning properties. This mechanism may have significant implications for the analysis of natural scenes by sensory systems.