Abstract
Spectro-temporal properties of auditory cortex neurons have been extensively studied with artificial sounds but it is still unclear whether they help in understanding neuronal responses to communication sounds. Here, we directly compared spectro-temporal receptive fields (STRFs) obtained from the same neurons using both artificial stimuli (dynamic moving ripples, DMRs) and natural stimuli (conspecific vocalizations) that were matched in terms of spectral content, average power and modulation spectrum. On a population of auditory cortex neurons exhibiting reliable tuning curves when tested with pure tones, significant STRFs were obtained for 62% of the cells with vocalizations and 68% with DMR. However, for many cells with significant vocalization-derived STRFs (STRFvoc) and DMR-derived STRFs (STRFdmr), the BF, latency, bandwidth and global STRFs shape differed more than what would be predicted by spiking responses simulated by a linear model based on a non-homogenous Poisson process. Moreover STRFvoc predicted neural responses to vocalizations more accurately than STRFdmr predicted neural response to DMRs, despite similar spike-timing reliability for both sets of stimuli. Cortical bursts, which potentially introduce nonlinearities in evoked responses, did not explain the differences between STRFvoc and STRFdmr. Altogether, these results suggest that the nonlinearity of auditory cortical responses makes it difficult to predict responses to communication sounds from STRFs computed from artificial stimuli.
Highlights
A major goal in auditory neuroscience is to characterize how communication sounds are represented in the auditory pathway, at the cortical level
A mapping of the cortical surface was made to confirm the location of AI: neuronal clusters were recorded with low impedance (,1 MV) electrodes until a progression from low to high frequency was observed in the caudo-rostral direction [31]
Performing the reverse analysis, we found that for 17/42 cells (44%), the STRFdmr was excitatory at the location where the STRFvoc was maximum, but for 21/42 (50%) of the cells, the STRFdmr was not significantly excitatory
Summary
A major goal in auditory neuroscience is to characterize how communication sounds are represented in the auditory pathway, at the cortical level. The spectro-temporal receptive field (STRF) is probably the most commonly used model to describe the way complex stimuli are processed by auditory cortex neurons. Due to the poor response elicited by white noise in the auditory cortex, families of synthetic stimuli have been preferred to characterize STRFs. Due to the poor response elicited by white noise in the auditory cortex, families of synthetic stimuli have been preferred to characterize STRFs These synthetic stimuli are commonly based on ripples (i.e. a sound modulated sinusoidally in the temporal and spectral domains: see [5,6,7,8,9,10,11]) or on random trains of pure tones [12,13,14,15,16]. More spectro-temporally complex than pure tones, these synthetic stimuli are still very different from conspecific vocalizations, both form the acoustical and the behavioral perspectives
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