Dataset Information

Impaired Processing in the Primary Auditory Cortex of an Animal Model of Autism.

ABSTRACT: Autism is a neurodevelopmental disorder clinically characterized by deficits in communication, lack of social interaction and repetitive behaviors with restricted interests. A number of studies have reported that sensory perception abnormalities are common in autistic individuals and might contribute to the complex behavioral symptoms of the disorder. In this context, hearing incongruence is particularly prevalent. Considering that some of this abnormal processing might stem from the unbalance of inhibitory and excitatory drives in brain circuitries, we used an animal model of autism induced by valproic acid (VPA) during pregnancy in order to investigate the tonotopic organization of the primary auditory cortex (AI) and its local inhibitory circuitry. Our results show that VPA rats have distorted primary auditory maps with over-representation of high frequencies, broadly tuned receptive fields and higher sound intensity thresholds as compared to controls. However, we did not detect differences in the number of parvalbumin-positive interneurons in AI of VPA and control rats. Altogether our findings show that neurophysiological impairments of hearing perception in this autism model occur independently of alterations in the number of parvalbumin-expressing interneurons. These data support the notion that fine circuit alterations, rather than gross cellular modification, could lead to neurophysiological changes in the autistic brain.

SUBMITTER: Anomal RF

PROVIDER: S-EPMC4644803 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Publications

Impaired Processing in the Primary Auditory Cortex of an Animal Model of Autism.

Anomal Renata Figueiredo RF de Villers-Sidani Etienne E Brandão Juliana Alves JA Diniz Rebecca R Costa Marcos R MR Romcy-Pereira Rodrigo N RN

Frontiers in systems neuroscience 20151116

Autism is a neurodevelopmental disorder clinically characterized by deficits in communication, lack of social interaction and repetitive behaviors with restricted interests. A number of studies have reported that sensory perception abnormalities are common in autistic individuals and might contribute to the complex behavioral symptoms of the disorder. In this context, hearing incongruence is particularly prevalent. Considering that some of this abnormal processing might stem from the unbalance o ...[more]

PMID: 26635548

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Project description:Neural processing of sounds in the dorsal and ventral streams of the (human) auditory cortex is optimized for analyzing fine-grained temporal and spectral information, respectively. Here we use a Wilson and Cowan firing-rate modeling framework to simulate spectro-temporal processing of sounds in these auditory streams and to investigate the link between neural population activity and behavioral results of psychoacoustic experiments. The proposed model consisted of two core (A1 and R, representing primary areas) and two belt (Slow and Fast, representing rostral and caudal processing respectively) areas, differing in terms of their spectral and temporal response properties. First, we simulated the responses to amplitude modulated (AM) noise and tones. In agreement with electrophysiological results, we observed an area-dependent transition from a temporal (synchronization) to a rate code when moving from low to high modulation rates. Simulated neural responses in a task of amplitude modulation detection suggested that thresholds derived from population responses in core areas closely resembled those of psychoacoustic experiments in human listeners. For tones, simulated modulation threshold functions were found to be dependent on the carrier frequency. Second, we simulated the responses to complex tones with missing fundamental stimuli and found that synchronization of responses in the Fast area accurately encoded pitch, with the strength of synchronization depending on number and order of harmonic components. Finally, using speech stimuli, we showed that the spectral and temporal structure of the speech was reflected in parallel by the modeled areas. The analyses highlighted that the Slow stream coded with high spectral precision the aspects of the speech signal characterized by slow temporal changes (e.g., prosody), while the Fast stream encoded primarily the faster changes (e.g., phonemes, consonants, temporal pitch). Interestingly, the pitch of a speaker was encoded both spatially (i.e., tonotopically) in Slow area and temporally in Fast area. Overall, performed simulations showed that the model is valuable for generating hypotheses on how the different cortical areas/streams may contribute toward behaviorally relevant aspects of auditory processing. The model can be used in combination with physiological models of neurovascular coupling to generate predictions for human functional MRI experiments.

Project description:Neurons in sensory areas of neocortex exhibit responses tuned to specific features of the environment. In visual cortex, information about features such as edges or textures with particular orientations must be integrated to recognize a visual scene or object. Connectivity studies in rodent cortex have revealed that neurons make specific connections within sub-networks sharing common input tuning. In principle, this sub-network architecture enables local cortical circuits to integrate sensory information. However, whether feature integration indeed occurs locally in rodent primary sensory areas has not been examined directly. We studied local integration of sensory features in primary visual cortex (V1) of the mouse by presenting drifting grating and plaid stimuli, while recording the activity of neuronal populations with two-photon calcium imaging. Using a Bayesian model-based analysis framework, we classified single-cell responses as being selective for either individual grating components or for moving plaid patterns. Rather than relying on trial-averaged responses, our model-based framework takes into account single-trial responses and can easily be extended to consider any number of arbitrary predictive models. Our analysis method was able to successfully classify significantly more responses than traditional partial correlation (PC) analysis, and provides a rigorous statistical framework to rank any number of models and reject poorly performing models. We also found a large proportion of cells that respond strongly to only one stimulus class. In addition, a quarter of selectively responding neurons had more complex responses that could not be explained by any simple integration model. Our results show that a broad range of pattern integration processes already take place at the level of V1. This diversity of integration is consistent with processing of visual inputs by local sub-networks within V1 that are tuned to combinations of sensory features.

Dataset Information

Impaired Processing in the Primary Auditory Cortex of an Animal Model of Autism.

Publications

Impaired Processing in the Primary Auditory Cortex of an Animal Model of Autism.

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