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Updated: Sep 27, 2026

Stereotactically-guided Ablation of the Rat Auditory Cortex, and Localization of the Lesion in the Brain
Published on: October 11, 2017
Directional sensitivity of neurons in the primary auditory (AI) cortex: effects of sound-source intensity level
Richard A Reale1, Rick L Jenison, John F Brugge
1Department of Physiology, Waisman Center, University of Wisconsin, Madison, Wisconsin 53711, USA. reale@physiology.wisc.edu
Abstract:
Transient sounds were delivered from different directions in virtual acoustic space while recording from single neurons in primary auditory cortex (AI) of cats under general anesthesia. The intensity level of the sound source was varied parametrically to determine the operating characteristics of the spatial receptive field. The spatial receptive field was constructed from the onset latency of the response to a sound at each sampled direction. Spatial gradients of response latency composing a receptive field are due partially to a systematic co-dependence on sound-source direction and intensity level. Typically, at any given intensity level, the distribution of response latency within the receptive field was unimodal with a range of approximately 3-4 ms, although for some cells and some levels, the spread could be as much as 20 or as little as 2 ms. Response latency, averaged across directions, differed among neurons for the same intensity level, and also differed among intensity levels for the same neuron. Generally, increases in intensity level resulted in decreases in the mean and variance, which follows an inverse Gaussian distribution. Receptive field models, based on response latency, are developed using multiple parameters (azimuth, elevation, intensity), validated with Monte Carlo simulation, and their spatial filtering described using spherical harmonic analysis. Observations from an ensemble of modeled receptive fields are obtained by linking the inverse Gaussian density to the probabilistic inverse problem of estimating sound-source direction and intensity. Upper bounds on acuity is derived from the ensemble using Fisher information, and the predicted patterns of estimation errors are related to psychophysical performance.
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