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J Neurophysiol 92: 444-457, 2004. First published March 10, 2004; doi:10.1152/jn.01173.2003
0022-3077/04 $5.00
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01173.2003v1
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Modular Functional Organization of Cat Anterior Auditory Field

Kazuo Imaizumi1, Nicholas J. Priebe1,2, Poppy A. C. Crum1, Purvis H. Bedenbaugh1,3, Steven W. Cheung1 and Christoph E. Schreiner1

1Coleman Memorial Laboratory, W.M. Keck Center for Integrative Neuroscience, Department of Otolaryngology, University of California, San Francisco, California 94143-0732; 2Department of Neurobiology and Physiology, Northwestern University, Evanston, Illinois 60208; and 3Departments of Neuroscience and Otolaryngology, University of Florida Brain Institute, Gainesville, Florida 32610-0244

Submitted 8 December 2003; accepted in final form 8 March 2004

Two tonotopic areas, the primary auditory cortex (AI) and the anterior auditory field (AAF), are the primary cortical fields in the cat auditory system. They receive largely independent, concurrent thalamocortical projections from the different thalamic divisions despite their hierarchical equivalency. The parallel streams of thalamic inputs to AAF and AI suggest that AAF neurons may differ from AI neurons in physiological properties. Although a modular functional organization in cat AI has been well documented, little is known about the internal organization of AAF beyond tonotopy. We studied how basic receptive field parameters (RFPs) are spatially organized in AAF with single- and multiunit recording techniques. A distorted tonotopicity with an underrepresentation in midfrequencies (1 and 5 kHz) and an overrepresentation in the high-frequency range was found. Spectral bandwidth (Q-values) and response threshold were significantly correlated with characteristic frequency (CF). To understand whether AAF has a modular organization of RFPs, CF dependencies were eliminated by a nonparametric, local regression model, and the residuals (difference between the model and observed values) were evaluated. In a given isofrequency domain, clusters of low or high residual RFP values were interleaved for threshold, spectral bandwidth, and latency, suggesting a modular organization. However, RFP modules in AAF were not expressed as robustly as in AI. A comparison of RFPs between AAF and AI shows that AAF neurons were more broadly tuned and had shorter latencies than AI neurons. These physiological field differences are consistent with anatomical evidence of largely independent, concurrent thalamocortical projections in AI and AAF, which strongly suggest field-specific processing.


Address for reprint requests and other correspondence: K. Imaizumi, W.M. Keck Center for Integrative Neuroscience, University of California at San Francisco, 513 Parnassus Ave., Box 0732, San Francisco, CA 94143-0732 (E-mail: kazuo{at}phy.ucsf.edu).




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