Abstract
The tuning, binaural properties, and encoding characteristics of neurons in the central nucleus of the inferior colliculus (CNIC) were investigated to shed light on nonlinearities in the responses of these neurons. Results were analyzed for three types of neurons (I, O, and V) in the CNIC of decerebrate cats. Rate responses to binaural stimuli were characterized using a 1st- plus 2nd-order spectral integration model. Parameters of the model were derived using broadband stimuli with random spectral shapes (RSS). This method revealed four characteristics of CNIC neurons: (1) Tuning curves derived from broadband stimuli have fixed (i. e., level tolerant) bandwidths across a 50–60 dB range of sound levels; (2) 1st-order contralateral weights (particularly for type I and O neurons) were usually larger in magnitude than corresponding ipsilateral weights; (3) contralateral weights were more important than ipsilateral weights when using the model to predict responses to untrained noise stimuli; and (4) 2nd-order weight functions demonstrate frequency selectivity different from that of 1st-order weight functions. Furthermore, while the inclusion of 2nd-order terms in the model usually improved response predictions related to untrained RSS stimuli, they had limited impact on predictions related to other forms of filtered broadband noise [e. g., virtual-space stimuli (VS)]. The accuracy of the predictions varied considerably by response type. Predictions were most accurate for I neurons, and less accurate for O and V neurons, except at the lowest stimulus levels. These differences in prediction performance support the idea that type I, O, and V neurons encode different aspects of the stimulus: while type I neurons are most capable of producing linear representations of spectral shape, type O and V neurons may encode spectral features or temporal stimulus properties in a manner not easily explained with the low-order model. Supported by NIH grant DC00115.
Highlights
The central nucleus of the inferior colliculus (CNIC) is an important site of convergence in the auditory system (Adams, 1979; Brunso-Bechtold et al, 1981; Winer, 2005)
Data presented in this paper are from neurons for which complete tone and random spectral shapes (RSS) responses were obtained across a range of sound levels
THE WEIGHT-FUNCTION MODEL Unlike spectro-temporal receptive field (STRF), weight-function maps computed in this study do not describe the temporal selectivity of CNIC neurons
Summary
The central nucleus of the inferior colliculus (CNIC) is an important site of convergence in the auditory system (Adams, 1979; Brunso-Bechtold et al, 1981; Winer, 2005). Despite the diversity of inputs, the cellular organization of CNIC is relatively homogeneous, with only a small number of morphological cell types that are not gathered into subnuclei or into an organized microstructure (Oliver and Morest, 1984; Malmierca et al, 1993; Ito and Oliver, 2012; Wallace et al, 2012). The lack of distinct morphological cell types and organized microstructure suggests that progress on the representation of sound in the CNIC will depend on physiologically defined neuron classes. One basis for such classes is the pattern of frequency selectivity of CNIC neurons in response to tones (Davis, 2005). Because tone responses typically do not accurately predict selectivity for broadband or natural stimuli (Nelken et al, 1997; Holmstrom et al, 2007; May et al, 2008), it seems important to derive models of spectral integration on the basis of responses to broadband stimuli
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