Abstract
Interaural time differences (ITDs) are the major cue for localizing low-frequency sounds. The activity of neuronal populations in the brainstem encodes ITDs with an exquisite temporal acuity of about . The response of single neurons, however, also changes with other stimulus properties like the spectral composition of sound. The influence of stimulus frequency is very different across neurons and thus it is unclear how ITDs are encoded independently of stimulus frequency by populations of neurons. Here we fitted a statistical model to single-cell rate responses of the dorsal nucleus of the lateral lemniscus. The model was used to evaluate the impact of single-cell response characteristics on the frequency-invariant mutual information between rate response and ITD. We found a rough correspondence between the measured cell characteristics and those predicted by computing mutual information. Furthermore, we studied two readout mechanisms, a linear classifier and a two-channel rate difference decoder. The latter turned out to be better suited to decode the population patterns obtained from the fitted model.
Highlights
The neuronal representation of the azimuthal position of a lowfrequency sound source has been extensively studied across many mammalian and avian species [1,2,3,4,5,6,7,8,9]
The following analyses are based on recordings from the dorsal nucleus of the lateral lemniscus (DNLL) of Mongolian gerbils (Meriones unguiculatus)
Responses of Interaural time differences (ITDs)-sensitive neurons in the DNLL of gerbils change with the frequency of a pure tone stimulus, similar to all other ITD sensitive neurons in the brainstem [25]
Summary
The neuronal representation of the azimuthal position of a lowfrequency sound source has been extensively studied across many mammalian and avian species [1,2,3,4,5,6,7,8,9]. There is general agreement that the stimulus parameter that carries most of this positional information is the interaural time difference (ITD), which is produced by the disparity of travelling times from the sound source to the two ears [10,11,12]. All quantitative coding theories have only considered ITD representations for stimuli with fixed spectral content [18,19,20]. Those theories showed that the psychophysical acuity can be explained by the rate statistics of the best single neurons. Taking into account additional stimulus dimensions complicates coding theories, because different activity patterns encode for the same ITD and the one-to-one relation between the firing rate of a single neuron and the stimulus ITD is lost
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