Dynamic spectrotemporal feature selectivity in the auditory midbrain

J Neurosci. 2008 May 21;28(21):5412-21. doi: 10.1523/JNEUROSCI.0073-08.2008.


The transformation of auditory information from the cochlea to the cortex is a highly nonlinear process. Studies using tone stimuli have revealed that changes in even the most basic parameters of the auditory stimulus can alter neural response properties; for example, a change in stimulus intensity can cause a shift in a neuron's preferred frequency. However, it is not yet clear how such nonlinearities contribute to the processing of spectrotemporal features in complex sounds. Here, we use spectrotemporal receptive fields (STRFs) to characterize the effects of stimulus intensity on feature selectivity in the mammalian inferior colliculus (IC). At low intensities, we find that STRFs are relatively simple, typically consisting of a single excitatory region, indicating that the neural response is simply a reflection of the stimulus amplitude at the preferred frequency. In contrast, we find that STRFs at high intensities typically consist of a combination of an excitatory region and one or more inhibitory regions, often in a spectrotemporally inseparable arrangement, indicating selectivity for complex auditory features. We show that a linear-nonlinear model with the appropriate STRF can predict neural responses to stimuli with a fixed intensity, and we demonstrate that a simple extension of the model with an intensity-dependent STRF can predict responses to stimuli with varying intensity. These results illustrate the complexity of auditory feature selectivity in the IC, but also provide encouraging evidence that the prediction of nonlinear responses to complex stimuli is a tractable problem.

MeSH terms

  • Acoustic Stimulation / methods
  • Animals
  • Dose-Response Relationship, Radiation
  • Evoked Potentials, Auditory, Brain Stem / physiology*
  • Gerbillinae
  • Inferior Colliculi / cytology*
  • Models, Neurological*
  • Neurons / physiology*
  • Nonlinear Dynamics*
  • Predictive Value of Tests
  • Sound Spectrography