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It is well known that auditory nerve (AN) fibers overcome bandwidth limitations through the volley principle, a form of multiplexing. What is less well known is that the volley principle introduces a degree of unpredictability into AN neural firing patterns that may be affecting even simple stimulus categorization learning. We use a physiologically grounded, unsupervised spiking neural network model of the auditory brain with spike time dependent plasticity learning to demonstrate that plastic auditory cortex is unable to learn even simple auditory object categories when exposed to the raw AN firing input without subcortical preprocessing. We then demonstrate the importance of nonplastic subcortical preprocessing within the cochlear nucleus and the inferior colliculus for stabilizing and denoising AN responses. Such preprocessing enables the plastic auditory cortex to learn efficient robust representations of the auditory object categories. The biological realism of our model makes it suitable for generating neurophysiologically testable hypotheses.

Original publication




Journal article


Neural Comput

Publication Date





1801 - 1829


Action Potentials, Animals, Auditory Pathways, Cochlear Nerve, Cochlear Nucleus, Computer Simulation, Haplorhini, Humans, Inferior Colliculi, Learning, Models, Neurological, Neural Networks, Computer, Neuronal Plasticity, Neurons, Pattern Recognition, Physiological, Rats, Synapses, Time Factors