Auditory orienting: automatic detection of auditory change over brief intervals of time: a neural net model of evoked brain potentials

摘要

The human auditory system has a neurophysiological component, mismatch negativity (MMN), that automatically registers change over time of a variety of simple auditory features, e.g., loudness, pitch, duration, and spatial location. A neural network automatic auditory orienting (AAO-MMN) model which simulates the MMN response is described. The main assumption of the proposed AAO-MMN model is that the broad range characteristic of MMN is achieved by local inhibition of the nonlocal thalamic sources of distributed neural activation. The model represents this activation source by a single thalamic (T) unit that is always fully active. The second assumption is that the buildup of MMN over several repetitions of the standard stimulus is accomplished by a local cumulative activation function. All the local accumulator neurons inhibit the nonlocal, steady-state, thalamic activation represented by T.