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Abstract:
Multisensory response enhancement (MRE) is the augmentation of
the response of a neuron to sensory input of one modality by
simultaneous input from another modality. The maximum likelihood
(ML) model presented here modifies the Bayesian model for MRE
(Anastasio et al.) by incorporating a decision strategy to
maximize the number of correct decisions. Thus the ML model can
also deal with the important tasks of stimulus discrimination and
identification in the presence of incongruent visual and auditory
cues. It accounts for the inverse effectiveness observed in
neurophysiological recording data, and it predicts a functional
relation between uni- and bimodal levels of discriminability that
is testable both in neurophysiological and behavioral
experiments.
References
Anastasio, T. J., P. E. Patton, and K. Belkacem-Boussaid
(2000). Using Bayes' rule to model multisensory enhancement in
the superior colliculus.
Neural Computation
, 12, 1165-1187.
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