Back to Search Start Over

Using Bayes' rule to model multisensory enhancement in the superior colliculus.

Authors :
Anastasio TJ
Patton PE
Belkacem-Boussaid K
Source :
Neural computation [Neural Comput] 2000 May; Vol. 12 (5), pp. 1165-87.
Publication Year :
2000

Abstract

The deep layers of the superior colliculus (SC) integrate multisensory inputs and initiate an orienting response toward the source of stimulation (target). Multisensory enhancement, which occurs in the deep SC, is the augmentation of a neural response to sensory input of one modality by input of another modality. Multisensory enhancement appears to underlie the behavioral observation that an animal is more likely to orient toward weak stimuli if a stimulus of one modality is paired with a stimulus of another modality. Yet not all deep SC neurons are multisensory. Those that are exhibit the property of inverse effectiveness: combinations of weaker unimodal responses produce larger amounts of enhancement. We show that these neurophysiological findings support the hypothesis that deep SC neurons use their sensory inputs to compute the probability that a target is present. We model multimodal sensory inputs to the deep SC as random variables and cast the computation function in terms of Bayes' rule. Our analysis suggests that multisensory deep SC neurons are those that combine unimodal inputs that would be more uncertain by themselves. It also suggests that inverse effectiveness results because the increase in target probability due to the integration of multisensory inputs is larger when the unimodal responses are weaker.

Details

Language :
English
ISSN :
0899-7667
Volume :
12
Issue :
5
Database :
MEDLINE
Journal :
Neural computation
Publication Type :
Academic Journal
Accession number :
10905812
Full Text :
https://doi.org/10.1162/089976600300015547