title: Adaptation in multisensory neurons: impact on cross-modal enhancement.
abstract: Adaptation is a ubiquitous property of sensory neurons. Multisensory neurons, receiving convergent input from different sensory modalities, also likely exhibit adaptation. The responses of multisensory superior colliculus neurons have been extensively studied, but the impact of adaptation on these responses has not been examined. Multisensory neurons in the superior colliculus exhibit cross-modal enhancement, an often non-linear and non-additive increase in response when a stimulus in one modality is paired with a stimulus in a different modality. We examine the possible impact of adaptation on cross-modal enhancement within the framework of a simple model of adaptation for a neuron employing a saturating, logistic response function. We consider how adaptation to an input's mean and standard deviation affects cross-modal enhancement, and also how the statistical correlations between two different modalities influence cross-modal enhancement. We determine the optimal bimodal stimuli to present a bimodal neuron that evoke the largest changes in cross-modal enhancement under adaptation to input statistics. The model requires separate gains for each modality, unless the statistics specific to each modality have been standardised by prior adaptation in earlier, unisensory neurons. The model also predicts that increasing the correlation coefficient between two modalities reduces a multisensory neuron's overall gain.
authors.affiliation: Department of Electronics and Computer Science, University of Southampton, Highfield, Southampton, SO17 1BJ, UK. te@ecs.soton.ac.uk
authors.forename: Terry
authors.initials: T
authors.lastname: Elliott
authors.forename: Xutao
authors.initials: X
authors.lastname: Kuang
authors.forename: Nigel R
authors.initials: NR
authors.lastname: Shadbolt
authors.forename: Klaus-Peter
authors.initials: KP
authors.lastname: Zauner
mesh_terms: D000222:Adaptation, Physiological / Q000502:physiology*; D000818:Animals; D008959:Models, Neurological; D016571:Neural Networks, Computer; D012677:Sensation; D011984:Sensory Receptor Cells / Q000502:physiology*; D013477:Superior Colliculi / Q000166:cytology