A dynamic neural model of localization of brief successive stimuli in saltation

Hil Ge Meijer,Dieter Kleinböhl,Jörg Trojan,Jan R Buitenweg,Rupert Hölzl

doi:10.1186/1471-2202-10-s1-p350

Hil Ge Meijer, Dieter Kleinböhl + Show 3 more

Open Access

https://doi.org/10.1186/1471-2202-10-s1-p350

Copy DOI

Journal: BMC neuroscience	Publication Date: Jul 13, 2009
Citations: 4	License type: CC BY 2.0

Affiliation: University of Twente, University of Mannheim

Abstract

Somatosensory saltation is an illusion robustly generated using short tactile stimuli [1,2]. There is a perceived displacement of a first stimulus if followed by a subsequent nearby stimulus with a short stimulus onset asynchrony (SOA). Experimental reports suggest that this illusion results from spatiotemporal integration in early processing stages, but the exact neural mechanism is unknown. The neuronal mechanism involved is probably quite generic as similar phenomena occur in other modalities, audition for example [3].

Highlights

Somatosensory saltation is an illusion robustly generated using short tactile stimuli [1,2]
With suitable stimulus onset asynchrony (SOA) and interstimulus distance our model shows that both stimuli are spatially attracted towards each other, as observed in the saltation illusion
The range of SOAs is within the range well known from psychophysical experiments observing the saltation effect

Summary

Introduction

Somatosensory saltation is an illusion robustly generated using short tactile stimuli [1,2]. Experimental reports suggest that this illusion results from spatiotemporal integration in early processing stages, but the exact neural mechanism is unknown. We propose a dynamic neural field model [4] with multiple layers for localization of brief tactile stimuli. An input layer processes inputs using lateral inhibition. It sends feedforward connections to a representation layer. This layer slowly integrates incoming sensory information and computes the stored location, by means of lateral inhibition. Feedback connections project the model output onto a perceptual body map. Reported control of spatial attention is modeled as a bias in the receptive fields. We study how the stimulus propagates across levels in the network and how the representation of stimulus location is influenced by concurrent or successive inputs

Results

Discussion

Getzmann S