Simulating the Effects of Cortical Feedback in the Superior Colliculus with Topographic Maps
Pavlou, A and Casey, MC Simulating the Effects of Cortical Feedback in the Superior Colliculus with Topographic Maps In: International Joint Conference on Neural Networks (IJCNN) 2010, 2010-07-18 - 2010-07-23, Barcelona.
2010_pavlou_casey_simulating_cortical_feedback.pdf - Accepted Version
Available under License : See the attached licence file.
Plain Text (licence)
The superior colliculus (SC) is a neural structure found in mammalian brains that acts as a sensory hub through which visual, auditory and somatosensory inputs are integrated. This integration is used to orient the eye's fovea towards a prominent stimulus, independently of which sensory modality it was detected in. A recently observed aspect of this integration is that it is moderated by cortical feedback. As a key sensorimotor function integrating low-level sensory information moderated by the cortex, studying the SC may therefore enable us to understand how natural systems prioritize sensory computation in real-time, possibly as a result of task dependent feedback. In this paper, we focus on such a biological model. From a computational perspective, understanding this combination of bottom-up processing with top-down moderation in a model is therefore appealing. We present for the first time a behavioral model of the SC which combines the development of unisensory and multisensory representations with simulated cortical feedback. Our model demonstrates how unisensory maps can be aligned and integrated automatically into a multisensory representation. Results demonstrate that our model can capture the basic properties of the SC, and in particular they show the influence of the simulated cortical feedback on multisensory responses, reproducing the observed multisensory enhancement and suppression phenomena compared to biological studies. This suggests that our unified competitive learning approach may successfully be used to represent spatial processing that is moderated by task, and hence could be more widely applied to other, task dependent processing.
|Item Type:||Conference or Workshop Item (Paper)|
|Divisions :||Faculty of Engineering and Physical Sciences > Computing Science|
|Identification Number :||10.1109/IJCNN.2010.5596839|
|Related URLs :|
|Depositing User :||Symplectic Elements|
|Date Deposited :||17 Jun 2011 15:17|
|Last Modified :||08 Nov 2013 12:07|
Actions (login required)
Downloads per month over past year