Seth, A. K., McKinstry, J.L., Edelman, G. M. and Krichmar, J L. (2004) Visual binding through reentrant connectivity and dynamic synchronization in a brain-based device. Cerebral Cortex, 14 (11). pp. 1185-1199. ISSN 1047-3211

Full text not available from this repository.

Abstract

Effective visual object recognition requires mechanisms to bind object features (e.g. color, shape and motion) while distinguishing distinct objects. Synchronously active neuronal circuits among reentrantly connected cortical areas may provide a basis for visual binding. To assess the potential of this mechanism, we have constructed a mobile brain-based device, Darwin VIII, which is guided by simulated analogues of cortical and sub-cortical areas required for visual processing, decision-making, reward and motor responses. These simulated areas are reentrantly connected and each area contains neuronal units representing both the mean activity level and the relative timing of the activity of groups of neurons. Darwin VIII learns to discriminate among multiple objects with shared visual features and associates target; objects with innately preferred auditory cues. We observed the co-activation of globally distributed neuronal circuits that corresponded to distinct objects in Darwin VIIIs visual field. These circuits, which are constrained by a reentrant neuroanatomy and modulated by behavior and synaptic plasticity, are necessary for successful discrimination. By situating Darwin VIII in a rich real-world environment involving continual changes in the size and location of visual stimuli due to self-generated movement, and by recording its behavioral and neuronal responses in detail, we were able to show that reentrant connectivity and dynamic synchronization provide an effective mechanism for binding the features of visual objects.

Item Type:	Article
Additional Information:	Publisher's version available at official url
Schools and Departments:	School of Engineering and Informatics > Informatics
Subjects:	Q Science > QA Mathematics > QA0075 Electronic computers. Computer science
Depositing User:	Chris Keene
Date Deposited:	14 Aug 2007
Last Modified:	30 Sep 2019 13:17
URI:	http://sro.sussex.ac.uk/id/eprint/1518
Google Scholar:	52 Citations

📧 Request an update