Cerebral Cortex Advance Access published online on May 13, 2004
Cerebral Cortex, doi:10.1093/cercor/bhh079
© 2004 by Oxford University Press
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
1 The Neurosciences Institute, 10640 John Jay Hopkins Drive, San Diego, CA 92121, USA
* To whom correspondence should be addressed. E-mail: seth{at}nsi.edu.
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 VIII's 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. Key Words:
brain-based device, Darwin VIII, reentrant connectivity, visual binding, visual object recognition
Article
Visual Binding Through Reentrant Connectivity and Dynamic Synchronization in a Brain-based Device
Abstract 
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  A. K. Seth and G. M. Edelman Distinguishing causal interactions in neural populations. Neural Comput., April 1, 2007; 19(4): 910 - 933. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. K. Seth, E. Izhikevich, G. N. Reeke, and G. M. Edelman Theories and measures of consciousness: An extended framework PNAS, July 11, 2006; 103(28): 10799 - 10804. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. L. McKinstry, G. M. Edelman, and J. L. Krichmar A cerebellar model for predictive motor control tested in a brain-based device PNAS, February 28, 2006; 103(9): 3387 - 3392. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. L. Krichmar, D. A. Nitz, J. A. Gally, and G. M. Edelman Characterizing functional hippocampal pathways in a brain-based device as it solves a spatial memory task PNAS, February 8, 2005; 102(6): 2111 - 2116. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
E. M. Izhikevich Polychronization: Computation with Spikes Neural Comput., February 1, 2005; 18(2): 245 - 282. [Abstract] [Full Text] [PDF]
|
|