A Biophysical Neural Model To Describe Spatial Visual Attention
- Department of Physics, SUNY at Buffalo, Buffalo, NY 14260 (United States)
- Department of Physics and Department of Physiology and Biophysics, SUNY at Buffalo, Buffalo, NY 14260 (United States)
Visual scenes have enormous spatial and temporal information that are transduced into neural spike trains. Psychophysical experiments indicate that only a small portion of a spatial image is consciously accessible. Electrophysiological experiments in behaving monkeys have revealed a number of modulations of the neural activity in special visual area known as V4, when the animal is paying attention directly towards a particular stimulus location. The nature of the attentional input to V4, however, remains unknown as well as to the mechanisms responsible for these modulations. We use a biophysical neural network model of V4 to address these issues. We first constrain our model to reproduce the experimental results obtained for different external stimulus configurations and without paying attention. To reproduce the known neuronal response variability, we found that the neurons should receive about equal, or balanced, levels of excitatory and inhibitory inputs and whose levels are high as they are in in vivo conditions. Next we consider attentional inputs that can induce and reproduce the observed spiking modulations. We also elucidate the role played by the neural network to generate these modulations.
- OSTI ID:
- 21055236
- Journal Information:
- AIP Conference Proceedings, Vol. 978, Issue 1; Conference: 3. Mexican meeting on mathematical and experimental physics, Mexico City (Mexico), 10-14 Sep 2007; Other Information: DOI: 10.1063/1.2891410; (c) 2008 American Institute of Physics; Country of input: International Atomic Energy Agency (IAEA); ISSN 0094-243X
- Country of Publication:
- United States
- Language:
- English
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