A neural network model of the functional neuroimaging data on perceptual grouping (CROSBI ID 619239)
Prilog sa skupa u zborniku | sažetak izlaganja sa skupa | međunarodna recenzija
Podaci o odgovornosti
Domijan, Dražen
engleski
A neural network model of the functional neuroimaging data on perceptual grouping
A neural network is proposed to explain how different patterns of brain activations arise in functional MRI during viewing of stimuli of various level of complexity. The model implements object-based selection by global inhibition applied to all background spatial locations and local excitation which enable activity spreading along the locations of the figure. It is assumed that excitatory neurotransmission along the dendritic trees provides a major contribution to the blood-oxygen-level-dependent (BOLD) signal. Computer simulations showed that increased perceptual complexity of the stimulus lead to the reduction of BOLD signal in V1. On the other hand, LOC exhibits opposite pattern with strongest BOLD activation for images with 3D interpretation. This pattern of activation is observed when there is no distractors present in the visual field. In the task of collinear contour grouping (with many distracting Gabor patches) both V1 and LOC showed elevated BOLD signal when perceptual group (contour) is present compared to the control condition. Also, the model explicated how attention contributes to the perceptual grouping through differential neural activations in parietal cortex. The proposed model is consistent with the concepts of base and incremental grouping derived from electrophysiological studies.
perceptivno grupiranje; funkcionalno oslikavanje; neuronski model
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Podaci o prilogu
46-x.
2010.
objavljeno
Podaci o matičnoj publikaciji
Perception
Pion
Podaci o skupu
33th European Conference on Visual Perception
poster
22.08.2010-26.08.2010
Lausanne, Švicarska