No abstract

Stereomatching of oblique and transparent surfaces is described using a model of cortical binocular 'tuned' neurons selective for disparities of individual visual features and neurons selective for the position, depth and 3D orientation of local surface patches. The model is based on a simple set of learning rules. In the model, monocular neurons project excitatory connection pathways to binocular neurons at appropriate disparities. Binocular neurons project excitatory connection pathways to appropriately tuned 'surface patch' neurons. The surface patch neurons project reciprocal excitatory connection pathways to the binocular neurons. Anisotropic intralayer inhibitory connection pathways project between neurons with overlapping receptive fields. The model's responses to simulated stereo image pairs depicting a variety of oblique surfaces and transparently overlaid surfaces are presented. For all the surfaces, the model (i) assigns disparity matches and surface patch representations based on global surface coherence and uniqueness, (ii) permits coactivation of neurons representing multiple disparities within the same image location, (iii) represents oblique slanted and tilted surfaces directly, rather than approximating them with a series of frontoparallel steps, (iv) assigns disparities to a cloud of points at random depths, like human observers and unlike Prazdny's (1985) method, and (v) causes globally consistent matches to override greedy local matches. The model represents transparency, unlike the model of Marr and Poggio (1976), and it assigns unique disparities, unlike the model of Prazdny.

The position, size, and shape of the receptive field (RF) of some cortical neurons change dynamically, in response to artificial scotoma conditioning (Pettet & Gilbert, 1992) and to retinal lesions (Chino et al., 1992; Darian-Smith & Gilbert, 1995) in adult animals. The RF dynamics are of interest because they show how visual systems may adaptively overcome damage (from lesions, scotomas, or other failures), may enhance processing efficiency by altering RF coverage in response to visual demand, and may perform perceptual learning. This paper presents an afferent excitatory synaptic plasticity rule and a lateral inhibitory synaptic plasticity rule--the EXIN rules (Marshall, 1995)--to model persistent RF changes after artificial scotoma conditioning and retinal lesions. The EXIN model is compared to the LISSOM model (Sirosh et al., 1996) and to a neuronal adaptation model (Xing & Gerstein, 1994). The rules within each model are isolated and are analyzed independently, to elucidate their roles in adult cortical RF dynamics. Based on computer simulations, the EXIN lateral inhibitory synaptic plasticity rule and the LISSOM lateral excitatory synaptic plasticity rule produced the best fit with current neurophysiological data on visual cortical plasticity in adult animals (Chino et al., 1992; Pettet & Gilbert, 1992; Darian-Smith & Gilbert, 1995) including (1) the retinal position and shape of the expanding RFs; (2) the corticotopic direction in which responsiveness returns to the silenced cortex; (3) the direction of RF shifts; (4) the amount of change in response to blank stimuli; and (5) the lack of dynamic RF changes during conditioning with a retinal lesion in one eye and the unlesioned eye kept open, in adult animals. The effects of the LISSOM lateral inhibitory synaptic plasticity rule during artificial scotoma conditioning are in conflict with those of the other two LISSOM synaptic plasticity rules. A novel "complementary scotoma" conditioning experiment, in which stimulation of two complementary regions of visual space alternates repeatedly, is proposed to differentiate the predictions of the EXIN and LISSOM rules.

Stereomatching of oblique and transparent surfaces is described using a model of cortical binocular 'tuned' neurons selective for disparities of individual visual features and neurons selective for the position, depth and 3D orientation of local surface patches. The model is based on a simple set of learning rules. In the model, monocular neurons project excitatory connection pathways to binocular neurons at appropriate disparities. Binocular neurons project excitatory connection pathways to appropriately tuned 'surface patch' neurons. The surface patch neurons project reciprocal excitatory connection pathways to the binocular neurons. Anisotropic intralayer inhibitory connection pathways project between neurons with overlapping receptive fields. The model's responses to simulated stereo image pairs depicting a variety of oblique surfaces and transparently overlaid surfaces are presented. For all the surfaces, the model (i) assigns disparity matches and surface patch representations based on global surface coherence and uniqueness, (ii) permits coactivation of neurons representing multiple disparities within the same image location, (iii) represents oblique slanted and tilted surfaces directly, rather than approximating them with a series of frontoparallel steps, (iv) assigns disparities to a cloud of points at random depths, like human observers and unlike Prazdny's (1985) method, and (v) causes globally consistent matches to override greedy local matches. The model represents transparency, unlike the model of Marr and Poggio (1976), and it assigns unique disparities, unlike the model of Prazdny.

Intracortical microstimulation (ICMS) of a single site in the somatosensory cortex of rats and monkeys for 2-6 h increases the number of neurons responsive to the skin region corresponding to the ICMS-site receptive field (RF), with very little effect on the position and size of the ICMS-site RF, and the response evoked at the ICMS site by tactile stimulation. Large changes in RF topography are also observed following several weeks of repetitive stimulation of a restricted skin region during tactile frequency discrimination training in monkeys. It has been suggested that these changes in RF topography are caused by competitive learning in excitatory pathways. This paper analyses the possible role of lateral inhibitory synaptic plasticity in producing cortical plasticity after ICMS and peripheral conditioning in adult animals. The 'EXIN' (afferent excitatory and lateral inhibitory) synaptic plasticity rules are used to model RF changes after ICMS and peripheral stimulation. The EXIN model produces RF topographical changes similar to those observed experimentally. It is shown that lateral inhibitory pathway plasticity is sufficient to model RF changes and increase in position discrimination after peripheral stimulation. Several novel and testable predictions are made based on the EXIN model.