Abstract
A remarkable accomplishment of self organizing models is their ability to simulate the development of feature maps in the cortex. Additionally, these models have been trained to tease out the differential causes of multiple feature maps, mapped on to the same output space. Recently, a Laterally Interconnected Synergetically Self Organizing Map (LISSOM) model has been used to simulate the mapping of eccentricity and meridional angle onto orthogonal axes in the primary visual cortex (V1). This model is further probed to simulate the development of the radial bias in V1, using a training set that consists of both radial (rectangular bars of random size and orientation) as well as non-radial stimuli. The radial bias describes the preference of the visual system toward orientations that match the angular position (meridional angle) of that orientation with respect to the point of fixation. Recent fMRI results have shown that there exists a coarse scale orientation map in V1, which resembles the meridional angle map, thereby providing a plausible neural basis for the radial bias. The LISSOM model, trained for the development of the retinotopic map, on probing for orientation preference, exhibits a coarse scale orientation map, consistent with these experimental results, quantified using the circular cross correlation (rc). The rc between the orientation map developed on probing with a thin annular ring containing sinusoidal gratings with a spatial frequency of 0.5 cycles per degree (cpd) and the corresponding meridional map for the same annular ring, has a value of 0.8894. The results also suggest that the radial bias goes beyond the current understanding of a node to node correlation between the two maps.
Highlights
Hyper-columns in V1, mapping the entire range of orientations possible, have a flattened spatial extent of ∼1 × 1 mm and ∼2 × 2 mm, in monkeys and humans respectively (Blasdel and Salama, 1986; Adams et al, 2007)
The global orientation map is developed on training the Laterally Interconnected Synergetically Self Organizing Map (LISSOM) model with dilated and rotated near radial rectangular bars as described in the Model Stimuli section
A computational model which simulates the development of the radial bias is described in this paper
Summary
Hyper-columns in V1, mapping the entire range of orientations possible, have a flattened spatial extent of ∼1 × 1 mm and ∼2 × 2 mm, in monkeys and humans respectively (Blasdel and Salama, 1986; Adams et al, 2007). SOM Model of Radial Bias hypotheses which attempt to explain these results: (a) Hyperacuity: There exists a sampling bias in the population activity of hyper-columns that contribute to each fMRI voxel, which on multivariate pattern analysis would yield orientation discriminability (Kamitani and Tong, 2005; Haynes and Rees, 2006); (b) Coarse scale orientation maps: There exists an orientation map at a spatial scale equivalent to that of the retinotopic map These maps have a radial bias, i.e., those orientations which match the retinotopic meridional angle are over-represented as compared to other orientations (Sasaki et al, 2006; Freeman et al, 2011). Meridional angle refers to the angular position of a stimulus with respect to the point of fixation, in radial co-ordinates.)
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