Representation of Angles Embedded within Contour Stimuli in Area V2 of Macaque Monkeys

Abstract

Angles and junctions embedded within contours are important features to represent the shape of objects. To study the neuronal basis to extract these features, we conducted extracellular recordings while two macaque monkeys performed a fixation task. Angle stimuli were the combination of two straight half-lines larger than the size of the classical receptive fields (CRFs). Each line was drawn from the center to outside the CRFs in 1 of 12 directions, so that the stimuli passed through the CRFs and formed angles at the center of the CRFs. Of 114 neurons recorded from the superficial layer of area V2, 91 neurons showed selective responses to these angle stimuli. Of these, 41 neurons (36.0%) showed selective responses to wide angles between 60°and 150°that were distinct from responses to straight lines or sharp angles (30°). Responses were highly selective to a particular angle in approximately one-fourth of neurons. When we tested the selectivity of the same neurons to individual half-lines, the preferred direction was more or less consistent with one or two components of the optimal angle stimuli. These results suggest that the selectivity of the neurons depends on both the combination of two components and the responses to individual components. Angle-selective V2 neurons are unlikely to be specific angle detectors, because the magnitude of their responses to the optimal angle was indistinguishable from that to the optimal half-lines. We suggest that the extraction of information of angles embedded within contour stimuli may start in area V2.

Receptive Field Properties of Neurons in the Early Visual Cortex Revealed by Local Spectral Reverse Correlation

“…Several previous studies show that cells selective to complex visual stimuli cannot generally be activated by stimulations using only a part of their optimal stimuli (Tanaka et al, 1991;Pasupathy and Connor, 2001;Ito and Komatsu, 2004). A possible neural mechanism that could explain this phenomenon is that the spiking threshold and nonlinearities are so large that individual parts of appropriate stimuli shown alone cannot achieve the excitation necessary for eliciting spikes.…”

“…did not test the neuron with such stimuli directly, this may mean that visual processing of complex features found in the higher-order areas (Gallant et al, 1993(Gallant et al, , 1996Hegde and Van Essen, 2000;Pasupathy and Connor, 2001;Ito and Komatsu, 2004) is started, at least partly, in the early visual cortex.…”

“…Because the cells in these areas are known to respond to more complex stimuli (Gallant et al, 1993(Gallant et al, , 1996Pasupathy and Connor, 2001;Ito and Komatsu, 2004), it is of interest to examine how local spectral response profiles are organized for cells in these areas. However, the current LSRC method is probably not applicable to neurons with strong position invariance such as those in the inferotemporal cortical area (Ito et al, 1995;Tanaka, 1996), because tunings for given oriented segments are not tied to specific locations within the receptive field in these areas.…”

Hierarchical K-Means Algorithm for Modeling Visual Area V2 Neurons

“…5 [15]. Each stimulus was a 14-by-14 image patch representing an angle in [15] for details. In addition, each stimulus was normalized to zero mean and unit variance.…”

“…To make quantitative comparison between the simulation results and physiological results in [15], we then generated a stimuli set with M = 12. Five quantities about the statistics of the response profiles of the model neurons on the stimuli set were calculated and presented in Fig.…”