Retention of a Brightness Discrimination Task in Paramecia, P. caudatum

Previous research into the possibility of learning in paramecia in this laboratory has shown that these organisms can learn to go to and remain in a specific location based on cathode shock reinforcement. The present experiment was designed to determine whether paramecia could retain (remember) the learned brightness discrimination task. The results indicate that the retention interval for this task in paramecia is shorter than 1 minute. It is possible that paramecia can remember this task for longer than a second but shorter than the 1-minute interval that was used during test. It is also possible that remembering for more than a few seconds requires a nervous system, which paramecia do not have.

Inhibition in Superior Colliculus Neurons in a Brightness Discrimination Task?

Simultaneous recordings were collected from between two and four buildup neurons from the left and right superior colliculi in rhesus monkeys in a simple two-choice brightness discrimination task. The monkeys were required to move their eyes to one of two response targets to indicate their decision. Neurons were identified whose receptive fields were centered on the response targets. The functional role of inhibition was examined by conditionalizing firing rate on a high versus low rate in target neurons 90 ms to 30 ms before the saccade and examining the firing rate in both contralateral and ipsilateral neurons. Two models with racing diffusion processes were fit to the behavioral data, and the same analysis was performed on simulated paths in the diffusion processes that have been found to represent firing rate. The results produce converging evidence for the lack of a functional role for inhibition between neural populations corresponding to the two decisions.

Novel Visual Illusions Related to Vasarely's ‘Nested Squares’ Show That Corner Salience Varies with Corner Angle

Vasarely's ‘nested-squares’ illusion shows that 90° corners can be more salient perceptually than straight edges. On the basis of this illusion we have developed a novel visual illusion, the ‘Alternating Brightness Star’, which shows that sharp corners are more salient than shallow corners (an effect we call ‘corner angle salience variation’) and that the same corner can be perceived as either bright or dark depending on the polarity of the angle (ie whether concave or convex: ‘corner angle brightness reversal’). Here we quantify the perception of corner angle salience variation and corner angle brightness reversal effects in twelve naive human subjects, in a two-alternative forced-choice brightness discrimination task. The results show that sharp corners generate stronger percepts than shallow corners, and that corner gradients appear bright or dark depending on whether the corner is concave or convex. Basic computational models of center – surround receptive fields predict the results to some degree, but not fully.

Depth Discrimination from Shading under Diffuse Lighting

The human visual system has a remarkable ability to interpret smooth patterns of light on a surface in terms of 3-D surface geometry. Classical studies of shape-from-shading perception have assumed that surface irradiance varies with the angle between the local surface normal and a collimated light source. This model holds, for example, on a sunny day. One common situation in which this model fails to hold, however, is under diffuse lighting such as on a cloudy day. Here we report on the first psychophysical experiments that address shape-from-shading under a uniform diffuse-lighting condition. Our hypothesis was that shape perception can be explained with a perceptual model that “dark means deep”. We tested this hypothesis by comparing performance in a depth-discrimination task to performance in a brightness-discrimination task, using identical stimuli. We found a significant correlation between responses in the two tasks, supporting a dark-means-deep model. However, overall performance in the depth-discrimination task was superior to that predicted by a dark-means-deep model. This implies that humans use a more accurate model than dark-means-deep to perceive shape-from-shading under diffuse lighting.