A neural mechanism for optic flow parsing in macaque visual cortex.

For the brain to compute object motion in the world during self-motion, it must discount the global patterns of image motion (optic flow) caused by self-motion. Optic flow parsing is a proposed visual mechanism for computing object motion in the world, and studies in both humans and monkeys have demonstrated perceptual biases consistent with the operation of a flow-parsing mechanism. However, the neural basis of flow parsing remains unknown.

How to reward animals based on their subjective percepts: A Bayesian approach to online estimation of perceptual biases.

Elucidating the neural basis of perceptual biases, such as those produced by visual illusions, can provide powerful insights into the neural mechanisms of perceptual inference. However, studying the subjective percepts of animals poses a fundamental challenge: unlike human participants, animals cannot be verbally instructed to report what they see, hear, or feel. Instead, they must be trained to perform a task for reward, and researchers must infer from their responses what the animal perceived.

Neurons in Primate Area MSTd Signal Eye Movement Direction Inferred from Dynamic Perspective Cues in Optic Flow.

Smooth eye movements are common during natural viewing; we frequently rotate our eyes to track moving objects or to maintain fixation on an object during self-movement. Reliable information about smooth eye movements is crucial to various neural computations, such as estimating heading from optic flow or judging depth from motion parallax. While it is well established that extraretinal signals (e.

Flexible coding of object motion in multiple reference frames by parietal cortex neurons.

Neurons represent spatial information in diverse reference frames, but it remains unclear whether neural reference frames change with task demands and whether these changes can account for behavior. In this study, we examined how neurons represent the direction of a moving object during self-motion, while monkeys switched, from trial to trial, between reporting object direction in head- and world-centered reference frames. Self-motion information is needed to compute object motion in world coordinates but should be ignored when judging object motion in head coordinates.

The Effects of Population Tuning and Trial-by-Trial Variability on Information Encoding and Behavior.

Identifying the features of population responses that are relevant to the amount of information encoded by neuronal populations is a crucial step toward understanding population coding. Statistical features, such as tuning properties, individual and shared response variability, and global activity modulations, could all affect the amount of information encoded and modulate behavioral performance. We show that two features in particular affect information: the modulation of population responses across conditions (population signal) and the inverse population covariability along the modulation axis (projected precision).

Coding of stereoscopic depth information in visual areas V3 and V3A.

The process of stereoscopic depth perception is thought to begin with the analysis of absolute binocular disparity, the difference in position of corresponding features in the left and right eye images with respect to the points of fixation. Our sensitivity to depth, however, is greater when depth judgments are based on relative disparity, the difference between two absolute disparities, compared to when they are based on absolute disparity. Therefore, the visual system is thought to compute relative disparities for fine depth discrimination.

Neural computations underlying depth perception.

Neural mechanisms underlying depth perception are reviewed with respect to three computational goals: determining surface depth order, gauging depth intervals, and representing 3D surface geometry and object shape. Accumulating evidence suggests that these three computational steps correspond to different stages of cortical processing. Early visual areas appear to be involved in depth ordering, while depth intervals, expressed in terms of relative disparities, are likely represented at intermediate stages.

Neurons in monkey visual area V2 encode combinations of orientations.

Contours and textures are important attributes of object surfaces, and are often described by combinations of local orientations in visual images. To elucidate the neural mechanisms underlying contour and texture processing, we examined receptive field (RF) structures of neurons in visual area V2 of the macaque monkey for encoding combinations of orientations. By measuring orientation tuning at several locations within the classical RF, we found that a majority (70%) of V2 neurons have similar orientation tuning throughout the RF.