These experiments use functional magnetic resonance imaging (fMRI) to reveal neural activity uniquely associated with perception of biological motion. We isolated brain areas activated during the viewing of point-light figures, then compared those areas to regions known to be involved in coherent-motion perception and kinetic-boundary perception. Coherent motion activated a region matching previous reports of human MT/MST complex located on the temporo-parieto-occipital junction. Kinetic boundaries activated a region posterior and adjacent to human MT previously identified as the kinetic-occipital (KO) region or the lateral-occipital (LO) complex. The pattern of activation during viewing of biological motion was located within a small region on the ventral bank of the occipital extent of the superior-temporal sulcus (STS). This region is located lateral and anterior to human MT/MST, and anterior to KO. Among our observers, we localized this region more frequently in the right hemisphere than in the left. This was true regardless of whether the point-light figures were presented in the right or left hemifield. A small region in the medial cerebellum was also active when observers viewed biological-motion sequences. Consistent with earlier neuroimaging and single-unit studies, this pattern of results points to the existence of neural mechanisms specialized for analysis of the kinematics defining biological motion.

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Brain Areas Involved in Perception of Biological Motion

Vol. 1 1. Neural Basis of Vision. 2. Color Vision. 3. Depth Perception. 4. Perception of Visual Motion. 5. Perceptual Organization in Vision. 6. Attention. 7. Visual Object Recognition. 8. Motor Control. 9. Neural Basis of Audition. 10. Auditory Perception and Cognition. 11. Music Perception and Cognition. 12. Speech Perception. 13. Neural Basis of Haptic Perception. 14. Touch and Haptics. 15. Perception of Pain and Temperature. 16. Taste. 17. Olfaction. Vol. 2 1. Kinds of Memory. 2. Models of Memory. 3. Cognitive Neuroscience. 4. Spatial Cognition. 5. Knowledge Representation. 6. Psycholinguistics. 7. Language Processing. 8. Problem Solving. 9. Reasoning. 10. Decision Making. 11. Concepts & Categorization. 12. Cognitive Development. 13. Culture & Cognition. Vol. 3 1. Associative Structures in Pavlovian and Instrumental Conditioning. 2. Learning: Laws and Models of Basic Conditioning. 3. Reinforcement Learning. 4. Neural Analysis of Learning in Simple Systems. 5. Learning Mutants. 6. Learning Instincts. 7. Perceptual Learning. 8. Spatial Learning. 9. Temporal Learning. 10. Role of Learning in Cognitive Development. 11. Language Acquisition. 12. Role of Learning in the Operation of Motivational Systems. 13. Emotional Plasticity. 14. Anatomy of Motivation. 15. Hunger Energy Homeostasis. 16. Thirst and Water-Salt Appetite. 17. Reproductive Motivation. 18. Social Behavior. 19. Addiction. Vol. 4 1. Representational Measurement Theory. 2. Signal Detection Theory. 3. Psychophysical Scaling. 4. Cognitive Neuropsychology. 5. Functional Brain Imaging. 6. Neural Network Modeling. 7. Parallel and Serial Processing. 8. Methodology and Statistics in Single-Subject Experiments. 9. Analysis, Interpretation, and Visual Presentation of Experimental Data. 10. Meta-Analysis. 11. Mathematical Modeling. 12. Analysis of Response Time Distributions. 13. Testing and Measurement. 14. Personality and Individual Differences. 15. Electrophysiology of Attention. 16. Single vs. Multiple Systems of Memory and Learning. 17. Infant Cognition. 18. Aging and Cognition.

Stevens' handbook of experimental psychology

Representation of statistical properties.

Eye movements are an integral and essential part of our human foveated vision system. Here, we review recent work on voluntary eye movements, with an emphasis on the last decade. More selectively, we address two of the most important questions about saccadic and smooth pursuit eye movements in natural vision. First, why do we saccade to where we do? We argue that, like for many other aspects of vision, several different circuits related to salience, object recognition, actions, and value ultimately interact to determine gaze behavior. Second, how are pursuit eye movements and perceptual experience of visual motion related? We show that motion perception and pursuit have a lot in common, but they also have separate noise sources that can lead to dissociations between them. We emphasize the point that pursuit actively modulates visual perception and that it can provide valuable information for motion perception.

Eye movements and perception: a selective review.

Suppose that the variability in our movements is caused not by noise in the motor system itself, nor by fluctuations in our intentions or plans, but rather by errors in our sensory estimates of the external parameters that define the appropriate action. For tasks in which precision is at a premium, performance would be optimal if no noise were added in movement planning and execution: motor output would be as accurate as possible given the quality of sensory inputs. Here we use visually guided smooth-pursuit eye movements in primates as a testing ground for this notion of optimality. In response to repeated presentations of identical target motions, nearly 92% of the variance in eye trajectory can be accounted for as a consequence of errors in sensory estimates of the speed, direction and timing of target motion, plus a small background noise that is observed both during eye movements and during fixations. The magnitudes of the inferred sensory errors agree with the observed thresholds for sensory discrimination by perceptual systems, suggesting that the very different neural processes of perception and action are limited by the same sources of noise.

/pdf/a-sensory-source-for-motor-variation-3l71ybrzjo.pdf

A sensory source for motor variation.

http://wexler.free.fr/library/files/de%20bruyn%20(1988)%20human%20velocity%20and%20direction%20discrimination%20measured%20with%20random%20dot%20patterns.pdf

Human velocity and direction discrimination measured with random dot patterns

Sequential presentation of a number of random-dot patterns which when super-imposed yield an expanding flow field leads to the perception of a coherent motion towards the observer. The motion vectors in this type of flow field all radiate from the origin. This percept of a global coherent expanding flow results only when the local speeds (magnitude of the local motion vectors) are zero at the centre and increase linearly towards the periphery. If all the dots radiate outwards but have the same speed, a clear percept of three-dimensional nonrigidity arises.

The importance of velocity gradients in the perception of three-dimensional rigidity.

Theoretically, optic flow, an important source of information for the perception of locomotion and three-dimensional structure of the environment, is described in terms of divergence, curl, and shear components. We measured how the detection of the type of flow field depends on directional information. We manipulated the local directions by rotating them through an anglex relative to the original direction (i.e., the direction of motion at that locus in an unaltered flow field), The results of the first experiments showed that divergence, curl, and shear can be detected even if the directional range of the individual motion vectors is as broad as 180°. Subsequent experiments revealed that the detection of the geometric components of the optic flow field is merely based on the integration of a few (10% of vectors) local directions correctly (within 10° of original direction) specifying the type of flow field. Other directions are irrelevant to this process. This is actually what one would expect if the optic flow is analyzed by special purpose mechanisms that detect and process the geometric components on the basis of the integration of motion information. The results indicate that as far as they integrate motion information, detectors for divergence, curl, and shear operate in a similar manner. Implications of the results for modeling such mechanisms are discussed.

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The role of direction information in the perception of geometric optic flow components

Naive observers of random-dot stereograms depicting complex surfaces often find that they require several tens of seconds before the impression of depth emerges. With practice, however, perception times often decrease markedly: perceptual learning occurs. Current explanations of these effects were assessed in two experiments. In the first experiment the perception times of naive observers for random-dot stereograms which depicted the same complex shape but contained different ranges of disparity were measured. In the second experiment the minimum times required by experienced observers to perceive a given complex shape in stereograms that contained different ranges of disparity were determined. Perception times for the naive observers were all very fast (<3 s) and showed no evidence of perceptual learning. There was no effect of disparity range on perception times in either experiment. It was found that very large-disparity (80 min arc) complex stereograms could be perceived quickly, even by naive observers. It is concluded that the long initial latencies previously reported are not due to surface complexity nor to the range of disparities present. Other factors. such as dot size, dot density, and the correlation of the stereo images, appear to be important determinants of efficient stereoscopic performance when viewing complex random-dot stereograms.

Bart De Bruyn

Papers

Human velocity and direction discrimination measured with random dot patterns

The importance of velocity gradients in the perception of three-dimensional rigidity.

The role of direction information in the perception of geometric optic flow components

Perceptual Latency and Complex Random-Dot Stereograms

Asymmetric spatial distributions of motion vectors yield characteristic errors in direction judgements.