... This article presents one alternative to the computer metaphor suggesting that brains are organized into independent modules. Evidence is reviewed that brains are organized into parallel processing streams with complementary properties. Hierarchical interactions within each stream and parallel interactions between streams create coherent behavioral representations that overcome the complementary deficiencies of each stream and support unitary conscious experiences. This perspective suggests how brain design reflects the organization of the physical world with which brains interact. Examples from perception, learning, cognition, and action are described, and theoretical concepts and mechanisms by which complementarity is accomplished are presented.

Electrophysiological studies indicate that neurons in the Middle Temporal (MT) area of the primate brain are selective for the velocity of visual stimuli. This paper describes a computational model of MT physiology, in which local image velocities are represented via the distribution of MT neuronal responses. The computation is performed in two stages, corresponding to neurons in cortical areas V1 and MT. Each stage computes a weighted linear sum of inputs, followed by rectification and divisive normalization. V1 receptive field weights are designed for orientation and direction selectivity. MT receptive field weights are designed for velocity (both speed and direction) selectivity. The paper includes computational simulations accounting for a wide range of physiological data, and describes experiments that could be used to further test and refine the model.

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Neurons in area MT of primate visual cortex encode the velocity of moving objects. We present a model of how MT cells aggregate responses from V1 to form such a velocity representation. Two different sets of units, with local receptive fields, receive inputs from motion energy filters. One set of units forms estimates of local motion, while the second set computes the utility of these estimates. Outputs from this second set of units "gate" the outputs from the first set through a gain control mechanism. This active process for selecting only a subset of local motion responses to integrate into more global responses distinguishes our model from previous models of velocity estimation. The model yields accurate velocity estimates in synthetic images containing multiple moving targets of varying size, luminance, and spatial frequency profile and deals well with a number of transparency phenomena. 1 INTRODUCTION Humans, and primates in general, are very good at complex motion...

Eye and head movements were measured in a group of infants at 2, 3, and 5 months of age as they were attentively tracking an object moving at 0.2 or 0.4 Hz in sinus or triangular mode. Smooth pursuit gain increased with age, especially until 3 months. At 2-3 months, the lag of the smooth pursuit was small for the sinusoidal motion but large for the triangular one. At 5 months, smooth pursuit was leading the sinusoidal motion and the lag for the triangular one was small. Head tracking increased substantially with age and its lag was always large. © 1997 Elsevier Science Ltd. Eye movements Infants Smooth pursuit Saccades Head movements

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When an expansion flow field of moving dots is overlapped by planar motion, observers perceive an illusory displacement of the focus of expansion (FOE) in the direction of the planar motion (Duffy and Wurtz, Vision Research, 1993;33:1481–1490). The illusion may be a consequence of induced motion, wherein an induced component of motion relative to planar dots is added to the motions of expansion dots to produce the FOE shift. While such a process could be mediated by local ‘center-surround’ receptive fields, the effect could also be due to a higher level process which detects and subtracts large-field planar motion from the flow field. We probed the mechanisms underlying this illusion by adding varying amounts of rotation to the expansion stimulus, and by varying the speed and size of the planar motion field. The introduction of rotation into the stimulus produces an illusory shift in a direction perpendicular to the planar motion. Larger FOE shifts were perceived for greater speeds and sizes of planar motion fields, although the speed effect saturated at high speeds. While the illusion appears to share a common mechanism with center-surround induced motion, our results also point to involvement of a more global mechanism that subtracts coherent planar motion from the flow field. Such a process might help to maintain visual stability during eye movements. © 1998

... This article presents one alternative to the computer metaphor suggesting that brains are organized into independent modules. Evidence is reviewed that brains are organized into parallel processing streams with complementary properties. Hierarchical interactions within each stream and parallel interactions between streams create coherent behavioral representations that overcome the complementary deficiencies of each stream and support unitary conscious experiences. This perspective suggests how brain design reflects the organization of the physical world with which brains interact. Examples from perception, learning, cognition, and action are described, and theoretical concepts and mechanisms by which complementarity is accomplished are presented.

processing

Visually guided navigation through a cluttered natural scene is a challenging problem that animals and humans accomplish with ease. The ViSTARS neural model proposes how primates use motion information to segment objects and determine heading for purposes of goal approach and obstacle avoidance in response to video inputs from real and virtual environments. The model produces trajectories similar to those of human navigators. It does so by predicting how computationally complementary processes in cortical areas MT- /MSTv and MT + /MSTd compute object motion for tracking and self-motion for navigation, respectively. The model retina responds to transients in the input stream. Model V1 generates a local speed and direction estimate. This local motion estimate is ambiguous due to the neural aperture problem. Model MT + interacts with MSTd via an attentive feedback loop to compute accurate heading estimates in MSTd that quantitatively simulate properties of human heading estimation data. Model MT- interacts with MSTv via an attentive feedback loop to compute accurate estimates of speed, direction and position of moving objects. This object information is combined with heading information to produce steering decisions wherein goals behave like attractors and obstacles behave like repellers. These steering decisions lead to navigational trajectories that closely match human performance.