scholarly journals The Contribution of Color to Motion Processing in Macaque Middle Temporal Area

1999 ◽  
Vol 19 (15) ◽  
pp. 6571-6587 ◽  
Author(s):  
Alexander Thiele ◽  
Karen R. Dobkins ◽  
Thomas D. Albright
Keyword(s):  
Motion Processing ◽  
Temporal Area ◽  
Middle Temporal ◽  
Middle Temporal Area

Visual motion processing in the anterior ectosylvian sulcus of the cat

1996 ◽  
Vol 76 (2) ◽  
pp. 895-907 ◽  
Author(s):  
J. W. Scannell ◽  
F. Sengpiel ◽  
M. J. Tovee ◽  
P. J. Benson ◽  
C. Blakemore ◽  
...  
Keyword(s):  
Visual Area ◽  
Motion Processing ◽  
Published Data ◽  
Anterior Ectosylvian Sulcus ◽  
Temporal Area ◽  
Middle Temporal ◽  
Visual Motion Processing ◽  
Pattern Motion ◽  
Middle Temporal Area ◽  
Component Motion

1. Neurons that are selectively sensitive to the direction of motion of elongated contours have been found in several cortical areas in many species. However, in the striate cortex of the cat and monkey, and the extrastriate posteromedial lateral suprasylvian visual area of the cat, such cells are generally component motion selective, signaling only the direction of movement orthogonal to the preferred orientation; a direction that is not necessarily the same as the motion of the entire pattern or texture of which the cell's preferred contour is part. The primate extrastriate middle temporal area is the only cortical region currently known to contain a substantial population of pattern-motion-selective cells that respond to the shared vector of motion of mixtures of contours. 2. From analyzing published data on the connectivity of the cat's cortex, we predicted that the anterior ectosylvian visual area (AEV), situated within the anterior ectosylvian sulcus, might be a higher-order motion processing area and thus likely to contain pattern-motion-selective neurons. This paper presents the results of a study on neuronal responses in AEV. 3. Ninety percent of AEV cells that responded strongly to drifting grating and/or plaid stimuli were directionally selective (directionality index > 0.5). For this group, the mean directionality index was 0.75. Moreover, 55% of these cells were unequivocally classified as pattern motion selective and only one neuron was classified as definitely component motion selective. Thus high-level pattern motion coding occurs in the cat extrastriate cortex and is not limited to the primate middle temporal area. 4. AEV contains a heterogeneous population of directionally selective cells. There was no clear relation between the degree of directional selectivity for plaids or gratings and the degree of selectivity for pattern motion or component motion. Nevertheless, 28% of the highly responsive cells were both more strongly modulated by plaids than gratings and more pattern motion selective than component motion selective. Such cells could correspond to a population of "selection units" signaling the salience of local motion information. 5. AEV lacks global retinotopic order but the preferred direction of motion of neurons (rather than axis of motion, as in the middle temporal area and the posteromedial lateral suprasylvian visual area) is mapped systematically across the cortex. Our data are compatible with AEV being a nonretinotopic, feature-mapped area in which cells representing similar parts of "motion space" are brought together on the cortical sheet.

scholarly journals Sensitivity of Neurons in the Middle Temporal Area of Marmoset Monkeys to Random Dot Motion

2017 ◽  
Author(s):  
Tristan A. Chaplin ◽  
Benjamin J. Allitt ◽  
Maureen A. Hagan ◽  
Nicholas S. Price ◽  
Ramesh Rajan ◽  
...  
Keyword(s):  
Primate Species ◽  
Neural Basis ◽  
Temporal Area ◽  
Middle Temporal ◽  
Mt Neurons ◽  
Wide Range ◽  
Middle Temporal Area ◽  
Dot Motion ◽  
Marmoset Monkeys ◽  
Random Dot Motion

AbstractNeurons in the Middle Temporal area (MT) of the primate cerebral cortex respond to moving visual stimuli. The sensitivity of MT neurons to motion signals can be characterized by using random-dot stimuli, in which the strength of the motion signal is manipulated by adding different levels of noise (elements that move in random directions). In macaques, this has allowed the calculation of “neurometric” thresholds. We characterized the responses of MT neurons in sufentanil/nitrous oxide anesthetized marmoset monkeys, a species which has attracted considerable recent interest as an animal model for vision research. We found that MT neurons show a wide range of neurometric thresholds, and that the responses of the most sensitive neurons could account for the behavioral performance of macaques and humans. We also investigated factors that contributed to the wide range of observed thresholds. The difference in firing rate between responses to motion in the preferred and null directions was the most effective predictor of neurometric threshold, whereas the direction tuning bandwidth had no correlation with the threshold. We also showed that it is possible to obtain reliable estimates of neurometric thresholds using stimuli that were not highly optimized for each neuron, as is often necessary when recording from large populations of neurons with different receptive field concurrently, as was the case in this study. These results demonstrate that marmoset MT shows an essential physiological similarity to macaque MT, and suggest that its neurons are capable of representing motion signals that allow for comparable motion-in-noise judgments.New and NoteworthyWe report the activity of neurons in marmoset MT in response to random-dot motion stimuli of varying coherence. The information carried by individual MT neurons was comparable to that of the macaque, and that the maximum firing rates were a strong predictor of sensitivity. Our study provides key information regarding the neural basis of motion perception in the marmoset, a small primate species that is becoming increasingly popular as an experimental model.

scholarly journals Biologically inspired computational modeling of motion based on middle temporal area

2018 ◽  
Vol 9 (1) ◽  
pp. 60-71 ◽  
Author(s):  
Fernanda da C. e C. Faria ◽  
Jorge Batista ◽  
Helder Araújo
Keyword(s):  
Receptive Fields ◽  
Biologically Inspired ◽  
Significant Information ◽  
Temporal Area ◽  
Middle Temporal ◽  
Complex Cells ◽  
Motion Computation ◽  
Reciprocal Connections ◽  
Middle Temporal Area ◽  
Last Stage

Abstract This paper describes a bio-inspired algorithm for motion computation based on V1 (Primary Visual Cortex) andMT (Middle Temporal Area) cells. The behavior of neurons in V1 and MT areas contain significant information to understand the perception of motion. From a computational perspective, the neurons are treated as two dimensional filters to represent the receptive fields of simple cells that compose the complex cells. A modified elaborated Reichardt detector, adding an output exponent before the last stage followed by a re-entry stage of modulating feedback from MT, (reciprocal connections of V1 and MT) in a hierarchical framework, is proposed. The endstopped units, where the receptive fields of cells are surrounded by suppressive regions, are modeled as a divisive operation. MT cells play an important role for integrating and interpreting inputs from earlier-level (V1).We fit a normalization and a pooling to find the most active neurons for motion detection. All steps employed are physiologically inspired processing schemes and need some degree of simplification and abstraction. The results suggest that our proposed algorithm can achieve better performance than recent state-of-the-art bio-inspired approaches for real world images.

scholarly journals A simple linear readout of MT supports motion direction-discrimination performance

2020 ◽  
Vol 123 (2) ◽  
pp. 682-694 ◽  
Author(s):  
Jacob L. Yates ◽  
Leor N. Katz ◽  
Aaron J. Levi ◽  
Jonathan W. Pillow ◽  
Alexander C. Huk
Keyword(s):  
Temporal Dynamics ◽  
Temporal Integration ◽  
Discrimination Performance ◽  
Neuron Activity ◽  
Motion Direction ◽  
Temporal Area ◽  
Middle Temporal ◽  
Motion Discrimination ◽  
Temporal Properties ◽  
Middle Temporal Area

Motion discrimination is a well-established model system for investigating how sensory signals are used to form perceptual decisions. Classic studies relating single-neuron activity in the middle temporal area (MT) to perceptual decisions have suggested that a simple linear readout could underlie motion discrimination behavior. A theoretically optimal readout, in contrast, would take into account the correlations between neurons and the sensitivity of individual neurons at each time point. However, it remains unknown how sophisticated the readout needs to be to support actual motion-discrimination behavior or to approach optimal performance. In this study, we evaluated the performance of various neurally plausible decoders, trained to discriminate motion direction from small ensembles of simultaneously recorded MT neurons. We found that decoding the stimulus without knowledge of the interneuronal correlations was sufficient to match an optimal (correlation aware) decoder. Additionally, a decoder could match the psychophysical performance of the animals with flat integration of up to half the stimulus and inherited temporal dynamics from the time-varying MT responses. These results demonstrate that simple, linear decoders operating on small ensembles of neurons can match both psychophysical performance and optimal sensitivity without taking correlations into account and that such simple read-out mechanisms can exhibit complex temporal properties inherited from the sensory dynamics themselves. NEW & NOTEWORTHY Motion perception depends on the ability to decode the activity of neurons in the middle temporal area. Theoretically optimal decoding requires knowledge of the sensitivity of neurons and interneuronal correlations. We report that a simple correlation-blind decoder performs as well as the optimal decoder for coarse motion discrimination. Additionally, the decoder could match the psychophysical performance with moderate temporal integration and dynamics inherited from sensory responses.

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