Faculty Opinions recommendation of Neural activity in the middle temporal area and lateral intraparietal area during endogenously cued shifts of attention.

Author(s):  
Michael E Goldberg
2008 ◽  
Vol 31 (2) ◽  
pp. 208-209 ◽  
Author(s):  
Bart Krekelberg

AbstractNeural activity in the middle temporal area (MT) is strongly correlated with motion perception. I analyzed the temporal relationship between the representation of direction in MT and the actual direction of a stimulus that continuously changed direction. The representation in MT lagged the stimulus by 45 msec. Hence, as far as the perception of direction is concerned, the hypothesis of lag compensation can be rejected.


2017 ◽  
Author(s):  
Tristan A. Chaplin ◽  
Benjamin J. Allitt ◽  
Maureen A. Hagan ◽  
Nicholas S. Price ◽  
Ramesh Rajan ◽  
...  

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.


2018 ◽  
Vol 9 (1) ◽  
pp. 60-71 ◽  
Author(s):  
Fernanda da C. e C. Faria ◽  
Jorge Batista ◽  
Helder Araújo

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.


Sign in / Sign up

Export Citation Format

Share Document