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

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.

Auditory modulation of spiking activity and local field potentials in area MT does not appear to underlie an audiovisual temporal illusion

The timing of brief stationary sounds has been shown to alter the perceived speed of visual apparent motion (AM), presumably by altering the perceived timing of the individual frames of the AM stimuli and/or the duration of the interstimulus intervals (ISIs) between those frames. To investigate the neural correlates of this “temporal ventriloquism” illusion, we recorded spiking and local field potential (LFP) activity from the middle temporal area (area MT) in awake, fixating macaques. We found that the spiking activity of most MT neurons (but not the LFP) was tuned for the ISI/speed (these parameters covaried) of our AM stimuli but that auditory timing had no effect on that tuning. We next asked whether the predicted changes in perceived timing were reflected in the timing of neuronal responses to the individual frames of the AM stimuli. Although spiking dynamics were significantly, if weakly, affected by auditory timing in a minority of neurons, the timing of spike responses did not systematically mirror the predicted perception of stimuli. Conversely, the duration of LFP responses in β- and γ-frequency bands was qualitatively consistent with human perceptual reports. We discovered, however, that LFP responses to auditory stimuli presented alone were robust and that responses to audiovisual stimuli were predicted by the linear sum of responses to auditory and visual stimuli presented individually. In conclusion, we find evidence of auditory input into area MT but not of the nonlinear audiovisual interactions we had hypothesized to underlie the illusion. NEW & NOTEWORTHY We utilized a set of audiovisual stimuli that elicit an illusion demonstrating “temporal ventriloquism” in visual motion and that have spatiotemporal intervals for which neurons within the middle temporal area are selective. We found evidence of auditory input into the middle temporal area but not of the nonlinear audiovisual interactions underlying this illusion. Our findings suggest that either the illusion was absent in our nonhuman primate subjects or the neuronal correlates of this illusion lie within other areas.

Biologically inspired computational modeling of motion based on middle temporal area

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.

Sensitivity of neurons in the middle temporal area of marmoset monkeys to random dot motion

Neurons 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 that 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 & NOTEWORTHY We 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 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.

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

Neurons 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.