Neural coding of multiple motion speeds in visual cortical area MT
Xin HuangiD, Bikalpa GhimireiD, Anjani Sreeprada ChakralaiD, Steven WiesneriD
Abstract
Motion speed provides a salient cue for visual segmentation, yet how the visual system represents and differentiates multiple speeds remains poorly understood. Here, we investigated the neural coding of multiple speeds. First, we characterized the perceptual capacity of human and macaque subjects to segment overlapping random-dot stimuli moving at different speeds. We then recorded from neurons in the middle temporal (MT) cortex of macaque monkeys to determine how multiple speeds are represented. We made a novel finding that the responses of MT neurons to two speeds showed a robust bias toward the faster speed component when both speeds were slow ([≤] 20{degrees}/s). This faster-speed bias emerged early in the neuronal response. It occurred regardless of whether the two speed components moved in the same or different directions, and even when attention was directed away from the receptive field. As stimulus speed increased, the faster-speed bias diminished. Our finding can be explained by a modified divisive normalization model, in which the weights for the speed components are proportional to the responses of a population of neurons, referred to as the weighting pool, elicited by the individual speeds. We suggest that the weighting pool include neurons with a broad range of speed preferences. We found that a classifier can differentiate the responses of MT neurons to two speeds versus a corresponding log-mean speed. We further showed that it was possible to decode two speeds from MT population response, supporting the theoretical framework of coding multiplicity of visual features in neuronal populations. The decoded speeds can account for the perceptual performance of segmenting two speeds with a large (x4) but not a small (x2) separation, raising questions for future investigations. Our findings help define the neural coding rule of multiple speeds. The faster-speed bias in MT at slow stimulus speeds could benefit important behavioral tasks such as figure-ground segregation, as figural objects tend to move faster than the background in the natural environment.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 6
- FWCI
- 4.18
- Field percentile
- top 13%
- Organism
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Mechanisms of Neural Representation and Segregation of Multiple Spatially Separated Visual Stimuli
Steven Wiesner, Bikalpa Ghimire, Xin Huang·bioRxiv·Sep 11, 2025
- Mechanisms of speed encoding in the human middle temporalcortex measured by 7T fMRI
Anna Gaglianese, Alessio Fracasso, … Natalia Petridou·Human Brain MappingPeer-reviewed·Jan 13, 2023
- Area MT carries acceleration information in a quickly and directly decodable representation
Penny Shuyi Chen, Alexander C. Huk·Journal of NeurosciencePeer-reviewed·Oct 29, 2026
- Beyond Inheritance: De novo Fast Motion Computation in Primate Visual Cortex
Keyan He, Lixuan Liu, … Wei Wang·bioRxiv·Dec 4, 2025
- Speed tuning in the macaque posterior parietal cortex
Eric Avila, Kaushik J. Lakshminarasimhan, … Dora E. Angelaki·Cerebral CortexPeer-reviewed·Oct 4, 2018
- Compound stimuli reveal the structure of visual motion selectivity in macaque MT neurons
Andrew David Zaharia, Robbe L. T. Goris, … Eero P. Simoncelli·eNeuroPeer-reviewed·Oct 11, 2019