Testing and refining a computational model of neural responses in area MT

E. P. Simoncelli, W. D. Bair, J. R. Cavanaugh, J. A. Movshon

Research output: Contribution to journalArticle

Abstract

Purpose: To test and refine a velocity-representation model for pattern MT cells (Simoncelli & Heeger, ARVO 1994). The model consists of two stages, corresponding to cortical areas V1 and MT. Each stage computes a weighted linear sum of inputs, followed by halfwave rectification, squaring, and normalization. The linear stage of an MT cell combines outputs of V1 cells tuned for all orientations and a broad range of spatial and temporal frequencies. The resulting MT response is tuned for the velocity (both speed and direction) of moving patterns. Methods: We recorded the responses of MT neurons to computer-generated visual targets in paralyzed and anesthetized macaque monkeys using conventional techniques. Results: We measured direction-tuning curves for sinusoidal grating stimuli over a wide range of temporal frequencies. The model predicts that such curves should become bimodal at very low temporal frequencies, and this prediction is supported by the data. We measured temporal frequency tuning curves at a wide range of spatial frequencies and found that the shifts in peak tuning frequency are consistent with the model. Finally, we used a drifting sinusoidal grating additively combined with a random texture pattern moving at the neuron's preferred speed and direction to probe the shape of the hypothesized linear weighting function used to construct a model MT pattern cell from V1 afferents. Conclusions: The model is able to account for the data, which may in turn be used to better specify such details as the shape of the linear weighting function in the MT stage.

Original languageEnglish (US)
Pages (from-to)S916
JournalInvestigative Ophthalmology and Visual Science
Volume37
Issue number3
StatePublished - Feb 15 1996

ASJC Scopus subject areas

  • Ophthalmology
  • Sensory Systems
  • Cellular and Molecular Neuroscience

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