To understand this apparent discrepancy, we recorded 59 MT neurons in anaesthetized macaques, and measured their responses to a broad-band compound grating stimulus presented at a broad range of velocities and contrasts. We presented the same stimuli to all neurons, adjusted only for receptive field location and preferred direction. As in previous studies with awake macaques, reducing contrast shifted the preferred velocity of most neurons toward slower speeds, as well as reducing response amplitude and tuning bandwidth. We constructed a population vector velocity decoder that operates on a neural population that includes the measured set of neurons, along with a "mirror" set tuned for the opposite direction. Using the synthetic population that represents both positive and negative velocities allows the decoder to capture the key characteristics of human velocity estimation and discrimination, including speed biases at low stimulus contrast. Specifically, we show that maintained discharge in such an MT population has an effect on the percept that is analogous to that of the slow speed prior characterized in Bayesian models of velocity perception (Stocker and Simoncelli, 2006).

We also examined optimal linear decoders, and found that they produce nearly veridical percepts when operating on the full neural population, assuming that variability in the individual neuronal responses is statistically independent. Restricting these decoders to operate on a small set of model neurons whose response properties are obtained by averaging the tuning curves of similarly tuned neurons leads to qualitatively good matches to the perceptual data, but only when the decoder is optimized for stimuli drawn from naturalistic prior distributions over speed and contrast. This suggests that the response characteristics of the MT population are matched to the statistics of the natural world, in that linear decoding can approximate optimal Bayesian inference.

References:

• CC Pack, JN Hunter, and RT Born. Contrast dependence of suppressive influences in cortical area MT of alert macaque. J. Neurophysiol., 93:1809-1815, 2005.
• Interactions between speed and contrast tuning in the middle temporal area: Implications for the neural code for speed. B Krekelberg, RJ van Wezel, and TD Albright. J. Neurosci, 26(35):8988-98, Aug 2006.
• AA Stocker and EP Simoncelli, Noise characteristics and prior expectations in human visual speed perception. Nature Neuroscience, 9(4):578-585, Apr 2006.