English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Accurate perception of motion depends critically on accurate estimation of retinal motion speed. Here we first analyse natural image movies to determine the optimal space-time receptive fields (RFs) for encoding local motion speed in a particular direction, given the constraints of the early visual system. Next, from the RF responses to natural stimuli, we determine the neural computations that are optimal for combining and decoding the responses into estimates of speed. The computations show how selective, invariant speed-tuned units might be constructed by the nervous system. Then, in a psychophysical experiment using matched stimuli, we show that human performance is nearly optimal. Indeed, a single efficiency parameter accurately predicts the detailed shapes of a large set of human psychometric functions. We conclude that many properties of speed-selective neurons and human speed discrimination performance are predicted by the optimal computations, and that natural stimulus variation affects optimal and human observers almost identically.

Optimal speed estimation in natural image movies predicts human performance