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Adrienne L. Fairhall
Researcher at University of Washington
Publications - 93
Citations - 5080
Adrienne L. Fairhall is an academic researcher from University of Washington. The author has contributed to research in topics: Stimulus (physiology) & Population. The author has an hindex of 33, co-authored 85 publications receiving 4352 citations. Previous affiliations of Adrienne L. Fairhall include Weizmann Institute of Science & Marine Biological Laboratory.
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Efficiency and ambiguity in an adaptive neural code.
TL;DR: In this paper, the authors examine the dynamics of a neural code in the context of stimuli whose statistical properties are themselves evolving dynamically, and show that adaptation to these statistics occurs over a wide range of timescales-from tens of milliseconds to minutes.
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Fractional differentiation by neocortical pyramidal neurons.
Brian Nils Lundstrom,Matthew H. Higgs,Matthew H. Higgs,William J. Spain,William J. Spain,Adrienne L. Fairhall +5 more
TL;DR: It is found that single rat neocortical pyramidal neurons adapt with a time scale that depends on the time scale of changes in stimulus statistics, which is consistent with fractional order differentiation.
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Shifts in coding properties and maintenance of information transmission during adaptation in barrel cortex.
TL;DR: The results suggest that adaptation enhances tactile representations in primary somatosensory cortex, where they could directly influence perceptual decisions.
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Mosquitoes use vision to associate odor plumes with thermal targets
TL;DR: Using a three-dimensional tracking system, it is shown that rather than gating heat sensing, the detection of CO₂ actually activates a strong attraction to visual features, which guides the mosquitoes to potential hosts where they are close enough to detect thermal cues.
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Timescales of inference in visual adaptation.
TL;DR: The dynamics of adaptation in the responses of mouse retinal ganglion cells depend on stimulus history and it is found that the retina exploits information contained in properties of the stimulus beyond the mean and variance to adapt more quickly when possible.