Tisztelt Kollegák,
2012. június 13-án szerdán du. 5 órakor Prof. Alex Pouget (University of Geneva) előadást
tart a CEU Kongitívtudományi tanszékén "Not noisy, just wrong" címmel. Részletek
a levél alján.
Alex Pouget az egyik legnevesebb elméleti kutató a systems neuroscience területén, aki
(számos kísérletes csoporttal együttműködve) alapvető felfedezéseket tett többek között a
neurális variabilitás szerepével kapcsolatban. Csak az elmúlt egy év terméséből:
Beck JM, Ma WJ, Pitkow X, Latham PE, Pouget A. Not noisy, just wrong: the role of
suboptimal inference in behavioral variability. Neuron. 74:30-9, 2012
Fetsch CR, Pouget A, DeAngelis GC, Angelaki DE. Neural correlates of reliability-based cue
weighting during multisensory integration. Nat Neurosci. 15:146-54, 2011.
Moreno-Bote R, Knill DC, Pouget A. Bayesian sampling in visual perception. Proc Natl Acad
Sci USA. 108:12491-6, 2011.
Ma WJ, Navalpakkam V, Beck JM, Berg R, Pouget A. Behavior and neural basis of near-optimal
visual search. Nat Neurosci. 14:783-90, 2011.
Bejjanki VR, Beck JM, Lu ZL, Pouget A. Perceptual learning as improved probabilistic
inference in early sensory areas. Nat Neurosci. 14:642-8, 2011.
Minden érdeklődőt szeretettel várunk.
Lengyel Máté
--
Mate Lengyel, PhD
Computational and Biological Learning Lab
Cambridge University Engineering Department
Trumpington Street, Cambridge CB2 1PZ, UK
tel: +44 (0)1223 748 532, fax: +44 (0)1223 332 662
email: m.lengyel(a)eng.cam.ac.uk
web:
www.eng.cam.ac.uk/~m.lengyel
*****
The CEU Department of Cognitive Science cordially invites you to a talk as part of its
Departmental Colloquium series
by
Alexandre Pouget
Dept of Basic Neuroscience
Universite de Geneve
Date: Wednesday, June 13, 2012 - 17:00 - 18:30
Location: Department of Cognitive Science, CEU, Frankel Leó út 30-34., Room G15
Title: Not noisy, just wrong
Abstract:
Behavior varies from trial to trial even when the stimulus is maintained as constant as
possible. One of the most important questions in neuroscience concerns the origin of this
variability. In many models, it is attributed to noise within the brain, often in the form
of independent Poisson variability in spike trains, or variations thereof. Here, we show
that suboptimal inference caused by the deterministic approximations of the statistical
structure of the sensory inputs provides another major cause of variability. Importantly,
we argue that in most tasks of interest, and particularly complex ones, this cause of
variability is likely to be the dominant component of behavioral variability. This
perspective explains a variety of intriguing observations, including why variability
appears to be larger on the sensory than on the motor side, and why our sensors are
sometimes surprisingly unreliable.