[koglist] Alex Pouget eloadasa

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.