Aller au contenuAller au menuAller à la recherche

Peggy Seriès‘The Power of Expectations in Perception and Decision-Making’

Abstract :


Expectations are known to greatly affect our experience of the world.
A growing idea in computational neuroscience is that perception and cognition can be successfully described using Bayesian inference models and that the brain is 'Bayes-optimal' under some constraints. In this context, expectations are particularly interesting, because they can be viewed as prior beliefs in the statistical inference process. Our aim is to clarify how expectations affect perception and decision-making, how long they take to build up or be unlearned, how complex they can be, and how they can inform us on the type of computations and learning that the brain performs.

I will start by reviewing recent psychophysical and modeling work from my team,showing how expectations about visual motion direction can be quickly and unconsciously learned through statistical learning, leading to perceptual biases and hallucinations in human observers (Chalk, Seitz & Series, Journal of Vision 2010).

I will also present recent work showing that the prior belief that visual objects are
static or move slowly rather than fast (Weiss, Adelson & Simoncelli, Nature Neuroscience, 2002), which is thought to reflect the long-term statistics of natural stimuli and to explain a number of visual illusions such as the "aperture problem", can be quickly unlearned and inverted (Sotiropoulos, Seitz & Series, Current Biology 2011).

I will finally describe another line of work in decision-making where we look at optimism as a prior belief on future reward.

Selected publications

S. Yarrow, E. Challis and P. Seriès (2012). Fisher and Shannon information in finite neural populations. Neural Computation. in press.
G. Sotiropoulos, A. Seitz and P. Seriès (2011). Changing expectations about speed alters perceived motion direction. Current Biology.8; 21(21) - R 883-4. -- Supplemental Information -- Movie of Stimulus
D. Reichert, P. Seriès and Amos Storkey (2011). Neuronal Adaptation for Sampling-Based Probabilistic Inference in Perceptual Bistability, Advances in Neural Information Processing Systems 24. To appear.
B. Tijms, P. Seriès, D. Willshaw, and S. Lawrie (2011), Extracting Networks from individual grey matter MRI . Cerebral Cortex .21(12).
Cortes JM, Marinazzo D, Series P, Oram MW, Sejnowski TJ, van Rossum MC (2011), The effect of neural adaptation on population coding accuracy. Journal of Computational Neurosicence . 21(12).

Scientific focus :

The aim of my work is to understand the relationship between the activity of single neurons and populations of neurons in sensory cortex with the perceptual world we experience.
More specifically, using simulations and theoretical methods, I am trying to understand how information is encoded and transmitted in the activity of single neurons and populations of neurons, and how it can be optimally decoded and related to behavioral performance/ conscious perception.
More recently, I've also become interested in more cognitive functions, such as attention, decision-making and mental disorders.

Françoise Dellu-Hagedorn de l'INCIA