Thesis Pauline ROSSEL

Current models of visual perception agree that vision is a proactive process. This implies that visual perception consists in constantly matching the characteristics of a visual input (e.g., two bright dots on a misty road) to expectations, built on past experiences and learnt regularities in the environment (e.g., high probability to encounter a car in the opposite direction). Such proactive processes would therefore facilitate the processing of frequently encountered stimuli. Indeed, past studies have shown that an expected stimulus (e.g., a soccer player on a soccer field) is categorized more quickly than unexpected ones (e.g., a soccer player in a kitchen). They would also be particularly useful in cases where the visual input is noisy or ambiguous and an analysis purely based on it would be inefficient (e.g., in the example above, the analysis of two bright dots would not enable to recognize the stimulus as a car, without prior expectations). Neurobiologically, this “predictive coding” of visual information has been modelled as the permanent interaction between different levels of the processing hierarchy of prediction (i.e., expected features of the input) and prediction error signals (i.e., unexpected features allowing to update expectations), which relative weights would vary according to visual constraints (e.g., prediction signals would weight more when the visual input is noisy while prediction error signals would weight more when the stimulus is unambiguous and expectations are invalid). However, how expectations modulate the processing of visual information and influence perception remains debated. For example, it has been suggested that prediction signals facilitate the processing of expected visual features by increasing the sensitivity of neurons tuned to these features, which would then be perceived as sharper. On the other hand, unexpected stimuli would result in increased prediction error signals, and thus increased activity in neuron populations tuned to unexpected features, leading to a more intense percept of these features. Recent experimental data support these assumptions but they have never been systematically tested.
The aim of the present PhD project is therefore to precise the mechanisms by which prior knowledge and expectations do influence visual perception, using perceptual judgment tasks on various stimuli characteristics (e.g., sharpness, vividness…) and according to different factors such as the availability and/or validity of expectations and the reliability of the visual inputs in behavioral studies. These studies will be performed in healthy individuals and may be followed by eye-tracking studies, in order to examine how expectations influence visual attention, as well as electroencephalography studies in order to assess the time course of these mechanisms at the cerebral level.

Encadrantes :
- Carole PEYRIN -  carole.peyrinuniv-grenoble-alpes.fr (carole[dot]peyrin[at]univ-grenoble-alpes[dot]fr)
- Louise KAUFFMANN - louise.kauffmanngmail.com (louise[dot]kauffmann[at]gmail[dot]com)

Keywords : électroencéphalographie,codage prédictif,perception visuelle