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Neural mechanisms of unsupervised visual learning

Primates, including humans, are sensitive to temporal regularities in their sensory environment and this is affected in various neurological and psychiatric diseases. The extraction of statistical regularities is referred to as “statistical learning”. Currently, it is unknown which areas – outside temporal cortex - represent visual statistical learning related signals, predictive signals and their violations in macaques. Unraveling the underlying network in macaques is necessary to obtain a mechanistic understanding of these phenomena by using invasive methods with high spatiotemporal resolution, which is the goal of the present project. We will investigate, combining fMRI, single unit recordings and causal perturbation techniques, the neural correlates of visual statistical learning in macaques which aims to clarify the neural mechanisms of statistical learning.

Date:9 Jul 2018  →  Today
Keywords:statistical learning, single unit recording
Disciplines:Neurosciences, Biological and physiological psychology, Cognitive science and intelligent systems, Developmental psychology and ageing
Project type:PhD project