The cortical circuits of associative learning (SomatoLearning)
The cortical circuits of associative learning
Start date: 01 Mar 2008,
End date: 29 Feb 2012
The neocortex decodes sensory information from the external world. Cortical circuits are organized in columns, each tuned to one specific sensory stimulus. A growing body of evidences suggests that the neocortex also participates to learning. In associative learning, a sensory stimulus that is initially neutral to a mouse, like the deflection of a whisker, acquires the emotional value of another sensory stimulus, like a foot shock, when the two are presented together. After conditioning, the mouse freezes at the deflection of that whisker alone. This form of learning correlates with changes in the barrel cortex, the region that contains the somatotopic representation of whiskers: more neurons become responsive to the conditioned whisker, regardless of their column. The emphasis on the representation of a learned stimulus could let the animal know what signal to “look for” in order to adopt rapidly the appropriate behavior next time it occurs. The paradigms inducing a conditioned behavior and the consequences for the sensory maps in the brain have been well described. Still, the specific cortical circuits involved in this phenomenon remain largely unknown. The cortical connections in the barrel cortex are segregated into two pathways, lemniscal and paralemniscal. Their distinct properties suggest they have different roles in associative learning. The recent optical technology laser scanning photostimulation permits studying the detailed diagram of functional neuronal circuits in brain slices. I will combine this approach with behavioral training to unveil the mechanisms of associative learning. I will identify the connections that are changed after conditioning and describe their plasticity mechanisms. I will also compare the ontogeny of cortical circuits with that of associative learning in “normal” animals as well as in animal models for mental retardation. This approach will bring important insights into the relationships between neuronal circuits and behavior.
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