Two important big resulta have been achieved:
Demonstrate RSC contribution to context-related flexible learning
We have tested RSC contribution to flexible learning by using several behavioral paradigms. We have verified that RSC is not needed to retrieve a memory but is necessary to update it.
Given the well-known contribution of RSC to navigation, we have also tested its involvement in the formation of allocentric or egocentric frames to represent spatial information and its role in switching from one to the other.
The egocentric frame is based on subject-to-object relations and leads to the creation of self-centered representations. An egocentric frame is fundamental in visuomotor control, as the planning and execution of an action needs the representation of the target location in relation to the body. On the other hand, the allocentric frame is supposed to be acquired later in life and is founded on world-based coordinates; within this reference, locations are described using object-to-object relationships, independently from the subject’s point of view. An increasing number of cognitive models are focusing on the relation between egocentric and allocentric frames, trying to explain how these processes combine to provide healthy and efficient spatial abilities. We have designed and validated an “egocentric” version of the MWM task in which correct navigation to the hidden platform only requires internal representation of space and sequential memory of previous turns. We have tested the capability of mice to acquire this kind of spatial memory when RSC was silenced. We have repeated the same measures for the classical or “allocentric” version of the MWM and, finally, we have tested the ability of animals to switch from one frame to the other in normal conditions or when RSC function was impaired.
Interestingly, RSC contribution to flexible learning is only evident when the task has a strong contextual component.
RSC guides behavior by pairing appropriate behavioral strategy to learning
The classical paradigm of the MWM task can provide much more information than simply the latency to reach the hidden platform or swimming speed or spatial representation. I have realized, indeed, that the behavioral strategy used by animals when looking for their goal is at least as valuable as the previously mentioned parameters. For this reason, in this part of my work I have focused on the detailed analysis of searching strategies in the MWM in order to pair RSC function with the selection of specific behaviors.
A training trial in a MWM task consists of an unconstrained search by a mouse of the entire area of the pool within a limited period of time. A submerged underwater platform provides an escape from water. A mouse naive to the water maze initially tends to swim along the wall of the pool (thigmotaxis). In later training trials, a mouse finds an escape platform by chance while making occasional searches of the inner area of the pool (random search). As training progresses, a mouse begins to search the whole surface area of the pool selectively scanning the inner area containing the escape platform (scanning). The development of a spatial memory for the platform location is reflected by a directed or focal search of a target quadrant, or by the direct swim to the platform. Occasionally, when the mouse is well adapted to the task but spatial representation is still not advanced a mouse may intermittently perform a circling behavior at the right distance from the walls of the pool (chaining). Thus, random search and scanning do not require a knowledge of any spatial relationship in the MWM and can be included in a more general category called “global search strategies”. By contrast, direct or focal search and direct swim imply an awareness of spatial relationships between platform position and distal cues and can be included into the “spatial search strategies” category. Chaining is an exception as external cues are still not used in order to find the platform but a knowledge of the distance of the platform from the pool walls is already present. It is a transient phase during behavior but mice go back to chaining very quickly whenever their memory about platform position is challenged. Dividing strategies in the global search or spatial search main categories allows a more quantitative method to combine the choice of specific search strategies to the level of spatial representation.
This detailed analysis of mouse behavior helped me demonstrate that RSC is crucially involved in assigning the correct match between degree of learning and behavioral execution.
