The Retrosplenial Cortex Spatial Transformation Network
Description
Special Seminar with Andrew Alexander, PhD
Zoom Link: https://mit.zoom.us/j/95854431055 (MIT credentials required)
The Retrosplenial Cortex Spatial Transformation Network
Spatial transformation is a critical neural computation in which the locations of stimuli in the external world, experienced via disparate sensory processes, are registered across distinct coordinate systems. During navigation, information about the configuration of external features is initially acquired via sensory modalities in egocentric coordinates, but is then transformed into a map-like internal model of locations, landmarks, and goals relative to the external world (i.e. allocentric coordinate frame) that can subsequently be utilized to guide actions. Beyond spatial cognition, spatial transformations are critical for the formation of contextually rich episodic memories. In my primary research program, I have examined the role of the retrosplenial cortex in spatial transformations. To this end, I have paired navigation tasks specifically designed to probe spatial relationships with multi-site in vivo electrophysiological recordings in awake, freely moving rats. This work demonstrated that retrosplenial ensembles possess the computational building blocks to mediate transformations between egocentric and allocentric coordinate frames, including the discovery of a subpopulation of retrosplenial cortex neurons that map the position of external features in egocentric coordinates. I have also explored how these signals could be synchronized with hippocampal processing in a state-dependent manner via network oscillations. Future work will utilize projection-specific neuroimaging and optogenetics to characterize and perturb dynamics in these neural circuits in both navigation and memory tasks, including during performance of a novel target pursuit assay designed to test the flexibility of navigation computations.
Zoom Link: https://mit.zoom.us/j/95854431055 (MIT credentials required)