Dynamic Reorganization of Neuronal Activity Patterns in Parietal Cortex

Publication date: Available online 17 August 2017
Source:Cell
Author(s): Laura N. Driscoll, Noah L. Pettit, Matthias Minderer, Selmaan N. Chettih, Christopher D. Harvey
Neuronal representations change as associations are learned between sensory stimuli and behavioral actions. However, it is poorly understood whether representations for learned associations stabilize in cortical association areas or continue to change following learning. We tracked the activity of posterior parietal cortex neurons for a month as mice stably performed a virtual-navigation task. The relationship between cells' activity and task features was mostly stable on single days but underwent major reorganization over weeks. The neurons informative about task features (trial type and maze locations) changed across days. Despite changes in individual cells, the population activity had statistically similar properties each day and stable information for over a week. As mice learned additional associations, new activity patterns emerged in the neurons used for existing representations without greatly affecting the rate of change of these representations. We propose that dynamic neuronal activity patterns could balance plasticity for learning and stability for memory.

Graphical abstract

Teaser

Contrary to the idea that representations of sensory stimuli or the activity patterns that accompany motor actions are stable, neuronal representations in the parietal cortex can change across days, possibly allowing for the tradeoff between stable encoding of information and flexibility for incorporating new information.


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