Event:

I will discuss two recent works in which we explored the dynamics of neural networks in the brain that represent low dimensional, continuous variables.

The first work is concerned with a form of smooth eye motion called fixational drift. This motion is tiny compared to saccades, but is highly consequential for high-acuity vision. Hence, its role in visual perception has been extensively studied throughout the past several decades. Nevertheless, the mechanisms that are responsible for fixational drift have remained completely obscur. We recently showed using neural recordings from primates (in collaboration with Mati Joshua at the Hebrew University) that most of the motion originates in central neural circuitry in the brain, upstream of the oculomotor nuclei. We propose a neural network mechanism that naturally explains both the magnitude and the detailed statistics of the motion. The mechanism has to do with random drifts in the internally represented eye position within the oculomotor integrator, a memory circuit which is responsible for maintaining a steady gaze between saccades.

In the second work (in collaboration with the Moser lab, NTNU), we examined for the first time the joint dynamics of grid cells in the entorhinal cortex of rats that belong to different modules, using high density silicon probe recordings. It has been argued on theoretical grounds (by us and others) that in order for grid cells to implement together an efficient coding scheme for position, network mechanisms must coordinate the activity of different grid cell modules when the internal representation of position in the brain deviates from the true position of the animal. In order to test whether such a mechanism exists, we decoded the joint activity of hundreds of grid cells, recorded in animals that were foraging in the dark.

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