How to keep a plan in mind: mouse neurons do it by sharing the job among members of a big population

May 25, 2012

Today in the Systems Neuroscience Journal Club at Cold Spring Harbor, my student John Sheppard presented a Nature paper by Chris Harvey,  Philip Coen & David Tank entitled, “Choice-specific sequences in parietal cortex during a virtual-navigation decision task.” In the paper, the authors used optical imaging to monitor the responses of neurons in the posterior parietal cortex, an association area in the rodent brain that has many similarities to primate area LIP. As discussed in a posting on Action Potential, this article provided a different view of sustained activity compared to previous recordings in monkeys because the authors were able to measure the activity of many neurons at once. Further, they used a “virtual reality” setup to display visual images that updated as the animal moved. Although the animal wasn’t freely moving, he was able to navigate down a long maze by running on a ball.

One of the most intriguing findings from this paper is this: although the population as a whole remained active through much of the long delay period imposed on each trial, the activity of individual cells was only transiently elevated. This is quite different from area LIP in monkeys where, at least on a memory guided saccade task, the same neurons are active throughout a 1000 ms delay. Although this could be a species difference, I would put my money on the possibility that the difference is in the cells that were recorded. Optical imaging targets cells in more superficial layers, while the sharp electrodes used to record from primate LIP can be advanced to deeper layers. Further, because of the size of the electrodes, and the speed at which they are advanced, experiments with sharp electrodes may tend to be restricted to a narrower population of cells compared to those recorded with optical imaging, or even tetrodes. An intriguing possibility is that the transiently active cells from the imaging study might provide inputs that are temporally integrated and reflected in the output of thecells recorded in LIP.

In any event, the paper was great to read and provoked a lively discussion: see pictures below of Gonzalo Hugo arguing with John about error trials and Glenn Turner questioning whether errors versus corrects is really the key comparison.



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Fairhall lab

Computational neuroscience at the University of Washington

Pillow Lab Blog

Neural Coding and Computation Lab @ Princeton University

Churchland lab

Perceptual decision-making at Cold Spring Harbor

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