Churchland lab

Last week I attended the Champalimaud Neuroscience in Lisbon, Portugal. I heard many fantastic talks, including those from Susana Lima, Dora Angelaki, Michale Fee and Matteo Carandini. I also got updates from many investigators with labs at the Champalimaud, a number of whom are thinking deeply about body movements: how to track them and what they tell us about underlying neural processes. I spoke with Megan Carey and some of her team who are investigating how sensory inputs are processed differently in the brains of moving versus stationary animals.

I also spoke in detail with Joe Paton whose lab has been tackling questions about how future decisions affect current movements. This approach builds on an existing body of work suggesting that a signature of developing decisions is sometimes evident in premotor areas, and even in the movements themselves. The animal’s in Joe’s lab are freely moving so getting handle on their complex full-body movements is a challenge. The standard approach is to track one or two parameters that might turn out to be important- head angle, for instance. Thiago Gouvêa along with Asma Motiwala, graduate students in Joe’s Lab, came up with an approach that is fundamentally different: rather than trying to guess what the right body parameter might be, they image the whole animal and then reduce the
dimensionality of the large collection of images that results (see below, and also this video).

Imaged body positions where the rat will ultimately go left (red) and will ultimately go right (green) are overlaid.

This analysis will inform them which dimensions are the right ones. Because the approach doesn’t commit the investigator to a particular movement parameter, it allows for the fact that animals might be different from each other, or that a single animal might change over time: for instance, early in training showing anticipatory movements that are suppressed when the animal is an expert at the task. This is a new project, but has the potential to lead to a novel method of evaluating movements during decisions. Down the line, the movements could be related to neurons in different parts of the brain, and could help to interpret how those neurons contribute to a developing choice.