Searching for collective behavior in a small brain

With only 302 neurons, Caenorhabditis elegans is one of the simplest organisms that exhibits complex neuronal functions such as locomotion, sensing, and associative learning. In larger networks, it is widely believed that function emerges through collective behavior of many interconnected neurons. The development of tools that allow simultaneous recording from a large fraction of all neurons in C. elegans creates the opportunity to ask if such collective behavior is universal, reaching down to the smallest brains. We analyze preliminary experiments on 50+ neurons by building the maximum entropy model that matches the mean activity and pairwise correlations among these neurons. To capture the graded nature of the neuronal responses, we assign each neuron multiple states. These models successfully predict higher order correlations, as well as the activity of single neurons conditional on the rest of the network. The effective energy landscape is glassy, with patterns of activity moving from one basin to another at rates related to the apparent energy barriers separating them. Finally, the parameters of the model indicate that the network operates close to criticality.