NCC 2014 - Neural Connectomics Challenge : From Imaging to Connectivity

Understanding the brain structure and some of its alterations caused by disease, is key to accompany research on the treatment of epilepsy and Alzheimer’s disease and other neuropathologies, as well as gaining understanding of the general functioning of the brain and its learning capabilities. At the neural level, recovering the exact wiring of the brain (connectome) including nearly 100 billion neurons, having on average 7000 synaptic connections to other neurons, is a daunting task. NoTraditional neuroanatomic methods of axonal tracing cannot scale up to very large networks. Could there be alternative methods recovering neural network structures from patterns of neural activity?
Today’s cutting edge optical imaging of neural activity (using fluorescent calcium indicator proteins) provides a tool to monitor the activity of tens of thousands of neurons simultaneously. Mathematical algorithms capable of discovering network structures are faced with the challenge of solving a new inverse problem: recover the neural network structure of a living system given the observation of a very large population of neurons. Monitoring changes in effective connectivity patterns of a network in action during behavior promises to advance our understanding of learning and intelligence. This challenge will stimulate the advancement of research on network structure learning algorithms from neurophysiological data, including causal discovery methods.
The goal of the challenge is to reconstruct the structure of a neural network from temporal patterns of activities of neurons. The activities are obtained from video recording of calcium fluorescence imaging.