2015/05/15 by Marius Buibas, Buibas, Marius, Gabriel A. Silva +1
Biochemistry, Genetics and Molecular Biology · Computer Science · Neuroscience · Physics and Astronomy · #Data Analysis #FOS: Biological sciences #FOS: Physical sciences #Functional Brain Connectivity Studies #Neural Networks and Applications #Neural dynamics and brain function #Neurons and Cognition (q-bio.NC) #Statistics and Probability (physics.data-an) #physics.data-an #q-bio.NC
paper · pdf · doi:10.48550/arxiv.1505.03964
9 pages
arxiv created 2015/05/15 · openalex publication_date 2015/05/15 · arxiv updated 2015/05/18 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
Cellular neural circuit and networks consisting of interconnected neurons and glia are ulti- mately responsible for the information processing associated with information processing in the brain. While there are major efforts aimed at mapping the structural and (electro)physiological connectivity of brain networks, such as the White House BRAIN Initiative aimed at the devel- opment of neurotechnologies capable of high density neural recordings, theoretical and compu- tational methods for analyzing and making sense of all this data seem to be further behind. Here, we propose and provide a summary of an approach for calculating effective connectivity from experimental observations of neuronal network activity. The proposed method operates on network-level data, makes use of all relevant prior knowledge, such as dynamical models of individual cells in the network and the physical structural connectivity of the network, and is broadly applicable to large classes of biological and non-biological networks.