title: Analysis of complex neural circuits with nonlinear multidimensional hidden state models.
abstract: A universal need in understanding complex networks is the identification of individual information channels and their mutual interactions under different conditions. In neuroscience, our premier example, networks made up of billions of nodes dynamically interact to bring about thought and action. Granger causality is a powerful tool for identifying linear interactions, but handling nonlinear interactions remains an unmet challenge. We present a nonlinear multidimensional hidden state (NMHS) approach that achieves interaction strength analysis and decoding of networks with nonlinear interactions by including latent state variables for each node in the network. We compare NMHS to Granger causality in analyzing neural circuit recordings and simulations, improvised music, and sociodemographic data. We conclude that NMHS significantly extends the scope of analyses of multidimensional, nonlinear networks, notably in coping with the complexity of the brain.
authors.affiliation: McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139;
authors.forename: Alexander
authors.initials: A
authors.lastname: Friedman
authors.affiliation: McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139;
authors.forename: Alanna F
authors.initials: AF
authors.lastname: Slocum
authors.affiliation: McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139;
authors.forename: Danil
authors.initials: D
authors.lastname: Tyulmankov
authors.affiliation: McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139;
authors.forename: Leif G
authors.initials: LG
authors.lastname: Gibb
authors.affiliation: Program on Crisis Leadership, Ash Center for Democratic Governance & Innovation, Kennedy School of Government, Harvard University, Cambridge, MA 02138; Department of Management, Faculty of Social Sciences, Bar-Ilan University, Ramat Gan, 5290002, Israel; Homeland Security Program, The Institute for National Security Studies, Tel Aviv, 6997556, Israel;
authors.forename: Alex
authors.initials: A
authors.lastname: Altshuler
authors.affiliation: McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139;
authors.forename: Suthee
authors.initials: S
authors.lastname: Ruangwises
authors.affiliation: McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139;
authors.forename: Qinru
authors.initials: Q
authors.lastname: Shi
authors.affiliation: McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139;
authors.forename: Sebastian E
authors.initials: SE
authors.lastname: Toro Arana
authors.affiliation: McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139;
authors.forename: Dirk W
authors.initials: DW
authors.lastname: Beck
authors.affiliation: Department of Musicology and Ethnomusicology, Boston University, Boston, MA 02215.
authors.forename: Jacquelyn E C
authors.initials: JE
authors.lastname: Sholes
authors.affiliation: McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139; graybiel@mit.edu.
authors.forename: Ann M
authors.initials: AM
authors.lastname: Graybiel
mesh_terms: D000465:Algorithms; D000818:Animals; D001921:Brain; D003657:Decision Making; D006801:Humans; D008297:Male; D008390:Markov Chains; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D009474:Neurons; D051381:Rats; D020318:Rats, Long-Evans
keywords: causal analysis; decoding; functional connectivity; hidden Markov models; machine learning