Professor of Physics; Concurrent Professor of Computer Science and Engineering
Living systems are far-from-equilibrium physical systems which, by taking up matter, energy and information from the environment perform a series of specific functions that are essential for their survival, at least over some finite time-scales. Function, however, is not a property of a system or a subsystem; it characterizes the relationship and the interactions of the system with other subsystems and the environment. By mapping out the network of interactions between the components of a biological system, the processes it supports and its information processing modalities (coding, decoding, error correction, etc.), we hope to discover the fundamental principles of biological organization. My current research focuses on neuronal networks in the mammalian brain, in particular on the existence of architectural network invariants at the interareal cortical level and its implications on information processing and disease. Other research interests within biophysics include energy landscapes (e.g., of short peptides), population and evolutionary dynamics, species diversity, origins of life and collective problem solving by extended biological populations.
- "The Mouse Cortical Connectome, Characterized by an Ultra-Dense Cortical Graph, Maintains Specificity by Distinct Connectivity Profiles" Gamanut, R.; Kennedy, H.; Toroczkai, Z.; Ercsey-Ravasz, M.; Van Essen, D.C.; Knoblauch, K.; Burkhalter, A. Neuron 2018, 97(3), 698-715. DOI: 10.1016/j.neuron.2017.12.037
- "Spatial Embedding and Wiring Cost åÊConstrain the Functional Layout of the Cortical Network of Rodents and Primates" Horvath, S.; Gamanut, R,; Ercsey-Ravasz, M.; Magrou, L.; Gamanut, B.; Van Essen, D.C.; Burkhalter, A.; Knoblauch, K.; Toroczkai, Z.; Kennedy, H. PLOS Biology 2016, 14(7), e1002512.
- "Cortical high-density counter-stream architectures" Markov, N.T.; Ercsey-Ravasz, M.; Van Essen, D.C.; Knoblauch, K.; Toroczkai, Z.; Kennedy, H. Science 2013, 342(6158), 1238406.
- "A predictive network model of cerebral cortical connectivity based on a distance rule" Ercsey-Ravasz, M.; Markov, N.T.; Lamy, C.; Van Essen, D.C.; Knoblauch, K.; Toroczkai, Z.; Kennedy, H. Neuron 2013, 80(1), 184-197.