Computational Modeling And Machine Learning Methods In Neurodevelopment And Neurodegeneration From Basic Research To Clinical Applications

Computational Modeling and Machine Learning Methods in Neurodevelopment and Neurodegeneration: from Basic Research to Clinical Applications

Computational models and machine-learning methods are increasingly valuable tools to shed light on the dynamics that govern information processing in the nervous system, as well as their disruption in pathological conditions. A variety of techniques has been used to understand how networks of neurons in the brain encode, elaborate and transmit information about the external world, and how this information influences decision-making and behavior. Structural and functional abnormalities in the above-mentioned networks can lead to a wide range of brain disorders. Recent advances in brain simulation and machine-learning techniques, together with progress in the neuroimaging field, have been essential for bridging the different spatial scales in the brain and uncovering the processes underlying cognitive, motor and behavioral impairment in neurodevelopmental and neurodegenerative disorders.

Neuronal Development and Degeneration

Computational Psychiatry

Psychiatrists and neuroscientists discuss the potential of computational approaches to address problems in psychiatry including diagnosis, treatment, and integration with neurobiology. Modern psychiatry is at a crossroads, as it attempts to balance neurological analysis with psychological assessment. Computational neuroscience offers a new lens through which to view such thorny issues as diagnosis, treatment, and integration with neurobiology. In this volume, psychiatrists and theoretical and computational neuroscientists consider the potential of computational approaches to psychiatric issues. This unique collaboration yields surprising results, innovative synergies, and novel open questions. The contributors consider mechanisms of psychiatric disorders, the use of computation and imaging to model psychiatric disorders, ways that computation can inform psychiatric nosology, and specific applications of the computational approach. Contributors Susanne E. Ahmari, Huda Akil, Deanna M. Barch, Matthew Botvinick, Michael Breakspear, Cameron S. Carter, Matthew V. Chafee, Sophie Denève, Daniel Durstewitz, Michael B. First, Shelly B. Flagel, Michael J. Frank, Karl J. Friston, Joshua A. Gordon, Katia M. Harlé, Crane Huang, Quentin J. M. Huys, Peter W. Kalivas, John H. Krystal, Zeb Kurth-Nelson, Angus W. MacDonald III, Tiago V. Maia, Robert C. Malenka, Sanjay J. Mathew, Christoph Mathys, P. Read Montague, Rosalyn Moran, Theoden I. Netoff, Yael Niv, John P. O'Doherty, Wolfgang M. Pauli, Martin P. Paulus, Frederike Petzschner, Daniel S. Pine, A. David Redish, Kerry Ressler, Katharina Schmack, Jordan W. Smoller, Klaas Enno Stephan, Anita Thapar, Heike Tost, Nelson Totah, Jennifer L. Zick