Neuroinformatics course
Name. Neuroinformatics
Code. 470724
Staff. Dr. A. van Ooyen
Credits. 6 ECTS
Period. March until June, Thursday afternoons from 16.00-19.00.
Aim. To provide master students with the essentials of modeling neurons and neuronal networks and of analyzing spatiotemporal patterns of neuronal activity.
Content. The new interdisciplinary field of neuroinformatics combines neuroscience with disciplines such as computer science, mathematics, physics and theoretical biology to advance and deepen our understanding of the nervous system. In particular, neuroinformatics is concerned with computational and mathematical modeling of neural systems, at all levels of biological organization, from synapse to cognition; computational and statistical analysis of complex experimental data; and developing and applying data bases and data-mining tools. During this course, we will address the following topics: (1) Modeling of single neurons and ion channels (single- and multiple-compartment models), synapses and synaptic plasticity (developmental plasticity and network formation, long- and short- term synaptic plasticity), neuronal networks (microcircuits, large-scale neuronal networks, associative memory, oscillations and synchrony), and learning and cognition (unsupervised, supervised, and reinforcement learning). (2) Approaches for analyzing spatial and temporal patterns of neuronal activity (EEG measurements, multi-electrode recordings, voltage-sensitive dye activity). (3) Use of the simulation packages NEURON and Matlab. (4) Introduction to numerical methods for solving differential equations, and phase-plane and bifurcation analysis of differential equations.
Form of tuition. Lectures, demonstrations, practical assignments. An important part of the course consists of computer experiments on modeling and data analysis.
Literature. Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems, Peter Dayan and L. F. Abbott, The MIT Press, Cambridge, Massachusetts, 2001, ISBN 0-262-04199-5, or later editions. And optional: Modeling Neural Development, Arjen van Ooyen (editor), The MIT Press, Cambridge, Massachusetts, 2003, ISBN 0-262-22066-0. Research and review papers will be handed out during the course.
Mode of assessment. Written examinations; open-end questions. Practical assignments and papers during the course.
Entry requirements. Participants of the Master of Neurosciences at the VU University Amsterdam have priority. In addition, when capacity allows, we will accommodate students from other master programmes who have at least a bachelor’s degree in Biology, Biomedical Sciences, or Psychology with profile Biological Psychology or Neuropsychology, with an affinity for mathematics and computer programming. Also students with a bachelor’s degree in Physics, Mathematics and alike, with an interest in neurobiology, can enter this course.
Remarks. Language: tuition in English. Application: course coordination, arjenX.vanX.ooyenX@gmail.com (remove Xs to get correct address). The course can be followed in parallel with other courses and internships, including an internship in Neuroinformatics. In 2010/2011, I attented the University Teaching course, which I completed very successfully. The video recordings that were made of me teaching the neuroinformatics course are now used in University Teaching courses as an example of good teaching practice.