Arjen van Ooyen

Computational Neuroscience

The brain is one of the most complex systems that exist. To get a true insight into its functioning and development, experimental studies need to be complemented by mathematical and computational modeling. The field of neuroscience that uses models to help to understand the nervous system is called computational neuroscience. My group operates in this field along the following research lines.

Research Lines
1. Information processing in the brain depends on spatiotemporal patterns of neuronal activity. We build computational models of large scale neuronal networks to simulate these patterns and to study their dependence on structural and functional synaptic connectivity. In particular, we investigate the role of inhibition and short-term synaptic plasticity in synchronization and spread of network activity.

2. The cortex is organized in neuronal microcircuits, consisting of different types of excitatory and inhibitory cells with a characteristic connectivity pattern. We build computational models of stereotypical microcircuits to explore how the fine structure of synaptic connectivity contributes to the dynamics of neuronal activity. In particular, we investigate how short-term synaptic plasticity and synapse localization influence the input-output characteristics of neuronal microcircuits.

3. Statistical analysis of spatiotemporal patterns of neuronal activity. We explore whether long-range temporal correlations observed in ongoing brain activity reflect working memory and attentional processes. How do these correlations arise, and how do they depend on structural and functional connectivity in neuronal networks? In collaboration with Dr. Mathisca de Gunst, we develop new statistical methods for the analysis of experimentally observed activity patterns in cortical brain slices of mice.

4. Learning requires modifications in the strength of synapses between neurons. However, none of the existing learning theories provides a strategy for modifying synaptic strength that is both powerful and biologically realistic. In collaboration with Dr. Pieter Roelfsema, we investigate how attentional processes mediated by feedback connections can improve reinforcement learning algorithms.

5. Studying the function of the mature nervous system can benefit greatly from knowing how the nervous system develops, since many plasticity mechanisms that operate during development are also involved in memory and learning. Topics of interest are modeling biophysical mechanisms of neurite outgrowth, homeostatic plasticity mechanisms in network development, and synaptic competition in the development of neuronal connectivity.

For further information on these research lines, see my website

Arjen van Ooyen
Center for Neurogenomics and Cognitive Research (CNCR) Dept. of Experimental Neurophysiology VU University Amsterdam De Boelelaan 1085, room C-454 1081 HV Amsterdam The Netherlands Phone: +31 (0)20 598 70 90 Fax: +31 (0)20 598 71 12 Room: C-454 E-mail: arjen.van.ooyen@cncr.vu.nl Website:www.bio.vu.nl/enf/vanooyen
Computational Neuroscience The brain is one of the most complex systems that exist. To get a true insight into its functioning and development, experimental studies need to be complemented by mathematical and computational modeling. The field of neuroscience that uses models to help to understand the nervous system is called computational neuroscience. My group operates in this field along the following research lines. Research Lines 1. Information processing in the brain depends on spatiotemporal patterns of neuronal activity. We build computational models of large scale neuronal networks to simulate these patterns and to study their dependence on structural and functional synaptic connectivity. In particular, we investigate the role of inhibition and short-term synaptic plasticity in synchronization and spread of network activity. 2. The cortex is organized in neuronal microcircuits, consisting of different types of excitatory and inhibitory cells with a characteristic connectivity pattern. We build computational models of stereotypical microcircuits to explore how the fine structure of synaptic connectivity contributes to the dynamics of neuronal activity. In particular, we investigate how short-term synaptic plasticity and synapse localization influence the input-output characteristics of neuronal microcircuits. 3. Statistical analysis of spatiotemporal patterns of neuronal activity. We explore whether long-range temporal correlations observed in ongoing brain activity reflect working memory and attentional processes. How do these correlations arise, and how do they depend on structural and functional connectivity in neuronal networks? In collaboration with Dr. Mathisca de Gunst, we develop new statistical methods for the analysis of experimentally observed activity patterns in cortical brain slices of mice. 4. Learning requires modifications in the strength of synapses between neurons. However, none of the existing learning theories provides a strategy for modifying synaptic strength that is both powerful and biologically realistic. In collaboration with Dr. Pieter Roelfsema, we investigate how attentional processes mediated by feedback connections can improve reinforcement learning algorithms. 5. Studying the function of the mature nervous system can benefit greatly from knowing how the nervous system develops, since many plasticity mechanisms that operate during development are also involved in memory and learning. Topics of interest are modeling biophysical mechanisms of neurite outgrowth, homeostatic plasticity mechanisms in network development, and synaptic competition in the development of neuronal connectivity. For further information on these research lines, see my website
Group Members: Dr. Ronald van Elburg Dr. Klaus Linkenkaer-Hansen Dr. Randal Koene (NIH) Rick Jansen (VU, Mathematics)	Postdoc Postdoc Postdoc PhD	www.vanelburg.net www.bio.vu.nl/enf/linkenkaer
Publications: All my publications can be found on my website. The full text of most papers is available in PDF. Abstracts in HTML are available for all papers.