About

I am an independent scientist and self-employed editor/proofreader affiliated with a proofreading company. I am trained as a (mathematical) biologist and specialized in computational neuroscience (CV). My long-term research interest is the role of homeostatic structural plasticity in the development and reorganization of neuronal networks. My hobbies include field biology, geology, and drawing.

E-mail: arjenX.vanX.ooyenX@gmail.com (remove Xs)
Websites: my home page, LinkedIn, Academia, Flickr

Computational neuroscience

The interdisciplinary field of computational neuroscience combines neuroscience with disciplines such as computer science, mathematics, and physics to advance and deepen our understanding of the nervous system. In particular, computational neuroscience is concerned with modeling neural systems and analyzing complex experimental data. In our main research line, we use mathematical and computational models to study how the need of neurons to maintain their average electrical activity at a particular level (homeostatic regulation) affects the development and reorganization of neuronal networks.

Homeostatic structural plasticity

Cognitive function strongly depends on the organization of synaptic connectivity in cortical networks. Synaptic connectivity determines how information is transmitted and what spatiotemporal patterns of electrical activity can arise.

During development, neurons form synapses when their growing axonal and dendritic arbors come in close proximity to each other. Strikingly, neurons retain their capacity for growth and synapse formation (structural plasticity) in the adult brain. Dendritic spines and axonal boutons, the pre- and postsynaptic parts of synapses, appear and disappear frequently, accompanied by synapse formation and elimination. Lasting alterations in afferent activity to the cortex, such as those caused by retinal lesions, trigger extensive spine dynamics, leading to massive structural adaptations in cortical synaptic connectivity.

The principles governing structural plasticity are, however, poorly understood. Our central hypothesis is that the attempt of neurons to maintain their average electrical activity at a particular level (homeostatic regulation) is a main organizing principle of neuronal networks. We conjecture that homeostatic regulation not only guides the formation of networks but also drives the compensatory structural changes following loss of input caused by lesions, stroke, and neurodegeneration.

To explore the potential implications of homeostatic structural plasticity for the development and reorganization of neuronal networks, we use network models in which each neuron creates new spines and boutons when its level of electrical activity is below a homeostatic set-point and deletes spines and boutons when its activity is above the set-point. Synapses are formed by merging spines and boutons.

Understanding the principles of structural plasticity may inspire novel treatments for stimulating functional repair after brain damage and neurodegeneration.

To read more about homeostatic structural plasticity, see network formation. Further, see neurite outgrowth, axon guidance, and synaptic competition.

Other research lines

Other research lines include the impact of neuronal morphology and synaptic connectivity on activity dynamics.

To read more, see firing patterns, synapse strengths, neuronal oscillations, and learning and memory.

Publications

Publications are listed under the various research topics as well as on my publications page. The full text of most papers is available in PDF format (please read copyright notice). Publications can also be downloaded from ResearchGate and Academia. For citations to my work, see Google Scholar.

Announcements

A new book chapter (Van Ooyen and Butz-Ostendorf, 2019) reviews model studies that show that activity-dependent neurite outgrowth, a form of homeostatic structural plasticity, can build critical networks.

Our model of homeostatic structural plasticity (Butz and Van Ooyen, 2013; Butz et al., 2014) has been implemented in NEST (see also Diaz-Pier et al., 2016).

Listed below are three key publications on modeling neural development and structural plasticity:

• Van Ooyen, A. (2011). Using theoretical models to analyse neural development. Nature Reviews Neuroscience 12: 311-326. (invited review)
  [Abstract] [Full text: PDF] [Corrigendum: PDF]

• Van Ooyen, A., and Butz-Ostendorf, M., eds. (2017). The Rewiring Brain: A Computational Approach to Structural Plasticity in the Adult Brain. San Diego: Academic Press.
  [Contents] [Full text: see preview at Elsevier Store or Google Books]

  

  In The Rewiring Brain, the editors bring together, for the first time, contemporary modeling studies that investigate the implications of structural plasticity for brain function and pathology. Starting with an experimental background on structural plasticity in the adult brain, the book covers computational studies on homeostatic structural plasticity, the impact of structural plasticity on cognition and cortical connectivity, the interaction between synaptic and structural plasticity, neurogenesis-related structural plasticity, and structural plasticity in neurological disorders.
  

• Van Ooyen, A., ed. (2003). Modeling Neural Development. Cambridge, MA: MIT Press.
  [Contents and book reviews]

  

  Modeling Neural Development is one of the first books to show how computational and mathematical models are used to study the development of the nervous system. The book's fourteen chapters follow loosely the chronology of neural development, from neurulation to the formation of ocular dominance columns. Each chapter contains an overview of the biology, a review of the modeling efforts, and some perspectives on future theoretical and experimental work.