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Network formation and reorganization
During development, neurons are able to form
synaptic connections when their axonal and dendritic arbors come in close proximity
to each other. Although many signaling mechanisms, such as chemical attraction and repulsion,
are involved in steering neuronal arbors prior to synapse formation, the extent to which accidental appositions between
axons and dendrites can account for synaptic
connectivity remains unclear.
To explore what synaptic connectivity patterns can emerge from neuronal
morphology alone, we generate in our simulation framework
NETMORPH
(Koene et al., 2009)
cortical networks of morphologically realistic neurons among which synapses
are formed when axonal and dendritic branches come within a threshold distance of each other.
Synapse formation is also modulated by
electrical activity. In particular, the formation of axonal boutons and dendritic spines,
the pre- and postsynaptic parts of synapses, is regulated by electrical activity—not
only during development but also in the adult brain.
For example, persistent alterations in afferent activity to the cortex, such as those caused by retinal lesions, trigger
extensive spine dynamics, leading to a massive reorganization of cortical synaptic connectivity.
The principles governing these structural changes are, however, poorly understood.
From the way electrical activity influences neurite outgrowth
and spine and bouton formation, we hypothesize that neurons try to maintain their average
level of electrical activity at a particular set-point (homeostatic regulation).
To examine whether homeostatic rules for spine and bouton formation (homeostatic structural plasticity)
may guide the development and reorganization of cortical synaptic connectivity, we use our model
of structural plasticity (MSP; Butz et al., 2008;
Van Ooyen, 2011),
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 activity is above the set-point or below a certain minimum level. Spine and bouton formation depend
solely on the neuron's own activity level, and synapses are formed by merging spines
and boutons independently of activity. Recently, MSP has been implemented in the neuronal network simulator
NEST
to study structural plasticity in large-scale neuronal networks
(Diaz-Pier et al., 2016).
MSP, which simulates the dynamics of spine and bouton formation, was
partly derived from a less detailed model of homeostatic structural plasticity
that uses circular neuritic fields to emulate the activity-dependent growth
of axons and dendrites. This latter model was used
to study network assembly (e.g., Van Ooyen et al., 1995) and
retinal mosaic formation (Eglen et al., 2000;
see movies)
and more recently also the development of self-organized criticality
(Tetzlaff et al., 2010;
Kossio et al., 2018).
A new book chapter
(Van Ooyen and Butz-Ostendorf, 2019)
reviews model studies that show that
activity-dependent neurite outgrowth can build critical networks.
- Homeostatic structural plasticity can build critical networks
Van Ooyen, A., and Butz-Ostendorf, M. (2019). In: Tomen, N., Herrmann, J. M., and Ernst, U., eds.
The Functional Role of Critical Dynamics in Neural Systems. Springer, pp. 117-137.
[Abstract]
[Full text: PDF]
- Is lesion-induced synaptic rewiring driven by activity homeostasis?
Butz-Ostendorf, M., and Van Ooyen, A. (2017). In: Van Ooyen, A., and Butz-Ostendorf, M., eds. The Rewiring Brain: A Computational Approach to Structural Plasticity in the Adult Brain. San Diego: Academic Press, pp. 71-92.
[Abstract]
[Full text: PDF]
- Network formation through activity-dependent
neurite outgrowth: a review of a simple model of homeostatic structural plasticity
Van Ooyen, A. (2017). In: Van Ooyen, A., and Butz-Ostendorf, M., eds. The Rewiring Brain: A Computational Approach to Structural Plasticity in the Adult Brain. San Diego: Academic Press, pp. 95-121.
[Abstract]
[Full text: PDF]
- A detailed model of homeostatic structural plasticity based on dendritic spine and
axonal bouton dynamics
Butz-Ostendorf, M., and Van Ooyen, A. (2017). In: Van Ooyen, A., and Butz-Ostendorf, M., eds. The Rewiring Brain: A Computational Approach to Structural Plasticity in the Adult Brain. San Diego: Academic Press, pp. 155-176.
[Abstract]
- Adult neurogenesis and synaptic rewiring in the hippocampal dentate gyrus
Van Ooyen, A., Teuchert-Noodt, G., Grafen, K., and Butz-Ostendorf, M. (2017). In: Van Ooyen, A., and Butz-Ostendorf, M., eds. The Rewiring Brain: A Computational Approach to Structural Plasticity in the Adult Brain. San Diego: Academic Press, pp. 389-408.
[Abstract]
- Editorial: Anatomy and plasticity in large-scale brain models
Butz, M., Schenck, W., and Van Ooyen, A. (2016).
Frontiers in Neuroanatomy doi: 10.3389/fnana.2016.00108.
[Abstract]
[Full text: PDF]
- NETMORPH
Van Ooyen, A., and Van Pelt, J. (2015).
Scholarpedia 10(6): 10213.
[Full text]
- Homeostatic structural plasticity can account for topology changes
following deafferentation and focal stroke
Butz, M., Steenbuck, I. D., and Van Ooyen, A. (2014).
Frontiers in Neuroanatomy doi: 10.3389/fnana.2014.00115.
[Abstract]
[Full text: PDF]
[Supplementary figure: PDF]
- Axonal and dendritic density field estimation from incomplete
single-slice neuronal reconstructions
Van Pelt, J., Van Ooyen, A., and Uylings, H. B. M. (2014).
Frontiers in Neuroanatomy doi: 10.3389/fnana.2014.00054.
[Abstract]
[Full text: PDF]
[Supplementary figures: PDF]
- Homeostatic structural plasticity increases the efficiency of small-world networks
Butz, M., Steenbuck, I. D., and Van Ooyen, A. (2014).
Frontiers in Synaptic Neuroscience doi: 10.3389/fnsyn.2014.00007.
[Abstract]
[Full text: PDF]
- A morpho-density approach to estimating neural connectivity
McAssey, P. M., Bijma, F., Tarigan, B., Van Pelt, J.,
Van Ooyen, A.*, and De Gunst, M. A.* (2014) (* joint senior authors).
PloS ONE 9(1): e86526. doi:10.1371/journal.pone.0086526.
[Abstract]
[Full text: PDF]
- Independently outgrowing neurons and geometry-based synapse
formation produce networks with realistic synaptic connectivity
Van Ooyen, A., Carnell, A., De Ridder, S., Tarigan, B., Mansvelder, H. D., Bijma, F.,
De Gunst, M., and Van Pelt, J. (2014).
PloS ONE 9(1): e85858. doi:10.1371/journal.pone.0085858.
[Abstract]
[Full text: PDF]
- Neuronal arborizations, spatial innervation, and emergent network connectivity
Van Pelt, J., Uylings, H. B. M., and Van Ooyen, A. (2014). In: Cuntz, H., Remme, M. W. H., and Torben-Nielsen, B., eds.
The Computing Dendrite. New York: Springer, pp. 61-78.
[Abstract]
[Full text: PDF]
- Estimating neuronal connectivity from axonal and dendritic
density fields
Van Pelt, J., and Van Ooyen, A. (2013).
Frontiers in Computational Neuroscience doi: 10.3389/fncom.2013.00160.
[Abstract]
[Full text: PDF]
[Supplementary data: PDF]
- A simple rule for dendritic spine and axonal bouton formation
can account for cortical reorganization after focal retinal lesions
Butz, M., and Van Ooyen, A. (2013).
PloS Computational Biology 9(10): e1003259. doi:10.1371/journal.pcbi.1003259.
[Abstract]
[Full text: PDF]
[Supporting figure: PDF]
[Corrected figures 8 and 12: PDF]
[Science Daily]
- An algorithm for finding candidate synaptic sites in computer generated networks of
neurons with realistic morphologies
Van Pelt, J., Carnell, A., De Ridder, S., Mansvelder, H. D., and Van Ooyen, A. (2010).
Frontiers in Computational Neuroscience doi: 10.3389/fncom.2010.00148.
[Abstract]
[Full text: PDF]
- A simple rule for axon outgrowth and synaptic competition generates
realistic connection lengths and filling fractions
Kaiser, M., Hilgetag, C. C., and Van Ooyen, A. (2009).
Cerebral Cortex 19: 3001-3010.
[Abstract]
[Full text: PDF]
[Supplementary data: PDF]
- Activity-dependent structural plasticity
Butz, M., Worgotter, F., and Van Ooyen, A. (2009).
Brain Research Reviews 60: 287-305.
[Abstract]
[Full text: PDF]
- A model for cortical rewiring following deafferentation
and focal stroke
Butz, M., Van Ooyen, A., and Worgotter, F. (2009).
Frontiers in Computational Neuroscience doi: 10.3389/neuro.10.010.2009.
[Abstract]
[Full text: PDF]
- NETMORPH: a framework for the stochastic generation
of large scale neuronal networks with realistic neuron morphologies
Koene, R. A., Tijms, B., Van Hees, P., Postma, F., De Ridder, A., Ramakers, G. J. A,
Van Pelt, J., and Van Ooyen, A. (2009).
Neuroinformatics 7: 195-210.
[Abstract]
[Full text: PDF]
- Inverse relationship between adult hippocampal cell proliferation and synaptic
rewiring in the dentate gyrus
Butz, M., Teuchert-Noodt, G., Grafen, K., and Van Ooyen, A. (2008).
Hippocampus 18: 879-898.
[Abstract]
[Full text: PDF]
- Homeostasis at multiple spatial and temporal scales
Houweling, A. R., and Van Ooyen, A. (2008).
In: Suire, L., ed.
New Encyclopedia of Neuroscience, in press
[Abstract]
[Full text: PDF]
- Activity-dependent neurite outgrowth: implications for network
development and neuronal morphology
Van Ooyen, A., Van Pelt, J., Corner, M. A., and Kater, S. B. (2003).
In: Van Ooyen, A., ed.
Modeling Neural Development.
Cambridge, MA: MIT Press, pp. 111-132.
[Abstract]
[Full text: PDF]
- The role of calcium signaling in early axonal and dendritic morphogenesis
of rat cerebral cortex neurons under non-stimulated growth conditions
Ramakers, G. J. A., Avci, B., Van Hulten, P., Van Ooyen, A., Van Pelt, J., Pool, C. W., and Lequin, M. B. (2001).
Dev. Brain Res. 126: 163-172.
[Abstract]
[Full text: PDF]
- Lateral cell movement driven by dendritic interactions
is sufficient to form retinal mosaics
Eglen, S. J., Van Ooyen, A., and Willshaw, D. J. (2000).
Network: Computation in Neural Systems 11: 103-118.
[Abstract]
[Full text: PDF]
- Modelling retinal mosaic development
with dendritic outgrowth and lateral cell movement
Eglen, S. J., and Van Ooyen, A. (1999).
In: Artificial Neural Networks - ICANN 1999,
9th International Conference on Artificial Neural Networks, Edinburgh, UK,
September 1999, pp. 377-382.
[Abstract]
[Full text: PDF]
- Effects of inhibition on neural
network development through activity-dependent neurite outgrowth
Van Oss, C., and Van Ooyen, A. (1997).
J. Theor. Biol. 185: 263-280.
[Abstract]
[Full text: PDF]
- Network connectivity changes through activity-dependent neurite
outgrowth
Van Ooyen, A., Pakdaman, K., Houweling, A. R., Van Pelt, J., and Vibert, J.-F. (1996).
Neural Processing Letters 3: 123-130.
[Abstract]
[Full text: PDF]
- Complex periodic behaviour in
a neural network model with activity-dependent neurite outgrowth
Van Ooyen, A, and Van Pelt, J. (1996).
J. Theor. Biol. 179: 229-242.
[Abstract]
[Full text: PDF]
- Growth cone dynamics
and activity-dependent processes in neuronal network development
Van Pelt, J., Van Ooyen, A., and Corner, M. A. (1996). In:
Mize, R. R., and Erzurumlu, R. S., eds. Neural Development and Plasticity,
Progress in Brain Research 108. Amsterdam: Elsevier, pp. 333-346.
[Abstract]
[Full text: PDF]
- Activity-Dependent Neurite Outgrowth: Implications for Network Development
Van Ooyen, A. (1995). PhD thesis, University of Amsterdam, The Netherlands, 197 pp.
[Contents]
[Full text: PDF]
[Full text per chapter: see contents]
- Implications of
activity-dependent neurite outgrowth for neuronal morphology and
network development
Van Ooyen, A., Van Pelt, J., and Corner, M. A. (1995).
J. Theor. Biol. 172: 63-82.
[Abstract]
[Full text: PDF]
- Activity-dependent neurite outgrowth
in a simple neural network model including excitation and inhibition
Van Oss, C., and Van Ooyen, A. (1995). In:
Proceedings ESANN 1995, European Symposium on Artificial
Neural Networks, Brussel, Belgium, April 1995, pp. 87-92.
[Abstract]
[Full text: PDF]
- Activity-dependent neural network development
Van Ooyen, A. (1994) (invited review).
Network: Computation in Neural Systems 5: 401-423.
[Abstract]
[Full text: PDF]
- Activity-dependent neurite outgrowth and neural network development
Van Ooyen, A., and Van Pelt, J. (1994). In: Van Pelt, J.,
Corner, M. A., Uylings, H. B. M., and Lopes da Silva, F. H., eds.
The Self-Organizing Brain: From Growth Cones to Functional Networks,
Progress in Brain Research 102. Amsterdam: Elsevier, pp. 245-259.
[Abstract]
- Activity-dependent outgrowth
of neurons and overshoot phenomena in developing neural networks
Van Ooyen, A., and Van Pelt, J. (1994).
J. Theor. Biol. 167: 27-43.
[Abstract]
[Full text: PDF]
- Hysteresis in a two-neuron network: basic characteristics
and physiological implications
Pakdaman, K., Van Ooyen, A., Houweling, A. R., and Vibert, J.-F. (1994).
In: Marinaro, M., and Morasso, P. G., eds.
Artificial Neural Networks - ICANN 1994, 4th International Conference
on Artificial Neural Networks, Sorrento, Italy, pp. 162-165.
[Abstract]
[Full text: PDF]
- Complex patterns of
oscillations in a neural network model with activity-dependent
outgrowth
Van Ooyen, A., and Van Pelt, J. (1994). In: Marinaro, M., and Morasso, P. G., eds.
Artificial Neural Networks - ICANN 1994, 4th International Conference
on Artificial Neural Networks, Sorrento, Italy, pp. 146-149.
[Abstract]
[Full text: PDF]
- Implications of activity-dependent
neurite outgrowth for developing neural networks
Van Ooyen, A., and Van Pelt, J. (1993). In: Gielen, S., and Kappen, B., eds.
Artificial Neural Networks - ICANN 1993, 3rd International Conference
on Artificial Neural Networks, Amsterdam, The Netherlands, pp. 177-182.
[Abstract]
[Full text: PDF]
- Phase transitions, hysteresis and overshoot in developing neural networks
Van Ooyen, A., and Van Pelt, J. (1992). In: Aleksander, I., and Taylor, J., eds.
Artificial Neural Networks 2 - ICANN 1992, 2nd International Conference
on Artificial Neural Networks, Brighton, UK, pp. 907-910.
[Abstract]
[Full text: PDF]
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