Computational Analysis of Spatiotemporal Patterns of Activity in Neuronal Networks


The project consists of three subprojects:
A
Development of a macroscopic neuronal network model with realistic functional and structural connectivity to simulate neuronal activity in cortical brain slices and cultured neuronal networks.
This subproject will be carried out in the Neurons & Networks Research Group at the Netherlands Institute for Brain Research, Amsterdam.
B
Development of statistical methods for analysis and comparison of experimentally observed spatiotemporal activity patterns.
This subproject will be carried out in the Stochastic Modelling and Statistical Analysis Research Group at the Department of Mathematics, Faculty of Sciences of the Vrije Universiteit, Amsterdam.
C
Development of a neuronal microcircuit model composed of neurons with full morphological complexity to investigate how the fine structure of synaptic connectivity contributes to the dynamics of neuronal activity.
This subproject will be carried out in the Experimental Neurophysiology Research Group at the Faculty of Biology, Vrije Universiteit, Amsterdam.


Summary
Information processing in the brain, in particular in the cortex, is based on spatiotemporal patterns of electrical activity in neuronal networks. Recently introduced experimental techniques allow the monitoring of these patterns in great detail by simultaneously recording of neuronal activity from a large number of locations in the network (e.g., in cortical brain slices and cultured neuronal networks). To be able to analyze and interpret the flood of data these new techniques produce, we intend to develop (i) mathematical and statistical methods for analyzing spatiotemporal patterns of neuronal activity, and (ii) computational models of neuronal networks to simulate these patterns and understand them in relation to structural and functional connectivity within the network. Goals (i) and (ii) will be pursued in close interaction, whereby the computational models are used to help to develop statistical methods, and the statistical methods in turn are used to test whether the model can capture the characteristics of the experimentally observed patterns. An essential part of (ii) is the development of a stochastic model for the generation of network connectivity and its variation. The methods and models will be validated with the extensive data we have on spatiotemporal patterns in cortical brain slices and cultured neuronal networks. Ultimately, these methods and models are indispensable in the search for key genetic regulators of network development, network activity and animal behavior. In particular, the data on spatiotemporal activity in brain slices obtained from normal (wild type) versus mutant mice (with a known genetic mutation) will be compared.

Summary

Introduction (in Dutch)
Analyse van spatiotemporele patronen van activiteit in neuronale netwerken.
Informatieverwerking in de hersenen is het resultaat van complexe electrische wisselwerkingen in netwerken van zeer grote aantallen gekoppelde zenuwcellen. Recentelijk ontwikkelde technieken maken het mogelijk om de elektrische activiteit in hersenplakjes af te leiden van een groot aantal zenuwcellen tegelijkertijd. Daarmee kunnen we nu zeer goed de spatiotemporele patronen van activiteit meten die ten grondslag liggen aan de werking van de hersenen. Om de op deze wijze verkregen data te analyseren willen we in dit project (i) statistische methoden ontwikkelen voor het beschrijven en analyseren van activiteits patronen, en (2) computer modellen ontwikkelen waarmee we de activiteit in hersenplakjes kunnen simuleren. Deze statistische methoden en computer modellen zullen ons inzicht geven in hoe de gemeten activiteits patronen afhangen van het netwerk en de eigenschappen van de onderlinge verbindingen tussen zenuwcellen. Onze methoden en modellen zijn essentieel bij het zoeken naar genen die, via hun invloed op de verbindingen tussen zenuwcellen, de activiteitspatronen in de hersenen veranderen en daarmee het gedrag van mens of dier be´nvloeden. In het bijzonder zullen onze methoden en modellen gebruikt worden om activiteitspatronen in normale muizen te vergelijken met die in muizen met een bekende genetische mutatie.