Integrated Multiscale Modeling of the Nervous System: Predicting Changes in Hippocampal Network Activity by a Positive AMPA Receptor Modulator

• Published in: IEEE transactions on biomedical engineering 2011-10, Vol.58 (10), p.3008-3011
• Main Authors: Bouteiller, Jean-Marie C., Allam, Sushmita L., Hu, Eric Y., Greget, Renaud, Ambert, Nicolas, Keller, Anne Florence, Bischoff, Serge, Baudry, Michel, Berger, Theodore W.
• Format: Article
• Language: English
• Subjects: Ampakine; bioinformatics; Biological system modeling; Brain modeling; CA1 Region, Hippocampal - cytology; CA1 Region, Hippocampal - physiology; Complexity theory; Computational Biology - methods; Computational modeling; Computer Science; Computer Simulation; EONS; glutamate receptor modulator; Modeling and Simulation; Models, Neurological; Modulation; multi-scale; Nerve Net - cytology; Nerve Net - physiology; Nervous system; neuronal firing; Neurons; Receptors, AMPA - metabolism; RHENOMS; synapse model; synaptic integration
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/TBME.2011.2158605

One of the fundamental characteristics of the brain is its hierarchical organization. Scales in both space and time that must be considered when integrating across hierarchies of the nervous system are sufficiently great as to have impeded the development of routine multilevel modeling methodologies. Complex molecular interactions at the level of receptors and channels regulate activity at the level of neurons; interactions between multiple populations of neurons ultimately give rise to complex neural systems function and behavior. This spatial complexity takes place in the context of a composite temporal integration of multiple, different events unfolding at the millisecond, second, minute, hour, and longer time scales. In this study, we present a multiscale modeling methodology that integrates synaptic models into single neuron, and multineuron, network models. We have applied this approach to the specific problem of how changes at the level of kinetic parameters of a receptor-channel model are translated into changes in the temporal firing pattern of a single neuron, and ultimately, changes in the spatiotemporal activity of a network of neurons. These results demonstrate how this powerful methodology can be applied to understand the effects of a given local process within multiple hierarchical levels of the nervous system.