Accepted manuscript
A network model for activity-dependent sleep regulation
Journal of theoretical biology, Vol.253(3), pp.462-468
2008
Handle:
https://hdl.handle.net/2376/114551
PMCID: PMC2592512
PMID: 18511082
Abstract
We develop and characterize a dynamical network model for activity-dependent sleep regulation. Specifically, in accordance with the activity-dependent theory for sleep, we view organism sleep as emerging from the local sleep states of functional units known as cortical columns; these local sleep states evolve through integration of local activity inputs, loose couplings with neighboring cortical columns, and global regulation (e.g. by the circadian clock). We model these cortical columns as coupled or networked activity-integrators that transition between sleep and waking states based on thresholds on the total activity. The model dynamics for three canonical experiments (which we have studied both through simulation and system-theoretic analysis) match with experimentally observed characteristics of the cortical-column network. Most notably, assuming connectedness of the network graph, our model predicts the recovery of the columns to a synchronized state upon temporary overstimulation of a single column and/or randomization of the initial sleep and activity-integration states. In analogy with other models for networked oscillators, our model also predicts the possibility for such phenomena as mode-locking.
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Details
- Title
- A network model for activity-dependent sleep regulation
- Creators
- Sandip Roy - Department of Electrical Engineering, Washington State University, P.O. Box 642752, Pullman, WA 99164, USAJames M Krueger - Department of Veterinary Comparative Anatomy, Pharmacology and Physiology (VCAPP), Washington State University, P.O. Box 646520, Pullman, WA 99164, USADavid M Rector - Department of Veterinary Comparative Anatomy, Pharmacology and Physiology (VCAPP), Washington State University, P.O. Box 646520, Pullman, WA 99164, USAYan Wan - Department of Electrical Engineering, Washington State University, P.O. Box 642752, Pullman, WA 99164, USA
- Publication Details
- Journal of theoretical biology, Vol.253(3), pp.462-468
- Academic Unit
- School of Electrical Engineering and Computer Science; Department of Integrative Physiology and Neuroscience
- Publisher
- Elsevier Ltd
- Number of pages
- 7
- Identifiers
- 99900547938401842
- Language
- English
- Resource Type
- Accepted manuscript