首页 | 本学科首页   官方微博 | 高级检索  
   检索      


BrainSignals Revisited: Simplifying a Computational Model of Cerebral Physiology
Authors:Matthew Caldwell  Tharindi Hapuarachchi  David Highton  Clare Elwell  Martin Smith  Ilias Tachtsidis
Institution:1Department of Medical Physics and Biomedical Engineering, University College London, London, UK;2Centre for Mathematics and Physics in the Life Sciences and Experimental Biology, University College London, London, UK;3Neurocritical Care Unit, University College Hospitals, London, UK;Georgia State University, UNITED STATES
Abstract:Multimodal monitoring of brain state is important both for the investigation of healthy cerebral physiology and to inform clinical decision making in conditions of injury and disease. Near-infrared spectroscopy is an instrument modality that allows non-invasive measurement of several physiological variables of clinical interest, notably haemoglobin oxygenation and the redox state of the metabolic enzyme cytochrome c oxidase. Interpreting such measurements requires the integration of multiple signals from different sources to try to understand the physiological states giving rise to them. We have previously published several computational models to assist with such interpretation. Like many models in the realm of Systems Biology, these are complex and dependent on many parameters that can be difficult or impossible to measure precisely. Taking one such model, BrainSignals, as a starting point, we have developed several variant models in which specific regions of complexity are substituted with much simpler linear approximations. We demonstrate that model behaviour can be maintained whilst achieving a significant reduction in complexity, provided that the linearity assumptions hold. The simplified models have been tested for applicability with simulated data and experimental data from healthy adults undergoing a hypercapnia challenge, but relevance to different physiological and pathophysiological conditions will require specific testing. In conditions where the simplified models are applicable, their greater efficiency has potential to allow their use at the bedside to help interpret clinical data in near real-time.
Keywords:
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号