Modeling Brain Energy Metabolism and Function: A Multiparametric Monitoring Approach

Vatov, Larisa; Kizner, Z. I.; Ruppin, Eytan; Meilin, Sigal; Manor, Tamar; Mayevsky, Avraham

doi:10.1007/s11538-005-9008-1

Cited by 22 publications

(13 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A next step for modeling SD in ischemia is analyzing both detailed (Dronne et al, 2006(Dronne et al, , 2008 and more phenomenological models (Revett et al, 1998;Vatov et al, 2006;Chapuisat et al, 2010) that include energy availability, to identify the key factors that determine frequency and duration of SDs. Reducing SD after stroke and global ischemia is a potential target for therapy (Lauritzen et al, 2011).…”

Section: Discussionmentioning

confidence: 99%

How does spreading depression spread? Physiology and modeling

Zandt

Haken

Putten³

et al. 2015

Reviews in the Neurosciences

View full text Add to dashboard Cite

AbstractSpreading depression (SD) is a wave phenomenon in gray matter tissue. Locally, it is characterized by massive redistribution of ions across cell membranes. As a consequence, there is sustained membrane depolarization and tissue polarization that depress any normal electrical activity. Despite these dramatic events, SD remains difficult to observe in humans noninvasively, which, for long, has slowed advances in this field. The growing appreciation of its clinical importance in migraine and stroke is therefore consistent with an increasing need for computational methods that tackle the complexity of the problem at multiple levels. In this review, we focus on mathematical tools to investigate the question of spread and its two complementary aspects: What are the physiological mechanisms and what is the spatial extent of SD in the cortex? This review discusses two types of models used to study these two questions, namely, Hodgkin-Huxley type and generic activator-inhibitor models, and the recent advances in techniques to link them.

show abstract

Section: Discussionmentioning

confidence: 99%

How does spreading depression spread? Physiology and modeling

Zandt

Haken

Putten³

et al. 2015

Reviews in the Neurosciences

View full text Add to dashboard Cite

show abstract

“…Finally, the following features have been neglected: cerebral autoregulation [47], cerebral oedema [11], emboli advection and blockage of the microcirculation [9,10], spreading of ischaemic tissue damage [79,80], etc. These phenomena are time-dependent and often rely on nonlinear processes.…”

Section: Limitationsmentioning

confidence: 99%

A porous circulation model of the human brain for in silico clinical trials in ischaemic stroke

et al. 2020

View full text Add to dashboard Cite

The advancement of ischaemic stroke treatment relies on resource-intensive experiments and clinical trials. In order to improve ischaemic stroke treatments, such as thrombolysis and thrombectomy, we target the development of computational tools for in silico trials which can partially replace these animal and human experiments with fast simulations. This study proposes a model that will serve as part of a predictive unit within an in silico clinical trial estimating patient outcome as a function of treatment. In particular, the present work aims at the development and evaluation of an organ-scale microcirculation model of the human brain for perfusion prediction. The model relies on a three-compartment porous continuum approach. Firstly, a fast and robust method is established to compute the anisotropic permeability tensors representing arterioles and venules. Secondly, vessel encoded arterial spin labelling magnetic resonance imaging and clustering are employed to create an anatomically accurate mapping between the microcirculation and large arteries by identifying superficial perfusion territories. Thirdly, the parameter space of the problem is reduced by analysing the governing equations and experimental data. Fourthly, a parameter optimization is conducted. Finally, simulations are performed with the tuned model to obtain perfusion maps corresponding to an open and an occluded (ischaemic stroke) scenario. The perfusion map in the occluded vessel scenario shows promising qualitative agreement with computed tomography images of a patient with ischaemic stroke caused by large vessel occlusion. The results highlight that in the case of vessel occlusion (i) identifying perfusion territories is essential to capture the location and extent of underperfused regions and (ii) anisotropic permeability tensors are required to give quantitatively realistic estimation of perfusion change. In the future, the model will be thoroughly validated against experiments.

show abstract

“…Nevertheless, recent mathematical models support central aspects of the Selfish-Brain theory (Conrad et al 2009;Langemann 2007;. Furthermore, the impact of brain energy on pathological conditions such as ischemia is emphasized by means of detailed modeling of the brain energy metabolism (Vatov et al 2006). The investigated dynamical system (Göbel et al 2010) is a further development of former mathematical models including the brain as major controller and heavy consumer, cf.…”

Section: Introductionmentioning

confidence: 98%

Systemic investigation of a brain-centered model of the human energy metabolism

Göbel

Langemann

2010

Theory Biosci.

View full text Add to dashboard Cite

The regulation of the human energy metabolism is crucial to ensure the functionality of the entire organism. Deregulations may lead to severe pathologies such as diabetes mellitus and obesity. The decisive role of the brain as active controller and heavy consumer in the complex whole-body energy metabolism is the object of recent research. Latest studies suggest the priority of the brain energy supply in the competition between brain and body periphery for the available energy resources. In this paper, a systemic investigation of the human energy metabolism is presented which consists of a compartment model including periphery, blood, and brain as well as signaling paths via insulin, appetite, and ingestion. The presented dynamical system particularly contains the competition for energy between brain and body periphery. Characteristically, the hormone insulin is regarded as central feedback signal of the brain. The model realistically reproduces the qualitative behavior of the energy metabolism. Short-time observations demonstrate the physiological periodic food intake generating the typical oscillating blood glucose variations. Integration over the daily cycle yields a long-term model which shows a stable behavior in accordance with the homeostatic regulation of the energy metabolism on a long-time scale. Two types of abstract constitutive equations describing the interaction between compartments and signals are taken into consideration. These are nonlinear and linear representatives from the class of feasible relations. The robustness of the model against the choice of the representative relation is linked to evolutionary stability of existing organisms.

show abstract

Modeling Brain Energy Metabolism and Function: A Multiparametric Monitoring Approach

Cited by 22 publications

References 32 publications

How does spreading depression spread? Physiology and modeling

How does spreading depression spread? Physiology and modeling

A porous circulation model of the human brain for in silico clinical trials in ischaemic stroke

Systemic investigation of a brain-centered model of the human energy metabolism

Contact Info

Product

Resources

About