Literature DB >> 27832709

A model of neurovascular coupling and the BOLD response: PART I.

E J Mathias1, M J Plank2, T David1.   

Abstract

The mechanisms with which neurons communicate with the vasculature to increase blood flow, termed neurovascular coupling is still unclear primarily due to the complex interactions between many parameters and the difficulty in accessing, monitoring and measuring them in the highly heterogeneous brain. Hence a solid theoretical framework based on existing experimental knowledge is necessary to study the relation between neural activity, the associated vasoactive factors released and their effects on the vasculature. Such a framework should also be related to experimental data so that it can be validated against repetitive experiments and generate verifiable hypothesis. We have developed a mathematical model which describes a signaling mechanism of neurovascular coupling with a model of pyramidal neuron and its corresponding fMRI BOLD response. In the first part of two papers we describe the integration of the neurovascular coupling unit extended to include a complex neuron model, which includes the important Na/K ATPase pump, with a model that provides a BOLD signal taking its input from the cerebral blood flow and the metabolic rate of oxygen consumption. We show that this produces a viable signal in terms of initial dip, positive and negative BOLD signals.

Entities:  

Keywords:  Neurovascular coupling; fMRI BOLD response; mathematical modelling

Mesh:

Substances:

Year:  2016        PMID: 27832709     DOI: 10.1080/10255842.2016.1255732

Source DB:  PubMed          Journal:  Comput Methods Biomech Biomed Engin        ISSN: 1025-5842            Impact factor:   1.763


  3 in total

1.  Grey-box modeling and hypothesis testing of functional near-infrared spectroscopy-based cerebrovascular reactivity to anodal high-definition tDCS in healthy humans.

Authors:  Yashika Arora; Pushpinder Walia; Mitsuhiro Hayashibe; Makii Muthalib; Shubhajit Roy Chowdhury; Stephane Perrey; Anirban Dutta
Journal:  PLoS Comput Biol       Date:  2021-10-06       Impact factor: 4.475

Review 2.  Existence of Initial Dip for BCI: An Illusion or Reality.

Authors:  Keum-Shik Hong; Amad Zafar
Journal:  Front Neurorobot       Date:  2018-10-26       Impact factor: 2.650

3.  Artificial neurovascular network (ANVN) to study the accuracy vs. efficiency trade-off in an energy dependent neural network.

Authors:  Bhadra S Kumar; Nagavarshini Mayakkannan; N Sowmya Manojna; V Srinivasa Chakravarthy
Journal:  Sci Rep       Date:  2021-07-05       Impact factor: 4.996

  3 in total

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