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Neurovascular coupling: a parallel implementation.

Katharina Dormanns1, Richard G Brown2, Tim David1

  • 1UC HPC Supercomputing Centre, University of Canterbury Christchurch, New Zealand.

Frontiers in Computational Neuroscience
|October 7, 2015
PubMed
Summary
This summary is machine-generated.

This study presents a numerical model of neurovascular coupling, linking neuronal activity to blood vessel changes. The model simulates how neuronal signals influence vasodilation and contraction via the neurovascular unit, impacting blood flow.

Keywords:
agonistic behaviorcomputational biologyneurovascular couplingneurovascular unitparallel computing

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Area of Science:

  • Computational neuroscience
  • Biophysics
  • Physiology

Background:

  • Neurovascular coupling (NVC) is crucial for regulating cerebral blood flow.
  • Understanding the mechanisms of NVC, involving neuronal activity, astrocytes, endothelial cells, and smooth muscle cells, is essential.
  • Existing models often simplify the complex interactions within the neurovascular unit (NVU).

Purpose of the Study:

  • To develop and present a numerical model of neurovascular coupling.
  • To simulate the relationship between neuronal activity and vascular responses (vasodilation/contraction).
  • To investigate the role of astrocytic perivascular K+ and smooth muscle cell (SMC) Ca2+ pathways in NVC.

Main Methods:

  • A numerical model of the neurovascular unit (NVU) was developed.
  • The model incorporates neuronal activity, astrocytic K+ flux, endothelial cell (EC) and smooth muscle cell (SMC) Ca2+ signaling, and P2Y receptor-mediated pathways.
  • A space-filling H-tree simulated the arterial tree, coupling NVUs to the vasculature via stretch-mediated Ca2+ channels.

Main Results:

  • The model successfully relates neuronal input signals to corresponding vessel reactions (contraction/dilation).
  • Calcium-induced calcium release (CICR) oscillations in SMCs were shown to inhibit NVC, linking blood flow to vessel dynamics.
  • Coupling between the vasculature and NVUs was found to be weak, influencing Ca2+ oscillation profiles and refilling times.

Conclusions:

  • The numerical model provides a framework for understanding complex neurovascular coupling mechanisms.
  • The study highlights the role of SMC Ca2+ oscillations in modulating NVC and blood flow regulation.
  • The model's solution algorithm demonstrates excellent scalability for complex simulations.