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Simultaneous fMRI and Electrophysiology in the Rodent Brain
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High-speed real-time resting-state FMRI using multi-slab echo-volumar imaging.

Stefan Posse1, Elena Ackley, Radu Mutihac

  • 1Department of Neurology, School of Medicine, The University of New Mexico , Albuquerque, NM , USA ; Department of Electrical and Computer Engineering, The University of New Mexico , Albuquerque, NM , USA ; Department of Physics and Astronomy, The University of New Mexico , Albuquerque, NM , USA.

Frontiers in Human Neuroscience
|August 30, 2013
PubMed
Summary
This summary is machine-generated.

Ultra-high-speed real-time fMRI using multi-slab echo-volumar imaging (MEVI) enhances mapping of brain networks and vascular pulsatility. This advanced technique shows promise for clinical neuroscience, especially in patients with neurological conditions.

Keywords:
arteriovenous malformationbrain tumorcerebrovascular pulsatilityepilepsyindependent component analysis (ICA)multi-slab echo-volumar imagingreal-time resting state fMRIseed-based functional connectivity

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Area of Science:

  • Neuroimaging
  • Functional Magnetic Resonance Imaging (fMRI)
  • Neuroscience

Background:

  • Ultra-high-speed real-time fMRI with multi-slab echo-volumar imaging (MEVI) offers increased sensitivity for mapping brain activity and resting-state networks (RSNs) compared to traditional echo-planar imaging.
  • Characterizing the sensitivity of MEVI for mapping RSN connectivity dynamics is crucial for understanding brain function in health and disease.

Purpose of the Study:

  • To evaluate the sensitivity of MEVI for mapping resting-state network (RSN) connectivity dynamics.
  • To compare the performance of independent component analysis (ICA) and a novel seed-based connectivity analysis (SBCA) for real-time RSN monitoring.
  • To investigate the potential of MEVI in mapping eloquent cortex near brain lesions and detecting abnormal connectivity in neurological disorders.

Main Methods:

  • Utilized ultra-high-speed real-time fMRI with multi-slab echo-volumar imaging (MEVI).
  • Employed independent component analysis (ICA) and a novel seed-based connectivity analysis (SBCA) combining sliding-window correlation with meta-statistics.
  • Assessed sensitivity in mapping RSN connectivity dynamics, including cardiac-related signal pulsation.

Main Results:

  • The novel SBCA approach effectively minimized confounds like movement and physiological noise, enabling real-time RSN monitoring.
  • MEVI demonstrated sensitive mapping of eloquent cortex in patients with brain tumors and arterio-venous malformations, and detected abnormal resting-state connectivity in epilepsy.
  • Cardiac pulsation mapping revealed distinct regional differences, elevated pulsatility in patients with arterio-venous malformations, and reduced pulsatility in gray matter of patients compared to controls.

Conclusions:

  • Ultra-high-speed real-time fMRI with MEVI significantly enhances the sensitivity for mapping resting-state connectivity dynamics and cerebro-vascular pulsatility.
  • This methodology is particularly valuable for mapping eloquent cortex in patients with neurological diseases who may have limited cooperation for task-based fMRI.
  • Mapping cardiac pulsation may provide important functional information distinguishing healthy from diseased vasculature, offering promising clinical and neuroscience research applications.