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Updated: Jan 10, 2026

A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia

A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia

Published on: September 16, 2017

Resting state functional magnetic resonance imaging processing techniques in stroke studies.

Golrokh Mirzaei, Hojjat Adeli

Reviews in the Neurosciences

|November 16, 2016

Summary

This summary is machine-generated.

Resting state functional magnetic resonance imaging (rsfMRI) reveals brain connectivity patterns. This review focuses on rsfMRI in stroke patients, discussing preprocessing and analysis techniques for potential rehabilitation applications.

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Area of Science:

Neuroscience
Medical Imaging
Computational Neuroscience

Background:

Brain connectivity research using resting state functional magnetic resonance imaging (rsfMRI) is rapidly advancing.
Studies have uncovered novel insights into brain mapping and functional communication networks.

Purpose of the Study:

To review brain connectivity and resting state networks, with a specific focus on rsfMRI in stroke studies.
To discuss preprocessing and connectivity processing techniques for rsfMRI data from stroke patients.

Main Methods:

Review of existing literature on brain connectivity and rsfMRI.
Focus on methodologies applicable to stroke patient data.
Examination of preprocessing and data analysis techniques.

Main Results:

rsfMRI provides valuable insights into brain network organization and functional communication.
Specific techniques for preprocessing and analyzing rsfMRI data in stroke populations have been identified.
Recent research highlights the potential of rsfMRI in understanding stroke-related brain changes.

Conclusions:

rsfMRI is a powerful tool for studying brain connectivity in stroke.
The reviewed techniques offer a foundation for further research and clinical applications.
This work aims to stimulate further interest in computational neuroscience for stroke rehabilitation.