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Brain Imaging

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...

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A Protocol for the Administration of Real-Time fMRI Neurofeedback Training

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Published on: August 24, 2017

Control of Brain Activity in hMT+/V5 at Three Response Levels Using fMRI-Based Neurofeedback/BCI.

Teresa Sousa^1,2,3, Bruno Direito¹, João Lima¹

¹Institute for Biomedical Imaging and Life Sciences (CNC.IBILI), Faculty of Medicine, University of Coimbra, Coimbra, Portugal.

|May 24, 2016

Summary

Brain-computer interface (BCI) research can achieve more than two control levels within a single brain region. This study demonstrates a parametric control system using brain activity modulation for enhanced neurofeedback applications.

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Area of Science:

Neuroscience
Human-Computer Interaction

Background:

Brain-computer interface (BCI) research faces challenges in increasing command classes and control levels.
Current BCI studies often rely on binary control (level 0 and 1), limiting nuanced interaction.
Enhanced control levels in BCI applications can significantly improve neurofeedback efficiency.

Purpose of the Study:

To test the hypothesis that more than two modulation levels can be achieved within the hMT+/V5 brain region.
To investigate the feasibility of parametric control systems based on brain region activity modulation.
To explore the impact of distinct imagery task instructions on achieving different control levels.

Main Methods:

Participants underwent neurofeedback training involving three distinct imagery tasks.
Tasks included imagining stationary dots, dots with two opposing motions, and dots with four opposing motions.
Brain activity in the hMT+/V5 complex was modulated based on the complexity of imagined motion.

Main Results:

A significant number of participants (17/20) achieved binary control levels.
A majority of participants (12/20) successfully reached three distinct control levels within a single session.
Individual-level control was confirmed, aligning with whole-group effects.

Conclusions:

It is possible to design a parametric control system with at least three distinct levels by modulating activity in a specific brain region.
Imagery task instructions, differentiated by motion alternations, enable the achievement of varied control levels in BCI and neurofeedback.
This approach offers a pathway to more sophisticated and efficient BCI and neurofeedback systems.