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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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Related Experiment Video

Updated: Mar 15, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

A Multi-facetted Visual Analytics Tool for Exploratory Analysis of Human Brain and Function Datasets.

Diego A Angulo¹, Cyril Schneider², James H Oliver³

¹IMAGINE, Systems and Computing Engineering, Universidad de los Andes Bogota, Colombia.

Frontiers in Neuroinformatics

|September 8, 2016

Summary

This summary is machine-generated.

BRAVIZ is a new software tool that integrates visualization and statistical analysis for neuroscience research. It simplifies exploring complex brain data, enabling researchers to uncover new insights from multi-faceted datasets.

Keywords:

MRI cohort studies exploratory analysis fMRI python tractography visual analytics

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Last Updated: Mar 15, 2026

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Published on: March 21, 2019

Area of Science:

Neuroscience
Data Science
Medical Informatics

Background:

Neuroscience research generates large, diverse datasets.
Current software tools often fragment data analysis, hindering exploration.
Inefficient data handling limits the full potential of neuroscience data.

Purpose of the Study:

Introduce BRAVIZ, an ancillary software tool for neuroscience data exploration.
Integrate interactive visualization with real-time statistical analyses.
Facilitate access to and analysis of multi-faceted neuroscience data.

Main Methods:

BRAVIZ integrates interactive visualization with real-time statistical analyses.
The tool prioritizes brain images in the analysis of individuals or groups.
A case study demonstrates integration of brain structure, function, and clinical data.

Main Results:

BRAVIZ automates cumbersome and error-prone tasks in data exploration.
The software facilitates exploration of trends and relationships in complex datasets.
It provides an integrated view of phenomena, supporting hypothesis generation.

Conclusions:

BRAVIZ enhances the exploration of multi-faceted neuroscience data.
The tool streamlines analysis by emphasizing visual data and integrating diverse data types.
BRAVIZ supports the discovery of new hypotheses in brain research.