From Brain Lobes to Neurons: Navigating the Brain Using Advanced 3D Modeling and Visualization Tools

Neuroscience education must convey 3D structure with clarity and accuracy. Traditional 2D renderings are limited as they lose depth information and hinder spatial understanding. High-resolution resources now exist, yet many are difficult to use in the class. Therefore, we developed an educational brain video that moves from gross to microanatomy using MRI-based models and the published literature. The pipeline used Fiji for preprocessing, MeshLab for mesh cleanup, Rhino 6 for target fixes, Houdini FX for materials, lighting, and renders, and Cinema4D for final refinement of the video. We had our brain models validated by two neuroscientists for educational fidelity. We tested the video in a class with 96 undergraduates randomized to video and lecture or lecture only. Students completed the same pretest and posttest questions. Student feedback revealed that comprehension and motivation to learn increased significantly in the group that watched the video, suggesting its potential as a useful supplement to traditional lectures. A short, well-produced 3D video can supplement lectures and improve learning in this setting. We share software versions and key parameters to support reuse.

Authors

Institutions

Publication Details

Journal
Journal of Imaging
Published
2025-09-01
DOI
https://doi.org/10.3390/jimaging11090298
Citations
1
Primary Topic
Neuroscience, Education and Cognitive Function
Type
article
Field-Weighted Citation Impact
1.43

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

From Brain Lobes to Neurons: Navigating the Brain Using Advanced 3D Modeling and Visualization Tools

Reem Khalil, Ahmad Shah Farhat, Mohamed Rowaizak
1 citations
Journal of Imaging
Neuroscience, Education and Cognitive Function
1.43
article

From Brain Lobes to Neurons: Navigating the Brain Using Advanced 3D Modeling and Visualization Tools

Reem Khalil, Ahmad Shah Farhat, Mohamed Rowaizak
article en
1 citations

Abstract

Neuroscience education must convey 3D structure with clarity and accuracy. Traditional 2D renderings are limited as they lose depth information and hinder spatial understanding. High-resolution resources now exist, yet many are difficult to use in the class. Therefore, we developed an educational brain video that moves from gross to microanatomy using MRI-based models and the published literature. The pipeline used Fiji for preprocessing, MeshLab for mesh cleanup, Rhino 6 for target fixes, Houdini FX for materials, lighting, and renders, and Cinema4D for final refinement of the video. We had our brain models validated by two neuroscientists for educational fidelity. We tested the video in a class with 96 undergraduates randomized to video and lecture or lecture only. Students completed the same pretest and posttest questions. Student feedback revealed that comprehension and motivation to learn increased significantly in the group that watched the video, suggesting its potential as a useful supplement to traditional lectures. A short, well-produced 3D video can supplement lectures and improve learning in this setting. We share software versions and key parameters to support reuse.

Journal of ImagingVol. 11(9)
American University of Sharjah (AE), Polish Academy of Sciences (PL)
American University of Sharjah
Openalex Percentile: Top 16%
Neuroscience, Education and Cognitive Function
1.43
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

From Brain Lobes to Neurons: Navigating the Brain Using Advanced 3D Modeling and Visualization Tools — Reem Khalil, Ahmad Shah Farhat, et al. · Journal of Imaging (2025) | TGRS Research Map | TGRS