Brain Structure Analysis
Brain Structure Analysis - Related Videos
17:06
Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
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Cited by 17 •
2012
We describe a novel approach for simultaneous analysis of brain function and structure using magnetic resonance imaging (MRI). We assess brain structure with high-resolution diffusion-weighted imaging and white-matter fiber tractography. Unlike standard structural MRI, these techniques allow us to directly relate anatomical connectivity to functional properties of brain networks.
05:33
Three-Dimensional Shape Modeling and Analysis of Brain Structures
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Cited by 2 •
2019
We introduce a semi-automatic protocol for shape analysis on brain structures, including image segmentation using open software, and further group-wise shape analysis using an automated modeling package. Here, we demonstrate each step of the 3D shape analysis protocol with hippocampal segmentation from brain MR images.
13:43
Correlative Microscopy for 3D Structural Analysis of Dynamic Interactions
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Cited by 15 •
2013
We describe a correlative microscopy method that combines high-speed 3D live-cell fluorescent light microscopy and high-resolution cryo-electron tomography. We demonstrate the capability of the correlative method by imaging dynamic, small HIV-1 particles interacting with host HeLa cells.
08:14
Comprehensive Analysis of Transcription Dynamics from Brain Samples Following Behavioral Experience
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Cited by 6 •
2014
This manuscript describes a protocol that applies comprehensive profiling for analysis of transcriptional programs induced in specific brain nuclei of rodents following behavioral paradigms. Herein, this approach is illustrated in the context of profiling genes induced in the nucleus accumbens (NAc) of mice following acute cocaine exposure, utilizing microfluidic qPCR arrays.
04:44
Processing of a Mouse Brain for Downstream Analysis
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2025
This video demonstrates a detailed step-by-step protocol for preparing frozen mouse brain tissue sections for downstream analyses.
FAQs
It links measurable features of anatomy to psychological functions by examining whether differences in regional volume, cortical thickness, or connections between brain areas correspond with differences in memory, emotion, perception, or decision-making. This approach helps researchers build more precise brain-behavior models while preserving the distinction between anatomical patterns and the psychological functions studied.
Regional volume describes the amount of tissue in a defined area, whereas cortical thickness focuses on the thickness of the cortex. Measures of connections address relationships between brain areas. Considering these features together gives researchers complementary structural information rather than relying on a single anatomical indicator when comparing psychological characteristics.
Comparisons allow researchers to examine whether anatomical patterns differ across people or populations associated with development, learning, mental health conditions, or aging. They can then evaluate how those structural differences relate to cognition and behavior, including memory, emotion, perception, and decision-making. The value lies in identifying systematic relationships rather than isolated observations.
A typical study obtains anatomical neuroimaging data, often with magnetic resonance imaging, and extracts measurements such as regional volume, cortical thickness, and connections between brain areas. Researchers then compare measurements across individuals or groups and examine their relationship to behavioral or cognitive patterns. This workflow converts brain images into structured evidence for psychological research.
By comparing anatomy across relevant individuals or groups, researchers can investigate structural patterns associated with mental health conditions and aging. The same measurements can be examined alongside cognition and behavior to study changes in memory, emotion, perception, or decision-making. This provides psychological research with anatomical context for modeling how these factors relate.
It can support studies of how learning and development influence neural structure, and how structural patterns relate to memory, emotion, perception, and decision-making. Researchers may also use it to examine aging or mental health conditions. These applications extend beyond describing anatomy by connecting physical organization with behaviorally meaningful outcomes.