Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Manipulation and Analysis

Manipulation and Analysis

GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Intraindividual cognitive variability predicts amyloid beta, tau PET, and dementia conversion in Down syndrome: a potential marker of cognitive resilience.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2026

Same author

Inflammation Associated With Obesity, Aging, and Amyloid Burden in Adults With Down Syndrome.

Obesity (Silver Spring, Md.)·2026

Same author

Leveraging STRAW +10 criteria to evaluate menopause stage effects on sleep quality.

Climacteric : the journal of the International Menopause Society·2026

Same author

Circadian Rest-Activity Rhythms, Cognition, and Alzheimer Disease Dementia in Adults With Down Syndrome.

Neurology·2026

Same author

Early syndecan-4 upregulation predicts cognitive and pathological trajectories in Alzheimer disease.

Alzheimer's research & therapy·2026

Same author

History of Traumatic Brain Injury with Loss of Consciousness and APOE <i>ε</i>4 Carriers Synergistically Increase Late-Life Amyloid PET Burden.

bioRxiv : the preprint server for biology·2026

Same journal

Obstacles and solutions for implementing amyloid-targeting treatments in Europe.

Alzheimer's & dementia (Amsterdam, Netherlands)·2026

Same journal

Elevated sclerostin levels in cerebrospinal fluid are associated with cognitive impairment in the Alzheimer's disease continuum.

Alzheimer's & dementia (Amsterdam, Netherlands)·2026

Same journal

FTLD-TDP versus LATE-NC: Experience of a Brain Bank specializing in FTLD-TDP.

Alzheimer's & dementia (Amsterdam, Netherlands)·2026

Same journal

Variable Aβ tracer uptake in hyperostosis frontalis interna: implications for brain Aβ PET/CT interpretation.

Alzheimer's & dementia (Amsterdam, Netherlands)·2026

Same journal

Deep contrastive learning framework identifies cell-type-specific drug targets in Alzheimer's disease.

Alzheimer's & dementia (Amsterdam, Netherlands)·2026

Same journal

Anti-amyloid therapy eligibility in a longitudinal brain-donor cohort with <i>post mortem</i> confirmation.

Alzheimer's & dementia (Amsterdam, Netherlands)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Aug 6, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

A practitioner's guide to geospatial analysis in a neuroimaging context.

Julie K Wisch¹, Ganesh M Babulal^1,2,3, Kalen Petersen¹

¹Department of Neurology Washington University in St. Louis St. Louis Missouri USA.

Alzheimer'S & Dementia (Amsterdam, Netherlands)

|March 20, 2023

Summary

This summary is machine-generated.

This study links neighborhood characteristics to brain health using geospatial analysis in St. Louis. Findings suggest environmental factors impact brain age gap, paving the way for targeted community interventions.

Keywords:

brain imaging epidemiologic methods magnetic resonance imaging

More Related Videos

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

Basics of Multivariate Analysis in Neuroimaging Data

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

Related Experiment Videos

Last Updated: Aug 6, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

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

Basics of Multivariate Analysis in Neuroimaging Data

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

Area of Science:

Neuroscience
Environmental Health
Geospatial Analysis

Background:

Health disparities stem from complex biological-environmental interactions.
Large neuroimaging cohorts enable investigation into environmental influences on the brain.
Geospatial methods offer a powerful approach to analyze these interactions within population studies.

Purpose of the Study:

To provide a practical guide for applying geospatial methods to neuroimaging data.
To investigate the relationship between neighborhood characteristics and brain structure.
To identify specific urban areas associated with altered brain development.

Main Methods:

Estimated brain age gap (BAG) using structural MRI in 239 St. Louis residents.
Utilized geospatial analysis to link neuroimaging data with neighborhood-level census data (American Community Survey).
Assessed the association between the Area Deprivation Index (ADI) and BAG.

Main Results:

Identified specific neighborhoods in St. Louis significantly associated with higher BAG.
Demonstrated a spatial relationship between environmental factors and brain structure variations.
Provided replication code for the geospatial analysis methods used.

Conclusions:

Neighborhood-level interventions may be effective in addressing brain health disparities.
Geocoding participant data is crucial for understanding biological-environmental interactions.
This study highlights the potential of geospatial approaches in neuroimaging research.