Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Jun 12, 2026

Automated Detection and Analysis of Exocytosis
13:28

Automated Detection and Analysis of Exocytosis

Published on: September 11, 2021

Spatial Point Pattern Analysis of Neurons Using Ripley's K-Function in 3D.

Mehrdad Jafari-Mamaghani1, Mikael Andersson, Patrik Krieger

  • 1Department of Neuroscience, Stockholm Brain Institute, Karolinska Institutet Stockholm, Sweden.

Frontiers in Neuroinformatics
|June 26, 2010
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

The hows and whys of physical activity and recovery after cytoreductive surgery and hyperthermic intraperitoneal chemotherapy: a mixed methods study.

Disability and rehabilitation·2026
Same author

Associations of adverse childhood experiences, sexual identity and sexual risk indicators with HPV vaccination uptake in Denmark - A nationwide epidemiological study.

Vaccine·2026
Same author

Correction to: Incidence Rates of Paediatric Traumatic Brain Injury in Denmark - the development over three decades: a nationwide, population-based registry study.

Acta neurochirurgica·2026
Same author

Severe Neurological Disorders in the Greenlandic Population: A Nationwide Register-Based Study.

Brain and behavior·2025
Same author

Sexual health and challenges among 15-89-year-old Danes with and without severe visual impairment: Baseline findings in a nationally representative cohort study.

Disability and health journal·2025
Same author

Incidence rates of paediatric traumatic brain injury in Denmark - the development over three decades: a nationwide, population-based registry study.

Acta neurochirurgica·2025
Same journal

Predicting vasovagal syncope during head-up tilt test: three machine learning approaches.

Frontiers in neuroinformatics·2026
Same journal

Decoding basal ganglia motor circuit dysfunction from handwriting: a physics-informed neural signal interpretation framework for Parkinson's disease screening.

Frontiers in neuroinformatics·2026
Same journal

FUSION-AD: interpretable AI framework for risk assessment and subgroup discovery in Alzheimer's disease.

Frontiers in neuroinformatics·2026
Same journal

A 3D-printed phantom to validate subject orientation in 3D imaging and recordings.

Frontiers in neuroinformatics·2026
Same journal

IntegriLAB: a blockchain-enabled electronic lab notebook for reproducible neuroimaging research.

Frontiers in neuroinformatics·2026
Same journal

Long-range correlations in alpha-band of electroencephalogram: a nonlinear embedding and detrended fluctuation analysis.

Frontiers in neuroinformatics·2026
See all related articles

This study extends Ripley's K-function for analyzing 3D spatial point patterns, specifically neuronal distribution. It addresses edge correction, crucial for accurate 3D biological data analysis.

Area of Science:

  • Neuroscience
  • Spatial Statistics
  • Computational Biology

Background:

  • Analyzing the 3D distribution of biological structures, like pyramidal neurons, is vital.
  • Technological advancements facilitate the acquisition of complex 3D biological data.
  • Existing methods for spatial point pattern analysis often lack robust 3D application, especially concerning edge effects.

Purpose of the Study:

  • To adapt and apply Ripley's K-function, a non-parametric tool, for analyzing 3D spatial point patterns.
  • To address the critical issue of edge correction in 3D Ripley's K-function analysis.
  • To enhance the theoretical and practical use of Ripley's K-function and bootstrap resampling in 3D domains.

Main Methods:

  • Utilized Ripley's K-function, a non-parametric spatial statistics tool.
Keywords:
Ripley's K-functionbootstrap resamplingedge correction in 3D

More Related Videos

Examining Local Network Processing using Multi-contact Laminar Electrode Recording
13:40

Examining Local Network Processing using Multi-contact Laminar Electrode Recording

Published on: September 8, 2011

Analyzing Dendritic Morphology in Columns and Layers
08:41

Analyzing Dendritic Morphology in Columns and Layers

Published on: March 23, 2017

Related Experiment Videos

Last Updated: Jun 12, 2026

Automated Detection and Analysis of Exocytosis
13:28

Automated Detection and Analysis of Exocytosis

Published on: September 11, 2021

Examining Local Network Processing using Multi-contact Laminar Electrode Recording
13:40

Examining Local Network Processing using Multi-contact Laminar Electrode Recording

Published on: September 8, 2011

Analyzing Dendritic Morphology in Columns and Layers
08:41

Analyzing Dendritic Morphology in Columns and Layers

Published on: March 23, 2017

  • Extended existing 2D methodologies for Ripley's K-function to a 3D context.
  • Incorporated bootstrap resampling for statistical testing in 3D.

    • Main Results:

    • Developed and validated an approach for 3D spatial point pattern analysis using Ripley's K-function.
    • Demonstrated the importance and implementation of edge correction in 3D analyses.
    • Provided a framework for more accurate inferences from 3D biological data.

    Conclusions:

    • The adapted Ripley's K-function provides a robust method for analyzing 3D neuronal distributions.
    • Effective edge correction is essential for reliable spatial statistics in 3D.
    • This work facilitates more accurate interpretation of complex biological structures in three dimensions.