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Parkinson's Disease: Overview

Parkinson's Disease: Overview

Neurodegenerative disorders are progressive diseases that cause irreversible damage and loss to neurons in specific brain areas. Examples of these disorders include Parkinson's disease, Alzheimer's disease, Multiple Sclerosis (MS), and Amyotrophic Lateral Sclerosis (ALS). These disorders share characteristics such as proteinopathies, selective neuronal vulnerability, and a complex interplay between genetic and environmental factors. The primary therapeutic goal for these conditions is...

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Related Experiment Video

Updated: Jan 13, 2026

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

Towards precision functional brain network mapping in Parkinson's disease.

Jacob Chernicky¹, Ally Dworetsky², Sarah Grossen³

¹Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Department of Psychology, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Department of Psychology, Florida State University, Tallahassee, FL, USA.

Neuroimage. Clinical

|January 7, 2026

Summary

Precision resting state functional connectivity (RSFC) is a reliable method for studying brain networks in Parkinson's disease (PD). This advanced technique offers potential for personalized diagnostics and identifying biomarkers for PD variability.

Keywords:

Functional connectivity Individual differences Parkinson’s Disease fMRI

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Last Updated: Jan 13, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

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Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping

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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

Area of Science:

Neuroscience
Medical Imaging
Neurology

Background:

Parkinson's disease (PD) presents significant individual variability in symptoms and progression.
Understanding brain network disruptions in PD is crucial but challenged by low reliability in conventional functional connectivity studies.
Precision resting state functional connectivity (RSFC) offers a potential solution by enhancing data collection and analysis for individual networks.

Purpose of the Study:

To assess the feasibility and reliability of precision RSFC in individuals with Parkinson's disease.
To compare the quality of precision RSFC measures against conventional methods and healthy controls.

Main Methods:

Collected over 100 minutes of RSFC data from 20 PD patients and 10 healthy controls (HC).
Evaluated motion, reliability, and stability of RSFC measures, comparing precision methods with conventional 5-minute data.
Benchmarked PD data against HC for comparability and created individualized network maps in PD participants.

Main Results:

Precision RSFC yielded reliable and stable brain network measures in PD participants, comparable to HC.
Precision RSFC significantly outperformed conventional 5-minute RSFC in terms of reliability and stability.
Individualized network maps in PD captured significant inter-individual and group-to-template variations, including in motor networks.

Conclusions:

Precision RSFC is a feasible and reliable neuroimaging technique for individuals with Parkinson's disease.
This method shows promise for developing personalized diagnostic tools for PD.
Precision RSFC can aid in identifying brain-based biomarkers that explain clinical variability in Parkinson's disease.