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Updated: Nov 30, 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

Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity.

Anusha Mishra¹, Catherine N Hall², Clare Howarth³

¹Department of Neurology, Jungers Center for Neurosciences Research, and Knight Cardiovascular Institute, Oregon Health & Science University, Portland, OR, USA.

Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences

|November 16, 2020

Summary

Understanding blood oxygen-level-dependent (BOLD) signals in functional MRI requires deep knowledge of neurovascular and neurometabolic coupling. Advances in neuroimaging and inter-species analysis enhance interpretation of BOLD signals for cognitive neuroscience.

Keywords:

BOLD fMRI ageing cerebral blood flow high field fMRI neurovascular coupling

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Last Updated: Nov 30, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

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Published on: June 26, 2013

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

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Published on: November 8, 2012

fMRI Validation of fNIRS Measurements During a Naturalistic Task

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Published on: June 15, 2015

Area of Science:

Neuroscience
Medical Imaging

Background:

Functional neuroimaging, particularly fMRI, uses blood oxygen-level-dependent (BOLD) signals to infer neuronal activity.
BOLD signals arise from neurovascular coupling, where neuronal activity increases blood flow.

Discussion:

Accurate interpretation of BOLD signals necessitates understanding neurovascular and neurometabolic coupling mechanisms.
Systemic factors like aging, disease, and arousal states can influence cerebral blood flow and BOLD signals.
Cellular-level signaling and regional variations in coupling mechanisms are critical for signal interpretation.

Key Insights:

High-field fMRI and inter-species comparative analysis bridge non-invasive data with invasive cellular studies.
Integrating knowledge of coupling mechanisms, cellular contributions, and systemic influences improves BOLD signal interpretation.
Decoding human cognition relies on a comprehensive understanding of the BOLD signal's underlying physiological processes.

Outlook:

Future research should focus on a multidisciplinary approach combining neuroimaging, neuroscience, and physiology.
Continued advancements in non-invasive imaging technologies will facilitate deeper mechanistic insights.
This work provides a framework for future studies in neurovascular and cognitive sciences.