Literature DB >> 25112809

The influence of physiological noise correction on test-retest reliability of resting-state functional connectivity.

Rasmus M Birn1, Maria Daniela Cornejo, Erin K Molloy, Rémi Patriat, Timothy B Meier, Gregory R Kirk, Veena A Nair, M Elizabeth Meyerand, Vivek Prabhakaran.   

Abstract

The utility and success of resting-state functional connectivity MRI (rs-fcMRI) depend critically on the reliability of this technique and the extent to which it accurately reflects neuronal function. One challenge is that rs-fcMRI is influenced by various sources of noise, particularly cardiac- and respiratory-related signal variations. The goal of the current study was to evaluate the impact of various physiological noise correction techniques, specifically those that use independent cardiac and respiration measures, on the test-retest reliability of rs-fcMRI. A group of 25 subjects were each scanned at three time points--two within the same imaging session and another 2-3 months later. Physiological noise corrections accounted for significant variance, particularly in blood vessels, sagittal sinus, cerebrospinal fluid, and gray matter. The fraction of variance explained by each of these corrections was highly similar within subjects between sessions, but variable between subjects. Physiological corrections generally reduced intrasubject (between-session) variability, but also significantly reduced intersubject variability, and thus reduced the test-retest reliability of estimating individual differences in functional connectivity. However, based on known nonneuronal mechanisms by which cardiac pulsation and respiration can lead to MRI signal changes, and the observation that the physiological noise itself is highly stable within individuals, removal of this noise will likely increase the validity of measured connectivity differences. Furthermore, removal of these fluctuations will lead to better estimates of average or group maps of connectivity. It is therefore recommended that studies apply physiological noise corrections but also be mindful of potential correlations with measures of interest.

Keywords:  cardiac; functional connectivity; physiological noise; reliability; respiration; resting state

Mesh:

Year:  2014        PMID: 25112809      PMCID: PMC4146390          DOI: 10.1089/brain.2014.0284

Source DB:  PubMed          Journal:  Brain Connect        ISSN: 2158-0014


  59 in total

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Authors:  M S Dagli; J E Ingeholm; J V Haxby
Journal:  Neuroimage       Date:  1999-04       Impact factor: 6.556

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3.  CORSICA: correction of structured noise in fMRI by automatic identification of ICA components.

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4.  Real-time shimming to compensate for respiration-induced B0 fluctuations.

Authors:  P van Gelderen; J A de Zwart; P Starewicz; R S Hinks; J H Duyn
Journal:  Magn Reson Med       Date:  2007-02       Impact factor: 4.668

5.  The respiration response function: the temporal dynamics of fMRI signal fluctuations related to changes in respiration.

Authors:  Rasmus M Birn; Monica A Smith; Tyler B Jones; Peter A Bandettini
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6.  A component based noise correction method (CompCor) for BOLD and perfusion based fMRI.

Authors:  Yashar Behzadi; Khaled Restom; Joy Liau; Thomas T Liu
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7.  Integration of motion correction and physiological noise regression in fMRI.

Authors:  Tyler B Jones; Peter A Bandettini; Rasmus M Birn
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8.  Test-retest reliability of resting-state connectivity network characteristics using fMRI and graph theoretical measures.

Authors:  Urs Braun; Michael M Plichta; Christine Esslinger; Carina Sauer; Leila Haddad; Oliver Grimm; Daniela Mier; Sebastian Mohnke; Andreas Heinz; Susanne Erk; Henrik Walter; Nina Seiferth; Peter Kirsch; Andreas Meyer-Lindenberg
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  30 in total

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Journal:  Neuroimage       Date:  2016-02-23       Impact factor: 6.556

Review 2.  Characterizing Resting-State Brain Function Using Arterial Spin Labeling.

Authors:  J Jean Chen; Kay Jann; Danny J J Wang
Journal:  Brain Connect       Date:  2015-10-06

3.  Quasi-periodic patterns of intrinsic brain activity in individuals and their relationship to global signal.

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4.  Sensitivity of the resting-state haemodynamic response function estimation to autonomic nervous system fluctuations.

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5.  Test-retest reliability of the default mode network in a multi-centric fMRI study of healthy elderly: Effects of data-driven physiological noise correction techniques.

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Journal:  Hum Brain Mapp       Date:  2016-03-17       Impact factor: 5.038

6.  Retrospective Correction of Physiological Noise: Impact on Sensitivity, Specificity, and Reproducibility of Resting-State Functional Connectivity in a Reading Network Model.

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7.  Twitches, Blinks, and Fidgets: Important Generators of Ongoing Neural Activity.

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8.  Impact of physiological noise in characterizing the functional MRI default-mode network in Alzheimer's disease.

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9.  Resting-state test-retest reliability of a priori defined canonical networks over different preprocessing steps.

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Journal:  Brain Struct Funct       Date:  2016-08-22       Impact factor: 3.270

Review 10.  Building a Science of Individual Differences from fMRI.

Authors:  Julien Dubois; Ralph Adolphs
Journal:  Trends Cogn Sci       Date:  2016-04-30       Impact factor: 20.229

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