Literature DB >> 18539049

A study of the brain's resting state based on alpha band power, heart rate and fMRI.

J C de Munck1, S I Gonçalves, Th J C Faes, J P A Kuijer, P J W Pouwels, R M Heethaar, F H Lopes da Silva.   

Abstract

Considering that there are several theoretical reasons why fMRI data is correlated to variations in heart rate, these correlations are explored using experimental resting state data. In particular, the possibility is discussed that the "default network", being a brain area that deactivates during non-specific general tasks, is a hemodynamic effect caused by heart rate variations. Of fifteen healthy controls ECG, EEG and fMRI were co-registered. Slice time dependent heart rate regressors were derived from the ECG data and correlated to fMRI using a linear correlation analysis where the impulse response is estimated from the data. It was found that in most subjects substantial correlations between heart rate variations and fMRI exist, both within the brain and at the ventricles. The brain areas with high correlation to heart rate are different from the "default network" and the response functions deviate from the canonical hemodynamic response function. Furthermore, a general negative correlation was found between heart beat intervals (reverse of heart rate) and alpha power. We interpret this finding by assuming that subject's state varies between drowsiness and wakefulness. Finally, given this large correlation, we re-examined the contribution of heart rate variations to earlier reported fMRI/alpha band correlations, by adding heart rate regressors as confounders. It was found that inclusion of these confounders most often had a negligible effect. From its strong correlation to alpha power, we conclude that the heart rate variations contain important physiological information about subject's resting state. However, it does not provide a full explanation of the behaviour of the "default network". Its application as confounder in fMRI experiments is a relatively small computational effort, but may have a substantial impact in paradigms where heart rate is controlled by the stimulus.

Mesh:

Year:  2008        PMID: 18539049     DOI: 10.1016/j.neuroimage.2008.04.244

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  40 in total

1.  Dissociated patterns of anti-correlations with dorsal and ventral default-mode networks at rest.

Authors:  Jingyuan E Chen; Gary H Glover; Michael D Greicius; Catie Chang
Journal:  Hum Brain Mapp       Date:  2017-02-02       Impact factor: 5.038

2.  Correction for pulse height variability reduces physiological noise in functional MRI when studying spontaneous brain activity.

Authors:  Petra J van Houdt; Pauly P W Ossenblok; Paul A J M Boon; Frans S S Leijten; Demetrios N Velis; Cornelis J Stam; Jan C de Munck
Journal:  Hum Brain Mapp       Date:  2010-02       Impact factor: 5.038

Review 3.  Functional connectivity MRI in infants: exploration of the functional organization of the developing brain.

Authors:  Christopher D Smyser; Abraham Z Snyder; Jeffrey J Neil
Journal:  Neuroimage       Date:  2011-03-03       Impact factor: 6.556

4.  Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization.

Authors:  Koene R A Van Dijk; Trey Hedden; Archana Venkataraman; Karleyton C Evans; Sara W Lazar; Randy L Buckner
Journal:  J Neurophysiol       Date:  2009-11-04       Impact factor: 2.714

5.  Multimodal Parcellations and Extensive Behavioral Profiling Tackling the Hippocampus Gradient.

Authors:  Anna Plachti; Simon B Eickhoff; Felix Hoffstaedter; Kaustubh R Patil; Angela R Laird; Peter T Fox; Katrin Amunts; Sarah Genon
Journal:  Cereb Cortex       Date:  2019-12-17       Impact factor: 5.357

Review 6.  Resting-state fMRI: a review of methods and clinical applications.

Authors:  M H Lee; C D Smyser; J S Shimony
Journal:  AJNR Am J Neuroradiol       Date:  2012-08-30       Impact factor: 3.825

7.  Genome-wide association analysis links multiple psychiatric liability genes to oscillatory brain activity.

Authors:  Dirk J A Smit; Margaret J Wright; Jacquelyn L Meyers; Nicholas G Martin; Yvonne Y W Ho; Stephen M Malone; Jian Zhang; Scott J Burwell; David B Chorlian; Eco J C de Geus; Damiaan Denys; Narelle K Hansell; Jouke-Jan Hottenga; Matt McGue; Catharina E M van Beijsterveldt; Neda Jahanshad; Paul M Thompson; Christopher D Whelan; Sarah E Medland; Bernice Porjesz; William G Lacono; Dorret I Boomsma
Journal:  Hum Brain Mapp       Date:  2018-06-26       Impact factor: 5.038

8.  Effects of model-based physiological noise correction on default mode network anti-correlations and correlations.

Authors:  Catie Chang; Gary H Glover
Journal:  Neuroimage       Date:  2009-05-14       Impact factor: 6.556

9.  Plasticity of brain networks in a randomized intervention trial of exercise training in older adults.

Authors:  Michelle W Voss; Ruchika S Prakash; Kirk I Erickson; Chandramallika Basak; Laura Chaddock; Jennifer S Kim; Heloisa Alves; Susie Heo; Amanda N Szabo; Siobhan M White; Thomas R Wójcicki; Emily L Mailey; Neha Gothe; Erin A Olson; Edward McAuley; Arthur F Kramer
Journal:  Front Aging Neurosci       Date:  2010-08-26       Impact factor: 5.750

Review 10.  Seven topics in functional magnetic resonance imaging.

Authors:  Peter A Bandettini
Journal:  J Integr Neurosci       Date:  2009-09       Impact factor: 2.117

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