Evaluating the sensitivity of functional connectivity measures to motion artifact in resting-state fMRI data

AbstractFunctional connectivity (FC) networks are typically inferred from resting-state fMRI data using the Pearson correlation between BOLD time series from pairs of brain regions. However, alternative methods of estimating functional connectivity have not been systematically tested for their sensitivity or robustness to head motion artifact. Here, we evaluate the sensitivity of six different functional connectivity measures to motion artifact using resting-state data from the Human Connectome Project. We report that FC estimated using full correlation has a relatively high residual distance-dependent relationship with motion compared to partial correlation, coherence and information theory-based measures, even after implementing rigorous methods for motion artifact mitigation. This disadvantage of full correlation, however, may be offset by higher test-retest reliability and system identifiability. FC estimated by partial correlation offers the best of both worlds, with low sensitivity to motion artifact and intermediate system identifiability, with the caveat of low test-retest reliability. We highlight spatial differences in the sub-networks affected by motion with different FC metrics. Further, we report that intra-network edges in the default mode and retrosplenial temporal sub-networks are highly correlated with motion in all FC methods. Our findings indicate that the method of estimating functional connectivity is an important consideration in resting-state fMRI studies and must be chosen carefully based on the parameters of the study.

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Test–Retest Reliability of Synchrony and Metastability in Resting State fMRI

Brain Sciences ◽

10.3390/brainsci12010066 ◽

2021 ◽

Vol 12 (1) ◽

pp. 66

Author(s):

Lan Yang ◽

Jing Wei ◽

Ying Li ◽

Bin Wang ◽

Hao Guo ◽

...

Keyword(s):

Resting State ◽

Resting State Fmri ◽

Resting State Networks ◽

Functional Magnetic Resonance ◽

Intra Class Correlation ◽

Retest Reliability ◽

Brain Signals ◽

Human Connectome Project ◽

Test Retest Reliability ◽

The Brain

In recent years, interest has been growing in dynamic characteristic of brain signals from resting-state functional magnetic resonance imaging (rs-fMRI). Synchrony and metastability, as neurodynamic indexes, are considered as one of methods for analyzing dynamic characteristics. Although much research has studied the analysis of neurodynamic indices, few have investigated its reliability. In this paper, the datasets from the Human Connectome Project have been used to explore the test–retest reliabilities of synchrony and metastability from multiple angles through intra-class correlation (ICC). The results showed that both of these indexes had fair test–retest reliability, but they are strongly affected by the field strength, the spatial resolution, and scanning interval, less affected by the temporal resolution. Denoising processing can help improve their ICC values. In addition, the reliability of neurodynamic indexes was affected by the node definition strategy, but these effects were not apparent. In particular, by comparing the test–retest reliability of different resting-state networks, we found that synchrony of different networks was basically stable, but the metastability varied considerably. Among these, DMN and LIM had a relatively higher test–retest reliability of metastability than other networks. This paper provides a methodological reference for exploring the brain dynamic neural activity by using synchrony and metastability in fMRI signals.

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Evaluating the sensitivity of functional connectivity measures to motion artifact in resting-state fMRI data

NeuroImage ◽

10.1016/j.neuroimage.2021.118408 ◽

2021 ◽

pp. 118408

Author(s):

Arun S. Mahadevan ◽

Ursula A. Tooley ◽

Maxwell A. Bertolero ◽

Allyson P. Mackey ◽

Danielle S. Bassett

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Motion Artifact ◽

Resting State Fmri ◽

Fmri Data

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Test-retest reliability of dynamic functional connectivity in resting state fMRI

NeuroImage ◽

10.1016/j.neuroimage.2018.08.021 ◽

2018 ◽

Vol 183 ◽

pp. 907-918 ◽

Cited By ~ 11

Author(s):

Chao Zhang ◽

Stefi A. Baum ◽

Viraj R. Adduru ◽

Bharat B. Biswal ◽

Andrew M. Michael

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Resting State Fmri ◽

Dynamic Functional Connectivity ◽

Retest Reliability ◽

Test Retest Reliability

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The Effect of General Anesthesia On Test-Retest Reliability of Resting-State FMRI Metrics And Optimization of Scan Length

10.21203/rs.3.rs-992129/v1 ◽

2021 ◽

Author(s):

Faezeh Vedaei ◽

Mahdi Alizadeh ◽

Victor M Romo ◽

Feroze B. Mohamed ◽

Chengyuan Wu

Keyword(s):

Resting State ◽

Intraclass Correlation ◽

Resting State Fmri ◽

Frequency Fluctuation ◽

Retest Reliability ◽

Factors Affecting ◽

Fractional Frequency ◽

Drug Resistant Epilepsy ◽

Test Retest Reliability ◽

Scan Length

Abstract Resting-state functional magnetic resonance imaging (rs-fMRI) has been known as a powerful tool in neuroscience. However, exploring the test-retest reliability of the metrics derived from rs-fMRI BOLD signal is essential particularly in the studies of patients with neurological development. Two factors affecting reliability of rs-fMRI measurements including the effect of anesthesia and scan length have been estimated in this study. A total of 9 patients with drug-resistant epilepsy (DRE) of requiring interstitial thermal therapy (LITT) were scanned in two states of awake and under anesthesia. At each state, two rs-fMRI sessions were obtained that each one lasted 15 minutes, and the effect of scan length was evaluated. Voxel-wise rs-fMRI metrics including amplitude of low fractional frequency fluctuation (ALFF), amplitude of low fractional frequency fluctuation (fALFF), functional connectivity (FC), and regional homogeneity (ReHo) were measured. Intraclass correlation coefficient (ICC) was calculated to estimate the reliability between two sessions of scanning for both states. Overall, our finding revealed that reliability improves under anesthesia as well as by increasing the scanning length of the scanning sessions. Furthermore, we showed that the optimal scan length to achieve reliable rs-fMRI measurements was 3.1 – 7.5 minutes shorter in an anesthetized, compared to wakeful state.

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Partial correlation mapping of brain functional connectivity with resting state fMRI

10.1117/12.709012 ◽

2007 ◽

Cited By ~ 1

Author(s):

Zonglei Zhen ◽

Jie Tian ◽

Wei Qin ◽

Hui Zhang

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Partial Correlation ◽

Resting State Fmri ◽

Brain Functional Connectivity

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The Identification of Alzheimer’s Disease Using Functional Connectivity Between Activity Voxels in Resting-State fMRI Data

IEEE Journal of Translational Engineering in Health and Medicine ◽

10.1109/jtehm.2020.2985022 ◽

2020 ◽

Vol 8 ◽

pp. 1-11

Author(s):

Yuhu Shi ◽

Weiming Zeng ◽

Jin Deng ◽

Weifang Nie ◽

Yifei Zhang

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Functional Connectivity ◽

Resting State ◽

Resting State Fmri ◽

Fmri Data

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Model testing for distinctive functional connectivity gradients with resting-state fMRI data

10.1101/298752 ◽

2018 ◽

Author(s):

Jonathan F. O’Rawe ◽

Jaime S. Ide ◽

Hoi-Chung Leung

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Functional Organization ◽

Region Of Interest ◽

Resting State Fmri ◽

Model Testing ◽

Fmri Data ◽

Extensive Literature ◽

Topographic Organization ◽

Lateral Organization

AbstractIn accordance with the concept of topographic organization of neuroanatomical structures, there is an increased interest in estimating and delineating continuous changes in the functional connectivity patterns across neighboring voxels within a region of interest using resting-state fMRI data. Fundamental to this functional connectivity gradient analysis is the assumption that the functional organization is stable and uniform across the region of interest. To evaluate this assumption, we developed a model testing procedure to arbitrate between overlapping, shifted, or different topographic connectivity gradients across subdivisions of a structure. We tested the procedure using the striatum, a subcortical structure consisting of the caudate nucleus and putamen, in which an extensive literature, primarily from rodents and non-human primates, suggest to have a shared topographic organization of a single diagonal gradient. We found, across multiple resting state fMRI data samples of different spatial resolutions in humans, and one macaque resting state fMRI data sample, that the models with different functional connectivity gradients across the caudate and putamen was the preferred model. The model selection procedure was validated in control conditions of checkerboard subdivisions, demonstrating the expected overlapping gradient. More specifically, while we replicated the diagonal organization of the functional connectivity gradients in both the caudate and putamen, our analysis also revealed a medial-lateral organization within the caudate. Not surprisingly, performing the same analysis assuming a unitary gradient obfuscates the medial-lateral organization of the caudate, producing only a diagonal gradient. These findings demonstrate the importance of testing basic assumptions and evaluating interpretations across species. The significance of differential topographic gradients across the putamen and caudate and the medial-lateral gradient of the caudate in humans should be tested in future studies.

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Whole brain mapping of somatosensory responses in awake marmosets investigated with ultra-high-field fMRI

Journal of Neurophysiology ◽

10.1152/jn.00480.2020 ◽

2020 ◽

Vol 124 (6) ◽

pp. 1900-1913

Author(s):

Justine C. Cléry ◽

Yuki Hori ◽

David J. Schaeffer ◽

Joseph S. Gati ◽

J. Andrew Pruszynski ◽

...

Keyword(s):

Functional Connectivity ◽

Brain Mapping ◽

Resting State ◽

High Field ◽

Body Representation ◽

Resting State Fmri ◽

Fmri Data ◽

Ultra High Field ◽

Somatosensory Stimulation ◽

Somatosensory Responses

We used somatosensory stimulation combined with functional MRI (fMRI) in awake marmosets to reveal the topographic body representation in areas S1, S2, thalamus, and putamen. We showed the existence of a body representation organization within the thalamus and the cingulate cortex by computing functional connectivity maps from seeds defined in S1/S2 using resting-state fMRI data. This noninvasive approach will be essential for chronic studies by guiding invasive recording and manipulation techniques.

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