Evaluation of confound regression strategies for the mitigation of micromovement artifact in studies of dynamic resting-state functional connectivity and multilayer network modularity

Dynamic functional connectivity reflects the spatiotemporal organization of spontaneous brain activity in health and disease. Dynamic functional connectivity may be susceptible to artifacts induced by participant motion. This report provides a systematic evaluation of 12 commonly used participant-level confound regression strategies designed to mitigate the effects of micromovements in a sample of 393 youths (ages 8–22 years). Each strategy was evaluated according to a number of benchmarks, including (a) the residual association between participant motion and edge dispersion, (b) distance-dependent effects of motion on edge dispersion, (c) the degree to which functional subnetworks could be identified by multilayer modularity maximization, and (d) measures of module reconfiguration, including node flexibility and node promiscuity. Results indicate variability in the effectiveness of the evaluated pipelines across benchmarks. Methods that included global signal regression were the most consistently effective de-noising strategies.

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Evaluation of confound regression strategies for the mitigation of micromovement artifact in studies of dynamic resting state functional connectivity and multilayer network modularity

10.31234/osf.io/rw5zt ◽

2018 ◽

Author(s):

David M. Lydon-Staley ◽

Rastko Ciric ◽

Theodore D. Satterthwaite ◽

Danielle S Bassett

Keyword(s):

Functional Connectivity ◽

Brain Activity ◽

Systematic Evaluation ◽

Resting State Functional Connectivity ◽

Multilayer Network ◽

Dynamic Functional Connectivity ◽

Spontaneous Brain Activity ◽

Global Signal ◽

Health And Disease ◽

Modularity Maximization

Dynamic functional connectivity reflects the spatiotemporal organization of spontaneous brain activity in health and disease. Dynamic functional connectivity may be susceptible to artifacts induced by participant motion. This report provides a systematic evaluation of 12 commonly-used participant-level confound regression strategies designed to mitigate the effects of micromovements in a sample of 393 youths (ages 8-22 years). Each strategy was evaluated according to a number of benchmarks, including (i) the residual association between participant motion and edge dispersion, (ii) distance-dependent effects of motion on edge dispersion, (iii) the degree to which functional sub-networks could be identified by multilayer-modularity maximization, and (iv) measures of module reconfiguration, including node flexibility and node promiscuity. Results indicate variability in the effectiveness of the evaluated pipelines across benchmarks. Methods that included global signal regression were the most consistently effective de-noising strategies.

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Belief in Communism and Theory of Mind

Frontiers in Psychology ◽

10.3389/fpsyg.2021.697251 ◽

2021 ◽

Vol 12 ◽

Author(s):

Outong Chen ◽

Fang Guan ◽

Yu Du ◽

Yijun Su ◽

Hui Yang ◽

...

Keyword(s):

Functional Connectivity ◽

Theory Of Mind ◽

Resting State ◽

Brain Activity ◽

Neural Correlates ◽

Resting State Functional Connectivity ◽

Neural Basis ◽

Spontaneous Brain Activity ◽

Multiple Regions ◽

Left Thalamus

A belief in communism refers to the unquestionable trust and belief in the justness of communism. Although former studies have discussed the political aim and social value of communism, the cognitive neural basis of a belief in communism remains largely unknown. In this study, we determined the behavioral and neural correlates between a belief in communism and a theory of mind (ToM). For study 1, questionnaire scores were measured and for study 2, regional homogeneity (ReHo) and resting-state functional connectivity (rsFC) were used as an index for resting-state functional MRI (rs-fMRI), as measured by the Belief in Communism Scale (BCS). The results showed that a belief in communism is associated with higher ReHo in the left thalamus and lower ReHo in the left medial frontal gyrus (MFG). Furthermore, the results of the rsFC analysis revealed that strength of functional connectivity between the left thalamus and the bilateral precuneus is negatively associated with a belief in communism. Hence, this study provides evidence that spontaneous brain activity in multiple regions, which is associated with ToM capacity, contributes to a belief in communism.

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Normalisation of brain connectivity through compensatory behaviour, despite congenital hand absence

eLife ◽

10.7554/elife.04605 ◽

2015 ◽

Vol 4 ◽

Cited By ~ 22

Author(s):

Avital Hahamy ◽

Stamatios N Sotiropoulos ◽

David Henderson Slater ◽

Rafael Malach ◽

Heidi Johansen-Berg ◽

...

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Brain Connectivity ◽

Brain Activity ◽

Adaptive Behaviour ◽

Resting State Functional Connectivity ◽

Spontaneous Brain Activity ◽

White Matter Microstructure ◽

Hand Region ◽

Ecological Behaviour

Previously we showed, using task-evoked fMRI, that compensatory intact hand usage after amputation facilitates remapping of limb representations in the cortical territory of the missing hand (<xref ref-type="bibr" rid="bib15">Makin et al., 2013a</xref>). Here we show that compensatory arm usage in individuals born without a hand (one-handers) reflects functional connectivity of spontaneous brain activity in the cortical hand region. Compared with two-handed controls, one-handers showed reduced symmetry of hand region inter-hemispheric resting-state functional connectivity and corticospinal white matter microstructure. Nevertheless, those one-handers who more frequently use their residual (handless) arm for typically bimanual daily tasks also showed more symmetrical functional connectivity of the hand region, demonstrating that adaptive behaviour drives long-range brain organisation. We therefore suggest that compensatory arm usage maintains symmetrical sensorimotor functional connectivity in one-handers. Since variability in spontaneous functional connectivity in our study reflects ecological behaviour, we propose that inter-hemispheric symmetry, typically observed in resting sensorimotor networks, depends on coordinated motor behaviour in daily life.

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Beyond the low frequency fluctuations morning and evening differences in human brain

10.31219/osf.io/pkrjs ◽

2019 ◽

Author(s):

Magdalena Fafrowicz ◽

Bartosz Bohaterewicz ◽

Anna Ceglarek ◽

Monika Cichocka ◽

Koryna Lewandowska ◽

...

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Human Performance ◽

Brain Activity ◽

Activity Patterns ◽

Low Frequency ◽

Basic Mechanism ◽

Time Of Day ◽

Resting State Functional Connectivity ◽

Circadian Typology

Human performance, alertness, and most biological functions express rhythmic fluctuations across a 24-hour-period. This phenomenon is believed to originate from differences in both circadian and homeostatic sleep-wake regulatory processes. Interactions between these processes result in time-of-day modulations of behavioral performance as well as brain activity patterns. Although the basic mechanism of the 24-hour clock is conserved across evolution, there are interindividual differences in the timing of sleep-wake cycles, subjective alertness and functioning throughout the day. The study of circadian typology differences has increased during the last few years, especially research on extreme chronotypes, which provide a unique way to investigate the effects of sleep-wake regulation on cerebral mechanisms. Using functional magnetic resonance imaging (fMRI), we assessed the influence of chronotype and time-of-day on resting-state functional connectivity. 29 extreme morning- and 34 evening-type participants underwent two fMRI sessions: about one hour after wake-up time (morning) and about ten hours after wake-up time (evening), scheduled according to their declared habitual sleep-wake pattern on a regular working day. Analysis of obtained neuroimaging data disclosed only an effect of time of day on resting-state functional connectivity; there were different patterns of functional connectivity between morning and evening sessions. The results of our study showed no differences between extreme morning-type and evening-type individuals. We demonstrate that circadian and homeostatic influences on the resting-state functional connectivity have a universal character, unaffected by circadian typology.

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Impact of Alzheimers Disease on the Functional Connectivity of Spontaneous Brain Activity

Current Alzheimer Research ◽

10.2174/156720509790147106 ◽

2009 ◽

Vol 6 (6) ◽

pp. 541-553 ◽

Cited By ~ 59

Author(s):

Christian Sorg ◽

Valentin Riedl ◽

Robert Perneczky ◽

Alexander Kurz ◽

Afra Wohlschlager

Keyword(s):

Functional Connectivity ◽

Brain Activity ◽

Alzheimers Disease ◽

Spontaneous Brain Activity

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Brain activity at rest: a multiscale hierarchical functional organization

Journal of Neurophysiology ◽

10.1152/jn.00895.2010 ◽

2011 ◽

Vol 105 (6) ◽

pp. 2753-2763 ◽

Cited By ~ 187

Author(s):

Gaëlle Doucet ◽

Mikaël Naveau ◽

Laurent Petit ◽

Nicolas Delcroix ◽

Laure Zago ◽

...

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Functional Organization ◽

Brain Activity ◽

Correlation Coefficients ◽

Temporal Correlation ◽

Hierarchical Level ◽

Spontaneous Brain Activity ◽

Dorsal Attentional Network

Spontaneous brain activity was mapped with functional MRI (fMRI) in a sample of 180 subjects while in a conscious resting-state condition. With the use of independent component analysis (ICA) of each individual fMRI signal and classification of the ICA-defined components across subjects, a set of 23 resting-state networks (RNs) was identified. Functional connectivity between each pair of RNs was assessed using temporal correlation analyses in the 0.01- to 0.1-Hz frequency band, and the corresponding set of correlation coefficients was used to obtain a hierarchical clustering of the 23 RNs. At the highest hierarchical level, we found two anticorrelated systems in charge of intrinsic and extrinsic processing, respectively. At a lower level, the intrinsic system appears to be partitioned in three modules that subserve generation of spontaneous thoughts (M1a; default mode), inner maintenance and manipulation of information (M1b), and cognitive control and switching activity (M1c), respectively. The extrinsic system was found to be made of two distinct modules: one including primary somatosensory and auditory areas and the dorsal attentional network (M2a) and the other encompassing the visual areas (M2b). Functional connectivity analyses revealed that M1b played a central role in the functioning of the intrinsic system, whereas M1c seems to mediate exchange of information between the intrinsic and extrinsic systems.

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Abnormal Spontaneous Brain Activity and Functional Connectivity of the Default Mode Network in Patients with Bipolar Disorder

10.21203/rs.3.rs-194210/v1 ◽

2021 ◽

Author(s):

Lei Zhao ◽

Qijing Bo ◽

Zhifang Zhang ◽

Feng Li ◽

Yuan Zhou ◽

...

Keyword(s):

Bipolar Disorder ◽

Functional Connectivity ◽

Default Mode Network ◽

Resting State ◽

Brain Activity ◽

Seed Region ◽

Potential Candidate ◽

Neural Basis ◽

Default Mode ◽

Spontaneous Brain Activity

Abstract Background: No consistent evidence on the specific brain regions is available in the default mode network (DMN), which show abnormal spontaneous activity in bipolar disorder (BD). We aim to identify this region that is particularly impaired in patients with BD by using several different indices measuring spontaneous brain activity and then investigate its functional connectivity (FC).Methods: A total of 56 patients with BD and 71 healthy controls (HC) underwent resting-state functional magnetic resonance imaging. Three commonly used functional indices were used to identify the brain region showing abnormal spontaneous brain activity in BD. Then, this region served as the seed region for resting-state FC analysis to identify its functional networks altered in BD.Results: The BD group exhibited decreased fALFF, ReHo, and DC values in the left precuneus. The BD group had decreased rsFC within the DMN, indicated by decreased resting-state FC within the left precuneus and between the left precuneus and the medial prefrontal cortex. The BD group had decreased negative connectivity between the left precuneus and the left putamen, extending to the left insula.Conclusions: The findings provide convergent evidence for the abnormalities in the DMN of BD, particularly located in the left precuneus. Decreased FC within the DMN and the disruptive anticorrelation between the DMN and the salience network are found in BD. These findings suggest that the DMN is a key aspect for understanding the neural basis of BD, and the altered functional patterns of DMN may be a potential candidate biomarker of BD.

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Predicting Individual Variability in Task-Evoked Brain Activity in Schizophrenia

10.1101/2020.05.25.114603 ◽

2020 ◽

Author(s):

Niv Tik ◽

Abigail Livny ◽

Shachar Gal ◽

Karny Gigi ◽

Galia Tsarfaty ◽

...

Keyword(s):

Functional Connectivity ◽

Prediction Model ◽

Resting State ◽

Brain Activity ◽

Strong Association ◽

Brain Activation ◽

Individual Variability ◽

Resting State Functional Connectivity ◽

Successful Prediction ◽

And Task

AbstractBACKGROUNDPatients suffering from schizophrenia demonstrate abnormal brain activity, as well as alterations in patterns of functional connectivity assessed by functional magnetic resonance imaging (fMRI). Previous studies in healthy participants suggest a strong association between resting-state functional connectivity and task-evoked brain activity that could be detected at an individual level, and show that brain activation in various tasks could be predicted from task-free fMRI scans. In the current study we aimed to predict brain activity in patients diagnosed with schizophrenia, using a prediction model based on healthy individuals exclusively. This offers novel insights regarding the interrelations between brain connectivity and activity in schizophrenia.METHODSWe generated a prediction model using a group of 80 healthy controls that performed the well-validated N-back task, and used it to predict individual variability in task-evoked brain activation in 20 patients diagnosed with schizophrenia.RESULTSWe demonstrated a successful prediction of individual variability in the task-evoked brain activation based on resting-state functional connectivity. The predictions were highly sensitive, reflected by high correlations between predicted and actual activation maps (Median = 0.589, SD = 0.193) and specific, evaluated by a Kolomogrov-Smirnov test (D = 0.25, p < 0.0001).CONCLUSIONSA Successful prediction of brain activity from resting-state functional connectivity highlights the strong coupling between the two. Moreover, our results support the notion that even though resting-state functional connectivity and task-evoked brain activity are frequently reported to be altered in schizophrenia, the relations between them remains unaffected. This may allow to generate task activity maps for clinical populations without the need the actually perform the task.

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The cue-reactivity paradigm: An ensemble of networks driving attention and cognition when viewing drug-related and natural-reward stimuli

10.1101/2020.02.26.966549 ◽

2020 ◽

Author(s):

Lauren D. Hill-Bowen ◽

Michael C. Riedel ◽

Ranjita Poudel ◽

Taylor Salo ◽

Jessica S. Flannery ◽

...

Keyword(s):

Functional Connectivity ◽

Brain Activity ◽

Cue Reactivity ◽

Dorsal Striatum ◽

Brain Regions ◽

Reward Processing ◽

Resting State Functional Connectivity ◽

Addictive Disorders ◽

Natural Reward ◽

Elemental Nature

ABSTRACTBackgroundThe cue-reactivity paradigm is a widely adopted neuroimaging probe assessing brain activity linked to attention, memory, emotion, and reward processing associated with the presentation of appetitive stimuli. Lacking, is the apperception of more precise brain regions, neurocircuits, and mental operations comprising cue-reactivity’s multi-elemental nature. To resolve such complexities, we employed emergent meta-analytic techniques to enhance insight into drug and natural cue-reactivity in the brain.MethodsOperating from this perspective, we first conducted multiple coordinate-based meta-analyses to define common and distinct brain regions showing convergent activation across studies involving drug-related and natural-reward cue-reactivity paradigms. In addition, we examined the activation profiles of each convergent brain region linked to cue-reactivity as seeds in task-dependent and task-independent functional connectivity analyses. Using methods to cluster regions of interest, we categorized cue-reactivity into cliques, or sub-networks, based on the functional similarities between regions. Cliques were further classified with psychological constructs.ResultsWe identified a total of 164 peer-reviewed articles: 108 drug-related, and 56 natural-reward. When considering cue-reactivity collectively, across both drug and natural studies, activity convergence was observed in the dorsal striatum, limbic, insula, parietal, occipital, and temporal regions. Common convergent neural activity between drug and natural cue-reactivity was observed in the caudate, amygdala, thalamus, cingulate, and temporal regions. Drug distinct convergence was observed in the putamen, cingulate, and temporal regions, while natural distinct convergence was observed in the caudate, parietal, occipital, and frontal regions. We seeded identified cue-reactivity regions in meta-analytic connectivity modeling and resting-state functional connectivity analyses. Consensus hierarchical clustering of both connectivity analyses identified six distinct cliques that were further functionally characterized using the BrainMap and Neurosynth databases.ConclusionsWe examined the multifaceted nature of cue-reactivity and decomposed this construct into six elements of visual, executive function, sensorimotor, salience, emotion, and self-referential processing. Further, we demonstrated that these elements are supported by perceptual, sensorimotor, tripartite, and affective networks, which are essential to understanding the neural mechanisms involved in the development and or maintenance of addictive disorders.

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Multifractal and entropy analysis of resting-state electroencephalography reveals spatial organization in local dynamic functional connectivity

Scientific Reports ◽

10.1038/s41598-019-49726-5 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 2

Author(s):

Frigyes Samuel Racz ◽

Orestis Stylianou ◽

Peter Mukli ◽

Andras Eke

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Spatial Organization ◽

Brain Activity ◽

Surrogate Data ◽

Brain Regions ◽

Local Dynamic ◽

Dynamic Functional Connectivity ◽

Multifractal Scaling ◽

The Brain

Abstract Functional connectivity of the brain fluctuates even in resting-state condition. It has been reported recently that fluctuations of global functional network topology and those of individual connections between brain regions expressed multifractal scaling. To expand on these findings, in this study we investigated if multifractality was indeed an inherent property of dynamic functional connectivity (DFC) on the regional level as well. Furthermore, we explored if local DFC showed region-specific differences in its multifractal and entropy-related features. DFC analyses were performed on 62-channel, resting-state electroencephalography recordings of twelve young, healthy subjects. Surrogate data testing verified the true multifractal nature of regional DFC that could be attributed to the presumed nonlinear nature of the underlying processes. Moreover, we found a characteristic spatial distribution of local connectivity dynamics, in that frontal and occipital regions showed stronger long-range correlation and higher degree of multifractality, whereas the highest values of entropy were found over the central and temporal regions. The revealed topology reflected well the underlying resting-state network organization of the brain. The presented results and the proposed analysis framework could improve our understanding on how resting-state brain activity is spatio-temporally organized and may provide potential biomarkers for future clinical research.

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