ArticleNeuroImage2017
Sources and implications of whole-brain fMRI signals in humans.
Article in NeuroImage, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 315 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
315 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Functional imaging studies of acute administration of classic psychedelics, ketamine, and MDMA: Methodological limitations and convergent results.Neuroscience and biobehavioral reviews · 2023Pooled it
- From Lung to Brain: Respiration Modulates Neural and Mental Activity.Neuroscience bulletin · 2023Pooled it
- The impact of an app-delivered mindfulness-based intervention on resting-state functional connectivity in pediatric concussion: a pilot study.Frontiers in neuroscience · 2026Trial
- Ketamine induces multiple individually distinct whole-brain functional connectivity signatures.eLife · 2024Trial
- Feasibility of training the dorsolateral prefrontal-striatal network by real-time fMRI neurofeedback.Scientific reports · 2022Trial
- Trial
- Functional Dysconnectivity of Frontal Cortex to Striatum Predicts Ketamine Infusion Response in Treatment-Resistant Depression.The international journal of neuropsychopharmacology · 2020Trial
- Article
- Dynamic Co-Modulation (DyCoM): A Unified Operator Framework for Dynamic Connectivity in Neuroimaging.bioRxiv : the preprint server for biology · 2026Article
- The Impact of Denoising Approaches on the Relationship Between Alzheimer's Disease Diagnostic Status and Network Topology Measures.Human brain mapping · 2026Article
- Brain network dynamics reflect psychiatric illness status and transdiagnostic symptom profiles across health and disease.Nature communications · 2026Article
- Functional inertia reveals history-dependent organization of large-scale brain dynamics.Research square · 2026Article
- The human claustrum supports cognitive networks for externally and internally driven task demands.PLoS biology · 2026Article
- Age-Related Low Frequency Amplitude Differences in Resting-State Blood Oxygenation Level-Dependent Signal in the Cerebellum.Human brain mapping · 2026Article
- Longitudinal Awake Mouse fMRI During Voluntary Locomotion Using Zero TE Imaging and a Novel Treadmill Training Protocol.Magnetic resonance in medicine · 2026Article
- Global Signal Removal (GSR) as graph spatial filtering.bioRxiv : the preprint server for biology · 2026Article
- Altered functional connectivity of the hippocampus in cortico-subcortical networks in early-stage and emerging psychosis.European archives of psychiatry and clinical neuroscience · 2026Article
- Article
- Task-evoked functional connectivity exhibits novel and strengthened relationships with executive function relative to the resting state.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- A new fMRI quality metric using multi-echo information: Theory, validation and implications.bioRxiv : the preprint server for biology · 2026Article
255 more citing papers are in PubMed but not listed here.
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4 authors.
Funding
Abstract
Whole-brain fMRI signals are a subject of intense interest: variance in the global fMRI signal (the spatial mean of all signals in the brain) indexes subject arousal, and psychiatric conditions such as schizophrenia and autism have been characterized by differences in the global fMRI signal. Further, vigorous debates exist on whether global signals ought to be removed from fMRI data. However, surprisingly little research has focused on the empirical properties of whole-brain fMRI signals. Here we map the spatial and temporal properties of the global signal, individually, in 1000+ fMRI scans. Variance in the global fMRI signal is strongly linked to head motion, to hardware artifacts, and to respiratory patterns and their attendant physiologic changes. Many techniques used to prepare fMRI data for analysis fail to remove these uninteresting kinds of global signal fluctuations. Thus, many studies include, at the time of analysis, prominent global effects of yawns, breathing changes, and head motion, among other signals. Such artifacts will mimic dynamic neural activity and will spuriously alter signal covariance throughout the brain. Methods capable of isolating and removing global artifactual variance while preserving putative "neural" variance are needed; this paper adopts no position on the topic of global signal regression.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.