Molecular-enriched functional connectivity in the human brain using multiband multi-echo simultaneous ASL/BOLD fMRI

Dipasquale, Ottavia; Cohen, Alexander D.; Martins, Daniel; Zelaya, Fernando; Turkheimer, Federico; Veronese, Mattia; Mehta, Mitul A.; Williams, Steven; Yang, Baolian; Banerjee, Suchandrima; Wang, Yan

doi:10.1038/s41598-023-38573-0

Cited by 4 publications

(2 citation statements)

References 77 publications

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“…We investigated the within-subject similarity of activation estimates by examining the voxel-wise spatial correlation between the Limited and Amplified motion scans for each subject. Spatial correlation has been used by several fMRI studies as a metric of similarity and stability across scans (Braban et al, 2023; Dipasquale et al, 2023; Gong et al, 2023; Kannurpatti et al, 2012; Yuan et al, 2013). The Limited motion scan for each subject served as an estimate of the ground-truth activation in our dataset.…”

Section: Discussionmentioning

confidence: 99%

Denoising task-correlated head motion from motor-task fMRI data with multi-echo ICA

Reddy¹,

Zvolanek²,

Moia

et al. 2023

Preprint

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Motor-task functional magnetic resonance imaging (fMRI) is crucial in the study of several clinical conditions, including stroke and Parkinson's disease. However, motor-task fMRI is complicated by task-correlated head motion, which can be magnified in clinical populations and confounds motor activation results. One method that may mitigate this issue is multi-echo independent component analysis (ME-ICA), which has been shown to separate the effects of head motion from the desired BOLD signal, but has not been tested in motor-task datasets with high amounts of motion. In this study, we collected an fMRI dataset from a healthy population who performed a hand grasp task with and without task-correlated amplified head motion to simulate a motor-impaired population. We analyzed these data using three models: single-echo (SE), multi-echo optimally combined (ME-OC), and ME-ICA. We compared the models' performance in mitigating the effects of head motion on the subject level and group level. On the subject level, ME-ICA better dissociated the effects of head motion from the BOLD signal; both ME models led to increased activation extent and t-statistics in brain motor regions. In scans with high levels of motion, ME-ICA additionally mitigated artifacts and led to potentially more reliable beta coefficient estimates, compared to ME-OC. On the group level, all three models produced activation clusters in expected motor areas in scans with both low and high motion, indicating that group-level averaging may also sufficiently resolve motion artifacts that vary by subject. These findings demonstrate that ME-ICA is a useful tool for subject-level analysis of motor-task data with high levels of task-correlated head motion. The improvements afforded by ME-ICA are critical to improve reliability of subject-level activation maps for clinical populations in which group-level analysis may not be feasible or appropriate, for example in a chronic stroke cohort with varying stroke location and degree of tissue damage.

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Section: Discussionmentioning

confidence: 99%

Denoising task-correlated head motion from motor-task fMRI data with multi-echo ICA

Reddy¹,

Zvolanek²,

Moia

et al. 2023

Preprint

View full text Add to dashboard Cite

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“…Running REACT comprises of a 2‐step multiple linear regression analysis within the REACT toolbox (https://github.com/ottaviadipasquale/react-fmri). 41 The 4D whole‐brain fMRI maps and PET maps were demeaned, and the PET maps used as spatial regressors to estimate the dominant BOLD fluctuations related to each of the molecular targets. Of note, a mask, generated by binarizing the PET maps, was used to restrict analysis to only the areas where information on transporter and receptor density was available.…”

Section: Methodsmentioning

confidence: 99%

Abnormal Glutamatergic and Serotonergic Connectivity in Visual Snow Syndrome and Migraine with Aura

Puledda,

Dipasquale,

Gooddy

et al. 2023

Annals of Neurology

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ObjectiveNeuropharmacological changes in visual snow syndrome (VSS) are poorly understood. We aimed to use receptor target maps combined with resting functional magnetic resonance imaging (fMRI) data to identify which neurotransmitters might modulate brain circuits involved in VSS.MethodsWe used Receptor‐Enriched Analysis of Functional Connectivity by Targets (REACT) to estimate and compare the molecular‐enriched functional networks related to 5 neurotransmitter systems of patients with VSS (n = 24), healthy controls (HCs; n = 24), and migraine patients ([MIG], n = 25, 15 of whom had migraine with aura [MwA]). For REACT we used receptor density templates for the transporters of noradrenaline, dopamine, and serotonin, GABA‐A and NMDA receptors, as well as 5HT1B and 5HT2A receptors, and estimated the subject‐specific voxel‐wise maps of functional connectivity (FC). We then performed voxel‐wise comparisons of these maps among HCs, MIG, and VSS.ResultsPatients with VSS had reduced FC in glutamatergic networks localized in the anterior cingulate cortex (ACC) compared to HCs and patients with migraine, and reduced FC in serotoninergic networks localized in the insula, temporal pole, and orbitofrontal cortex compared to controls, similar to patients with migraine with aura. Patients with VSS also showed reduced FC in 5HT2A‐enriched networks, largely localized in occipito‐temporo‐parietal association cortices. As revealed by subgroup analyses, these changes were independent of, and analogous to, those found in patients with migraine with aura.InterpretationOur results show that glutamate and serotonin are involved in brain connectivity alterations in areas of the visual, salience, and limbic systems in VSS. Importantly, altered serotonergic connectivity is independent of migraine in VSS, and simultaneously comparable to that of migraine with aura, highlighting a shared biology between the disorders. ANN NEUROL 2023

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Connectome dysfunction in patients at clinical high risk for psychosis and modulation by oxytocin

Davies,

Martins,

Dipasquale

et al. 2024

Mol Psychiatry

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Abnormalities in functional brain networks (functional connectome) are increasingly implicated in people at Clinical High Risk for Psychosis (CHR-P). Intranasal oxytocin, a potential novel treatment for the CHR-P state, modulates network topology in healthy individuals. However, its connectomic effects in people at CHR-P remain unknown. Forty-seven men (30 CHR-P and 17 healthy controls) received acute challenges of both intranasal oxytocin 40 IU and placebo in two parallel randomised, double-blind, placebo-controlled cross-over studies which had similar but not identical designs. Multi-echo resting-state fMRI data was acquired at approximately 1 h post-dosing. Using a graph theoretical approach, the effects of group (CHR-P vs healthy control), treatment (oxytocin vs placebo) and respective interactions were tested on graph metrics describing the topology of the functional connectome. Group effects were observed in 12 regions (all pFDR < 0.05) most localised to the frontoparietal network. Treatment effects were found in 7 regions (all pFDR < 0.05) predominantly within the ventral attention network. Our major finding was that many effects of oxytocin on network topology differ across CHR-P and healthy individuals, with significant interaction effects observed in numerous subcortical regions strongly implicated in psychosis onset, such as the thalamus, pallidum and nucleus accumbens, and cortical regions which localised primarily to the default mode network (12 regions, all pFDR < 0.05). Collectively, our findings provide new insights on aberrant functional brain network organisation associated with psychosis risk and demonstrate, for the first time, that oxytocin modulates network topology in brain regions implicated in the pathophysiology of psychosis in a clinical status (CHR-P vs healthy control) specific manner.

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Molecular-enriched functional connectivity in the human brain using multiband multi-echo simultaneous ASL/BOLD fMRI

Cited by 4 publications

References 77 publications

Denoising task-correlated head motion from motor-task fMRI data with multi-echo ICA

Denoising task-correlated head motion from motor-task fMRI data with multi-echo ICA

Abnormal Glutamatergic and Serotonergic Connectivity in Visual Snow Syndrome and Migraine with Aura

Connectome dysfunction in patients at clinical high risk for psychosis and modulation by oxytocin

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