Machine learning of large-scale multimodal brain imaging data reveals neural correlates of hand preference

Chormai, Pattarawat; Pu, Yi; Hu, Haoyu; Fisher, Simon E.; Francks, Clyde; Kong, Xiangzhen

doi:10.1016/j.neuroimage.2022.119534

Cited by 12 publications

(8 citation statements)

References 58 publications

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“…A reverse trend between brain lymphatic system function and human age has currently been confirmed (Jessen et al, 2015;. In addition, handedness and the dominant brain side influence the thickness of the superior longitudinal fasciculus (Chormai et al, 2022). This may have an impact on the measurement of ALPS, and therefore, the results may not be as accurate as expected, which also contributes to laterality.…”

Section: Lateralization Of Dti-alpsmentioning

confidence: 86%

“…Diffusion tensor image (DTI) metrics are currently the most common indices depicting the microstructural integrity of white matter. Among them, fractional anisotropy (FA) represents axonal alterations (Tavazzi et al, 2022), and mean diffusivity (MD) is associated with cerebral edema (Chormai et al, 2022). Previous studies showed that DTI metrics are the reliable quantitative metrics of CST that correlate with motor function outcomes and Fugl-Meyer assessment (FMA) scores in stroke rehabilitation (Haque et al, 2021;Lee et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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DTI-ALPS: An MR biomarker for motor dysfunction in patients with subacute ischemic stroke

Qin

Li²,

Qiao

et al. 2023

Front. Neurosci.

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PurposeBrain glymphatic dysfunction is involved in the pathologic process of acute ischemic stroke (IS). The relationship between brain glymphatic activity and dysfunction in subacute IS has not been fully elucidated. Diffusion tensor image analysis along the perivascular space (DTI-ALPS) index was used in this study to explore whether glymphatic activity was related to motor dysfunction in subacute IS patients.MethodsTwenty-six subacute IS patients with a single lesion in the left subcortical region and 32 healthy controls (HCs) were recruited in this study. The DTI-ALPS index and DTI metrics (fractional anisotropy, FA, and mean diffusivity, MD) were compared within and between groups. Spearman's and Pearson's partial correlation analyses were performed to analyze the relationships of the DTI-ALPS index with Fugl-Meyer assessment (FMA) scores and with corticospinal tract (CST) integrity in the IS group, respectively.ResultsSix IS patients and two HCs were excluded. The left DTI-ALPS index of the IS group was significantly lower than that of the HC group (t = −3.02, p = 0.004). In the IS group, a positive correlation between the left DTI-ALPS index and the simple Fugl-Meyer motor function score (ρ = 0.52, p = 0.019) and a significant negative correlation between the left DTI-ALPS index and the FA (R = −0.55, p = 0.023) and MD (R = −0.48, p = 0.032) values of the right CST were found.ConclusionsGlymphatic dysfunction is involved in subacute IS. DTI-ALPS could be a potential magnetic resonance (MR) biomarker of motor dysfunction in subacute IS patients. These findings contribute to a better understanding of the pathophysiological mechanisms of IS and provide a new target for alternative treatments for IS.

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Section: Lateralization Of Dti-alpsmentioning

confidence: 86%

Section: Introductionmentioning

confidence: 99%

DTI-ALPS: An MR biomarker for motor dysfunction in patients with subacute ischemic stroke

Qin

Li²,

Qiao

et al. 2023

Front. Neurosci.

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“…The first reason may come from the handedness of our subjects, who were all right-handed. The dominant brain side, often coinciding with handedness, tends to have a diameter of superior longitudinal fasciculus bundle, which would influence the measurement of ALPS [ 63 ]. Another potential explanation proposed by Zhang et.…”

Section: Discussionmentioning

confidence: 99%

Glymphatic-System Function Is Associated with Addiction and Relapse in Heroin Dependents Undergoing Methadone Maintenance Treatment

Wang,

Qin,

et al. 2023

Brain Sciences

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This study investigates the impact of methadone maintenance treatment (MMT) on the brain glymphatic system (GS) in opioid addiction in China. A total of 51 male MMT patients, 48 demographically matched healthy controls (HCs), and 20 heroin dependents (HDs) were recruited for this study. The GS functioning was assessed using diffusion-tensor-imaging analysis along perivascular spaces (DTI-ALPS index) and the bilateral ALPS divergency (DivALPS). Group differences were analyzed utilizing ANOVA and two-sample t-tests. The relationship between DivALPS and relapse rate was explored using regression analysis. The DTI-ALPS index was significantly higher for the left-side brain than the right side in all three groups. There was a significant difference for the right side (p = 0.0098) between the groups. The MMT and HD groups showed significantly higher DTI-ALPS than the HC group (p = 0.018 and 0.016, respectively). The DivALPS varied significantly among the three groups (p = 0.04), with the HD group showing the lowest and the HC group the highest values. Significant negative relationships were found between relapse count, DivALPS (p < 0.0001, Exp(B) = 0.6047), and age (p < 0.0001, Exp(B) = 0.9142). The findings suggest that MMT may contribute to promoting brain GS recovery in heroin addicts, and modulation of the GS may serve as a potential biomarker for relapse risk, providing insights into novel therapeutic strategies.

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“…Because of such differences, left-handed individuals are often excluded from neuroimaging studies. Studies looking into handedness as the only proxy for hemispheric asymmetry are sparse 24 , as handedness has a complex relationship with lateralization of different functions (e.g. language) 25 .…”

Section: Introductionmentioning

confidence: 99%

“…Finding a brain proxy for handedness could enable the inclusion of left-handed people in neuroimaging studies. Chormai et al 24 managed to classify handedness with 72 % accuracy using functional connectivity. They also tried to interpret the model and looked at the features that were most important for handedness prediction.…”

Section: Introductionmentioning

confidence: 99%

Predicting phenotypes of elderly from resting state fMRI

Verovnik,

Hajduk,

Hulle

2023

Preprint

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Machine learning techniques are increasingly embraced in neuroimaging studies of healthy and diseased human brains. They have been used successfully in predicting phenotypes, or even clinical outcomes, and in turning functional connectome metrics into phenotype biomarkers of both healthy individuals and patients. In this study, we used functional connectivity characteristics based on resting state functional magnetic resonance imaging data to accurately classify healthy elderly in terms of their phenotype status. Additionally, as the functional connections that contribute to the classification can be identified, we can draw inferences about the network that is predictive of the investigated phenotypes. Our proposed pipeline for phenotype classification can be expanded to other phenotypes (cognitive, psychological, clinical) and possibly be used to shed light on the modifiable risk and protective factors in normative and pathological brain aging.

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Machine learning of large-scale multimodal brain imaging data reveals neural correlates of hand preference

Cited by 12 publications

References 58 publications

DTI-ALPS: An MR biomarker for motor dysfunction in patients with subacute ischemic stroke

DTI-ALPS: An MR biomarker for motor dysfunction in patients with subacute ischemic stroke

Glymphatic-System Function Is Associated with Addiction and Relapse in Heroin Dependents Undergoing Methadone Maintenance Treatment

Predicting phenotypes of elderly from resting state fMRI

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