A functional connectome phenotyping dataset including cognitive state and personality measures

Mendes, Natacha; Oligschläger, Sabine; Lauckner, Mark E.; Golchert, Johannes; Huntenburg, Julia M.; Falkiewicz, Marcel; Ellamil, Melissa; Krause, Sarah; Bączkowski, Błażej M.; Cozatl, Roberto; Osoianu, Anastasia; Kumral, Deniz; Pool, Jared; Golz, Laura; Dreyer, Maria V.; Haueis, Philipp; Jost, Rebecca; Kramarenko, Yelyzaveta; Engen, Haakon; Ohrnberger, Katharina; Gorgolewski, Krzysztof J.; Farrugia, Nicolas; Babayan, Anahit; Reiter, Andrea; Schaare, H. Lina; Reinelt, Janis; Röbbig, Josefin; Uhlig, Marie; Erbey, Miray; Gaebler, Michael; Smallwood, Jonathan; Villringer, Arno; Margulies, Daniel S.

doi:10.1038/sdata.2018.307

Cited by 77 publications

(55 citation statements)

References 97 publications

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“…A complementary project by Mendes et al . 21 included 194 participants of which 109 participants completed both protocols which enables repeated-measures (e.g., test-retest) analyses. Some data from Mendes et al .…”

Section: Methodsmentioning

confidence: 99%

“…The preprocessing of the rs-fMRI data was implemented in Nipype and the details of it can be found in the complementary project by Mendes et al . 21 . The pipeline is available at https://github.com/NeuroanatomyAndConnectivity/pipelines/tree/master/src/lsd_lemon and comprised the following steps: (i) discarding the first five EPI volumes to allow for signal equilibration and steady state, (ii) 3D motion correction (FSL MCFLIRT) 82 , (iii) distortion correction (FSL FUGUE) 83 , (iv) rigid-body coregistration of unwarped temporal mean image to the individual’s anatomical image (FreeSurfer bbregister) 84 , (v) denoising (Nipype rapidart and aCompCor) 85 , (vi) band-pass filtering between 0.01-0.1 Hz (FSL), mean-centering, as well as variance normalization of the denoised time series (Nitime) 86 , (vii) spatial normalization to MNI152 2 mm standard space via transformation parameters derived during structural preprocessing (ANTs SyN) 87 .…”

Section: Methodsmentioning

confidence: 99%

“…The preprocessing of the T1 MP2RAGE data was implemented in Nipype and the details of it can be found in the complementary project by Mendes et al . 21 . The pipeline is available at https://github.com/NeuroanatomyAndConnectivity/pipelines/tree/master/src/lsd_lemon and comprised the following steps: The background of the uniform T1-weighted image was removed using CBS Tools 91 , and the masked image was used for cortical surface reconstruction using FreeSurfer’s full version of recon-all 92,93 .…”

Section: Methodsmentioning

confidence: 99%

“…Taken in conjunction with the data acquired in the complementary project by Mendes et al . 21 , the MPI-Leipzig Mind-Brain-Body (MPILMBB) database aims to enable exploration of individual variance across a wide range of cognitive, emotional, physiological phenotypes in relation to the brain.…”

Section: Background and Summarymentioning

confidence: 99%

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A mind-brain-body dataset of MRI, EEG, cognition, emotion, and peripheral physiology in young and old adults

et al. 2019

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We present a publicly available dataset of 227 healthy participants comprising a young (N=153, 25.1±3.1 years, range 20–35 years, 45 female) and an elderly group (N=74, 67.6±4.7 years, range 59–77 years, 37 female) acquired cross-sectionally in Leipzig, Germany, between 2013 and 2015 to study mind-body-emotion interactions. During a two-day assessment, participants completed MRI at 3 Tesla (resting-state fMRI, quantitative T1 (MP2RAGE), T2-weighted, FLAIR, SWI/QSM, DWI) and a 62-channel EEG experiment at rest. During task-free resting-state fMRI, cardiovascular measures (blood pressure, heart rate, pulse, respiration) were continuously acquired. Anthropometrics, blood samples, and urine drug tests were obtained. Psychiatric symptoms were identified with Standardized Clinical Interview for DSM IV (SCID-I), Hamilton Depression Scale, and Borderline Symptoms List. Psychological assessment comprised 6 cognitive tests as well as 21 questionnaires related to emotional behavior, personality traits and tendencies, eating behavior, and addictive behavior. We provide information on study design, methods, and details of the data. This dataset is part of the larger MPI Leipzig Mind-Brain-Body database.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Background and Summarymentioning

confidence: 99%

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A mind-brain-body dataset of MRI, EEG, cognition, emotion, and peripheral physiology in young and old adults

et al. 2019

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“…tional volumes, motion correction (FSL MCFLIRT; Jenkinson, Bannister, Brady, & Smith, 2002), distortion correction (FSL FUGUE; Jenkinson, Beckmann, Behrens, Woolrich, & Smith, 2012), coregistration of the temporal mean image to the individual's anatomical image (bbregister; Greve & Fischl, 2009), denoising (rapidart and aCo-mpCor;Behzadi, Restom, Liau, & Liu, 2007), spatial normalisation to MNI 152 2 mm (Sample 1) and 3 mm (Sample 2) standard space (ANTs;Avants et al, 2011). The details of the pipeline are described inMendes et al, 2019. …”

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confidence: 99%

Hemispheric asymmetries in resting‐state EEG and fMRI are related to approach and avoidance behaviour, but not to eating behaviour or BMI

Morys

Janssen

Cesnaite

et al. 2019

Human Brain Mapping

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Much of our behaviour is driven by two motivational dimensions—approach and avoidance. These have been related to frontal hemispheric asymmetries in clinical and resting‐state EEG studies: Approach was linked to higher activity of the left relative to the right hemisphere, while avoidance was related to the opposite pattern. Increased approach behaviour, specifically towards unhealthy foods, is also observed in obesity and has been linked to asymmetry in the framework of the right‐brain hypothesis of obesity. Here, we aimed to replicate previous EEG findings of hemispheric asymmetries for self‐reported approach/avoidance behaviour and to relate them to eating behaviour. Further, we assessed whether resting fMRI hemispheric asymmetries can be detected and whether they are related to approach/avoidance, eating behaviour and BMI. We analysed three samples: Sample 1 (n = 117) containing EEG and fMRI data from lean participants, and Samples 2 (n = 89) and 3 (n = 152) containing fMRI data from lean, overweight and obese participants. In Sample 1, approach behaviour in women was related to EEG, but not to fMRI hemispheric asymmetries. In Sample 2, approach/avoidance behaviours were related to fMRI hemispheric asymmetries. Finally, hemispheric asymmetries were not related to either BMI or eating behaviour in any of the samples. Our study partly replicates previous EEG findings regarding hemispheric asymmetries and indicates that this relationship could also be captured using fMRI. Our findings suggest that eating behaviour and obesity are likely to be mediated by mechanisms not directly relating to frontal asymmetries in neuronal activation quantified with EEG and fMRI.

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Patient‐specific geometrical distortion corrections of MRI images improve dosimetric planning accuracy of vestibular schwannoma treated with gamma knife stereotactic radiosurgery

Safari,

Fatemi,

Afkham

et al. 2023

J Applied Clin Med Phys

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PurposeTo investigate the impact of MRI patient‐specific geometrical distortion (PSD) on the quality of Gamma Knife stereotactic radiosurgery (GK‐SRS) plans of the vestibular schwannoma (VS) tumors.Methods and materialsThree open access datasets including the MPI‐Leipzig Mind‐Brain‐Body (318 patients), the slow event‐related fMRI designs dataset (62 patients), and the VS dataset (242 patients) were used. We used first two datasets to train a 3D convolution network to predict the distortion map of third dataset that were then used to calculate and correct the PSD. GK‐SRS plans of VS dataset were used to evaluate dose distribution of PSD‐corrected MRI images. GK‐SRS prescription dose of VS cases was 12 Gy. Geometric and dosimetric discrepancies were assessed between the dose distributions and contours before and after the PSD corrections. Geometry indices were center of the contours, Dice coefficient (DC), Hausdorff distance (HD), and dosimetric indices were , , , and doses, target coverage (TC), Paddick's conformity index (PCI), Paddick's gradient index (GI), and homogeneity index (HI).ResultsGeometric distortions of about 1.2 mm were observed at the air‐tissue interfaces at the air canal and nasal cavity borders. Average center of the targets was significantly distorted along the frequency encoding direction after the PSD‐correction. Average DC and HD metrics were 0.90 and 2.13 mm. Average , and in Gy significantly increased after PSD correction from 16.85 to 17.25, 12.30 to 12.77, and from 8.98 to 9.92. did not significantly change after the correction. Average TC and PCI significantly increased from 0.97 to 0.98, and 0.94 to 0.96. Average GI decreased significantly from 2.24 to 2.15 after PSD correction. However, HI did not significantly change after the correction.ConclusionThe proposed method could predict and correct the PSD that indicates the importance of PSD correction before GK‐SRS plans of the VS patients.

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A functional connectome phenotyping dataset including cognitive state and personality measures

Cited by 77 publications

References 97 publications

A mind-brain-body dataset of MRI, EEG, cognition, emotion, and peripheral physiology in young and old adults

A mind-brain-body dataset of MRI, EEG, cognition, emotion, and peripheral physiology in young and old adults

Hemispheric asymmetries in resting‐state EEG and fMRI are related to approach and avoidance behaviour, but not to eating behaviour or BMI

Patient‐specific geometrical distortion corrections of MRI images improve dosimetric planning accuracy of vestibular schwannoma treated with gamma knife stereotactic radiosurgery

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