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

Babayan, Anahit; Erbey, Miray; Kumral, Deniz; Reinelt, Janis; Reiter, Andrea; Röbbig, Josefin; Schaare, H. Lina; Uhlig, Marie; Anwander, Alfred; Bazin, Pierre‐Louis; Horstmann, Annette; Lampe, Leonie; Nikulin, Vadim V.; Okon‐Singer, Hadas; Preusser, Sven; Pampel, André; Rohr, Christiane S.; Sacher, Julia; Thöne-Otto, Angelika; Trapp, Sabrina; Nierhaus, Till; Altmann, Denise; Arélin, Katrin; Blöchl, Maria; Bongartz, Edith; Breig, Patric; Cesnaite, Elena; Chen, Sufang; Cozatl, Roberto; Czerwonatis, Saskia; Dambrauskaite, Gabriele; Dreyer, Maria V.; Enders, Jessica; Engelhardt, Melina; Fischer, M.; Forschack, Norman; Golchert, Johannes; Golz, Laura; Guran, Catherine-Noémie Alexandrina; Hedrich, Susanna; Hentschel, Nicole; Hoffmann, D.; Huntenburg, Julia M.; Jost, Rebecca; Kosatschek, Anna; Kunzendorf, Stella; Lammers, H. Bruce; Lauckner, Mark E.; Mahjoory, Keyvan; Kanaan, Ahmad S.; Mendes, Natacha; Menger, Ramona; Morino, Enzo; Näthe, Karina; Neubauer, Jennifer; Noyan, Handan; Oligschläger, Sabine; Panczyszyn-Trzewik, Patricia; Poehlchen, Dorothee; Putzke, Nadine; Roski, Sabrina; Schaller, Marie-Catherine; Schieferbein, Anja; Schlaak, Benito; Schmidt, Robert; Gorgolewski, Krzysztof J.; Schmidt, Hanna Maria; Schrimpf, Anne; Stasch, Sylvia; Voss, Maria; Wiedemann, Annett; Margulies, Daniel S.; Gaebler, Michael; Villringer, Arno

doi:10.1038/sdata.2018.308

Cited by 251 publications

(338 citation statements)

References 105 publications

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“…In the present report, we assessed a number of within-and between-person correlates of resting EEG microstate temporal dynamics using a large sample of healthy adults. The data for this study were acquired from a publicly available dataset of 227 individuals, comprised of younger and older age-group samples, that was collected between 2013 and 2015 (Babayan et al, 2019). Microstate parameters were derived from 16 minutes of scalp-recorded EEG, collected at rest, from separate eyes closed and eyes open epochs each lasting 8 minutes in duration.…”

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confidence: 99%

“…Second, we examined between-person differences in microstate temporal parameters and transitions as a function of age group (older versus younger adults) and gender. And finally, we explored associations between microstate parameters and measures of personality, mood, and cognitive function included in the larger study assessment battery (Babayan et al, 2019). For personality measures, we selected two commonly used scales that assess motivational tendencies and wellcharacterized dimensions of personality, respectively: The Behavioral Inhibition and Behavioral Activation scale of Carver and White (1994) and the NEO Five Factor Inventory of Costa and McCrae (1992).…”

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Within and Between-person Correlates of the Temporal Dynamics of Resting EEG Microstates

Zanesco

King

Skwara

et al. 2019

Preprint

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Microstates reflect transient brain states resulting from the activity of synchronously active brain networks that predominate in the broadband EEG time series. Despite increasing interest in understanding how the functional organization of the brain varies across individuals, or the extent to which its spatiotemporal dynamics are state dependent, comparatively little research has examined within and between-person correlates of microstate temporal parameters in healthy populations. In the present study, neuroelectric activity recorded during eyes-closed rest and during simple visual fixation was segmented into a time series of transient microstate intervals. It was found that five data-driven microstate configurations explained the preponderance of topographic variance in the EEG time series of the 374 recordings (from 187 participants) included in the study. We observed that the temporal dynamics of microstates varied within individuals to a greater degree than they differed between persons, with within-person factors explaining a large portion of the variance in mean microstate duration and occurrence rate.Nevertheless, several individual differences were found to predict the temporal dynamics of microstates. Of these, age and gender were the most reliable. These findings suggest that not only do the rich temporal dynamics of whole-brain neuronal networks vary considerably withinindividuals, but that microstates appear to differentiate persons based on trait individual differences. The current findings suggest that rather than focusing exclusively on between-person differences in microstates as measures of brain function, researchers should turn their attention towards understanding the factors contributing to within-person variation.

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confidence: 99%

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confidence: 99%

Within and Between-person Correlates of the Temporal Dynamics of Resting EEG Microstates

Zanesco

King

Skwara

et al. 2019

Preprint

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“…Exclusion criteria included: History of psychiatric or neurological disease, substance abuse, hypertension, MRI‐related contraindications (cf. table 1 in Babayan et al ()). Data available for this sample included self‐reported eating (TFEQ) and approach/avoidance behaviour (BIS/BAS) questionnaires, anthropometric data (BMI), rsEEG and rsfMRI (Table S2).…”

Section: Methodsmentioning

confidence: 98%

“…Sample 1 consisted of 117 healthy, right‐handed, predominantly lean participants aged 20–35 years (mean age: 25 years, mean BMI: 23.01 kg/m 2 , range: 17.95–37.80 kg/m 2 ; 42 women, Table S1) taken from the “Leipzig Study for Mind‐Body‐Emotion Interactions” (Babayan et al, ). Exclusion criteria included: History of psychiatric or neurological disease, substance abuse, hypertension, MRI‐related contraindications (cf.…”

Section: Methodsmentioning

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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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Intact microstructure of the right corticostriatal pathway predicts creative ability in healthy adults

2020

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Creativity has been defined both as a trait and state. Creativity as a trait is also referred to as creative potential, which can potentially predict creativity as a state or creative achievement (Jauk et al., 2014; Runco & Jaeger, 2012). Neuropsychologic batteries developed to assess trait creativity often evaluate the ability for disengagement and divergent thinking, as in the test of creative imagery abilities (TCIA), finding alternative uses for objects, as in the alternative uses task (AUT), or less commonly the ability for associative and convergent thinking, as required in the remote associates test (RAT; Guildford et al., 1978; Jankowska & Karwowski, 2015; Lee et al., 2014). State creativity is often quantified based on real-life creative achievements using the qualitative creative achievement questionnaire (CAQ; Carson et al., 2005). Famously, creative achievement has been correlated with creative trait and openness

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

Cited by 251 publications

References 105 publications

Within and Between-person Correlates of the Temporal Dynamics of Resting EEG Microstates

Within and Between-person Correlates of the Temporal Dynamics of Resting EEG Microstates

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

Intact microstructure of the right corticostriatal pathway predicts creative ability in healthy adults

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