The methodology and dataset of the coscience eeg-personality project – a large-scale, multi-laboratory project grounded in cooperative forking paths analysis

Paul, Katharina; Short, Cassie Ann; Beauducel, André; Carsten, Hannes Per; Härpfer, Kai; Hennig, Jürgen; Hewig, Johannes; Hildebrandt, Andrea; Kührt, Corinna; Mueller, Erik M.; Munk, Aisha J.L.; Osinsky, Roman; Porth, Elisa; Riesel, Anja; Rodrigues, Johannes; Scheffel, Christoph; Stähl, Jutta; Strobel, Alexander; Wacker, Jan

doi:10.5964/ps.7177

Cited by 8 publications

(4 citation statements)

References 41 publications

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“…Del Giudice and Gangestad 2021, proposed that assessment of equivalence of the options/forking paths in terms of measurement, effect, and power/precision may help to reduce the number of forking paths. A sampling method across all the forking paths can also be conducted to reduce the number of forking paths (Paul et al 2022).…”

Section: Discussionmentioning

confidence: 99%

“…The large number of options available to researchers for preprocessing and analyzing their data has been cited as one of the reasons for the replication crisis in science (Paul et al 2022). A huge heterogeneity in data analysis has recently been reported in cognitive neuroscience based on functional magnetic resonance imaging (fMRI) data (Botvinik-Nezer et al 2020).…”

Section: Introductionmentioning

confidence: 99%

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An Extended Active Learning Approach to Multiverse Analysis: Predictions of Latent Variables from Graph Theory Measures of the Human Connectome and Their Direct Replication

Kristanto,

Gießing,

Marek

et al. 2023

Brainiacs

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Multiverse analysis has been proposed as a powerful technique to disclose the large number of degrees of freedom in data preprocessing and analysis that strongly contribute to the current replication crisis in science. However, in the field of imaging neuroscience, where multidimensional, complex and noisy data are measured, multiverse analysis may be computationally infeasible. The number of possible forking paths given by different methodological decisions and analytical choices is immense. Recently, Dafflon et al. (2022) proposed an active learning approach as an alternative to exhaustively exploring all forking paths. Here, we aimed to extend their active learning pipeline by integrating latent underlying variables which are not directly observable. The extension to latent outcomes is particularly valuable for computational psychiatry and neurocognitive psychology, where latent traits are conceptualized as common cause of a variety of observable neural and behavioral symptoms. To illustrate our approach and to test its direct replicability, we analyzed the individual organization and topology of functional brain networks of two relatively large samples from the ABCD study dataset (N = 1491) and HCP dataset (N = 833). Graph-theoretical parameters that take into account both brain-wide and region-specific network properties were used as predictors of a latent variable reflecting general cognition. Our results demonstrate the ability of the extended method to selectively explore the multiverse when predicting a latent variable. First, the low-dimensional space created with the proposed approach was able to cluster the forking paths according to their similarity. Second, the active learning approach successfully estimated the prediction performance of all pipelines in both datasets. To interactively explore the multiverse of results, we developed a Shiny app to visualize the predictive accuracy resulting from each forking path and to illustrate the similarity between pipelines created by different combinations of data processing choice. The code for active learning and the app are available at the Github repository ExtendedAL.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Extended Active Learning Approach to Multiverse Analysis: Predictions of Latent Variables from Graph Theory Measures of the Human Connectome and Their Direct Replication

Kristanto,

Gießing,

Marek

et al. 2023

Brainiacs

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“…Stimulus processing was evaluated using an EPSP. This paradigm has proven to be a suitable implicit measure of sexual interest, especially when combined with ERP techniques Gormley, 2009, 2012;Munk et al, 2018Munk et al, , 2020 and several studies confirm the usability of Emotional Stroop Paradigms for eliciting ERPs (Thomas et al, 2007;Bertsch et al, 2009;Franken et al, 2009;Munk et al, 2018Munk et al, , 2020Imbir et al, 2021;Paul et al, 2022). Due to the comprehensive nature of the overall project, several emotional stimulus categories were included (Schmidt et al, 2022).…”

Section: Emotional Picture Stroop Paradigm (Epsp)mentioning

confidence: 97%

Interplay between sexual excitation and inhibition: impact on sexual function and neural correlates of erotic stimulus processing in women

Schmidt,

Hennig,

Munk

2024

Front. Behav. Neurosci.

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BackgroundAs outlined by the dual control model (DCM), individual differences in the regulation of sexual arousal following sexual stimulation depend on two distinct neurophysiological processes: sexual excitation (SE) and sexual inhibition (SI). Although associations with sexual function, behavior, and cue processing have been demonstrated in previous research, underlying neural correlates remain insufficiently explored. Moreover, interactive effects of SE/SI as proposed by the DCM, as well as factors impacting SE/SI properties, such as the use of oral contraceptives (OCs), have not received adequate attention in existing research.Methods90 healthy, sexually active women (n = 51 using OCs, n = 39 naturally cycling) completed an Emotional-Picture-Stroop-Paradigm (EPSP) while a 64-channel EEG was recorded. LPP amplitudes toward erotic and neutral stimuli were consecutively computed as a marker of motivational salience and approach motivation. Additionally, women provided self-reports of SE/SI and sexual function. Moderation analyses were performed to assess interactive effects of SE/SI in predicting LPP amplitudes and sexual function.ResultsSexual function was negatively associated with SI levels but unrelated to SE. Higher SI was associated with reduced LPP amplitudes in response to erotic stimuli. This negative association was, however, attenuated for women high in SE, suggesting interactive effects of SE/SI. Furthermore, women using OCs reported lower SE compared to naturally cycling women.ConclusionThe observed findings provide additional psychophysiological evidence supporting the DCM and underscore the relevance of interactive SE/SI effects in stimulus processing and approach motivation. They also highlight the possible impact of OCs on psychosexual variables that warrants further research.

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“…There are several possible ways of identifying the complex multiverse of choices for an fMRI analysis pipeline. For example, expert workshops have been used to crowdsource analytical decisions (Paul et al, 2022). Multi-analyst project, such as the one published in the fMRI field by Botvinik-Nezer et al (2020) is another option.…”

Section: Introductionmentioning

confidence: 99%

The multiverse of data preprocessing and analysis in graph-based fMRI: A systematic literature review of analytical choices fed into a decision support tool for informed analysis

Kristanto,

Burkhardt,

Thiel

et al. 2024

Preprint

Self Cite

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The large number of different analytical choices researchers use may be partly responsible for the replication challenge in neuroimaging studies. For robustness analysis, knowledge of the full space of options is essential. We conducted a systematic literature review to identify the analytical decisions in functional neuroimaging data preprocessing and analysis in the emerging field of cognitive network neuroscience. We found 61 different steps, with 17 of them having debatable options. Scrubbing, global signal regression, and spatial smoothing are among the controversial steps. There is no standardized order in which different steps are applied, and the options within several steps vary widely across studies. By aggregating the pipelines across studies, we propose three taxonomic levels to categorize analytical choices: 1) inclusion or exclusion of specific steps, 2) distinct sequencing of steps, and 3) parameter tuning within steps. To facilitate access to the data, we developed a decision support app with high educational value called METEOR, which allows researchers to explore the space of choices as reference for well-informed robustness (multiverse) analysis.

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The methodology and dataset of the coscience eeg-personality project – a large-scale, multi-laboratory project grounded in cooperative forking paths analysis

Cited by 8 publications

References 41 publications

An Extended Active Learning Approach to Multiverse Analysis: Predictions of Latent Variables from Graph Theory Measures of the Human Connectome and Their Direct Replication

An Extended Active Learning Approach to Multiverse Analysis: Predictions of Latent Variables from Graph Theory Measures of the Human Connectome and Their Direct Replication

Interplay between sexual excitation and inhibition: impact on sexual function and neural correlates of erotic stimulus processing in women

The multiverse of data preprocessing and analysis in graph-based fMRI: A systematic literature review of analytical choices fed into a decision support tool for informed analysis

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