@article{AsterRomanosWalitzaetal.2022,
  author    = {Aster, Hans-Christoph and Romanos, Marcel and Walitza, Susanne and Gerlach, Manfred and M{\"u}hlberger, Andreas and Rizzo, Albert and Andreatta, Marta and Hasenauer, Natalie and Hartrampf, Philipp E. and Nerlich, Kai and Reiners, Christoph and Lorenz, Reinhard and Buck, Andreas K. and Deserno, Lorenz},
  title     = {Responsivity of the striatal dopamine system to methylphenidate — A within-subject I-123-β-CIT-SPECT study in male children and adolescents with attention-deficit/hyperactivity disorder},
  series = {Frontiers in Psychiatry},
  volume    = {13},
  journal   = {Frontiers in Psychiatry},
  issn      = {1664-0640},
  doi       = {10.3389/fpsyt.2022.804730},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-270862},
  year      = {2022},
  abstract  = {Background: Methylphenidate (MPH) is the first-line pharmacological treatment of attention-deficit/hyperactivity disorder (ADHD). MPH binds to the dopamine (DA) transporter (DAT), which has high density in the striatum. Assessments of the striatal dopamine transporter by single positron emission computed tomography (SPECT) in childhood and adolescent patients are rare but can provide insight on how the effects of MPH affect DAT availability. The aim of our within-subject study was to investigate the effect of MPH on DAT availability and how responsivity to MPH in DAT availability is linked to clinical symptoms and cognitive functioning. Methods Thirteen adolescent male patients (9-16 years) with a diagnosis of ADHD according to the DSM-IV and long-term stimulant medication (for at least 6 months) with MPH were assessed twice within 7 days using SPECT after application of I-123-β-CIT to examine DAT binding potential (DAT BP). SPECT measures took place in an on- and off-MPH status balanced for order across participants. A virtual reality continuous performance test was performed at each time point. Further clinical symptoms were assessed for baseline off-MPH. Results On-MPH status was associated with a highly significant change (-29.9\%) of striatal DAT BP as compared to off-MPH (t = -4.12, p = 0.002). A more pronounced change in striatal DAT BP was associated with higher off-MPH attentional and externalizing symptom ratings (Pearson r = 0.68, p = 0.01). Striatal DAT BP off-MPH, but not on-MPH, was associated with higher symptom ratings (Pearson r = 0.56, p = 0.04). Conclusion Our findings corroborate previous reports from mainly adult samples that MPH changes striatal DAT BP availability and suggest higher off-MPH DAT BP, likely reflecting low baseline DA levels, as a marker of symptom severity.},
  language  = {en}
}
@article{WaltmannSchlagenhaufDeserno2022,
  author    = {Waltmann, Maria and Schlagenhauf, Florian and Deserno, Lorenz},
  title     = {Sufficient reliability of the behavioral and computational readouts of a probabilistic reversal learning task},
  series = {Behavior Research Methods},
  volume    = {54},
  journal   = {Behavior Research Methods},
  number    = {6},
  issn      = {1554-3528},
  doi       = {10.3758/s13428-021-01739-7},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-324246},
  pages     = {2993-3014},
  year      = {2022},
  abstract  = {Task-based measures that capture neurocognitive processes can help bridge the gap between brain and behavior. To transfer tasks to clinical application, reliability is a crucial benchmark because it imposes an upper bound to potential correlations with other variables (e.g., symptom or brain data). However, the reliability of many task readouts is low. In this study, we scrutinized the retest reliability of a probabilistic reversal learning task (PRLT) that is frequently used to characterize cognitive flexibility in psychiatric populations. We analyzed data from N = 40 healthy subjects, who completed the PRLT twice. We focused on how individual metrics are derived, i.e., whether data were partially pooled across participants and whether priors were used to inform estimates. We compared the reliability of the resulting indices across sessions, as well as the internal consistency of a selection of indices. We found good to excellent reliability for behavioral indices as derived from mixed-effects models that included data from both sessions. The internal consistency was good to excellent. For indices derived from computational modeling, we found excellent reliability when using hierarchical estimation with empirical priors and including data from both sessions. Our results indicate that the PRLT is well equipped to measure individual differences in cognitive flexibility in reinforcement learning. However, this depends heavily on hierarchical modeling of the longitudinal data (whether sessions are modeled separately or jointly), on estimation methods, and on the combination of parameters included in computational models. We discuss implications for the applicability of PRLT indices in psychiatric research and as diagnostic tools.},
  language  = {en}
}
@article{BeierleSchobelVogeletal.2021,
  author    = {Beierle, Felix and Schobel, Johannes and Vogel, Carsten and Allgaier, Johannes and Mulansky, Lena and Haug, Fabian and Haug, Julian and Schlee, Winfried and Holfelder, Marc and Stach, Michael and Schickler, Marc and Baumeister, Harald and Cohrdes, Caroline and Deckert, J{\"u}rgen and Deserno, Lorenz and Edler, Johanna-Sophie and Eichner, Felizitas A. and Greger, Helmut and Hein, Grit and Heuschmann, Peter and John, Dennis and Kestler, Hans A. and Krefting, Dagmar and Langguth, Berthold and Meybohm, Patrick and Probst, Thomas and Reichert, Manfred and Romanos, Marcel and St{\"o}rk, Stefan and Terhorst, Yannik and Weiß, Martin and Pryss, R{\"u}diger},
  title     = {Corona Health — A Study- and Sensor-Based Mobile App Platform Exploring Aspects of the COVID-19 Pandemic},
  series = {International Journal of Environmental Research and Public Health},
  volume    = {18},
  journal   = {International Journal of Environmental Research and Public Health},
  number    = {14},
  issn      = {1660-4601},
  doi       = {10.3390/ijerph18147395},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-242658},
  year      = {2021},
  abstract  = {Physical and mental well-being during the COVID-19 pandemic is typically assessed via surveys, which might make it difficult to conduct longitudinal studies and might lead to data suffering from recall bias. Ecological momentary assessment (EMA) driven smartphone apps can help alleviate such issues, allowing for in situ recordings. Implementing such an app is not trivial, necessitates strict regulatory and legal requirements, and requires short development cycles to appropriately react to abrupt changes in the pandemic. Based on an existing app framework, we developed Corona Health, an app that serves as a platform for deploying questionnaire-based studies in combination with recordings of mobile sensors. In this paper, we present the technical details of Corona Health and provide first insights into the collected data. Through collaborative efforts from experts from public health, medicine, psychology, and computer science, we released Corona Health publicly on Google Play and the Apple App Store (in July 2020) in eight languages and attracted 7290 installations so far. Currently, five studies related to physical and mental well-being are deployed and 17,241 questionnaires have been filled out. Corona Health proves to be a viable tool for conducting research related to the COVID-19 pandemic and can serve as a blueprint for future EMA-based studies. The data we collected will substantially improve our knowledge on mental and physical health states, traits and trajectories as well as its risk and protective factors over the course of the COVID-19 pandemic and its diverse prevention measures.},
  language  = {en}
}