Prof. Dr. Ulrike Lüken
Profil
Zusammenfassung
Prof. Dr. Ulrike Lüken erforscht, wie man vorhersagen kann, welche Patient:innen von Psychotherapie profitieren und welche nicht — insbesondere bei Angststörungen und Zwangsstörungen. Sie entwickelt Methoden, um individuelle Behandlungsergebnisse frühzeitig zu erkennen und Therapien gezielt anzupassen, damit mehr Menschen wirksam geholfen wird.
Skills
Stammdaten
Identität, Organisation und Kontakt aus HU-FIS.
Forschungsthemen14
Ausbauphase des Deutschen Zentrums für Psychische Gesundheit (DZPG): Umsetzung am Standort Berlin-Potsdam
Quelle ↗Förderer: Bundesministerium für Forschung, Technologie und Raumfahrt Zeitraum: 07/2025 - 06/2030 Projektleitung: Prof. Dr. Ulrike Lüken, Prof. Dr. rer. nat. Isabel Dziobek
Deutschen Zentrums für Psychische Gesundheit (DZPG) - Standort Berlin-Potsdam
Quelle ↗Förderer: Bundesministerium für Forschung, Technologie und Raumfahrt Zeitraum: 06/2023 - 07/2030 Projektleitung: Prof. Dr. rer. nat. Isabel Dziobek
Deutsches Zentrum für Psychische Gesundheit
Quelle ↗Förderer: Bundesministerium für Forschung, Technologie und Raumfahrt Zeitraum: 06/2023 - 05/2025 Projektleitung: Prof. Dr. Ulrike Lüken, Prof. Dr. Raymond Dolan, Prof. Dr. rer. nat. Isabel Dziobek
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Publikationen4
Top 25 nach Zitationen — Quelle: OpenAlex (BAAI/bge-m3 embedded für Matching).
European Psychologist · 70 Zitationen · DOI
Abstract. The COVID-19 pandemic is one of the most serious health and economic crises of the 21st century. From a psychological point of view, the COVID-19 pandemic and its consequences can be conceptualized as a multidimensional and potentially toxic stressor for mental health in the general population. This selective literature review provides an overview of longitudinal studies published until June 2021 that have investigated the impact of the COVID-19 pandemic on mental health in the European population. Risk and protective factors identified in the studies are summarized. Forty-two studies that met inclusion and search criteria ( COVID-19, mental health, longitudinal, and Europe) in PubMed, PsycInfo, and Web of Science databases indicate differential effects of the pandemic on mental distress, depression, and anxiety, depending on samples and methods used. Age-specific (e.g., young age), social (e.g., female, ethnical minority, loneliness), as well as physical and mental health-related factors (e.g., pre-pandemic illness) were identified as risk factors for poor mental health. The studies point to several protective factors such as social support, higher cognitive ability, resilience, and self-efficacy. Increasing evidence supports the assumption of the pandemic being a multidimensional stressor on mental health, with some populations appearing more vulnerable than others, although inconsistencies arise. Whether the pandemic will lead to an increase in the prevalence of mental disorders is an open question. Further high-quality longitudinal and multi-national studies and meta-analyses are needed to draw the complete picture of the consequences of the pandemic on mental health.
NeuroImage · 33 Zitationen · DOI
Following the interoceptive inference framework, we set out to replicate our previously reported association of self-control and interoceptive prediction and strived to investigate the neural underpinnings subserving the relationship between self-control and aversive interoceptive predictive models. To this end, we used fMRI and a within-subject design including an inspiratory breathing-load task to examine the prediction of aversive interoceptive perturbation and a craving-regulation for palatable foods task to measure self-control. In this current study, we could successfully replicate previous effects with an independent sample (n = 39) and observed that individuals who ‘over-estimated’ their upcoming interoceptive state with respect to experienced dyspnea (i.e., anticipated versus experienced) were more effective in the down-regulation of craving using negative future-thinking strategies. These individuals, again, obtained higher scores on a measure of trait self-control, i.e. self-regulation to achieve long-term goals. On a neural level, we found evidence that the anterior insula (AI) and the presupplementary motor area (preSMA), which were recruited in both tasks, partly accounted for these effects. Specifically, levels of AI activation during the anticipation of the aversive interoceptive state (breathing restriction) were associated with self-controlled behavior in the craving task, whereas levels of interoceptive prediction during the breathing task were conversely associated with activation in preSMA during the down-regulation of craving, whose anticipatory activity was correlated with self-control success. Moreover, during the self-control task, levels of interoceptive prediction were associated with connectivity in a spatially distributed network including among other areas the insula and regions of cognitive control, while during the interoceptive prediction task, levels of self-control were associated with connectivity in a spatially distributed network including among other regions the insula and preSMA. In sum, these findings consolidate the notion that self-control is directly linked to interoceptive inference and highlight the contribution of AI and preSMA as candidate regions underlying this relationship possibly creating processing advantages in self-control situations referring to the prediction of future internal states.
Statistica Neerlandica · 2 Zitationen · DOI
Many phenomena in the life sciences can be analyzed by using a fixed design regression model with a regression function m that exhibits a crossing‐point in the following sense: the regression function runs below or above its mean level , respectively, according as the input variable lies to the left or to the right of that crossing‐point, or vice versa. We propose a non‐parametric estimator and show weak and strong consistency as long as the crossing‐point is unique. It is defined as maximizing point arg max of a certain marked empirical process. For testing the hypothesis H 0 that the regression function m actually is constant (no crossing‐point), a decision rule is designed for the specific alternative H 1 that m possesses a crossing‐point. The pertaining test‐statistic is the ratio max/argmax of the maximum value and the maximizing point of the marked empirical process. Under the hypothesis the ratio converges in distribution to the corresponding ratio of a reflected Brownian bridge, for which we derive the distribution function. The test is consistent on the whole alternative and superior to the corresponding Kolmogorov–Smirnov test, which is based only on the maximal value max. Some practical examples of possible applications are given where a certain study about dental phobia is discussed in more detail.
Kooperationen16
Bestätigte Forscher↔Partner-Paare aus HU-FIS — Gold-Standard-Positive für das Matching.
Veränderung kognitiver Prozesse basierend auf internalen und externalen Signalen bei Kindern mit Sozialer Angststörung
university
Ausbauphase des Deutschen Zentrums für Psychische Gesundheit (DZPG): Umsetzung am Standort Berlin-Potsdam
university
Ausbauphase des Deutschen Zentrums für Psychische Gesundheit (DZPG): Umsetzung am Standort Berlin-Potsdam
other