Prevention and intervention research

Effective psychiatric treatment and prevention require knowledge of risk factors for psychological disorders and their neurobiological mechanisms. Although the clinical efficacy of several interventions is well documented, there is an urgent need to investigate treatment-related neurobiological changes in order to identify epigenetic, molecular biomarkers and regional brain functional biomarkers associated with therapy response. Based on this, the development, application, and expansion of multivariate, computer-based machine-learning technologies represents a promising, innovative technique for predicting individual therapy response.

The key objectives of this research groups are (a) to investigate the neurobiological mechanisms of specific and unspecific treatments in prospective case-control studies, (b) to discover specific biotypes of patients and stratifying them according to the potentially most effective treatment options, (c) to improve and develop individual predictions based on a combination of neurobiological and clinical data using multivariate pattern classification techniques, and finally, (d) to develop and evaluate innovative psychotherapeutic interventions and prevention strategies based on clinical, environmental and neurobiological markers.

Further research areas include imaging genetics, neurobiological associations of body dysmorphic disorders, work psychological aspects of psychological disorders and neurobiological child and adolescent psychiatry.

Current funding

  • DFG „Brain functional and structural long-term effects of electroconvulsive therapy and its association with clinical response and cognitive side effects” (2019, RE4458/1-1)
  • IMF „Neurobiological effects of Cognitive Behavioral Therapy in depression“ (2017, RE111722)
  • IMF „Auswirkungen der Elektrokonvulsionstherapie auf neurobiologische Substrate emotionaler Prozesse bei depressiven Patienten“ (2016, RE111604)

Current selected publications

Enneking V., Leehr J, Dannlowski U, Redlich R (2020). Brain structural effects of treatments for depression and biomarkers of response: A systematic review of neuroimaging studies. Psychological Medicine. In press.  (IF=5,64)

Enneking V, Krüssel P, Zaremba D, Dohm K, Grotegerd D, Förster K, Meinerst S.…, Redlich R Dannlowski U (2019). Social anhedonia in major depressive disorder: a symptom-specific neuroimaging approach. Neuropsychopharmacology, 44, 883–889. (IF=7.16)

Opel N, Redlich R, Dohm K, Zaremba D, Goltermann J, Repple J, et al. (2019): Mediation of the influence of childhood maltreatment on depression relapse by cortical structure: a 2-year longitudinal observational study. The Lancet Psychiatry. 6: 318–326. (IF=18.32)

Redlich R, Opel N, Grotegerd D, Dohm K, Zaremba D, Bürger C, et al (2016). Prediction of Individual Response to Electroconvulsive Therapy via Machine Learning on Structural Magnetic Resonance Imaging Data. JAMA Psychiatry 73: 557–64. (IF=15.31)

Redlich R, Almeida JR, Grotegerd D, Opel N, Kugel H, Heindel W, et al (2014). Brain Morphometric Biomarkers Distinguishing Unipolar and Bipolar Depression. JAMA Psychiatry 71: 1222. (IF=12.10)

Redlich R, Opel N, Bürger C, Dohm K, Grotegerd D, Förster K, et al (2018). The Limbic System in Youth Depression: Brain Structural and Functional Alterations in Adolescent In-patients with Severe Depression. Neuropsychopharmacology 43: 546–554. (IF=6.54)

Redlich R, Bürger C, Dohm K, Grotegerd D, Opel N, Zaremba D, et al (2017). Effects of electroconvulsive therapy on amygdala function in major depression - a longitudinal functional magnetic resonance imaging study. Psychological Medicine 47: 2166–2176. (IF=5.23)

Redlich R, Dohm K, Grotegerd D, Opel N, Zwitserlood P, Heindel W, et al (2015a). Reward Processing in Unipolar and Bipolar Depression: A Functional MRI Study. Neuropsychopharmacology 40: 2623–31. (IF=6.40)

Redlich R, Schneider I, Kerkenberg N, Opel N, Bauhaus J, Enneking V, et al. (2019): The role of BDNF methylation and Val 66 Met in amygdala reactivity during emotion processing. Hum Brain Mapp, in press. (IF=4.93)

Redlich R, Grotegerd D, Opel N, Kaufmann C, Zwitserlood P, Kugel H, et al (2015b). Are you gonna leave me? Separation Anxiety is associated with increased amygdala responsiveness and volume. Social Cognitive Affective Neuroscience 10: 278–84. (IF=5.40)

Redlich R, Stacey D, Opel N, Grotegerd D, Dohm K, Kugel H, et al (2015c). Evidence of an IFN-gamma by early life stress interaction in the regulation of amygdala reactivity to emotional stimuli. Psychoneuroendocrinology 62: 166–173. (IF=4.70)

Zaremba D, Dohm K, Redlich R, Grotegerd D, Strojny R, Meinert S, et al (2018). Association of Brain Cortical Changes with Relapse in Patients with Major Depressive Disorder. JAMA Psychiatry 75: 484. (IF=16.64)

Enneking, V., Dzvonyar, F., Dannlowski, U., & Redlich, R. (2019). Neuronal effects and biomarkers of antidepressant treatments: Current review from the perspective of neuroimaging. /Nervenarzt/, /90/(3), 319–329.


PD Dr. Dipl.-Psych. Ronny Redlich
Senior Group Leader
E-Mail: r.redlich(at)­uni-muenster(dot)­de

Administration assistance:
Bettina Walden

Tel.: +49 (0)251 / 83-56610
E-Mail: bettina.walden(at)­ukmuenster(dot)­de