In order to understand mental health, it is crucial to consider the complex interplay of an individual with its environment. This includes biological and psychological factors as well as social interactions or the use of digital media. In our lab, we conduct research on this exciting field with the aim to:

  • identify adverse influences for mental health as well as protective factors 

  • provide modern tools to allow individualised diagnostics and preventive strategies

  • develop personalised interventions to support mental health


Our team consists of a mix of methodologically-oriented clinicians and clinically-oriented methodologists, which allows us to live a close interaction between research and clinical application. Together we aim at the clinical translation of novel tools inspired by data-science oriented approaches such as:

  • machine-learning and big data analytics to identify informative patterns in behavioural or biological data

  • network models to characterise complex relationships between symptoms, risk and protective factors

  • dynamic systems modelling to provide a mechanistic understanding of brain in health and disease

  • meta-analysis to address essential clinical questions based on a large body of evidence



We hope that by extending the focus to the development of behavioural, cognitive and neuro-imaging biomarkers, we can improve our understanding of mental health and generate models for individualised prediction in psychiatric patients or individuals at risk. Ultimately, we aim to personalise behavioural, pharmacological and psychotherapeutic interventions in the complex human-digital setting of psychiatry today using our expertise in machine learning and computational methods.



PhD Position in Computational Neurosciences / Translational Clinical Neurosciences

PhD Position in Computational Neurosciences / Translational Clinical Neurosciences

We have an open PhD position @kambeitzlab in cooperation with the Forschungszentrum Jülich, Institute of Neuroscience and Medicine - Cognitive Neuroscience (INM-3) in the area Computational Neurosciences / Translational Clinical Neurosciences. The scope of the research is the investigation of neurobiological mechanisms underlying brain dynamics using multimodal neuroimaging data and computational neurosciences approaches, more specifically the changes of brain dynamics in the context of psychological or neurological disorders, as well as the relationship to risk- and resilience-factors. More information can be found here.



Joseph Kambeitz


Lana Kambeitz-Ilankovic


Theresa Lichtenstein


Desirée Zeus


Marlene Rosen


Pedro Costa Klein


Laura Völkel

cand. med.

Simon Herstell

cand. med.

Ana Muthesius


Julian Wenzel


Melanie Rohde


Pilar Albert Porcar


Luzie Badde

cand. med.

Uma Rzayeva

cand. med.

Carolin Doll


Linda Betz


Nora Penzel


Alina Zubair

cand. med.

Nina Walter

cand. med.



Transdiagnostic phenotyping of psychopathology in a help-seeking population (PhenoNetz) - an experience sampling study

Transdiagnostic phenotyping of psychopathology in a help-seeking population (PhenoNetz) - an experience sampling study

Longitudinal course of cannabis-induced psychosis (CIP)

Longitudinal course of cannabis-induced psychosis (CIP)

Personalized cognitive training

Personalized cognitive training

Individualised prediction in clinical high risk

Individualised prediction in clinical high risk

Understanding Schizophrenia using Computational Modeling: Biological Simulations of the Brain’s Functional Connectome Copy

Understanding Schizophrenia using Computational Modeling: Biological Simulations of the Brain’s Functional Connectome Copy

Symptom networks in psychotic and affective disorders

Symptom networks in psychotic and affective disorders



Dr. Martin Hebart
Revealing Interpretable Representational Dimensions Shared Between Humans and Deep Neural Networks
Dr. Nils Opel
Challenges for Translational Psychiatry in the Age of Big Data
Dr. Urs Braun
Network Neuroscience in Psychiatry
Dr. Stephanie Forkel
White matter tractography & its application in health and disease
Dr. Diana Prata
Neuroimaging Genetics in Psychiatry

Check here for upcoming talks from invited speakers.



We frequently offer research projects in the area of mental health, machine learning & big data and neuroimaging. Feel free to get in contact if you are interested in collaborating or working with us.



  • Haidl TK, Hedderich DM, Rosen M, Kaiser N, Seves M, Lichtenstein T, Penzel N, Wenzel J, Kambeitz-Ilankovic L, Ruef A, Popovic D, Schultze-Lutter F, Chisholm K, Upthegrove R, Salokangas RKR, Pantelis C, Meisenzahl E, Wood SJ, Brambilla P, Borgwardt S, Ruhrmann S, Kambeitz J, Koutsouleris N (2021): The non-specific nature of mental health and structural brain outcomes following childhood trauma. Psychol Med. 2021 Jul 6:1-10. doi: 10.1017/S0033291721002439

  • Preuss UW, Huestis MA, Schneider M, Hermann D, Lutz B, Hasan A, Kambeitz J, Wong JWM, Hoch E (2021): Cannabis Use and Car Crashes: A Review. Front Psychiatry. 2021 May 28;12:643315. doi: 10.3389/fpsyt.2021.643315. eCollection 2021.

  • Chamorro Y, Betz LT, Philipsen A, Kambeitz J, Ettinger U (2021): The Eyes Have It: A Meta-analysis of Oculomotor Inhibition in Attention-Deficit/Hyperactivity Disorder. Biol Psychiatry Cogn Neurosci Neuroimaging. 2021 May 27:S2451-9022(21)00144-0. doi: 10.1016/j.bpsc.2021.05.004.

  • Goerigk SA, Padberg F, Chekroud A, Kambeitz J, Bühner M, Brunoni AR (2021): Parsing the antidepressant effects of non-invasive brain stimulation and pharmacotherapy: A symptom clustering approach on ELECT-TDCS. Brain Stimul. 2021 Jul-Aug;14(4):906-912. doi: 10.1016/j.brs.2021.05.008. Epub 2021 May 26.

  • Hauke DJ, Schmidt A, Studerus E, Andreou C, Riecher-Rössler A, Radua J, Kambeitz J, Ruef A, Dwyer DB, Kambeitz-Ilankovic L, Lichtenstein T, Sanfelici R, Penzel N, Haas SS, Antonucci LA, Lalousis PA, Chisholm K, Schultze-Lutter F, Ruhrmann S, Hietala J, Brambilla P, Koutsouleris N, Meisenzahl E, Pantelis C, Rosen M, Salokangas RKR, Upthegrove R, Wood SJ, Borgwardt S; PRONIA Group (2021): Multimodal prognosis of negative symptom severity in individuals at increased risk of developing psychosis. Transl Psychiatry. 2021 May 24;11(1):312. doi: 10.1038/s41398-021-01409-4

  • Haidl TK, Gruen M, Dizinger J, Rosen M, Doll CM, Penzel N, Daum L, Große Hokamp N, Klosterkötter J, Ruhrmann S, Vogeley K, Schultze-Lutter F, Kambeitz J (2021): Is there a diagnosis-specific influence of childhood trauma on later educational attainment? A machine learning analysis in a large help-seeking sample. J Psychiatr Res. 2021 Jun;138:591-597. doi: 10.1016/j.jpsychires.2021.04.040. Epub 2021 Apr 30.

  • Padberg F, Bulubas L, Mizutani-Tiebel Y, Burkhardt G, Kranz GS, Koutsouleris N, Kambeitz J, Hasan A, Takahashi S, Keeser D, Goerigk S, Brunoni AR (2021): The intervention, the patient and the illness - Personalizing non-invasive brain stimulation in psychiatry. Exp Neurol. 2021 Jul;341:113713. doi: 10.1016/j.expneurol.2021.113713. Epub 2021 Mar 31.

  • Lalousis PA, Wood SJ, Schmaal L, Chisholm K, Griffiths SL, Reniers RLEP, Bertolino A, Borgwardt S, Brambilla P, Kambeitz J, Lencer R, Pantelis C, Ruhrmann S, Salokangas RKR, Schultze-Lutter F, Bonivento C, Dwyer D, Ferro A, Haidl T, Rosen M, Schmidt A, Meisenzahl E, Koutsouleris N, Upthegrove R; PRONIA Consortium (2021): Heterogeneity and Classification of Recent Onset Psychosis and Depression: A Multimodal Machine Learning Approach. Schizophr Bull. 2021 Jul 8;47(4):1130-1140. doi: 10.1093/schbul/sbaa185.

  • Antonucci LA, Penzel N, Pigoni A, Dominke C, Kambeitz J, Pergola G (2020): Flexible and specific contributions of thalamic subdivisions to human cognition. Neurosci Biobehav Rev. 2021 May;124:35-53. DOI: 10.1016/j.neubiorev.2021.01.014. Epub 2021 Jan 23.

  • Wenzel J, Haas SS,  Dwyer DB, Ruef A, Oeztuerk OF, Antonucci LA, von Saldern S, Bonivento C, Garzitto M, Ferro A, Paolini M, Blautzik J, Borgwardt S, Brambilla P, Meisenzahl E, Salokangas RKR, Upthegrove R, Wood SJ, Kambeitz J, Koutsouleris N, Kambeitz-Ilankovic L, PRONIA consortium (2021): Cognitive subtypes in recent onset psychosis: distinct neurobiological fingerprints? Neuropsychopharmacology. DOI:

  • Penzel N, Antonucci LA, Betz LT, Sanfelici R, Weiske J, Pogarell O, Cumming P, Quednow BB, Howes O, Falkai P, Upthegrove R, Bertolino A, Borgwardt S, Brambilla P, Lencer R, Meisenzahl E, Rosen M, Haidl T, Kambeitz-Ilankovic L, Ruhrmann S, Salokangas RRK, Pantelis C, Wood SJ, Koutsouleris N, Kambeitz J, PRONIA Consortium (2021): Association between age of cannabis initiation and gray matter covariance networks in recent onset psychosis. Neuropsychopharmacology. DOI: 10.1038/s41386-021-00977-9.

  • Rosen M, Betz LT, Schultze-Lutter F, Chisholm K, Haidl TK, Kambeitz-Ilankovic L, Bertolino A, Borgwardt S, Brambilla P, Lencer R, Meisenzahl E, Ruhrmann S, Salokangas RKR, Upthegrove R, Wood SJ, Koutsouleris N, Kambeitz J, PRONIA Consortium (2021): Towards Clinical Application of Prediction Models for Transition to Psychosis: A Systematic Review and External Validation Study in the PRONIA Sample. Neurosci Biobehav Rev. 2021 Feb 23;S0149-7634(21)00086-5. DOI: 10.1016/j.neubiorev.2021.02.03

  • Betz LT, Penzel N, Kambeitz-Ilankovic L, Rosen M, Chisholm K, Stainton A, Haidl TK, Wenzel J, Bertolino A, Borgwardt S, Brambilla P, Lencer R, Meisenzahl E, Ruhrmann S, Salokangas RKR, Schultze-Lutter F, Wood SJ, Upthegrove R, Koutsouleris N, Kambeitz J, PRONIA consortium (2020): General psychopathology links burden of recent life events and psychotic symptoms in a network approach. npj Schizophrenia volume 6, Article number: 40. DOI:

  • Betz LT, Penzel N, Rosen M, Kambeitz J (2020): Relationships between childhood trauma and perceived stress in the general population: a network perspective. Psychol Med 1–11. DOI: 10.1017/S003329172000135X

  • Kambeitz J, Goerigk S, Gattaz W, Falkai P, Benseñor IM, Lotufo PA, et al. (2020): Clinical patterns differentially predict response to transcranial direct current stimulation (tDCS) and escitalopram in major depression: A machine learning analysis of the ELECT-TDCS study. J Affect Disord 265: 460–467. DOI: 10.1016/j.jad.2020.01.118

  • Proebstl L, Kamp F, Manz K, Krause D, Adorjan K, Pogarell O, ..., Kambeitz, J. (2019): Effects of stimulant drug use on the dopaminergic system: A systematic review and meta-analysis of in vivo neuroimaging studies. Eur Psychiatry 59: 15–24. DOI: 10.1016/j.eurpsy.2019.03.003

  • Kambeitz-Ilankovic L, Betz LT, Dominke C, Haas SS, Subramaniam K, Fisher M, et al. (2019): Multi-outcome meta-analysis (MOMA) of cognitive remediation in schizophrenia: Revisiting the relevance of human coaching and elucidating interplay between multiple outcomes. Neurosci Biobehav Rev 107: 828–845. DOI: 10.1016/j.neubiorev.2019.09.031

  • Kamp F, Proebstl L, Penzel N, Adorjan K, Ilankovic A, Pogarell O, ..., Kambeitz, J. (2019): Effects of sedative drug use on the dopamine system: a systematic review and meta-analysis of in vivo neuroimaging studies. Neuropsychopharmacology 44: 660–667. DOI: 10.1038/s41386-018-0191-9

  • Betz LT, Brambilla P, Ilankovic A, Premkumar P, Kim M-S, Raffard S, et al. (2019): Deciphering reward-based decision-making in schizophrenia: A meta-analysis and behavioral modeling of the Iowa Gambling Task. Schizophr Res 204: 7–15. DOI: 10.1016/j.schres.2018.09.009

  • Koutsouleris N, Kambeitz-Ilankovic L, Ruhrmann S, Rosen M, Ruef A, Dwyer DB, et al. (2018): Prediction Models of Functional Outcomes for Individuals in the Clinical High-Risk State for Psychosis or With Recent-Onset Depression: A Multimodal, Multisite Machine Learning Analysis. JAMA Psychiatry 75: 1156–1172. DOI: 10.1001/jamapsychiatry.2018.2165

  • Steffens M, Meyhöfer I, Fassbender K, Ettinger U, Kambeitz J (2018): Association of Schizotypy With Dimensions of Cognitive Control: A Meta-Analysis. Schizophr Bull 44: S512–S524. DOI: 10.1093/schbul/sby030

  • Kambeitz J, Cabral C, Sacchet MD, Gotlib IH, Zahn R, Serpa MH, et al. (2017): Detecting Neuroimaging Biomarkers for Depression: A Meta-analysis of Multivariate Pattern Recognition Studies. Biol Psychiatry 82: 330–338. DOI: 10.1016/j.biopsych.2016.10.028

  • Kambeitz J, la Fougère C, Werner N, Pogarell O, Riedel M, Falkai P, Ettinger U (2016): Nicotine-dopamine-transporter interactions during reward-based decision making. Eur Neuropsychopharmacol 26: 938–947. DOI: j.euroneuro.2016.03.011

  • Kambeitz J, Kambeitz-Ilankovic L, Cabral C, Dwyer DB, Calhoun VD, van den Heuvel MP, et al. (2016): Aberrant Functional Whole-Brain Network Architecture in Patients With Schizophrenia: A Meta-analysis. Schizophr Bull 42 Suppl 1: S13–21. DOI: 10.1093/schbul/sbv174

For a complete list of publications, please click here.



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