Joseph Kambeitz, MD, Neuropsychologist,                           

Head of CIP-Study

Research Focus

The main aim of our research is to generate models that can help patients and health care professionals to better identify, treat and understand psychiatric diseases such as depression, bipolar disorder or psychosis. By employing novel statistical approaches such as machine learning or computational modelling, we can combine different data modalities such as clinical, neurocognitive and neuroimaging data from large cohorts (e.g. PRONIA) to help us predict diagnosis, quantify risk factors or select treatments on an individual level. Moreover, in a recently started longitudinal, multimodal neuroimaging, we are investigating the effects of cannabis abuse on the risk to develop psychotic disorders. In parallel, computational modelling approaches are employed to represent behavioural data and to simulate neuroimaging data with the help of biologically realistic models.


Kambeitz J, Kambeitz J, Cabral C, Sacchet M, Gotlib I, Zahn R, Serpa MH, Walter M, Falkai P, Koutsouleris N: Detecting neuroimaging biomarkers for depression: A meta-analysis of multivariate pattern recognition studies (accepted in Biological Psychiatry)

Kambeitz J, Kambeitz-Ilankovic L, Cabral C, Dwyer D, Calhoun V, van den Heuvel M, Falkai P, Koutsouleris N, Malchow B: Aberrant functional whole-brain network architecture in patients with schizophrenia: a meta-analysis. Schizophr Bull. 2016 Jul;42 Suppl 1:S13-21.

Kambeitz-Ilankovic L, Meisenzahl EM, Cabral C, von Saldern S, Kambeitz J, Falkai P, Möller HJ, Reiser M, Koutsouleris N.: Prediction of outcome in the psychosis prodrome using neuroanatomical pattern classification. Schizophr Res. 2016 Jun;173(3):159-65.

Cabral C, Kambeitz-Ilankovic L, Kambeitz J, Calhoun VD, Dwyer DB, von Saldern S, Urquijo MF, Falkai P, Koutsouleris N.: Classifying Schizophrenia Using Multimodal Multivariate Pattern Recognition Analysis: Evaluating the Impact of Individual Clinical Profiles on the Neurodiagnostic Performance. Schizophr Bull. 2016 Jul;42 Suppl 1:S110-7.

Kambeitz J, la Fougere C, Costa A, Werner N, Pogarell O, Riedel M, Falkai P, Ettinger U Computational Modelling Analysis of Nicotine-Dopamine Interactions During Reward-Based Decision Making. Eur Neuropsychopharmacol. 2016 Jun;26(6):938-47.

Ettinger U, Merten N, Kambeitz J: Meta-analysis of the Association of the SLC6A3 3’-UTR VNTR with Cognition. Neurosci Biobehav Rev. 2016 Jan;60:72-81. 

Schoeler T, Kambeitz J, Behlke I, Murray R, Bhattacharyya S: The effects of cannabis on memory function in users with and without a psychotic disorder: findings from a combined meta-analysis. Psychol Med. 2016 Jan;46(1):177-88.

Kambeitz J, Kambeitz-Ilankovic L, Leucht S, Wood S, Davatzikos C, Malchow B, et al. (2015): Detecting Neuroimaging Biomarkers for Schizophrenia: A Meta-Analysis of Multivariate Pattern Recognition Studies. Neuropsychopharmacology. 2015 Jun;40(7):1742-51.


Telephone: 089/440055880


PRONIA-Early Diagnosis

CIP Study

Hospital of the University of Munich
Clinic for Psychiatry and Psychotherapy

Nussbaumstraße 7
80336 München