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Distinguishing first-episode psychosis patients on the basis of precuneus activation

Interview with Ms. Eva Rikandi and Dr. Tuukka Raij at ECNP 2015

Rikandi|Raij 1-HD 1080p


P.1.i.035 Differentiation between first-episode psychosis patients and healthy subjects on the basis of precuneus activation E. Rikandi1 °, S. Pamilo1, T. M¨antyl¨a1, J. Suvisaari2, R. Hari1, M. Sepp¨a1, T. Raij1 1Aalto University, Department of Neuroscience and Biomedical Engineering, Helsinki, Finland; 2The National Institute for Health and Welfare, Mental Health Unit, Helsinki, Finland

Purpose of the study: The brain basis of psychotic disorders remains inadequately understood. In this study we used multivariate machine-learning methods to differentiate brain fingerprints of first-episode psychosis patients and healthy control subjects. Earlier machine-learning classification of functional magnetic resonance imaging (fMRI) data have mainly focused on brain activity of chronic patients and data have been collected during resting-state [1] or simple tasks [2]. However, resting-state results are difficult to interpret because ongoing thoughts and experiences are likely to drastically differ between patients and healthy control subjects. Simplistic, such as working memory or verbal learning tasks, can match the experience between the groups but capture only a narrow field of information processing and may therefore miss the functions that are most affected in every-day life. Here we set out to unravel brain activation patterns related to naturalistic stimuli in first-episode psychosis patients and healthy control subjects. We hypothesized that brain networks earlier shown to be affected in psychotic disorders—such as the default mode, executive and salience networks—would be identified as discriminative features between the groups and that the severity of psychotic state would be correlated with the success of classification within the patient group.

Methods: We recorded 3-T fMRI from 46 first-episode psychosis patients and 32 healthy control subjects who viewed episodes with both realistic and supernatural content from the movie Alice in Wonderland [3]. Compared with just resting, viewing a movie decreases the variance between patients and control subjects in experience but still provides naturalistic accounts to the richness of everyday experiences. Patients’ symptom severity was assessed at baseline and at 2-mo follow up by using the Brief Psychiatric Rating Scale Extended (BPRS-E). Machine learning methods were used to classify patients and healthy control subjects on the basis of both voxel- and time-point patterns.

Results: The majority of (136 out of 194) voxels that best classified the groups were clustered in an anatomically contiguous bilateral region of the precuneus (PC). Seed-based analysis showed the PC region to be functionally connected to defaultmode network and middle temporal gyri. Classification accuracies were up to 79.5% (p = 1.61*10−9), and the higher classification frequency across several classifiers, the higher were the positive symptom scores of patients.

Conclusions: These are the first findings to show abnormalities in PC functioning during naturalistic information processing in first-episode psychosis patients. The symptom-severity-related findings further propose the association of the functional PC alteration with psychotic state. PC is known as a central hub for the integration of self- and episodic-memory-related information and thus its dysfunction might give insights into understanding of psychosis. Our findings indicate the usefulness of natural stimuli in classification analyses based on brain-imaging data and call for future research on the role of precuneus in psychosis.

References [1] Bleich-Cohen, M., Jamshy, S., Sharon, H., Weizman, R., Intrator, N., Poyurovsky, M., Hendler, T., 2014. Machine learning fMRI classifier delineates subgroups of schizophrenia patients. Schizophrenia Research 160, 196–200. [2] Calhoun, V.D., Maciejewski, P.K., Pearlson, G.D., Kiehl, K.A., 2008. Temporal lobe and “default” hemodynamic brain modes discriminate between schizophrenia and bipolar disorder. Human Brain Mapping 29, 1265–1275. [3] Tim Burton, Walt Disney Pictures, 2010; Finnish soundtrack.


ECNP President-Elect, Professor Celso Arango (Madrid) commented on the research:

“The interesting question  here is how patients with psychosis, even in their first episode, process information in a different way.  Specifically how a movie such as Alice in Wonderland elicits the participation of different brain areas, and how that relate to the history of the person watching. What we would like to know is if patients with psychosis might see this as more or less relevant to their own life than would healthy controls. This movie is about a fantasy world, would it be different with other types of movie?”