MedicalResearch.com Interview with:
Irina Rish PhD
IBM T.J. Watson Research Center
Yorktown Heights, NY 10598
MedicalResearch.com: What is the background for this study? What are the main findings?
Schizophrenia is a chronic and severe psychiatric disorder that affects roughly about 1% of population. Although it is not as common as other mental disorders, such as depression, anxiety, and attention deficit disorder (ADD), and so on, schizophrenia is perhaps one of the most debilitating psychiatric disorders, preventing people from normal functioning in daily life. It is characterized primarily by a range of psychotic symptoms, including hallucinations (false auditory, visual or tactile perceptions detached from reality), as well as delusions, disorganized thoughts, speech and behavior, and multiple other symptoms including difficulty showing (and recognizing) emotions, poor executive functioning, inattentiveness, problems with working memory, and so one. Overall, schizophrenia has a devastating impact not only on patients and their families, but on the economy, as it was estimated to cost the US about 2% off gross national product in treatment costs, missed work, etc.
Thus, taking steps towards better understanding of the disease can potentially lead to more accurate early diagnosis and better treatments.
In this work, the objective was to identify "statistical biomarkers' of schizophrenia from brain imaging data (specifically, functional MRI), i.e. brain activity patterns that would be capable of accurately discriminating between schizophrenic patients and controls, and reproducible (stable) across multiple datasets. The focus on both predictive accuracy (generalization to previously unseen subjects) as well as on stability (reproducibility) across multiple datsets differentiates our work from majority of similar studies in neuroimaging field that tend to focus only on statistically significant differences between such patterns on a fixed dataset, and may not reliably generalize to new data.
Our prior work on neuroimaging-based analysis of schizoprenia http://journals.plos.org/plosone/article/related?id=10.1371/journal.pone.0050625
, as well as other research in the field, suggest that disrupted functional connectivity can be a much more informative source of discriminative patterns than local changes in brain activations, since schizophrenia is well known to be a "network disease", rather than a localized one.