Predicting individual variability in task-evoked brain activity in schizophrenia.
Niv TikAbigail LivnyShachar GalKarny GigiGalia TsarfatyMark WeiserIdo TavorPublished in: Human brain mapping (2021)
What goes wrong in a schizophrenia patient's brain that makes it so different from a healthy brain? In this study, we tested the hypothesis that the abnormal brain activity in schizophrenia is tightly related to alterations in brain connectivity. Using functional magnetic resonance imaging (fMRI), we demonstrated that both resting-state functional connectivity and brain activity during the well-validated N-back task differed significantly between schizophrenia patients and healthy controls. Nevertheless, using a machine-learning approach we were able to use resting-state functional connectivity measures extracted from healthy controls to accurately predict individual variability in the task-evoked brain activation in the schizophrenia patients. The predictions were highly accurate, sensitive, and specific, offering novel insights regarding the strong coupling between brain connectivity and activity in schizophrenia. On a practical perspective, these findings may allow to generate task activity maps for clinical populations without the need to actually perform any tasks, thereby reducing patients inconvenience while saving time and money.
Keyphrases
- resting state
- functional connectivity
- bipolar disorder
- end stage renal disease
- magnetic resonance imaging
- machine learning
- newly diagnosed
- ejection fraction
- chronic kidney disease
- peritoneal dialysis
- magnetic resonance
- artificial intelligence
- room temperature
- multiple sclerosis
- blood brain barrier
- contrast enhanced