Psychotic disorders present significant challenges in understanding their causes and
developing effective interventions. Functional magnetic resonance imaging (fMRI)
has become a valuable tool for investigating these disorders and identifying potential
biomarkers. This thesis aimed to explore functional connectivity patterns in restingstate networks (RSNs) among children and adolescent offspring of individuals with
Schizophrenia (SzO), bipolar disorder (BpO), and controls.
Resting-state fMRI ...
Psychotic disorders present significant challenges in understanding their causes and
developing effective interventions. Functional magnetic resonance imaging (fMRI)
has become a valuable tool for investigating these disorders and identifying potential
biomarkers. This thesis aimed to explore functional connectivity patterns in restingstate networks (RSNs) among children and adolescent offspring of individuals with
Schizophrenia (SzO), bipolar disorder (BpO), and controls.
Resting-state fMRI data acquired at baseline and during a follow-up period were
analyzed using statistical techniques to examine connectivity between and within
RSNs associated with psychosis. The results revealed significant differences in RSN
connectivity, particularly in the DMN and CEN. Abnormal functional interactions
between the DMN and CEN were observed in the SzO group, indicating an aberrant dynamic between these networks. Age-related variations in connectivity patterns were also found, highlighting distinct associations between RSNs and brain
maturation processes in the different groups.
The study underscores the potential of fMRI as a tool for identifying objective
biomarkers. Moreover, it highlights the significance of including variables that facilitate better extrapolation to the clinical reality of psychiatry. By addressing these
considerations, future research can build upon these findings and further advance
our understanding of psychotic disorders.
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