While functional near-infrared spectroscopy (fNIRS) had previously been suggested for major depressive disorder (MDD) diagnosis, the clinical application to predict antidepressant treatment response (ATR) is still unclear. To address this, the aim of the current study is to investigate MDD ATR using fNIRS and micro-ribonucleic acids (miRNAs). Our proposed algorithm includes a custom inter-subject variability reduction based on the Principal Component Analysis (PCA).
Resilience is an important indicator of our defence mechanism against mental illness. Its assessment is conventionally done using psychological questionnaires and has also been recently investigated using neuroimaging modalities. These modalities provide objective and physiological-based assessment of resilience for prognosis and training purposes such as in the neurofeedback and behavioural therapies. This study investigates the use of electroencephalogram (EEG) to assess mental resilience in 2-Class, 3-Class and 4-Class models during resting and task conditions.