Biomarkers in neurophysiological signals can be analyzed to determine indicators of mood disorders for diagnosis. In this paper, EEG signals were analyzed from a public database of 119 subjects ages 18 to 24 performing a cognitive task. 45 subjects had moderate to severe anxiety and/or depression and the remaining 74 subjects had minimal or none. A subject's level of depression and/or anxiety was classified by standard psychological tests. EEG signals were preprocessed and separated into frequency bands: beta (12-30 Hz), alpha (8-12 Hz), theta (4-8 Hz) and delta (0.5-4 Hz). Features were extracted including Higuchi Fractal Dimension, correlation dimension, approximate entropy, Lyapunov exponent and detrended fluctuation analysis. Similarities, and asymmetry can be examined between the left and right brain hemispheres as well as the prefrontal cortex channels. ANOVA II analysis showed a significant difference (p<0.05) for topographical region comparisons of several features between the affected and unaffected subjects for specific features. The results demonstrate physiological asymmetry between high scoring subjects indicating a mood disorder, with low scoring, to be used as an indicator of illness. Understanding the complexities of how depression and anxiety are manifested physiologically including its comorbidities, is critical for accurate and objective diagnosis of mood and anxiety order disorders.