Highlights Mechanisms underlying treatment-resistant schizophrenia are unclear. Effective connectivity within cortico-striatal network differentially disrupted in resistant patients. Resistance associated with lack of top-down control and aberrant glutamate function. We suggest a subtype of schizophrenia with distinct neurobiological mechanism. Results are important for guiding treatment strategies and developing new drugs.

Psychotic illness is associated with cognitive control deficits and abnormal recruitment of neural circuits subserving cognitive control. It is unclear to what extent this dysfunction underlies the development and/or maintenance of positive and negative symptoms typically observed in schizophrenia. In this study we compared fMRI activation on a standard Stroop task and its relationship with positive and negative symptoms in early psychosis (EP, N = 88) and chronic schizophrenia (CHR-SZ, N = 38) patients. CHR-SZ patients showed reduced frontal, striatal, and parietal activation across incongruent and congruent trials compared to EP patients. Higher positive symptom severity was associated with reduced activation across both trial types in supplementary motor area (SMA), middle temporal gyrus and cerebellum in EP, but not CHR-SZ patients. Higher negative symptom severity was associated with reduced cerebellar activation in EP, but not in CHR-SZ patients. A negative correlation between negative symptoms and activation in SMA and precentral gyrus was observed in EP patients and in CHR-SZ patients. The results suggest that the neural substrate of positive symptoms changes with illness chronicity, and that cognitive control related neural circuits may be most relevant in the initial development phase of positive symptoms. These findings also highlight a changing role for the cerebellum in the development and later maintenance of both positive and negative symptoms.

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BackgroundAspects of cognitive function decline with age. This phenomenon is referred to as age-related cognitive decline (ARCD). Improving the understanding of these changes that occur as part of the ageing process can serve to enhance the detection of the more incapacitating neurodegenerative disorders such as Alzheimer’s disease (AD). In this study, we employ novel methods to assess ARCD by exploring the utility of the alpha3/alpha2 electroencephalogram (EEG) power ratio – a marker of AD, and a novel virtual reality (VR) functional cognition task – VStore, in discriminating between young and ageing healthy adults.Materials and methodsTwenty young individuals aged 20–30, and 20 older adults aged 60–70 took part in the study. Participants underwent resting-state EEG and completed VStore and the Cogstate Computerised Cognitive Battery. The difference in alpha3/alpha2 power ratios between the age groups was tested using t-test. In addition, the discriminatory accuracy of VStore and Cogstate were compared using logistic regression and overlying receiver operating characteristic (ROC) curves. Youden’s J statistic was used to establish the optimal threshold for sensitivity and specificity and model performance was evaluated with the DeLong’s test. Finally, alpha3/alpha2 power ratios were correlated with VStote and Cogstate performance.ResultsThe difference in alpha3/alpha2 power ratios between age cohorts was not statistically significant. On the other hand, VStore discriminated between age groups with high sensitivity (94%) and specificity (95%) The Cogstate Pre-clinical Alzheimer’s Battery achieved a sensitivity of 89% and specificity of 60%, and Cogstate Composite Score achieved a sensitivity of 83% and specificity of 85%. The differences between the discriminatory accuracy of VStore and Cogstate models were statistically significant. Finally, high alpha3/alpha2 power ratios correlated strongly with VStore (r = 0.73), the Cogstate Pre-clinical Alzheimer’s Battery (r = -0.67), and Cogstate Composite Score (r = -0.76).ConclusionWhile we did not find evidence that the alpha3/alpha2 power ratio is elevated in healthy ageing individuals compared to young individuals, we demonstrated that VStore can classify age cohorts with high accuracy, supporting its utility in the assessment of ARCD. In addition, we found preliminary evidence that elevated alpha3/alpha2 power ratio may be linked to lower cognitive performance.