Patricia Therese Michie

Region-specific associations between cerebral arterial elasticity and grey matter volume: Evidence for lateral prefrontal vulnerability

The paper investigates how regional cerebral arterial elasticity relates to grey matter volume decline with age, finding partial mediation in the left prefrontal cortex and sex-specific effects.

Cardiorespiratory fitness and cardiometabolic health are associated with distinct cognitive domains in cognitively healthy older adults.

Neuroanatomical Correlates of Negative Symptoms in Schizophrenia

This study identifies small but consistent anatomical correlates of negative symptom dimensions in schizophrenia, linking them to prefrontal cortical thickness and limbic subcortical volumes.

Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study

This study investigates how structural brain alterations in schizophrenia relate to network architecture, finding hub susceptibility and shared epicenters across disease stages and disorders.

Estimating multimodal brain variability in schizophrenia spectrum disorders: A worldwide ENIGMA study

This study examines structural brain heterogeneity in schizophrenia using multimodal MRI data from the ENIGMA dataset, finding higher frontotemporal heterogeneity and left parahippocampal homogeneity in patients.

Reconsidering electrophysiological markers of response inhibition in light of trigger failures in the stop-signal task

This study uses a parametric ex-Gaussian model to analyze stop-signal task performance, revealing differences in neural correlates of response inhibition between stop-success and stop-failure trials.

The effect of NMDA-R antagonist, MK-801, on Neuronal Mismatch along the Auditory Thalamocortical System

This study investigates how the NMDA-R antagonist MK-801 affects neuronal mismatch responses in the rat auditory thalamocortical pathway, finding it enhances repetition suppression in thalamus and prediction error in cortex.

Auditory prediction errors as individual biomarkers of schizophrenia

This paper uses EEG and machine learning to classify schizophrenia patients and controls using auditory prediction error responses, achieving 80.48% accuracy and correlating MMN with functioning scores.