Hi all,

I am a PhD student in the Sunshine Coast, Australia.

My thesis examines neuro-imaging indices predictive of oral low-dose ketamine treatment response in suicidality and depression. Specifically, I am interested in ketamine-induced changes in neurometabolite concentrations (MRS), and EEG complexity dynamics (entropy and information flow).

This novel approach is informed by the action of ketamine at the NMDA receptor; a key regulator of synaptic plasticity dynamics, and hence, hierarchical (active) inference. Drawing from the free-energy principle, entropy brain hypothesis, and active (Bayesian) inferences theories, ketamine’s pertubation of synaptic dynamics (i.e. information flow) is proposed to deprecate the confidently held priors that uphold mental health psychopathology.

Considering the application of Bayesian inference to my thesis, it was only logical that I employed the accompanying statistical methodology.

Coding: R, Python, Matlab
Stats: Bayesian (BRMS) Padawan