From raw signal to objective biomarker
Every diagnosis we work toward is grounded in a measurement. These are the signals our pipeline reads — spectral power, neural firing, network coupling, and modelled stimulation fields.
Spectral power
Absolute and relative power across δ, θ, α, β and γ bands — and the ratios that track psychiatric presentations.
Neural firing
Spike-train dynamics across channels — the raster view of when and where the brain is active over time.
Network coupling
Phase-locking and coherence between regions — isolating the hyper- and hypo-connected hubs behind symptoms.
Electric-field model
Individually modelled tDCS current flow — optimising the montage before a single electrode is placed.
Eight divisions, one question
How do distributed brain networks produce cognition, emotion, behaviour — and psychiatric illness? Each division attacks a different facet, from computation to the clinic.
Computational Psychiatry
Predictive ML models, symptom-network analysis, digital phenotyping, and Bayesian & reinforcement-learning cognitive models — the engine of precision psychiatry.
Cognitive Neuroscience
Attention, executive function, working memory, cognitive flexibility, inhibition, decision-making, emotion regulation, and learning — including neuropsychological models of ADHD.
Brain Network Science
Functional and dynamic connectivity, oscillatory networks, connectomics, and network biomarkers of large-scale brain systems.
Deep Oscillatory Networks (DONs)
How oscillatory interactions among distributed networks generate cognition, emotion, and symptoms — applied across OCD, depression, ADHD, bipolar, schizophrenia, autism, anxiety, and functional neurological disorders.
Neurotechnology
Development and validation of EEG, qEEG, neurofeedback, tDCS, tACS, tVNS, and digital biomarkers.
Clinical Psychiatry Research
Treatment-outcome studies, biomarkers, psychopharmacology, psychotherapy, neuromodulation, and longitudinal cohorts.
Digital Mental Health
Smartphone monitoring, passive sensing, digital phenotyping, remote assessment, and AI-assisted care.
Behavioural Science
Objective behavioural phenotyping — including the structure of personality and temperament — through naturalistic and task-based paradigms, behavioural biomarkers, and behaviour-change studies that link observable action to cognition, emotion, and network dynamics.
Divisions share data, methods, and a single pipeline — so a biomarker found in one becomes a tool for all.
Five lenses on mental illness
Objective Psychiatry
Measurable biological and cognitive markers for diagnosis.
Precision Psychiatry
Matching patients to the most effective treatment using objective data.
Network Psychiatry
Disorders as disturbances of distributed neural networks.
Oscillatory Psychiatry
Illness understood through abnormalities in brain oscillations.
Computational Network Psychiatry
EEG, cognition, AI and dynamic network analysis, combined.
The laboratories we intend to establish
A staged build-out of the physical and computational infrastructure the institute's research requires.
Neurophysiology Lab
Clinical EEG, qEEG, brain-stimulation and physiological recording systems.
Cognitive Assessment Lab
Computerised testing — Stroop, N-back, Go/No-Go, task-switching, SART, reaction-time and executive-function batteries.
Computational Neuroscience Lab
AI models, statistical pipelines, machine-learning systems, network-analysis tools, and simulations.
Digital Psychiatry Lab
Digital biomarkers, smartphone tools, AI clinical assistants, and patient-monitoring systems.
Clinical Trials Unit
Studies of medication, psychotherapy, neuromodulation, and biomarker-guided precision treatment.
Ethics & data
An Institutional Ethics Committee, data-governance framework, responsible-AI policy, and patient-privacy standards underpin every lab.
What we intend to build
EEG Biomarker Program
Biomarkers for depression, OCD, ADHD, psychosis, anxiety, and bipolar disorder.
Cognitive Biomarker Program
Objective cognitive phenotyping using computerised tasks.
Oscillatory Brain Network Project
Mapping dynamic oscillatory interactions in psychiatric disorders.
Precision Neuromodulation Project
Optimising brain stimulation using biomarkers.
AI Psychiatry Platform
Large-scale predictive models integrating clinical data, EEG, cognition, psychometrics, and longitudinal outcomes.
What we're standing up first
We're in setup — these are the first, concrete projects we're building. Each is tagged with its honest current stage.
qEEG Biomarker Pilot
Building the EEG acquisition and automated preprocessing pipeline, and computing our first quantitative biomarkers on real patient data.
Deep Oscillatory Network Mapping
Mapping dynamic oscillatory interactions across disorders — the groundwork for our signature research theme.
Behavioural Phenotyping Studies
Objective, task-based and naturalistic behavioural measures — building behavioural biomarkers alongside the cognitive and EEG work.
Personality & Behavioural Studies
Mapping personality structure and temperament to objective markers — linking trait dimensions with cognition, emotion regulation, and brain-network dynamics.
Neuropsychological Models of ADHD
Formal cognitive and computational models of attention, inhibition and executive control in ADHD — tied to EEG and behavioural biomarkers.
Precision Neuromodulation Protocol
Biomarker-guided, individually modelled tDCS — turning network findings into optimised, personalised stimulation.
AI Psychiatry Platform
A research data registry and predictive models integrating clinical data, EEG, cognition, behaviour, and longitudinal outcomes.
We publish our stage honestly. Projects move from concept → planning → setup → active as the institute matures.