Duke’s Cognitive Neuroscience PhD bridges high-field MRI, intracranial electrophysiology, and deep-learning modeling to explain how neural circuits generate cognition. Candidates design VR paradigms for moral-dilemma navigation, decode real-time fMRI signals into semantic maps, and build closed-loop brain–computer interfaces for adaptive neuro-rehab. Weekly translational clinics connect bench discoveries to psychiatric care, and policy fellowships let trainees brief legislators on neurotechnology ethics.
Deep-learning reconstruction of visual scenes from occipital activity
Closed-loop DBS algorithm for treatment-resistant depression
EEG hyperscanning study of joint attention in cooperative gaming
VR task probing spatial memory in early Alzheimer’s detection
Optogenetic rodent model dissecting curiosity-driven exploration
Graph-theory analysis of functional connectivity during mind-wandering
Wearable MEG system for mobile language processing studies
Explainable AI for predicting ADHD treatment response
Citizen-science sleep app linking chronotype to risk decision-making
Policy white paper on workplace neuro-monitoring regulations
Neuroethical podcast series interviewing patients with BCIs
Bayesian model of predictive coding in auditory hallucinations
VR empathy training for bias mitigation in policing
Open-source toolbox for multimodal data synchronization
Blockchain-secured repository of anonymized neuro-datasets
Interrogate the neural code of thought and action with Duke’s CognNeuro PhD.
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