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model of human working memory. During the project, we will follow an intertwined model-experimental approach. First, we will use electroencephalography (EEG) experiments to investigate the neural basis
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. Electroencephalography (EEG) has emerged as a non-invasive and economical alternative technique for studying neurological disorders. However, current approaches rely primarily on single-channel or pairwise connectivity
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assessments, neuroimaging (EEG and/or fMRI), oxytocin quantification in plasma/saliva, and pharmacological interventions. Part 1 involves the continuation and completion of an ongoing MRC-funded clinical study
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involve EEG, eye-tracking, or applied fieldwork, depending on interest and expertise. While this is not a confirmed PhD place, a small number of outstanding candidates will be supported to develop a strong
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to measure how young brains track information content within screen media in real-time. The project will involve collecting and analysing EEG, fNIRS and home wearable recordings from babies and children
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project will involve collecting and analysing EEG, fNIRS and home wearable recordings from babies and children. Experience of advanced data analytics, including if possible experience of coding in Matlab
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no research. We propose to leverage state-of-the-art techniques to measure how young brains track information content within screen media in real-time. The project will involve collecting and analysing EEG
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patricia.davies@colostate.edu Position Summary Dr. Patricia Davies’ ICR Grant. The successful applicants will assist in all aspects of the current research which involves collecting EEG data, conducting blood draws
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, stress markers, EEG, and ECG — will be collected by VR headsets and IoT devices. ML algorithms will analyse this data to identify trends, project risk factors, and propose tailored treatments. By combining
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electroencephalography (EEG), behavioural tasks, and computational modelling, the student will examine how these interventions influence brain dynamics, cognition, and subjective experience.