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Computational cognitive science laboratory


Principal Investigators:
Prof. Jianfeng Feng
Associate Prof. Jie Zhang


Research Directions:
1. Computational Psychiatry
2. Computational Genetics
3. Cognitive Neuroscience


Neuropsychiatric disorders such as depression, Alzheimer’s disease, attention deficit hyperactivity disorder, schizophrenia and autism are affecting an increased proportion of the world. People affected by these disorders range from adolescents to adults. Accurate classification of neuropsychiatric disorders, using resting-state functional fMRI of individuals, has been a challenge that holds immense promise for translational medicine and the understanding of the mechanisms of such neuropsychiatric disorders.


Traditionally, the diagnosis of neuropsychiatric disorders has been based on a categorical taxonomy, arrived at from clinical observations and questionnaires, combined with rating scales. The results have always been reported to be inconsistent. Our lab is devoted to finding highly predictive biological markers which characterise multiple levels of an individual, namely the genome, physiology and the brain. We have the aim to understand the mechanisms of such diseases through mathematical analyses, and modelling across all three levels of description. We use mathematical tools such as statistical inference, causality analysis, and dynamical modelling. We plan to quantify the multiple factors responsible for neuropsychiatric disorders (including the physical and social environments) by combining modern biomedical experiments (e.g., multi modal neuroimaging, physiological and genetic tools) with mathematical and statistical analyses. We intend to set up a quantitative biomarker system, for the early warning of general neuropsychiatric disorders, and a medical platform suitable for early diagnoses.

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