����Vlog�ٷ� Cambridge: Dr Zhen-Qi Liu

Position Governing Body Fellow Junior Research Fellow
School Clinical Medicine Department of Psychiatry (inc Brain Mapping Unit and Developmental Psychopathology
Personal website
Email zql21@cam.ac.uk
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Zhen-Qi is a computational neuroscientist investigating how complex cognition emerges from brain network structure and dynamics. He is a Royal Society Newton International Fellow at the Department of Psychiatry and a Junior Research Fellow at ��Vlog�ٷ�.

Zhen-Qi completed his undergraduate studies at Xi'an Jiaotong University through the Honors Youth Program. His undergraduate thesis investigated long-range temporal correlations in neural networks with applications to brain-inspired computing. He subsequently pursued graduate training at McGill University, earning an MSc (2020) and a PhD (2025) in Neuroscience at the Montreal Neurological Institute under the supervision of Dr Bratislav Misic.

His doctoral research focused on the relationship between brain structure and function, a central puzzle in neuroscience. The brain's white matter pathways form a fixed anatomical scaffold, yet neural activity patterns are remarkably flexible, reconfiguring from moment to moment to support different cognitive demands. Zhen-Qi developed computational approaches to characterize how these two levels of organization relate to one another, examining how structural connections shape functional dynamics across different measurement techniques, temporal scales, and species. He also worked with clinicians to study how network organization is disrupted in neurodegeneration and psychiatric conditions.

In 2025, Zhen-Qi was awarded a Newton International Fellowship from the Royal Society to pursue postdoctoral research at the University of Cambridge, where he will continue developing computational approaches for multimodal brain mapping and cross-species translation.

Zhen-Qi's research is driven by a fundamental question: how does the brain's physical wiring give rise to the rich dynamics that underlie cognition and behaviour? The challenge is that the brain operates across multiple scales simultaneously, from molecular gradients and cellular architecture to long-range fiber tracts and whole-brain dynamics. Network neuroscience offers a promising framework for describing these systems, representing the brain as a complex system of interconnected regions and characterizing how information flows through this architecture. Zhen-Qi develops and applies computational methods that integrate structural and functional neuroimaging data to map these relationships across spatial scales, temporal dynamics, and imaging modalities. He is also committed to open and reproducible science, contributing to software toolboxes that help researchers contextualize brain maps and apply network methods. These resources have supported studies linking brain organization to genetics, cognition, and disease.

At Cambridge, Zhen-Qi is extending this work in two directions. The first involves cross-species translation: findings from human neuroimaging are difficult to connect with mechanistic insights from animal models because the data live in different coordinate systems and use different measurement techniques. He is developing computational tools and frameworks to align multimodal brain maps across species, with the goal of enabling more direct comparisons between human and preclinical research. The second direction applies statistical approaches to large psychiatric genetics datasets, asking how genetic variants associated with illness relate to spatial patterns of brain organization. By modeling how individual brains deviate from population norms, this work may help clarify the neurobiological pathways linking genetic risk to psychiatric outcomes. Both lines of research reflect a broader aim: to understand the organizing principles that shape brain networks and how their disruption contributes to disease.