1. Brain Mapping and Cognitive Modeling

The cognitive function and neural basis of the human brain has always been a hot topic in neural science and artificial intelligence. It provides important guidance in achieving brain-inspired intelligence and artificial general intelligence (AGI). At present, most researches are focused on basic sensing and motor functions, especially the visual and auditory functions. However, to achieve a meaningful form of brain-inspired intelligence, it is necessary to focus on advanced cognitive functions that are uniquely human, such as language, reasoning, working memory, and decision processes. Research into human brain mapping and the neural network has provided important tools to understand brain functions and structure.

This research has laid the groundwork for designing and training AI algorithms, allowing us to model, decode and analyze the dynamic process of advanced cognitive functions of the human brain, and contributes to brain disease diagnosis and personal treatment.

2. Intelligent Analysis of Multimodal Brain Images
Based on multimodal brain images, Dr. Zhang’s research applies intelligent analysis and deep mining to understand the structures, connections, and functions of the human brain. This method provides the researchers with precise information about the brain regions and localization of brain functions for each participant in the study. Combined with lower dimensional presentations of the brain structure and functions, obtained by deep learning of large-scale brain image dataset, the technology could provide personalized information on disease prediction and diagnosis. Specifically, Dr. Zhang’s research includes: 1) using multimodal brain image and connectome analysis to explore the precise regions and localization of brain function in the cerebral cortex and in deep brain nuclei to inform brain disease diagnosis and assist in treatment; 2) using multimodal brain images to explore specificity in brain structure, connections and functions of different subjects in different developmental stages, races, and language environments; 3) based on personalized brain map, using advanced algorithms in machine learning and deep learning to process radiomics information and learn abstract presentations in high dimensions about brain image information, providing insights for predicting clinical and behavioral manifestation and exploring biomarkers for brain diseases.

Dr. ZHANG participated in or led the following research projects:

l  Research of multimodal brain image structuring based on graphical models (2021), a startup project at Zhejiang Lab, project leader, ongoing project

l  Spatiotemporal coding of cognitive function in human brain (2018-2020), project supported by IVADO, Canada, project leader, concluded project

l  Deep learning modeling for brain function (2018-2023), project supported by the Courtois Foundation, Canada, major participant, ongoing project

l  Dopamine pathways and behavioral intervention (2015-2022), project supported by the Canadian Institutes of Health Research (CIHR), major participant, ongoing project

l  Next-generation map of brain network (2011-2015), project supported by the National Basic Research Program of China, major participant, concluded project

Dr. ZHANG has participated in several national research projects in China and in Canada and independently led a postdoctoral project supported by the IVADO (Institut de valorisation des données), Canada. She has published 22 SCI papers (including 9 papers published as the first author, and her publications were cited 1,360 times). In the past five years, she published 14 papers, for 6 of which she was the first author or co-first author. These papers were published in eLife (2017), Journal of Neuroscience (2018), Neuroimage (2017，2021), etc. The papers she co-authored were published on core periodicals in the field, including PNAS, PLOS Biology, Biological Psychiatry, and Cerebral Cortex.

Selected Publications:

1. Yu Zhang, Loïc Tetrel, Bertrand Thirion, and Pierre Bellec. 2021. Functional Annotation of Human Cognitive States using Deep Graph Convolution; NeuroImage 231 (May): 117847.

2. Yu Zhang, Kevin Larcher, Bratislav Misic, and Alain Dagher. 2017. Anatomical and Functional Organization of the Human Substantia Nigra and Its Connections. eLife. 26653.

3. Yu Zhang, Lingzhong Fan, Svenja Caspers, Stefan Heim, Ming Song, Cirong Liu, Yin Mo, Simon B. Eickhoff, Katrin Amunts, and Tianzi Jiang. 2017. Cross-Cultural Consistency and Diversity in Intrinsic Functional Organization of Broca’s Region. NeuroImage 150 (April): 177; 90.

4. Daniel Vosberg*, Yu Zhang*, Aurore Menegaux, Amanda Chalupa, Colleen Manitt, Simone Zehntner, Conrad Eng, et al. 2018. Mesocorticolimbic Connectivity and Volumetric Alterations in DCC Mutation Carriers. The Journal of Neuroscience 38 (20): 4655; 65.

5. Lingzhong Fan, Hai Li, Junjie Zhuo, Yu Zhang, Jiaojian Wang, Liangfu Chen, Zhengyi Yang, et al. 2016. The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture. Cerebral Cortex 26 (8): 3508; 26. 

Google scholar: https://scholar.google.ca/citations?user=lZwQ9mgAAAAJ