Dr Lei Zhang BSc, MSc, PhD

Dr Lei Zhang

School of Psychology
Associate Professor

Dr. Lei Zhang is a cognitive computational neuroscientist. He directs the Adaptive Learning Psychology and Neuroscience Lab, ALP(e)N Lab, which addresses the fundamental question of the “adaptive brain” by studying the cognitive, computational, and neurobiological basis of (social) learning and decision-making in health and disease (i.e. Computational Psychiatry).

Qualifications

  • PhD in Cognitive Neuroscience (summa cum laude), University of Hamburg & University Medical Center Hamburg-Eppendorf, Germany; Awarded Chinese Government Prize for Outstanding Doctoral Dissertation Abroad
  • MSc in Cognitive Neuroscience, University of the Basque Country & Basque Center on Cognition, Brain & Language, Spain
  • BSc in Psychology, Beijing Normal University, China

Biography

Dr Lei Zhang obtained his BSc in Psychology from Beijing Normal University, China, and his MSc in Cognitive Neuroscience at Basque Center on Cognition, Brain and Language, Spain. He received his PhD (summa cum laude), along with a one-year transition postdoc, with Dr Jan Gläscher at the Institute of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Germany. Between 2016 and 2017, he was a Roche intern for Scientific Exchange (RiSE) at one of the research-based pharmaceutical companies, F. Hoffmann-La Roche AG, based in Basel, Switzerland. Between 2019 and 2022, he worked as a postdoctoral fellow with Prof Claus Lamm at the Social Cognitive and Affective Neuroscience Unit (SCAN-Unit), University of Vienna, Austria. Dr Zhang joined the Centre for Human Brain Health, Institute of Mental Health, and School of Psychology at University of Birmingham as an Associate Professor in winter 2022.

Teaching

Dr Lei Zhang performs research-informed teaching. He teaches an MSc-level module on Proposing Research in Psychology.

Postgraduate supervision

PhD students: Students interested in working with Dr Zhang should email him to discuss potential funding opportunities. Current funding schemes include MRC-AIM, BBSRC-MIBTP, and CSC.

Postdoc researchers: Excellent and motivated postdoc researchers are welcome to contact Dr Zhang to discuss potential projects and funding opportunities (both national and international).

Research

Learning and decision-making, flexible & adaptive (learning) behavior, decision neuroscience/neuroeconomics, social learning, reinforcement learning, cognitive modeling, Bayesian methods, neuroimaging, fMRI, TMS, pain, aversive learning, computational psychiatry

Other activities

Awards

  • Rising Star Award, Association for Psychological Science (APS), 2022
  • Commendation Award for Open Science, European Society for Cognitive and Affective Neuroscience (ESCAN), 2022
  • Open & Reproducible Science Award, Society for Social Neuroscience (S4SN), 2021
  • Trainee Professional Development Award, Society for Neuroscience (SfN), 2020
  • Teaching Award for Early Career Researchers, University of Vienna, 2020
  • Fellow, Kavli Summer Institute in Cognitive Neuroscience (“Brain Camp”), Santa Barbara, CA, USA, 2019

Responsibilities

  • eLife Community Ambassador (2022-2024)
  • OHBM Student and Postdoc Special Interest Group (2021-2023)
  • S4SN Open Science Committee, Society for Social Neuroscience (2021–2022)
  • ALBA Network Member for diversity and equality in neurosciences (2021-present)
  • COS Ambassador, Center for Open Science (2020–present)
  • Steering committee member, Chinese Open Science Network (2018–present)

Publications

Highlight publications

Zhang, L & Gläscher, J 2020, 'A brain network supporting social influences in human decision-making', Science Advances. https://doi.org/10.1126/sciadv.abb4159

Crawley, D, Zhang, L, Jones, EJH, Ahmad, J, Oakley, B, San José Cáceres, A, Charman, T, Buitelaar, JK, Murphy, DGM, Chatham, C, den Ouden, H & Loth, E 2020, 'Modeling flexible behavior in childhood to adulthood shows age-dependent learning mechanisms and less optimal learning in autism in each age group', PLoS Biology, vol. 18, no. 10. https://doi.org/10.1371/journal.pbio.3000908

Zhang, L, Lengersdorff, L, Mikus, N, Gläscher, J & Lamm, C 2020, 'Using reinforcement learning models in social neuroscience: frameworks, pitfalls and suggestions of best practices', Social Cognitive and Affective Neuroscience, vol. 15, no. 6, pp. 695-707. https://doi.org/10.1093/scan/nsaa089

Zhao, Y, Zhang, L, Rütgen, M, Sladky, R & Lamm, C 2021, 'Neural dynamics between anterior insular cortex and right supramarginal gyrus dissociate genuine affect sharing from perceptual saliency of pretended pain', eLife, vol. 10, e69994. https://doi.org/10.7554/eLife.69994

Ahn, WY, Haines, N & Zhang, L 2017, 'Revealing neurocomputational mechanisms of reinforcement learning and decision-making with the hBayesDM package', Computational Psychiatry, vol. 1, pp. 24-57. https://doi.org/10.1162/CPSY_a_00002

Recent publications

Article

Geiger, SJ, White, MP, Davison, SMC, Zhang, L, McMeel, O, Kellett, P & Fleming, LE 2023, 'Coastal proximity and visits are associated with better health but may not buffer health inequalities', Communications Earth and Environment, vol. 4, no. 1, 166. https://doi.org/10.1038/s43247-023-00818-1

Zhao, Y, Zhang, L, Rütgen, M, Sladky, R & Lamm, C 2022, 'Effective connectivity reveals distinctive patterns in response to others’ genuine affective experience of disgust', NeuroImage, vol. 259, 119404. https://doi.org/10.1016/j.neuroimage.2022.119404

Zhang, L 2022, 'Examining mental disorders with computational neuroscience', Nature Reviews Psychology. https://doi.org/10.1038/s44159-022-00131-2

Mitter, B, Zhang, L, Bauer, P, Baca, A & Tschan, H 2022, 'Modeling the relationship between load and repetitions to failure in resistance training: A Bayesian analysis', European Journal of Sport Science. https://doi.org/10.1080/17461391.2022.2089915

Neuromatch, Hart, BM & Zhang, L 2022, 'Neuromatch Academy: a 3-week, online summer school in computational neuroscience', Journal of Open Source Education, vol. 5, no. 49, 118. https://doi.org/10.21105/JOSE.00118

Joue, G, Chakroun, K, Bayer, J, Gläscher, J, Zhang, L, Fuss, J, Hennies, N & Sommer, T 2022, 'Sex differences and exogenous estrogen influence learning and brain responses to prediction errors', Cerebral Cortex, vol. 32, no. 9, pp. 2022-2036. https://doi.org/10.1093/cercor/bhab334

Kreis, I, Zhang, L, Moritz, S & Pfuhl, G 2022, 'Spared performance but increased uncertainty in schizophrenia: evidence from a probabilistic decision-making task', Schizophrenia Research, vol. 243, pp. 414-423. https://doi.org/10.1016/j.schres.2021.06.038

Yao, Y-W, Chopurian, V, Zhang, L, Lamm, C & Heekeren, HR 2021, 'Effects of non-invasive brain stimulation on visual perspective taking: a meta-analytic study', NeuroImage, vol. 242, 118462. https://doi.org/10.1016/j.neuroimage.2021.118462

Zhao, Y, Rütgen, M, Zhang, L & Lamm, C 2021, 'Pharmacological fMRI provides evidence for opioidergic modulation of discrimination of facial pain expressions', Psychophysiology, vol. 58, no. 2, e13717. https://doi.org/10.1111/psyp.13717

Schmalz, X, Biurrun Manresa, J & Zhang, L 2021, 'What is a Bayes factor?', Psychological Methods. https://doi.org/10.1037/met0000421

Comment/debate

Geng, H, Chen, J, Hu, C-P, Jin, J, Chan, RCK, Li, Y, Hu, X, Zhang, R-Y & Zhang, L 2022, 'Promoting computational psychiatry in China', Nature Human Behaviour, vol. 6, no. 5, pp. 615–617. https://doi.org/10.1038/s41562-022-01328-4

Preprint

Hu, C-P, Geng, H, Zhang, L, Fengler, A, Frank, M & Zhang, R-Y 2022 'A Hitchhiker’s Guide to Bayesian Hierarchical Drift-Diffusion Modeling with dockerHDDM' PsyArXiv. https://doi.org/10.31234/osf.io/6uzga

Zhang, L, Kandil, FI, Zhao, K, Fu, X, Lamm, C, Hilgetag, CC & Gläscher, J 2022 'A causal role of the human left temporoparietal junction in computing social influence during goal-directed learning' bioRxiv. https://doi.org/10.1101/2022.06.13.495824

Pan, Y, Vinding, M, Zhang, L, Lundqvist, D & Olsson, A 2022 'A multi-brain mechanism for observational threat learning' Research Square. https://doi.org/10.21203/rs.3.rs-2215515/v1

Hollá Kutliková, H, Zhang, L, Eisenegger, C, van Honk, J & Lamm, C 2022 'Testosterone eliminates strategic prosocial behavior' bioRxiv. https://doi.org/10.1101/2022.04.27.489681

View all publications in research portal