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School of Biological and Behavioural Sciences

Dr Yul Kang


Lecturer in Psychology

Centre: Fellow of Digital Environment Research Institute

Room Number: Fogg 3.16
Twitter: @YulKang1


Research Interests:

My group is interested in finding optimal algorithms to perform cognitive tasks under uncertainty, using probabilistic neural representation models inspired by robotics and machine learning methods, and comparing it with data from the literature or experimental collaborators. We also design and perform human behavioural experiments ourselves. We have applied this approach to areas including perceptual decision-making, spatial navigation, episodic memory, and active sensing.

  • Spatial navigation: grid fields (often called a “ruler in the brain”), which were thought to “deform” depending on the geometry of the environment, in fact represent uncertainty about the animal’s own location (Cosyne 2020 Presenters Travel AwardBernstein 2021 Contributed Talk: Here we developed:
    • a normative theory that jointly predicts the deformation in the neural representation as well as bias and variability in homing behavior.
    • an ideal observer model that takes as input the video from the 1st-person perspective and egocentric motion, and outputs the posterior belief over the agent’s allocentric location, which allows it to be applied to any setup without handcrafted features, as demonstrated by my re-analysis of historic results.
  • Episodic memory: memory of a unique episode is retained with a graded sense of uncertainty, which has not been considered quantitatively in the domain of episodic memory. We showed that not only is this uncertainty used in causal inference, as reflected in explicit choices, but also betrayed by gazes even after accounting for the explicit choices (CCN 2019).
  • Dual-task: two decisions about one object cannot be made simultaneously; they are made one by one, and evidence for each accumulates in an interleaved fashion. We showed this by developing novel behavioral tasks & efficient drift-diffusion models, which fit the joint distribution of choices & reaction times (2021 eLifeCosyne 2021 Contributed Talk).


Kang YHR*, Löffler A*, Jeurissen D*, Zylberberg A†, Wolpert DM†, Shadlen MN† (2021), Multiple decisions about one object involve parallel sensory acquisition but time-multiplexed evidence incorporation. eLife 10, e63721.

Lee DS, Kang YHR, Ruiz-Lambides A, Higham J (2021), The observed pattern and hidden process of female reproductive trajectories across the lifespan in a nonhuman primate. J Animal Ecology 2021;00:1-14.

Bakkour A, Palombo DJ, Zylberberg A, Kang YHR, Reid A, Verfaellie M, Shadlen MN, and Shohamy D (2019), The hippocampus supports deliberation during value-based decisions. eLife 8, e46080.

Kang YHR*, Mahr J*, Nagy M, Andrási K, Csibra G†, Lengyel M† (2019), Eye movements reflect causal inference during episodic memory retrieval. Cognitive Computational Neuroscience (CCN).

Kang, Yul HR*, Frederike H. Petzschner*, Daniel M. Wolpert, and Michael N. Shadlen (2017), Piercing of consciousness as a threshold crossing operation, Curr Biol.

Lee, DS and HR Kang (2012), The categorization of “bad animal” and its relation to animal appearances: 
a study of 6-year-old children’s perceptions, J Soc Evo Cultural Psych.

Yoon, Sujung, CS Jun, HY An, HR Kang, TY Jun (2009), Patterns of temperament and character in patients with PTSD and their association with symptom severity, Comprehensive Psychiatry 50, no. 3: 226-231.

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