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Overview

Dr Ulrik Beierholm

Associate Professor

PhD, MSc, BSc, HEA Fellow


Affiliations
AffiliationRoom numberTelephone
Associate Professor in the Department of PsychologyL13+44 (0) 191 33 43249
Fellow in the Durham Research Methods Centre  
Member of the Centre for Vision and Visual Cognition  

Biography

I am very interested in how the nervous system deals with uncertainty, whether in perception, decision making or learning. We use computational ideas (e.g. bayesian inference or reinforcement learning) to model this and test these ideas using several techniques such as psychphysics, fMRI, pharmacology etc.

Research interests

  • Computational Neuroscience, Perception, Decision Making, Neuroeconomics, Machine Learning

Awarded Grants

  • 2017: Leverhulme Trust - 'Learning to Perceive and Act Under Uncertainty' (£258k), with Marko Nardini

Esteem Indicators

  • 2016: Awards: Facebook Faculty Award - Virtual Reality ;
  • Editor roles: Assciate Editor for ;PLoS Comp. Biol., Editor of the Springer Publishers Encyclopedia of Computational Neuroscience (Bayesian methods section)
  • Workshop organising: Co-organised the Durham Computational Biology Symposium (Durham, Nov 2018).

    Co-organisedthe Durham Probabilistic Brain Workshop (Durham, Mar 2018).

    Co-organised the Computational Models of Social Interaction Workshop (Birmingham, Oct 2014)

    Organised the Human Decision Making Workshop (Birmingham, Oct 2012)

Publications

Chapter in book

  • Reniers, R., Beierholm, U. & Wood, S. (2018). Reward sensitivity and behavioural control: neuroimaging evidence for brain systems underlying risk-taking behaviour. In The Wiley Blackwell Handbook of Forensic Neuroscience. Beech, Anthony R., Carter, Adam J., Mann, Ruth E. & Rotshtein, Pia Wiley-Blackwell.
  • Beierholm, Ulrik R. (2015). Bayesian Approaches in Computational Neuroscience: Overview. In Encyclopedia of Computational Neuroscience. Springer New York. 7-8.
  • Shams, Ladan & Beierholm, Ulrik R. (2011). Humans' Multisensory Perception, from Integration to Segregation, Follows Bayesian Inference Sensory Cue Integration. In Sensory Cue Integration. Trommershäuser, Julia, Kording, Konrad & Landy, Michael S. Oxford Univ Press.

Conference Paper

Journal Article

Other (Print)

  • Beierholm, Ulrik R. (2015). Bayesian models of perception. 2236-2239.

Supervision students