Institutional Research Information Service
UCL Logo
Please report any queries concerning the funding data grouped in the sections named "Externally Awarded" or "Internally Disbursed" (shown on the profile page) to your Research Finance Administrator. Your can find your Research Finance Administrator at https://www.ucl.ac.uk/finance/research/rs-contacts.php by entering your department
Please report any queries concerning the student data shown on the profile page to:

Email: portico-services@ucl.ac.uk

Help Desk: http://www.ucl.ac.uk/ras/portico/helpdesk
Publication Detail
Continual task learning in natural and artificial agents
  • Publication Type:
    Journal article
  • Authors:
    Flesch T, Saxe A, Summerfield C
  • Publisher:
    Elsevier BV
  • Publication date:
  • Journal:
    Trends in Neurosciences
  • Medium:
  • Status:
  • Country:
  • PII:
  • Language:
  • Keywords:
    Hebbian gating, machine learning, neural networks, neuroimaging, representational geometry
  • Notes:
    © 2022 The Authors. Published by Elsevier Ltd. under a Creative Commons license (https://creativecommons.org/licenses/by/4.0/).
How do humans and other animals learn new tasks? A wave of brain recording studies has investigated how neural representations change during task learning, with a focus on how tasks can be acquired and coded in ways that minimise mutual interference. We review recent work that has explored the geometry and dimensionality of neural task representations in neocortex, and computational models that have exploited these findings to understand how the brain may partition knowledge between tasks. We discuss how ideas from machine learning, including those that combine supervised and unsupervised learning, are helping neuroscientists understand how natural tasks are learned and coded in biological brains.
Publication data is maintained in RPS. Visit https://rps.ucl.ac.uk
 More search options
UCL Researchers
Gatsby Computational Neurosci Unit
University College London - Gower Street - London - WC1E 6BT Tel:+44 (0)20 7679 2000

© UCL 1999–2011

Search by