Search Results for author: Timothy E. J. Behrens

Found 6 papers, 2 papers with code

Actionable Neural Representations: Grid Cells from Minimal Constraints

1 code implementation30 Sep 2022 William Dorrell, Peter E. Latham, Timothy E. J. Behrens, James C. R. Whittington

We suggest the brain must represent this consistent meaning of actions across space, as it allows you to find new short-cuts and navigate in unfamiliar settings.

Navigate

How to build a cognitive map: insights from models of the hippocampal formation

no code implementations3 Feb 2022 James C. R. Whittington, David McCaffary, Jacob J. W. Bakermans, Timothy E. J. Behrens

Learning and interpreting the structure of the environment is an innate feature of biological systems, and is integral to guiding flexible behaviours for evolutionary viability.

Hippocampus

Relating transformers to models and neural representations of the hippocampal formation

no code implementations ICLR 2022 James C. R. Whittington, Joseph Warren, Timothy E. J. Behrens

Many deep neural network architectures loosely based on brain networks have recently been shown to replicate neural firing patterns observed in the brain.

Position

Prediction and Generalisation over Directed Actions by Grid Cells

1 code implementation ICLR 2021 Changmin Yu, Timothy E. J. Behrens, Neil Burgess

Knowing how the effects of directed actions generalise to new situations (e. g. moving North, South, East and West, or turning left, right, etc.)

Continuous Control Translation

Generalisation of structural knowledge in the hippocampal-entorhinal system

no code implementations NeurIPS 2018 James C. R. Whittington, Timothy H. Muller, Shirley Mark, Caswell Barry, Timothy E. J. Behrens

We propose that to generalise structural knowledge, the representations of the structure of the world, i. e. how entities in the world relate to each other, need to be separated from representations of the entities themselves.

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