Generalisation of structural knowledge in the hippocampal-entorhinal system
Authors: James Whittington, Timothy Muller, Shirely Mark, Caswell Barry, Tim Behrens
NeurIPS 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We implement our proposal in an ANN tasked with predicting sensory observations when walking on 2D graph worlds, where each vertex is associated with a sensory experience. ... Our network learns representations that mirror those found in the brain, with different entorhinal-like representations forming depending on transition statistics. We further present analyses of a remapping experiment [5], which support our model assumptions... We show that by predicting sensory observations in environments that share structure, the model learns to generalise structural knowledge. ... We show the representations learned by our network in Fig 4 and 5 by plotting spatial activity maps of particular neurons. |
| Researcher Affiliation | Academia | James C.R. Whittington* University of Oxford, UK james.whittington@magd.ox.ac.uk Timothy H. Muller* University of Oxford, UK timothymuller127@gmail.com Shirley Mark University College London, UK s.mark@ucl.ac.uk Caswell Barry University College London, UK caswell.barry@ucl.ac.uk Timothy E.J. Behrens University of Oxford, UK behrens@fmrib.ox.ac.uk |
| Pseudocode | No | The paper does not contain any pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | No | The paper does not provide any explicit statement or link for open-source code. |
| Open Datasets | Yes | We empirically test this prediction in data from a remapping experiment [5] where both place and grid cells were recorded from rats in two different environments. ... [5] C. Barry, L. L. Ginzberg, J. O Keefe, and N. Burgess. Grid cell firing patterns signal environmental novelty by expansion. Proceedings of the National Academy of Sciences, 109(43):17687 17692, 2012. |
| Dataset Splits | No | The paper does not specify exact training, validation, or test dataset splits for either the model's experiments or the analysis of the remapping experiment data. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., CPU/GPU models, memory) used for running the experiments. |
| Software Dependencies | No | The paper does not specify any software dependencies with version numbers. |
| Experiment Setup | No | The paper states: 'Further implementation details in SM.' implying that specific experimental setup details (e.g., hyperparameters) are not provided in the main text. |