No free lunch from deep learning in neuroscience: A case study through models of the entorhinal-hippocampal circuit
Research in Neuroscience, as in many scientific disciplines, is undergoing a renaissance
based on deep learning. Unique to Neuroscience, deep learning models can be used not …
based on deep learning. Unique to Neuroscience, deep learning models can be used not …
Self-supervised learning of representations for space generates multi-modular grid cells
To solve the spatial problems of map**, localization and navigation, the mammalian
lineage has developed striking spatial representations. One important spatial representation …
lineage has developed striking spatial representations. One important spatial representation …
Winning the lottery with neural connectivity constraints: Faster learning across cognitive tasks with spatially constrained sparse rnns
Recurrent neural networks (RNNs) are often used to model circuits in the brain and can
solve a variety of difficult computational problems requiring memory, error correction, or …
solve a variety of difficult computational problems requiring memory, error correction, or …
Multiple bumps can enhance robustness to noise in continuous attractor networks
R Wang, L Kang - PLOS Computational Biology, 2022 - journals.plos.org
A central function of continuous attractor networks is encoding coordinates and accurately
updating their values through path integration. To do so, these networks produce localized …
updating their values through path integration. To do so, these networks produce localized …
Robust variability of grid cell properties within individual grid modules enhances encoding of local space
Although grid cells are one of the most well studied functional classes of neurons in the
mammalian brain, the assumption that there is a single grid orientation and spacing per grid …
mammalian brain, the assumption that there is a single grid orientation and spacing per grid …
[PDF][PDF] 1Computer Science, Stanford University
R Schaeffer, M Khona, IR Fiete - 2022 - scholar.archive.org
Research in Neuroscience, as in many scientific disciplines, is undergoing a renaissance
based on deep 11 learning. Unique to Neuroscience, deep learning models can be used not …
based on deep 11 learning. Unique to Neuroscience, deep learning models can be used not …
Hippocampal coding of positions of visual objects and prediction of their future interactions
T Dvořáková - 2022 - dspace.cuni.cz
The hippocampus is a crucial brain structure involved in spatial navigation. It contains
populations of spatially sensitive cells as the place cells, head-direction cells, grid cells …
populations of spatially sensitive cells as the place cells, head-direction cells, grid cells …