ArticleCell reports2022
Excitatory-inhibitory recurrent dynamics produce robust visual grids and stable attractors.
Article in Cell reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 10 citations in OpenAlex.
- Artificial intelligence as a surrogate brain: bridging neural dynamical models and data.National science review · 2026Review
- Mediodorsal thalamus regulates task uncertainty to enable cognitive flexibility.Nature communications · 2025Article
- Training biologically plausible recurrent neural networks on cognitive tasks with long-term dependencies.bioRxiv : the preprint server for biology · 2023Article
- Are Grid-Like Representations a Component of All Perception and Cognition?Frontiers in neural circuits · 2022Article
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Authors and funding
4 authors at 2 institutions in 2 countries.
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Abstract
Spatially modulated grid cells have been recently found in the rat secondary visual cortex (V2) during active navigation. However, the computational mechanism and functional significance of V2 grid cells remain unknown. To address the knowledge gap, we train a biologically inspired excitatory-inhibitory recurrent neural network to perform a two-dimensional spatial navigation task with multisensory input. We find grid-like responses in both excitatory and inhibitory RNN units, which are robust with respect to spatial cues, dimensionality of visual input, and activation function. Population responses reveal a low-dimensional, torus-like manifold and attractor. We find a link between functional grid clusters with similar receptive fields and structured excitatory-to-excitatory connections. Additionally, multistable torus-like attractors emerged with increasing sparsity in inter- and intra-subnetwork connectivity. Finally, irregular grid patterns are found in recurrent neural network (RNN) units during a visual sequence recognition task. Together, our results suggest common computational mechanisms of V2 grid cells for spatial and non-spatial tasks.
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