ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2014
Coordinated learning of grid cell and place cell spatial and temporal properties: multiple scales, attention and oscillations.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
18 citing papers in PubMed.
- Context-Aware Evidence-Gated Plasticity for Multi-Goal Learning in Spiking Neural Networks.Research square · 2026Article
- Context-Aware Evidence-Gated Plasticity for Multi-Goal Learning in Spiking Neural Networks.bioRxiv : the preprint server for biology · 2026Article
- Neural network models of autonomous adaptive intelligence and artificial general intelligence: how our brains learn large language models and their meanings.Frontiers in systems neuroscience · 2025Article
- Neuromodulation of the anterior thalamus: Current approaches and opportunities for the future.Current research in neurobiology · 2023Review
- A Neural Model of Intrinsic and Extrinsic Hippocampal Theta Rhythms: Anatomy, Neurophysiology, and Function.Frontiers in systems neuroscience · 2021Review
- Identifying Core Regions for Path Integration on Medial Entorhinal Cortex of Hippocampal Formation.Brain sciences · 2020Review
- A Path Toward Explainable AI and Autonomous Adaptive Intelligence: Deep Learning, Adaptive Resonance, and Models of Perception, Emotion, and Action.Frontiers in neurorobotics · 2020Review
- Developmental Designs and Adult Functions of Cortical Maps in Multiple Modalities: Perception, Attention, Navigation, Numbers, Streaming, Speech, and Cognition.Frontiers in neuroinformatics · 2020Review
- The resonant brain: How attentive conscious seeing regulates action sequences that interact with attentive cognitive learning, recognition, and prediction.Attention, perception & psychophysics · 2019Article
- Backtracking during navigation is correlated with enhanced anterior cingulate activity and suppression of alpha oscillations and the 'default-mode' network.Proceedings. Biological sciences · 2019Article
- The Embodied Brain of SOVEREIGN2: From Space-Variant Conscious Percepts During Visual Search and Navigation to Learning Invariant Object Categories and Cognitive-Emotional Plans for Acquiring Valued Goals.Frontiers in computational neuroscience · 2019Review
- A neural model of normal and abnormal learning and memory consolidation: adaptively timed conditioning, hippocampus, amnesia, neurotrophins, and consciousness.Cognitive, affective & behavioral neuroscience · 2017Article
- Acetylcholine Neuromodulation in Normal and Abnormal Learning and Memory: Vigilance Control in Waking, Sleep, Autism, Amnesia and Alzheimer's Disease.Frontiers in neural circuits · 2017Review
- The Preferred Directions of Conjunctive Grid X Head Direction Cells in the Medial Entorhinal Cortex Are Periodically Organized.PloS one · 2016Article
- Models of Innate Neural Attractors and Their Applications for Neural Information Processing.Frontiers in systems neuroscience · 2015Article
- Space in the brain: how the hippocampal formation supports spatial cognition.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2014Review
- Real-time learning of predictive recognition categories that chunk sequences of items stored in working memory.Frontiers in psychology · 2014Article
- How does the modular organization of entorhinal grid cells develop?Frontiers in human neuroscience · 2014Article
Corrections and comments
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2 authors.
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Abstract
A neural model proposes how entorhinal grid cells and hippocampal place cells may develop as spatial categories in a hierarchy of self-organizing maps (SOMs). The model responds to realistic rat navigational trajectories by learning both grid cells with hexagonal grid firing fields of multiple spatial scales, and place cells with one or more firing fields, that match neurophysiological data about their development in juvenile rats. Both grid and place cells can develop by detecting, learning and remembering the most frequent and energetic co-occurrences of their inputs. The model's parsimonious properties include: similar ring attractor mechanisms process linear and angular path integration inputs that drive map learning; the same SOM mechanisms can learn grid cell and place cell receptive fields; and the learning of the dorsoventral organization of multiple spatial scale modules through medial entorhinal cortex to hippocampus (HC) may use mechanisms homologous to those for temporal learning through lateral entorhinal cortex to HC ('neural relativity'). The model clarifies how top-down HC-to-entorhinal attentional mechanisms may stabilize map learning, simulates how hippocampal inactivation may disrupt grid cells, and explains data about theta, beta and gamma oscillations. The article also compares the three main types of grid cell models in the light of recent data.
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