AIMC Topic: Entorhinal Cortex
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Enhanced role of the entorhinal cortex in adapting to increased working memory load.
Nature communications
Jul 1, 2025
In daily life, we frequently encounter varying demands on working memory (WM), yet how the brain adapts to high WM load remains unclear. To address this question, we recorded intracranial EEG from hippocampus, entorhinal cortex (EC), and lateral temp...
Deep Learning-Emerged Grid Cells-Based Bio-Inspired Navigation in Robotics.
Sensors (Basel, Switzerland)
Mar 4, 2025
Grid cells in the brain's entorhinal cortex are essential for spatial navigation and have inspired advancements in robotic navigation systems. This paper first provides an overview of recent research on grid cell-based navigation in robotics, focusin...
Determinantal point process attention over grid cell code supports out of distribution generalization.
eLife
Aug 1, 2024
Deep neural networks have made tremendous gains in emulating human-like intelligence, and have been used increasingly as ways of understanding how the brain may solve the complex computational problems on which this relies. However, these still fall ...
An Optimized Deep Learning Model for Predicting Mild Cognitive Impairment Using Structural MRI.
Sensors (Basel, Switzerland)
Jun 16, 2023
Early diagnosis of mild cognitive impairment (MCI) with magnetic resonance imaging (MRI) has been shown to positively affect patients' lives. To save time and costs associated with clinical investigation, deep learning approaches have been used widel...
Normalized unitary synaptic signaling of the hippocampus and entorhinal cortex predicted by deep learning of experimental recordings.
Communications biology
May 5, 2022
Biologically realistic computer simulations of neuronal circuits require systematic data-driven modeling of neuron type-specific synaptic activity. However, limited experimental yield, heterogeneous recordings conditions, and ambiguous neuronal ident...
Hippocampal formation-inspired probabilistic generative model.
Neural networks : the official journal of the International Neural Network Society
Apr 8, 2022
In building artificial intelligence (AI) agents, referring to how brains function in real environments can accelerate development by reducing the design space. In this study, we propose a probabilistic generative model (PGM) for navigation in uncerta...
Flexible modulation of sequence generation in the entorhinal-hippocampal system.
Nature neuroscience
Apr 12, 2021
Exploration, consolidation and planning depend on the generation of sequential state representations. However, these algorithms require disparate forms of sampling dynamics for optimal performance. We theorize how the brain should adapt internally ge...
Biomimetic FPGA-based spatial navigation model with grid cells and place cells.
Neural networks : the official journal of the International Neural Network Society
Feb 13, 2021
The mammalian spatial navigation system is characterized by an initial divergence of internal representations, with disparate classes of neurons responding to distinct features including location, speed, borders and head direction; an ensuing converg...
Introduction to part two of the special issue on computational models of hippocampus and related structures.
Hippocampus
Nov 13, 2020
Extensive computational modeling has focused on the hippocampal formation and related cortical structures. This introduction describes the topics addressed by individual articles in part two of this special issue of the journal Hippocampus on the top...
Recurrent amplification of grid-cell activity.
Hippocampus
Oct 6, 2020
High-level cognitive abilities such as navigation and spatial memory are thought to rely on the activity of grid cells in the medial entorhinal cortex (MEC), which encode the animal's position in space with periodic triangular patterns. Yet the neura...
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