Hippocampus
51 papers with code • 0 benchmarks • 0 datasets
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Latest papers with no code
Measuring Feature Dependency of Neural Networks by Collapsing Feature Dimensions in the Data Manifold
Our method is based on the principle that if a model is dependent on a feature, then removal of that feature should significantly harm its performance.
A Coupled Neural Field Model for the Standard Consolidation Theory
At longer times, perturbation of the hippocampal neural fields by neurogenesis erases the hippocampus pattern, leading to a final state where the memory pattern is exclusively evoked in the neocortex.
Positioning is All You Need
One can drive safely with a GPS without memorizing a world map (not to mention the dark regions that humans have never explored).
Altered patterning of neural activity in a tauopathy mouse model
Alzheimer's disease (AD) is a complex neurodegenerative condition that manifests at multiple levels and involves a spectrum of abnormalities ranging from the cellular to cognitive.
ComS2T: A complementary spatiotemporal learning system for data-adaptive model evolution
Motivated by complementary learning in neuroscience, we introduce a prompt-based complementary spatiotemporal learning termed ComS2T, to empower the evolution of models for data adaptation.
Analyzing Regional Organization of the Human Hippocampus in 3D-PLI Using Contrastive Learning and Geometric Unfolding
Understanding the cortical organization of the human brain requires interpretable descriptors for distinct structural and functional imaging data.
Semantic segmentation for recognition of epileptiform patterns recorded via Microelectrode Arrays in vitro
To address this challenge, we here present two lightweight algorithms, the ZdensityRODE and the AMPDE, for identifying relevant events from LFPs by utilizing semantic segmentation, which involves extracting different levels of information from the LFP and relevant events from it.
Brain-Like Replay Naturally Emerges in Reinforcement Learning Agents
Can replay, as a widely observed neural activity pattern in brain regions, particularly in the hippocampus and neocortex, emerge in an artificial agent?
BrainSLAM: SLAM on Neural Population Activity Data
This system uses a convolutional neural network (CNN) to decode velocity and familiarity information from wavelet scalograms of neural local field potential data recorded from rats as they navigate a 2D maze.
Manifold GCN: Diffusion-based Convolutional Neural Network for Manifold-valued Graphs
We propose two graph neural network layers for graphs with features in a Riemannian manifold.
