Hippocampus
51 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Hippocampus
Most implemented papers
Latent dynamical variables produce signatures of spatiotemporal criticality in large biological systems
Understanding the activity of large populations of neurons is difficult due to the combinatorial complexity of possible cell-cell interactions.
Point process models for sequence detection in high-dimensional neural spike trains
Sparse sequences of neural spikes are posited to underlie aspects of working memory, motor production, and learning.
A biologically plausible neural network for Slow Feature Analysis
Furthermore, when trained on naturalistic stimuli, SFA reproduces interesting properties of cells in the primary visual cortex and hippocampus, suggesting that the brain uses temporal slowness as a computational principle for learning latent features.
Learning identifiable and interpretable latent models of high-dimensional neural activity using pi-VAE
Specifically, we propose to construct latent variable models of neural activity while simultaneously modeling the relation between the latent and task variables (non-neural variables, e. g. sensory, motor, and other externally observable states).
Stable deep neural network architectures for mitochondria segmentation on electron microscopy volumes
danifranco/BiaPy
•
•
For that reason, and following a recent code of best practices for reporting experimental results, we present an extensive study of the state-of-the-art deep learning architectures for the segmentation of mitochondria on EM volumes, and evaluate the impact in performance of different variations of 2D and 3D U-Net-like models for this task.
Complementary Structure-Learning Neural Networks for Relational Reasoning
The neural mechanisms supporting flexible relational inferences, especially in novel situations, are a major focus of current research.
DualNet: Continual Learning, Fast and Slow
phquang/DualNet
•
•
NeurIPS 2021
According to Complementary Learning Systems (CLS) theory~\citep{mcclelland1995there} in neuroscience, humans do effective \emph{continual learning} through two complementary systems: a fast learning system centered on the hippocampus for rapid learning of the specifics and individual experiences, and a slow learning system located in the neocortex for the gradual acquisition of structured knowledge about the environment.
Can the brain use waves to solve planning problems?
A variety of behaviors like spatial navigation or bodily motion can be formulated as graph traversal problems through cognitive maps.
Multimodal neural networks better explain multivoxel patterns in the hippocampus
The human hippocampus possesses "concept cells", neurons that fire when presented with stimuli belonging to a specific concept, regardless of the modality.
ROOD-MRI: Benchmarking the robustness of deep learning segmentation models to out-of-distribution and corrupted data in MRI
To address these limitations, we propose ROOD-MRI: a platform for benchmarking the Robustness of DNNs to Out-Of-Distribution (OOD) data, corruptions, and artifacts in MRI.
