AIMC Topic: Hippocampus
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A neural network model for online one-shot storage of pattern sequences.
PloS one
Jun 20, 2024
Based on the CRISP theory (Content Representation, Intrinsic Sequences, and Pattern completion), we present a computational model of the hippocampus that allows for online one-shot storage of pattern sequences without the need for a consolidation pro...
Contrastive Learning vs. Self-Learning vs. Deformable Data Augmentation in Semantic Segmentation of Medical Images.
Journal of imaging informatics in medicine
Jun 10, 2024
To develop a robust segmentation model, encoding the underlying features/structures of the input data is essential to discriminate the target structure from the background. To enrich the extracted feature maps, contrastive learning and self-learning ...
A recurrent network model of planning explains hippocampal replay and human behavior.
Nature neuroscience
Jun 7, 2024
When faced with a novel situation, people often spend substantial periods of time contemplating possible futures. For such planning to be rational, the benefits to behavior must compensate for the time spent thinking. Here, we capture these features ...
PyHFO: lightweight deep learning-powered end-to-end high-frequency oscillations analysis application.
Journal of neural engineering
May 28, 2024
. This study aims to develop and validate an end-to-end software platform, PyHFO, that streamlines the application of deep learning (DL) methodologies in detecting neurophysiological biomarkers for epileptogenic zones from EEG recordings.. We introdu...
Geodesic shape regression based deep learning segmentation for assessing longitudinal hippocampal atrophy in dementia progression.
NeuroImage. Clinical
May 26, 2024
Longitudinal hippocampal atrophy is commonly used as progressive marker assisting clinical diagnose of dementia. However, precise quantification of the atrophy is limited by longitudinal segmentation errors resulting from MRI artifacts across multipl...
Comparative assessment of established and deep learning-based segmentation methods for hippocampal volume estimation in brain magnetic resonance imaging analysis.
NMR in biomedicine
May 7, 2024
In this study, our objective was to assess the performance of two deep learning-based hippocampal segmentation methods, SynthSeg and TigerBx, which are readily available to the public. We contrasted their performance with that of two established tech...
Minicolumn-Based Episodic Memory Model With Spiking Neurons, Dendrites and Delays.
IEEE transactions on neural networks and learning systems
May 2, 2024
Episodic memory is fundamental to the brain's cognitive function, but how neuronal activity is temporally organized during its encoding and retrieval is still unknown. In this article, combining hippocampus structure with a spiking neural network (SN...
Uncovering Predictors of Low Hippocampal Volume: Evidence from a Large-Scale Machine-Learning-Based Study in the UK Biobank.
Neuroepidemiology
Apr 1, 2024
INTRODUCTION: Hippocampal atrophy is an established biomarker for conversion from the normal ageing process to developing cognitive impairment and dementia. This study used a novel hypothesis-free machine-learning approach, to uncover potential risk ...
Deep learning-based, fully automated, pediatric brain segmentation.
Scientific reports
Feb 22, 2024
The purpose of this study was to demonstrate the performance of a fully automated, deep learning-based brain segmentation (DLS) method in healthy controls and in patients with neurodevelopmental disorders, SCN1A mutation, under eleven. The whole, cor...
High-resolution CMOS-based biosensor for assessing hippocampal circuit dynamics in experience-dependent plasticity.
Biosensors & bioelectronics
Jun 12, 2023
Experiential richness creates tissue-level changes and synaptic plasticity as patterns emerge from rhythmic spatiotemporal activity of large interconnected neuronal assemblies. Despite numerous experimental and computational approaches at different s...
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