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Hippocampus

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A complementary learning systems approach to temporal difference learning.

Neural networks : the official journal of the International Neural Network Society
Complementary Learning Systems (CLS) theory suggests that the brain uses a 'neocortical' and a 'hippocampal' learning system to achieve complex behaviour. These two systems are complementary in that the 'neocortical' system relies on slow learning of...

Hippocampal segmentation for brains with extensive atrophy using three-dimensional convolutional neural networks.

Human brain mapping
Hippocampal volumetry is a critical biomarker of aging and dementia, and it is widely used as a predictor of cognitive performance; however, automated hippocampal segmentation methods are limited because the algorithms are (a) not publicly available,...

Molecular expression profiles of morphologically defined hippocampal neuron types: Empirical evidence and relational inferences.

Hippocampus
Gene and protein expressions are key determinants of cellular function. Neurons are the building blocks of brain circuits, yet the relationship between their molecular identity and the spatial distribution of their dendritic inputs and axonal outputs...

Quantifying brain metabolism from FDG-PET images into a probability of Alzheimer's dementia score.

Human brain mapping
F-fluorodeoxyglucose positron emission tomography (FDG-PET) enables in-vivo capture of the topographic metabolism patterns in the brain. These images have shown great promise in revealing the altered metabolism patterns in Alzheimer's disease (AD). ...

Modeling place cells and grid cells in multi-compartment environments: Entorhinal-hippocampal loop as a multisensory integration circuit.

Neural networks : the official journal of the International Neural Network Society
Hippocampal place cells and entorhinal grid cells are thought to form a representation of space by integrating internal and external sensory cues. Experimental data show that different subsets of place cells are controlled by vision, self-motion or a...

Bursts with High and Low Load of Epileptiform Spikes Show Context-Dependent Correlations in Epileptic Mice.

eNeuro
Hypersynchronous network activity is the defining hallmark of epilepsy and manifests in a wide spectrum of phenomena, of which electrographic activity during seizures is only one extreme. The aim of this study was to differentiate between different t...

A comprehensive knowledge base of synaptic electrophysiology in the rodent hippocampal formation.

Hippocampus
The cellular and synaptic architecture of the rodent hippocampus has been described in thousands of peer-reviewed publications. However, no human- or machine-readable public catalog of synaptic electrophysiology data exists for this or any other neur...

Characterization of Nanoscale Organization of F-Actin in Morphologically Distinct Dendritic Spines Using Supervised Learning.

eNeuro
The cytoarchitecture of a neuron is very important in defining morphology and ultrastructure. Although there is a wealth of information on the molecular components that make and regulate these ultrastructures, there is a dearth of understanding of ho...

A Machine Learning Approach to Characterize the Modulation of the Hippocampal Rhythms Via Optogenetic Stimulation of the Medial Septum.

International journal of neural systems
The medial septum (MS) is a potential target for modulating hippocampal activity. However, given the multiple cell types involved, the changes in hippocampal neural activity induced by MS stimulation have not yet been fully characterized. We combined...

A deep learning model for early prediction of Alzheimer's disease dementia based on hippocampal magnetic resonance imaging data.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: It is challenging at baseline to predict when and which individuals who meet criteria for mild cognitive impairment (MCI) will ultimately progress to Alzheimer's disease (AD) dementia.