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Hippocampus

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Dorsoventral and Proximodistal Hippocampal Processing Account for the Influences of Sleep and Context on Memory (Re)consolidation: A Connectionist Model.

Computational intelligence and neuroscience
The context in which learning occurs is sufficient to reconsolidate stored memories and neuronal reactivation may be crucial to memory consolidation during sleep. The mechanisms of context-dependent and sleep-dependent memory (re)consolidation are un...

Feature selective temporal prediction of Alzheimer's disease progression using hippocampus surface morphometry.

Brain and behavior
INTRODUCTION: Prediction of Alzheimer's disease (AD) progression based on baseline measures allows us to understand disease progression and has implications in decisions concerning treatment strategy. To this end, we combine a predictive multi-task m...

Dendritic spine classification using shape and appearance features based on two-photon microscopy.

Journal of neuroscience methods
BACKGROUND: Neuronal morphology and function are highly coupled. In particular, dendritic spine morphology is strongly governed by the incoming neuronal activity. The first step towards understanding the structure-function relationships is to classif...

Cognitive memory and mapping in a brain-like system for robotic navigation.

Neural networks : the official journal of the International Neural Network Society
Electrophysiological studies in animals may provide a great insight into developing brain-like models of spatial cognition for robots. These studies suggest that the spatial ability of animals requires proper functioning of the hippocampus and the en...

Differential diagnosis of mild cognitive impairment and Alzheimer's disease using structural MRI cortical thickness, hippocampal shape, hippocampal texture, and volumetry.

NeuroImage. Clinical
This paper presents a brain T1-weighted structural magnetic resonance imaging (MRI) biomarker that combines several individual MRI biomarkers (cortical thickness measurements, volumetric measurements, hippocampal shape, and hippocampal texture). The ...

Why do some neurons in cortex respond to information in a selective manner? Insights from artificial neural networks.

Cognition
Why do some neurons in hippocampus and cortex respond to information in a highly selective manner? It has been hypothesized that neurons in hippocampus encode information in a highly selective manner in order to support fast learning without catastro...

Machine learning of structural magnetic resonance imaging predicts psychopathic traits in adolescent offenders.

NeuroImage
Classification models are becoming useful tools for finding patterns in neuroimaging data sets that are not observable to the naked eye. Many of these models are applied to discriminating clinical groups such as schizophrenic patients from healthy co...

Goal-oriented robot navigation learning using a multi-scale space representation.

Neural networks : the official journal of the International Neural Network Society
There has been extensive research in recent years on the multi-scale nature of hippocampal place cells and entorhinal grid cells encoding which led to many speculations on their role in spatial cognition. In this paper we focus on the multi-scale nat...

Hippocampome.org: a knowledge base of neuron types in the rodent hippocampus.

eLife
Hippocampome.org is a comprehensive knowledge base of neuron types in the rodent hippocampal formation (dentate gyrus, CA3, CA2, CA1, subiculum, and entorhinal cortex). Although the hippocampal literature is remarkably information-rich, neuron proper...

Machine learning classification of mesial temporal sclerosis in epilepsy patients.

Epilepsy research
BACKGROUND AND PURPOSE: Novel approaches applying machine-learning methods to neuroimaging data seek to develop individualized measures that will aid in the diagnosis and treatment of brain-based disorders such as temporal lobe epilepsy (TLE). Using ...