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Role of Hippocampus in Memory

Role of Hippocampus in Memory

The hippocampus, a critical brain structure, plays an essential role in memory processing, particularly in the formation and retrieval of memory. This small, seahorse-shaped region is located within the medial temporal lobe, with one hippocampus in each brain hemisphere. Experimental studies involving lesions in the hippocampi of rats have demonstrated significant impairments in tasks such as object recognition and maze navigation, indicating the hippocampus involvement in both recognition and...

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Related Experiment Video

Updated: Feb 22, 2026

High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging

High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging

Published on: November 10, 2015

HIPS: A new hippocampus subfield segmentation method.

José E Romero¹, Pierrick Coupé², José V Manjón¹

¹Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain.

|September 30, 2017

Summary

This summary is machine-generated.

This study introduces an automated method for segmenting hippocampus subfields, crucial for neuroimaging research in diseases like Alzheimer's. The novel pipeline improves accuracy and speed for both high and standard resolution magnetic resonance data.

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Last Updated: Feb 22, 2026

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Published on: November 10, 2015

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Area of Science:

Neuroimaging
Neuroscience
Medical Image Analysis

Background:

The hippocampus is vital for studying neurodegenerative diseases like Alzheimer's.
Accurate segmentation of hippocampus subfields is challenging due to structural complexity and limited high-resolution MRI data.
Existing segmentation methods are insufficient for detailed hippocampus subfield analysis.

Purpose of the Study:

To develop an automated pipeline for hippocampus subfield segmentation.
To enable accurate analysis using both high and standard resolution magnetic resonance (MR) data.
To improve upon current state-of-the-art segmentation techniques.

Main Methods:

A novel multi-atlas label fusion approach utilizing multi-contrast patch matching (T1w and T2w images).
Integration of two established hippocampus subfield delineation protocols.
A neural network-based error correction step for post-processing segmentation results.

Main Results:

The proposed method demonstrates high accuracy in hippocampus subfield segmentation.
The pipeline is effective for both high and standard resolution MR images.
Achieved superior accuracy and reduced execution time compared to existing methods.

Conclusions:

The developed pipeline offers an accurate and efficient solution for automatic hippocampus subfield segmentation.
This method advances neuroimaging capabilities for studying hippocampus-related neurological disorders.
The approach is versatile, applicable to various MR data resolutions.