AIMC Topic: Hippocampus

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Hippocampus Segmentation Based on Iterative Local Linear Mapping With Representative and Local Structure-Preserved Feature Embedding.

IEEE transactions on medical imaging
Hippocampus segmentation plays a significant role in mental disease diagnoses, such as Alzheimer's disease, epilepsy, and so on. Patch-based multi-atlas segmentation (PBMAS) approach is a popular method for hippocampus segmentation and has achieved a...

Unsupervised and real-time spike sorting chip for neural signal processing in hippocampal prosthesis.

Journal of neuroscience methods
BACKGROUND: Damage to the hippocampus will result in the loss of ability to form new long-term memories and cognitive disorders. At present, there is no effective medical treatment for this issue. Hippocampal cognitive prosthesis is proposed to repla...

Bio-inspired visual self-localization in real world scenarios using Slow Feature Analysis.

PloS one
We present a biologically motivated model for visual self-localization which extracts a spatial representation of the environment directly from high dimensional image data by employing a single unsupervised learning rule. The resulting representation...

Estimation of neural connections from partially observed neural spikes.

Neural networks : the official journal of the International Neural Network Society
Plasticity is one of the most important properties of the nervous system, which enables animals to adjust their behavior to the ever-changing external environment. Changes in synaptic efficacy between neurons constitute one of the major mechanisms of...

Transfer Learning for Image Segmentation by Combining Image Weighting and Kernel Learning.

IEEE transactions on medical imaging
Many medical image segmentation methods are based on the supervised classification of voxels. Such methods generally perform well when provided with a training set that is representative of the test images to the segment. However, problems may arise ...

A memristive plasticity model of voltage-based STDP suitable for recurrent bidirectional neural networks in the hippocampus.

Scientific reports
Memristive systems have gained considerable attention in the field of neuromorphic engineering, because they allow the emulation of synaptic functionality in solid state nano-physical systems. In this study, we show that memristive behavior provides ...

Sum Rate of MISO Neuro-Spike Communication Channel With Constant Spiking Threshold.

IEEE transactions on nanobioscience
Communication among neurons, known as neuro-spike communication, is the most promising technique for realization of a bio-inspired nanoscale communication paradigm to achieve biocompatible nanonetworks. In neuro-spike communication, the information, ...

Effect of dilution in asymmetric recurrent neural networks.

Neural networks : the official journal of the International Neural Network Society
We study with numerical simulation the possible limit behaviors of synchronous discrete-time deterministic recurrent neural networks composed of N binary neurons as a function of a network's level of dilution and asymmetry. The network dilution measu...

A unified hierarchical oscillatory network model of head direction cells, spatially periodic cells, and place cells.

The European journal of neuroscience
Spatial cells in the hippocampal complex play a pivotal role in the navigation of an animal. Exact neural principles behind these spatial cell responses have not been completely unraveled yet. Here we present two models for spatial cells, namely the ...