AIMC Topic: Brain

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3D Deep Learning for Multi-modal Imaging-Guided Survival Time Prediction of Brain Tumor Patients.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
High-grade glioma is the most aggressive and severe brain tumor that leads to death of almost 50% patients in 1-2 years. Thus, accurate prognosis for glioma patients would provide essential guidelines for their treatment planning. Conventional surviv...

Early Diagnosis of Alzheimer's Disease by Joint Feature Selection and Classification on Temporally Structured Support Vector Machine.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
The diagnosis of Alzheimer's disease (AD) from neuroimaging data at the pre-clinical stage has been intensively investigated because of the immense social and economic cost. In the past decade, computational approaches on longitudinal image sequences...

Developmental metaplasticity in neural circuit codes of firing and structure.

Neural networks : the official journal of the International Neural Network Society
Firing-rate dynamics have been hypothesized to mediate inter-neural information transfer in the brain. While the Hebbian paradigm, relating learning and memory to firing activity, has put synaptic efficacy variation at the center of cortical plastici...

BrainNetCNN: Convolutional neural networks for brain networks; towards predicting neurodevelopment.

NeuroImage
We propose BrainNetCNN, a convolutional neural network (CNN) framework to predict clinical neurodevelopmental outcomes from brain networks. In contrast to the spatially local convolutions done in traditional image-based CNNs, our BrainNetCNN is compo...

Bioinspired decision architectures containing host and microbiome processing units.

Bioinspiration & biomimetics
Biomimetic robots have been used to explore and explain natural phenomena ranging from the coordination of ants to the locomotion of lizards. Here, we developed a series of decision architectures inspired by the information exchange between a host or...

A Realistic Seizure Prediction Study Based on Multiclass SVM.

International journal of neural systems
A patient-specific algorithm, for epileptic seizure prediction, based on multiclass support-vector machines (SVM) and using multi-channel high-dimensional feature sets, is presented. The feature sets, combined with multiclass classification and post-...

A Possible Neural Representation of Mathematical Group Structures.

Bulletin of mathematical biology
Every cognitive activity has a neural representation in the brain. When humans deal with abstract mathematical structures, for instance finite groups, certain patterns of activity are occurring in the brain that constitute their neural representation...

Brief isoflurane anaesthesia affects differential gene expression, gene ontology and gene networks in rat brain.

Behavioural brain research
Much is still unknown about the mechanisms of effects of even brief anaesthesia on the brain and previous studies have simply compared differential expression profiles with and without anaesthesia. We hypothesised that network analysis, in addition t...

Maze learning by a hybrid brain-computer system.

Scientific reports
The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the co...

Driving reservoir models with oscillations: a solution to the extreme structural sensitivity of chaotic networks.

Journal of computational neuroscience
A large body of experimental and theoretical work on neural coding suggests that the information stored in brain circuits is represented by time-varying patterns of neural activity. Reservoir computing, where the activity of a recurrently connected p...