AI Medical Compendium Topic:
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Biophysically interpretable recurrent neural network for functional magnetic resonance imaging analysis and sparsity based causal architecture discovery.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Recent efforts use state-of-the-art Recurrent Neural Networks (RNN) to gain insight into neuroscience. A limitation of these works is that the used generic RNNs lack biophysical meaning, making the interpretation of the results in a neuroscience cont...

[Review of the research of spiking neuron network based on memristor].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
The rapid development of artificial intelligence put forward higher requirements for the computational speed, resource consumption and the biological interpretation of computational neuroscience. Spiking neuron networks can carry a large amount of in...

Correlations between synapses in pairs of neurons slow down dynamics in randomly connected neural networks.

Physical review. E
Networks of randomly connected neurons are among the most popular models in theoretical neuroscience. The connectivity between neurons in the cortex is however not fully random, the simplest and most prominent deviation from randomness found in exper...

A Real-Time Reconfigurable Multichip Architecture for Large-Scale Biophysically Accurate Neuron Simulation.

IEEE transactions on biomedical circuits and systems
Simulation of brain neurons in real-time using biophysically meaningful models is a prerequisite for comprehensive understanding of how neurons process information and communicate with each other, in effect efficiently complementing in-vivo experimen...

An Extreme Learning Machine-Based Neuromorphic Tactile Sensing System for Texture Recognition.

IEEE transactions on biomedical circuits and systems
Despite significant advances in computational algorithms and development of tactile sensors, artificial tactile sensing is strikingly less efficient and capable than the human tactile perception. Inspired by efficiency of biological systems, we aim t...

Skeleton-Based Human Action Recognition With Global Context-Aware Attention LSTM Networks.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Human action recognition in 3D skeleton sequences has attracted a lot of research attention. Recently, long short-term memory (LSTM) networks have shown promising performance in this task due to their strengths in modeling the dependencies and dynami...

Distributed representations of action sequences in anterior cingulate cortex: A recurrent neural network approach.

Psychonomic bulletin & review
Anterior cingulate cortex (ACC) has been the subject of intense debate over the past 2 decades, but its specific computational function remains controversial. Here we present a simple computational model of ACC that incorporates distributed represent...

Speech emotion recognition based on brain and mind emotional learning model.

Journal of integrative neuroscience
Speech emotion recognition is a challenging obstacle to enabling communication between humans and machines. The present study introduces a new model of speech emotion recognition based on the relationship between the human brain and mind. According t...

Relative wave energy-based adaptive neuro-fuzzy inference system for estimation of the depth of anaesthesia.

Journal of integrative neuroscience
The advancement in medical research and intelligent modeling techniques has lead to the developments in anaesthesia management. The present study is targeted to estimate the depth of anaesthesia using cognitive signal processing and intelligent model...