Bhatti A., Lee K.H., Garmestani H., Lim C.P. (eds.) Emerging Trends in Neuro Engineering and Neural Computation

Singapore: Springer, 2017. - 267 p.This book focuses on neuro-engineering and neural computing, a multi-disciplinary field of research attracting considerable attention from engineers, neuroscientists, microbiologists and material scientists. It explores a range of topics concerning the design and development of innovative neural and brain interfacing technologies, as well as novel information acquisition and processing algorithms to make sense of the acquired data. The book also highlights emerging trends and advances regarding the applications of neuro-engineering in real-world scenarios, such as neural prostheses, diagnosis of neural degenerative diseases, deep brain stimulation, biosensors, real neural network-inspired artificial neural networks (ANNs) and the predictive modeling of information flows in neuronal networks. The book is broadly divided into three main sections including: current trends in technological developments, neural computation techniques to make sense of the neural behavioral data, and application of these technologies/techniques in the medical domain in the treatment of neural disorders.CMOS-Based High-Density Microelectrode Arrays: Technology and Applications
Microelectrode Arrays: Architecture, Challenges and Engineering Solutions
Revolutionizing Causal Circuitry Neurostimulation Utilizing the Optogenetic Technique Through Advanced Microsystems Development
Physiological Monitoring in Deep Brain Stimulation: Toward Closed-Loop Neuromodulation Therapies
Mechanism of Docosahexaenoic Acid in the Enhancement of Neuronal Signalling
Insects Neural Model: Potential Alternate to Mammals for Electrophysiological Studies
Synchronization Criteria for Delay Coupled Izhikevich NeuronsCapturing Cognition via EEG-Based Functional Brain Networks
Modelling of Tumour-Induced Angiogenesis Influenced by Haptotaxis
Noise Reduction in ECG Signals Using Wavelet Transform and Dynamic Thresholding
Development of a Co-evolutionary Radial Basis Function Neural Classifier by a k-Random Opponents Topology
Mining Outliers from Medical Datasets Using Neighbourhood Rough Set and Data Classification with Neural Network
A Modified Functional Link Neural Network for Data Classification
Experimental Study of Elman Network in Temporal Classification
Monotone Data Samples Do Not Always Generate Monotone Fuzzy If-Then Rules