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Emerging Trends in Neuro Engineering and Neural Computation

  • Book
  • © 2017

Overview

Editors:
  1. Asim Bhatti

    1. Geelong Waurn Ponds Campus, Deakin University, Institute for Intelligent Systems Research and Innovation, 3216 Waurn Ponds, Australia

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  2. Kendall H. Lee

    1. Mayo Clinic, 55905 Rochester, USA

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  3. Hamid Garmestani

    1. Materials Science and Engineering, Georgia Institute of Technology, 30332-0245 Atlanta, USA

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  4. Chee Peng Lim

    1. Geelong Waurn Ponds Campus, Deakin University, Institute for Intelligent Systems Research and Innovation, 3216 Waurn Ponds, Australia

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    You can also search for this editor in PubMed   Google Scholar

  • Outlines the current research and technology trends and future prospects of the emerging multidisciplinary field of neuro-engineering and neural computing
  • Covers diverse topics, ranging from fundamental theoretical aspects and technologies to novel analysis techniques, as well as a variety of applications
  • Written by leading experts in the field
  • Includes supplementary material: sn.pub/extras

Part of the book series: Series in BioEngineering (SERBIOENG)

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Table of contents (15 chapters)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Neuro Engineering

    1. Front Matter

      Pages 1-1
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    2. CMOS-Based High-Density Microelectrode Arrays: Technology and Applications

      • Marie Engelene J. Obien, Wei Gong, Urs Frey, Douglas James Bakkum
      Pages 3-39

    3. Microelectrode Arrays: Architecture, Challenges and Engineering Solutions

      • Dhurgham Khudhair, Saeid Nahavandi, Hamid Garmestani, Asim Bhatti
      Pages 41-59

    4. Revolutionizing Causal Circuitry Neurostimulation Utilizing the Optogenetic Technique Through Advanced Microsystems Development

      • R. P. Kale, S. Paek, S. J. Tye, A. Z. Kouzani
      Pages 61-80

    5. Physiological Monitoring in Deep Brain Stimulation: Toward Closed-Loop Neuromodulation Therapies

      • Seungleal (Brian) Paek, Rajas P. Kale, Katheryn M. Wininger, J. Luis Lujan
      Pages 81-97

    6. Mechanism of Docosahexaenoic Acid in the Enhancement of Neuronal Signalling

      • Md Ahsan Ul Bari, Julie Gaburro, Agnes Michalczyk, M. Leigh Ackland, Catherine Williams, Asim Bhatti
      Pages 99-117

    7. Insects Neural Model: Potential Alternate to Mammals for Electrophysiological Studies

      • Julie Gaburro, Saeid Nahavandi, Asim Bhatti
      Pages 119-130

    8. Synchronization Criteria for Delay Coupled Izhikevich Neurons

      • Imali T. Hettiarachchi, Lakshmanan Shanmugam, Asim Bhatti, Saeid Nahavandi
      Pages 131-144

  3. Neural Computation

    1. Front Matter

      Pages 145-145
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    2. Capturing Cognition via EEG-Based Functional Brain Networks

      • Md. Hedayetul Islam Shovon, D. (Nanda) Nandagopal, Bernadine Cocks, Ramasamy Vijayalakshmi
      Pages 147-172

    3. Modelling of Tumour-Induced Angiogenesis Influenced by Haptotaxis

      • Wei Chen, Li Zhang, Chengyu Liu, Alamgir Hossain
      Pages 173-191

    4. Noise Reduction in ECG Signals Using Wavelet Transform and Dynamic Thresholding

      • Diptangshu Pandit, Li Zhang, Chengyu Liu, Nauman Aslam, Samiran Chattopadhyay, Chee Peng Lim
      Pages 193-206

    5. Development of a Co-evolutionary Radial Basis Function Neural Classifier by a k-Random Opponents Topology

      • Bee Yan Hiew, Shing Chiang Tan, Way Soong Lim
      Pages 207-217

    6. Mining Outliers from Medical Datasets Using Neighbourhood Rough Set and Data Classification with Neural Network

      • Pey Yun Goh, Shing Chiang Tan, Wooi Ping Cheah
      Pages 219-228

    7. A Modified Functional Link Neural Network for Data Classification

      • Toktam Babaei, Chee Peng Lim, Hamid Abdi, Saeid Nahavandi
      Pages 229-244

    8. Experimental Study of Elman Network in Temporal Classification

      • Shih Yin Ooi, Shing Chiang Tan, Wooi Ping Cheah
      Pages 245-254

    9. Monotone Data Samples Do Not Always Generate Monotone Fuzzy If-Then Rules

      • Chin Ying Teh, Kai Meng Tay
      Pages 255-264
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Keywords

About this book

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.

Editors and Affiliations

  • Geelong Waurn Ponds Campus, Deakin University, Institute for Intelligent Systems Research and Innovation, 3216 Waurn Ponds, Australia

    Asim Bhatti, Chee Peng Lim

  • Mayo Clinic, 55905 Rochester, USA

    Kendall H. Lee

  • Materials Science and Engineering, Georgia Institute of Technology, 30332-0245 Atlanta, USA

    Hamid Garmestani

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