Computational Techniques in Neuroscience

The text discusses the techniques of deep learning and machine learning in the field of neuroscience, engineering approaches to study the brain structure and dynamics, convolutional networks for fast, energy-efficient neuromorphic computing, and reinforcement learning in feedback control. It showcases case studies in neural data analysis. Features: - Focuses on neuron modeling, development, and direction of neural circuits to explain perception, behavior, and biologically inspired intelligent agents for decision making - Showcases important aspects such as human behavior prediction using smart technologies and understanding the modeling of nervous systems - Discusses nature-inspired algorithms such as swarm intelligence, ant colony optimization, and multi-agent systems - Presents information-theoretic, control-theoretic, and decision-theoretic approaches in neuroscience. Includes case studies in functional magnetic resonance imaging (fMRI) and neural data analysis This reference text addresses different applications of computational neuro-sciences using arti-cial intelligence, deep learning, and other machine learning techniques to -ne-tune the models, thereby solving the real-life problems prominently. It will further discuss important topics such as neural rehabili-tation, brain-computer interfacing, neural control, neural system analysis, and neurobiologically inspired self-monitoring systems. It will serve as an ideal reference text for graduate students and academic researchers in the -elds of electrical engineering, electronics and communication engineering, computer engineering, information technology, and biomedical engineering.

Dr. Kamal Malik is currently working as a Professor in CSE in the School of Engineering and Technology at CTU Ludhiana, Punjab, India. She has published Scientific Research Publications in reputed International Journals, including SCI and Scopus indexed Journals such as Adhoc and senior Wireless Networks, 50, Engineering, Technology and Applied Sciences Research, Journals of Advanced Research in Engineering, Research Journal of Applied Sciences of Engineering & Technology(RJASET- Maxwell Sciences), SSRN-Electronic Journal, Design Engineering, Indian Journal of Science and Technology(IJST), International Journal of Computer Applications(IJCA), and many more. She has also attended many National and International Conferences of repute like Springer, and Elsevier in India. Her major research areas are Artificial Intelligence, Machine Learning and Deep Learning, Data Analytics, Computational Neurosciences, and bio-inspired computing. She has more than 13 years of rich Academic and Research experience. She has guided 3 research scholars and currently guiding 8 research Scholars at CT University, Ludhiana. She has worked in renowned Institutes and Universities like RIMT Mandigobindgarh, Maharishi Markandeshwar University, Mullana, GNA University, Phagwara. She has also chaired various sessions in Springer and Elsevier. She has also been awarded with the preeminent researcher award from Green Thinkerz society at CII, Chandigarh. She has completed her Doctorate of Philosophy in Computer Science from IKGPTU Kapurthala in 2017, her Masters and Graduation from Kurukshetra University, Kurukshetra in 2009 and 2006 respectively. Dr. Harsh Sadawarti is currently working as Vice Chancellor of CT University and Professor of Computer Science and Engineering in School of Engineering and Technology at CTU Ludhiana, Punjab India. He has published Scientific research Publications in reputed International Journals including SCI indexed and Scopus indexed Journals such as Journal of Intelligent and Fuzzy Systems , Journal of Applied Sciences, International Journal of Scientific and Technology research(IJSTR), International Journal of Advanced Research in Engineering and Technology(IJARET), International Journal of light and electron optics(Optik Elesevier Journal). International Journal of Computer Science and Communication Engineering(IJCSCE), International Journal of Advanced Research in Computer science and Software Engineering, Maxwell's Sciences and many more. Apart from it, he has attended many National, International Conferences and IEEE conferences of repute like Springer, Elsevier in India as well as abroad. He has visited more than 20 countries in his academic career for presenting his scientific research. His major areas of Research are Machine Learning, Artificial Intelligence, Deep learning, Parallel processing, Computational Neurosciences, Bio-inspired Computing, Security in cloud computing. He is having more than 28 years of Teaching, Academic and Research experience in various reputed Engineering Institutions named as RIMT Mandigobindgarh, Baba Banda Singh Bahadur Institute of Engg and Technology. He has also chaired various International Conferences of Springer, Elsevier. He has guided 12 Ph.D Schorals and currently guiding 8 Research Scholars. He has also been awarded as a Punjab Ratan (Punjab State Intellectuals honor) by All India Conference of Intellectuals at India International Centre New Delhi on 26th of December, 2010. He is also an eminent reviewer of many reputed Journals like Elsevier, Springer etc,. He has also been awarded as the best Young Vice Chancellor award from IARE i.e,. (International Academic and Research Excellence Awards). He has done his Doctor of Philosophy (Ph.D.) in Computer Science and Engineering and M.Tech (CSE) from Thapar University and his B.Tech(CSE) from Nagpur University in year 1999. Mr. Moolchand Sharma is currently an Assistant Professor in the Department of Computer Science and Engineering at the Maharaja Agrasen Institute of Technology, GGSIPU Delhi. He has published scientific research publications in reputed international journals and conferences, including SCI-indexed and Scopus-indexed journals such as Expert Systems (Wiley), Cognitive Systems Research (Elsevier), Physical Communication(Elsevier), Journal of Electronic Imaging (SPIE ), Intelligent Decision Technologies: An International Journal, Cyber-Physical Systems (Taylor & Francis Group), International Journal of Image & Graphics (World Scientific), International Journal of Innovative Computing and Applications (Inderscience) and Innovative Computing and Communication Journal (Scientific Peer-reviewed Journal). He has authored/co-authored chapters with International publishers like Elsevier, Wiley, and De Gruyter. He has authored/edited four books with a National/International level publisher (CRC Press, Bhavya publications). His research areas include Artificial Intelligence, Nature-Inspired Computing, Security in Cloud Computing, Machine Learning, and Search Engine Optimization. He is associated with various professional bodies like IEEE, ISTE, IAENG, ICSES, UACEE, Internet Society, and life membership of the Universal Inovators research lab, etc. He possesses teaching experience more than nine years. He is the co-convener of the ICICC, DOSCI, ICDAM & ICCCN springer Scopus Indexed conference series and ICCRDA-2020 Scopus Indexed IOP Material Science & Engineering conference series. He is also the organizer and co-convener of the International Conference on Innovations and Ideas towards Patents (ICIIP) series. He is also the advisory and TPC committee member of the ICCIDS-2022 Elsevier SSRN Conference. He is also the reviewer of many reputed journals like Springer, Elsevier, IEEE, Wiley, Taylor & Francis Group, IJEECS and World Scientific Journal, and many springer conferences. He is also served as a session chair in many international springer conferences. He is a doctoral researcher at DCR University of Science & Technology, Haryana. He completed his Post Graduation in 2012 from SRM UNIVERSITY, NCR CAMPUS, GHAZIABAD, and Graduated in 2010 from KNGD MODI ENGG. COLLEGE, GBTU. Dr. Umesh Gupta is currently an Assistant Professor at the School of Computer Science Engineering and Technology at Bennett University, Times of India Group, Greater Noida, Uttar Pradesh, India. He received a Doctor of Philosophy (Ph.D.) (Machine Learning) from the National Institute of Technology, Arunachal Pradesh, India. He has awarded a gold medalist for his Master of Engineering (M.E.) from the National Institute of Technical Teachers Training and Research (NITTTR), Chandigarh, India, and Bachelor of Technology (B.Tech.) from Dr. APJ, Abdul Kalam Technical University, Lucknow, India. His research interests include SVM, ELM, RVFL, machine learning, and deep learning approaches. He has published over 35 referred journal and conference papers of international repute. His scientific research has been published in reputable international journals and conferences, including SCI-indexed and Scopus-indexed journals like Applied soft computing (Elsevier) and Applied Intelligence (Springer), each of which is a peer-reviewed journal. His publications have more than 158 citations with an h-index of 8 and an i10-index of 8 on Google Scholar as of March 1, 2023. He is a senior Member of IEEE (SMIEEE) and an active member of ACM, CSTA, and other scientific societies. He also reviewed papers for many scientific journals and conferences in the US and abroad. He led sessions at the 6th International conference (ICICC-2023), 3rd International Conference on Data Analytics and Management (ICDAM 2023), the 3rd International Conference on Computing and Communication Networks (ICCCN 2022), and other international conferences like Springer ETTIS 2022 and 2023. He is currently supervising two Ph.D. students. He is the co-principal investigator (co-PI) of TWO major research projects. He published three patents in the years 2021-2023. He also published four book chapters with Springer, CRC. Dr. Prayag Tiwari received his Ph.D. degree from the University of Padova, Italy. He is currently working as a Postdoctoral Researcher at Aalto University. Previously, he worked as a Marie Curie Researcher at the University of Padova, Italy. He also worked as a research assistant at the NUST ``MISiS", Moscow, Russia. He has several publications in top journals and conferences, including Neural Networks, Information Fusion, IPM, IJCV, IEEE TNNLS, IEEE TFS, IEEE TII, IEEE JBHI, IEEE IOTJ, IEEE BIBM, ACM TOIT, CIKM, SIGIR, AAAI, etc. His research interests include Machine Learning, Deep Learning, Quantum Machine Learning, Information Retrieval, Healthcare, and IoT. He is also associated with one Funded-based project named "Data Literacy for Responsible Decision-Making" Short title (STN LITERACY/Marttinen). He is also the reviewer of many reputed journals like Springer, Elsevier, IEEE, Wiley, Taylor & Francis Group, IJEECS and World Scientific Journal, and many springer conferences.

Chapter 1 Dynamic Intuitionistic Fuzzy Weighting Averaging Operator: A Multi-Criteria Decision-Making Technique for the Diagnosis of Brain Tumor Vijay Kumar, H D Arora, Kiran Pal Chapter 2 NEURAL MODELING AND NEURAL COMPUTATION IN MEDICAL APPROACH Simran Singh, Anshika Gupta, Kalpana Chapter 3 Neural networks and Neurodiversity - The Key foundation for Neuroscience Hera Fatma, Harshit Mishra, Kalpana Katiyar Chapter 4 Brain Waves, Neuroimaging (fMRI, EEG, MEG, PET, NIR) Surbhi Kumari, Amit Kumar Dutta Chapter 5 EEG: Concepts, Research-based Analytics, and Applications Rashmi Gupta, Sonu Purohit, Jeetendra Kumar Chapter 6 Classification of gait signals for detection of neurodegenerative diseases using Log-energy entropy and ANN Classifier Prasanna J, S. Thomas George, M.S.P Subathra Chapter 7 An Optimized Text Summarization for Healthcare Analytics using Swarm Intelligence. Rekha Jain, Pratistha Mathur, Manisha Chapter 8 Computer-Aided Diagnosis of neurodegenerative diseases using Discrete Wavelet Transform and Artificial Neural network Prasanna J, S. Thomas George, M.S.P Subathra Chapter 9 EEG Artifact Detection and Removal Techniques: A Brief Review Sandhyalati Behera and Mihir Narayan Mohanty Chapter 10 Analysis of Neural Network and Neuromorphic Computing with hardware- A Survey Manish Bhardwaj, Kailash Nath Tripathi, Yogendra Narayan Prajapati, Analp Pathak