Cognitive Neurodynamics - Special Issue Call for Paper

Special issue title

New Frontiers in Brain-like Computing: Towards New Trends and Future Advances

Guest editors

Dr. J. Alfred Daniel, Dhanalakshmi Srinivasan Engineering College, Anna University, India
Dr. Awais Ahmad, Dipartmento di Informatica, Università Degli Studi di Milano, Milan, Italy
Dr. Boris Tomaš, Faculty of Organization and Informatics, University of Zagreb, Croatia
Dr. C Chandru Vignesh, Department of Computer Science and Engineering, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology,  India

About the special issue

In the current scenario of the modern computing world, it is an inevitable fact that the brain and mind are the final frontiers of computing science. In general, computers use artificial intelligence to make predictions and recall previously learned information, which is highly energy-and-time-intensive, specifically in cases where a plethora of data is transmitted between separate memory and processing units. To efficiently solve this issue, it is important to design and develop computational tools and methods, which simultaneously process and store information, just like the human brain. The primary principle here is to mimic the mechanism of the brain rather than completely imitating the brain. Though the technology of brain-like computing is still in infancy, experts strongly believe that research in this background is essential to run extensive, real-time simulations and make new discoveries across various fields such as neuroscience, medicine, etc. If explored properly, this stream of research will be used to revolutionize computer design, paving the way for more powerful and efficient artificial intelligence algorithms.

Practically speaking, the complex technologies of the future, such as robots and autonomous vehicles, need to access and utilize a large amount of data and information in real-time. At present, to a limited extent, these functionalities are made with the help of artificial intelligence and machine learning techniques that depend on the power of supercomputers. But these requirements are increasing, and size, speed, and power are emerging as a prime hindrance. Brain-like computing, a crucial upgrade to traditional systems, offers compact, portable, and energy-efficient solutions when dealing with complex systems. With the help of brain-like computing techniques, neural network models are trained to function like a human brain, analyze facts, memorize information, and make decisions. Presently, the ability of brain-like computing techniques to perform complex computational tasks with a small amount of computational power has attained the attention of the technological industry. Some of the futuristic trends and advances include low-power sensors, power-efficient supercomputers, and self-learning robots. Undoubtedly, exploring the frontiers in brain-like computing will truly unlock its potential in experimental, theoretical, and computational aspects of the computing world. Further, understanding this emerging technology will fundamentally change our interactions with intelligent machines. Also, it takes us to the final step in creating cognitive computing systems that can learn, remember, reason and help humans to make better decisions.

This special issue aims to bring out a comprehensive view of new frontiers and future advances in brain-like computing. There are only a few potential applications of brain-like computing today. We welcome revolutionary research works that focus on size, scope, architecture, design, scalability, and efficiency measures relating to brain-like computing for its ultimate realization. From a technical standpoint, novel and innovative state-of-the art-research works and cutting-edge innovations are most invited.

Possible topics include, but are not limited to the following:

• Exploring inspiring innovations of brain-like computing for the future technological era
• Trends in brain-computer interfaces and future advances
• Advances in brain-like computing for parallel computing of complex tasks
• Trends in spiking neural networks
• Effective ways of attaining the next level of artificial intelligence with brain-like computing techniques
• Brain-inspired artificial intelligence and machine learning
• Prospects of brain-computer interface technology
• Implications of brain-like computing across healthcare, robotics, industry, etc.
• Brain-machine intelligence and future advances
• Cognitive and computational foundations for brain-like computing
• Brain-inspired complex systems and future advances
• Neural information coding, decoding and learning

Important Dates

Manuscript Submission Deadline: 15 November 2022    
Authors Notification: 27 February 2023
Revised Papers Due: 5 April 2023    
Final notification: 1 June 2023