The Resonant Brain: A Themed Issue Dedicated to Professor Stephen Grossberg

Dear Colleagues,

This Special Issue is centered on answering how the human brain processes information in all its complexity to give rise to what is called “the mind”. Information is a concept that reaches well beyond the realm of data, and in the largest possible sense it may be defined as everything that we are able to process in our brains to produce knowledge. Clearly, the concept of information per se would not exist without a human brain capable of perceiving and processing it, and there would be no definition of what is to be understood by the concept without a conscious mind capable of providing it. Information produces what we humans call knowledge, and knowledge is formed inside, and transformed by, what we call the human mind. Yet, how can a mind understand itself? How is it possible to understand the processes our brain uses to understand the world? Professor Stephen Grossberg’s book Conscious Mind, Resonant Brain: How Each Brain Makes a Mind, published in 2021, provides an introductory and self-contained description of some of the exciting answers to these questions that modern theories of mind and brain have recently proposed. Stephen Grossberg is broadly acknowledged to be among the pioneers and research leaders in the field of neural networks who has, for the past 50 years, modeled how brains give rise to minds, and notably how neural circuits in multiple brain regions interact together to generate psychological functions. This research has led to a unified understanding of how, where, and why our brains can consciously see, hear, feel, and know about the world, and effectively plan and act within it. His lifelong work has sought to clarify how autonomous adaptive intelligence is achieved. It provides mechanistic explanations of adaptive behaviors, and solutions to large-scale problems in machine learning, technology, and Artificial Intelligence that provide a blueprint for autonomously intelligent algorithms and robots. As brains embody a universal developmental code, unifying insights also emerge about shared laws that are found in all living cellular tissues, from the most primitive to the most advanced, notably how the laws governing networks of interacting cells support developmental and learning processes in all species. The fundamental brain design principles of complementarity, uncertainty, and resonance that Grossberg has discovered also reflect laws of the physical world with which our brains ceaselessly interact, and which enable our brains to incrementally learn to understand those laws, thereby enabling humans to understand the world scientifically.

This Special Issue is dedicated to Stephen Grossberg, Professor Emeritus with the Department of Biomedical Engineering of Boston University (BU), Wang Professor of Cognitive and Neural Systems, and former Director of the Center for Adaptive Systems of BU. Grossberg is an internationally acclaimed scientist and pioneer in fundamental principles, mechanisms, and model architectures that form the foundation of contemporary neural network research. Grossberg and his colleagues have built models that have been used to analyze and predict interdisciplinary data about mind and brain and suggest novel architectures for technological applications. In this Special Issue, we invite articles on interdisciplinary topics devoted to cooperative–competitive processes underlying brain integration for human information processing and the design of predictive Artificial Intelligence and/or conscious representation by the human mind.

Both research papers and review articles are welcome.

Prof. Dr. Birgitta Dresp-Langley
Prof. Dr. Luiz Pessoa
Guest Editors

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