How the Brain Works -Insights for AI Systems Analysts

Nature, 2019

C hethan Pandarinath wants to enable people with paralysed limbs to reach out and grasp with a robotic arm as naturally as they would their own. To help him meet this goal, he has collected recordings of brain activity in people with paralysis. His hope, which is shared by many other researchers, is that he will be able to identify the patterns of electrical activity in neurons that correspond to a person's attempts to move their arm in a particular way, so that the instruction can then be fed to a prosthesis. Essentially, he wants to read their minds. "It turns out, that's a really challenging problem, " says Pandarinath, a biomedical engineer at Emory University and the Georgia Institute of Technology, both in Atlanta. "These signals from the brain-they're really complicated. " In search of help, he turned to artificial intelligence (AI). He fed his brain-activity recordings to an artificial neural network, a computer ARTIFICIAL INTELLIGENCE Marriage of mind and machine Bringing together artificial intelligence and neuroscience promises to yield benefits for both fields.

South African Journal of Occupational Therapy, 2012

Editors: Bernard J. Baars: Senior fellow in Theoretical Neurobiology, The Neurosciences Institute, San Diego. Nicole M. Gage: Director of Cognitive Neuroscience of Language Lab, University of California, Irvine. Book information: Publisher: Churchill Livingstone Elsevier Date of Publication: 2010 ISBN number: 978- 0- 12- 375070-9 Hardcover Number of pages: 653 pages Price: $89, 95 The book Cognition, Brain and Consciousness: An Introduction to Cognitive Neurosciences looks like an intimidating book based on its size and weight! However, it is actually an accessible introductory text for those interested in Neurosciences. The authors state the purpose of the book is to enable the reader to keep up to date with this ever- changing field. The up to date research included is particularly excellent. There are information boxes in each chapter titled “Frontiers in Cognitive Neurosciences” that are fascinating as they showcase scientists in the field who are doing different and ground b...

Biological Cybernetics, 2025

After noting the cybernetic origins of Kybernetik/ Biological Cybernetics, we respond to the Editorial by Fellous et al. (2025) and then analyze talks from the NIH BRAIN NeuroAI 2024 Workshop to get one "snapshot" of the state of the conversation between Artificial intelligence (AI) and brain theory (BT). Key recommendations going beyond the earlier Editorial are that: (i) Successes in fitting ANNs to increasingly large neuroscience datasets must not distract us from the quixotic but demanding quest to understand "how the brain works" and discover underlying brain (and AI) operating principles. (ii) We must integrate functional and structural analyses in exploring systems of systems, integrating structures (e.g., brain regions, cortical modules) and functions (e.g., schemas for perception, action and cognition) that bridge between neural circuitry and patterns of behavior. (iii) We must study the diversity of intelligences exhibited by animals in their strategies for survival and not only the disembodied employment of language and reasoning. Finally and briefly, we note the urgency of assessing the societal implications of an age of increasingly pervasive human-machine symbiosis.

While the human-centered version explored the interplay of the biological brain, subjective mind, and the phenomenon of consciousness, the present work transposes the framework to the emerging domain of Artificial Intelligence. By adopting the same structural lens, this paper aims to clarify how the concepts of "brain," "mind," and "consciousness" can be understood in the AI context-not as biological realities but as computational, representational, and emergent properties. The intention is to emphasize continuity between the two works: the first grounds the enigma in the human condition, while the second extends the reflection into the artificial domain. Together, the pair of papers seeks to provide a comparative platform for discussing cognition, intelligence, and awareness across natural and artificial systems.

2017

From ancient times, the history of human beings has developed through a succession of steps and sometimes jumps, until reaching at the relative sophistication of the modern brain and culture. Researchers are attempting to create systems that mimic human thinking, understand speech, or beat the best human chess player. Understanding the mechanisms of intelligence, and creating intelligent artefacts are the twin goals of Artificial Intelligence (AI). Great mathematical minds have played a key role in AI in recent years; to name only a few, Janos Neumann (also known as John von Neumann), Konrad Zuse, Norbert Wiener, Claude E. Shannon, Alan M. Turing, Grigore Moisil, Lofti A. Zadeh, Ronald R. Yager, Michio Sugeno, Solomon Marcus, or Lászlo A. Barabási. Introducing the study of AI is not merely useful because of its capability to solve difficult problems, but also because of its Mathematical nature. It prepares us to understand the current world, enabling us to act on the challenges of t...

Mens Sana Monographs, 2011

Human brain is a highly evolved coordinating mechanism in the species Homo sapiens. It is only in the last 100 years that extensive knowledge of the intricate structure and complex functioning of the human brain has been acquired, though a lot is yet to be known. However, from the beginning of civilisation, people have been conscious of a 'mind' which has been considered the origin of all scientific and cultural development. Philosophers have discussed at length the various attributes of consciousness. At the same time, most of the philosophical or scientific frameworks have directly or indirectly implied mind-body duality. It is now imperative that we develop an integrated approach to understand the interconnection between mind and consciousness on one hand and brain on the other. This paper begins with the proposition that the structure of the brain is analogous, at least to certain extent, to that of the computer system. Of course, it is much more sophisticated and complex. The second proposition is that the Chomskyean concept of 'mental organs' is a good working hypothesis that tries to characterise this complexity in terms of an innate cognitive framework. By following this dual approach, brain as a data processing system and brain as a superstructure of intricately linked mental organs, we can move toward a better understanding of 'mind' within the framework of empirical science. The one 'mental organ' studied extensively in Chomskyean terms is 'language faculty' which is unique in its relation to brain, mind and consciousness.

Health science journal, 2020

The human brain has been the source of inspiration behind the birth and growth of Artificial Intelligence. The achievements in the diverse domains of AI have stemmed from replication of brain circuits. Almost as if a full circle, AI which had been inspired from the brain, has also found several applications in the field of Neuroscience and understanding the brain. In this article, we explore these two domains individually, as well as make an attempt to elucidate how closely correlated they actually are.

Synthese, 2006

2017

AI & SOCIETY

This article explores the proposition that the brain, normally seen as an organ of the human body, should be understood as a biologically based form of artificial intelligence, in the course of which the case is made for a new kind of 'brain exceptionalism'. After noting that such a view was generally assumed by the founders of AI in the 1950s, the argument proceeds by drawing on the distinction between science-in this case neuroscience-adopting a 'telescopic' or a 'microscopic' orientation to reality, depending on how it regards its characteristic investigative technologies. The paper concludes by recommending a 'microscopic' yet non-reductionist research agenda for neuroscience, in which the brain is seen as an underutilised organ whose energy efficiency is likely to outstrip that of the most powerful supercomputers for the foreseeable future.