Is brain just a machine?

Title : Is brain just a machine?

Abstract:

The presentation starts by discussing issues related to Behavioural and Cognitive Neuroscience Next- Gen BCIs, Digital Biomarkers and Organoid Intelligence.
Emerging technologies like machine vision, high-density silicon probes, optogenetics, and artificial intelligence are transforming behavioural neuroscience.
These tools allow scientists to capture complex animal and human behaviours with high precision while simultaneously recording and manipulating large-scale neural population activity. Artificial intelligence is increasingly being integrated with neurophysiological tools like Electroencephalography (EEG) and Functional Near-Infrared Spectroscopy (fNIRS) to create "neuroadaptive" systems.
The future of cognitive neuroscience is not merely a story of technological advancement; it is a profound invitation to rethink the nature of learning, identity, and human potential. As we develop tools that can read, adapt to, and interact with the brain’s intricate dynamics, our greatest challenge will not be engineering smarter algorithms, but cultivating the philosophical wisdom and ethical frameworks necessary to ensure these technologies elevate, rather than diminish, the human experience.
Social neuroscience is moving from “brains in isolation” to “brains in context, in interaction, and in networks.” Four pillars: computational methods, naturalistic paradigms, hyperscanning and social-world embedding.
On the more speculative frontier, researchers are exploring "organoid intelligence"—the use of lab-grown, three-dimensional human brain cell cultures integrated with silicon-based computing systems. While still in its infancy, this bio-hybrid approach challenges our traditional definitions of computation and cognition, potentially offering unprecedented models for studying learning and memory at a cellular level.
Computer vision and pattern recognition are currently the most impactful implementations of AI in neurology. Machine learning algorithms can now analyse MRI scans, CT scans, and EEGs with remarkable precision, often in a fraction of the time it takes a human.
Spotting the Invisible: AI excels at identifying subtle, early-stage abnormalities in brain tissue that might be too small for the human eye to catch. This is proving critical for the early detection of Alzheimer's disease, brain tumours, and subtle signs of a stroke. 
Faster Scans: New AI-powered image reconstruction systems (like deep resolve technologies) are dramatically accelerating how fast MRI scans can be completed while improving image clarity.
I will then dissect concepts like, Bio-Hybrid Computing, AI in Neurology, Brain -Reading AI, Social Neuroscience and Naturalistic Neuroscience. The keynote will move on to tackle issues like Hyperscanning, Neuroscience and Sensor Technology, Neuroinformatics, Neuro-Embodied AGI and Computational Brain Models. Finally, I will present areas like, Neuro-Symbolic Brain Models, Quantum Brain Computation and Neurorobotics.

Biography:

In 2020 he was elected as the member of The Academia Europaea. In 2017 he received a degree of Prof. Honoris Causa from the Univ. of Tourism and Management Skopje, North Macedonia. In 2024 was rated among the 100 best scientists in Business and Management by Research. com. During 2015 - 2017 he was professor of BioMarketing and Futures Research at the DCU Business School, Dublin City University, Ireland. This was the first Chair in the world on both domains - BioMarketing and Futures Research. Previously, and for 20 years, he had been appointed as the Foundation Chair of Marketing at the Adam Smith Business School, University of Glasgow, Scotland. He completed his PhD at the University of Sheffield in 1982. He has been a Full Professor for 35 years and held posts at Cardiff Business School, University of Wales College of Cardiff, Cleveland State University, Ohio, USA, Northern Arizona University, USA and California State University, USA. He has held Visiting Professorship positions at numerous universities in China, Lithuania, Austria, New Zealand, Denmark, Slovenia, Portugal, Hungary, Taiwan, Brazil, Colombia, Fiji and Cyprus.

Between 1987 and 1989 he was the director of the Doctoral Programmes at the Confederation of Scottish Business Schools and at the Cardiff Business School between 1993 and 1996. He was director of the Doctoral Programme in Management at the University of Glasgow between 1996 and 2004. Professor Moutinho is the Founding Editor-in-Chief of the Journal of Modelling in Management (JM2) and Co-editor-in-Chief of the Innovative Marketing Journal. He has another 4 associate editorships as well as being in the editorial boards of another 47 international academic journals. His areas of research interest encompass marketing and management futurecast, artificial intelligence, biometrics and neuroscience in marketing, futures research algorithmic self, EmoWear - a wearable tech device that detects human emotions, evolutionary algorithms, human-computer interaction, the use of artificial neural networks in marketing, modelling processes of consumer behaviour and tourism futurecast.
He has developed a number of conceptual models over the years in areas such as tourism destination decision processes, automated banking, supermarket patronage, among other areas. The testing of these research models has been based on the application of many different statistical, computer and mathematical modelling techniques ranging from multidimensional scaling, multinomial logit generalised linear models (GLMs) and linear structural relations to neural networks, ordered probit, simulated annealing, tabu search, genetic algorithms, memetic algorithms and fuzzy logic. Prof. Moutinho has given keynote speeches, lectures, seminars, talks, etc. in 49 countries worldwide. Prof. Moutinho has 39 books published, over 161 articles published in refereed academic journals. He has 171419 academic citations, the h-index of 59 and the i10-index of 166 (Google Scholar, April,27th, 2024).