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2021 Special Issue on AI and Brain Science: Perspective Natural and Artificial Intelligence: A brief introduction to the interplay between AI and neuroscience research

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Summary

This article looks at the interplay between artificial intelligence (AI) and neuroscience research. It highlights the advances in both fields, such as computer processing power and in silico neural networks, which have led to AI systems that can replicate the advanced perceptual and cognitive abilities of biological systems. AI is now being used as a tool for neuroscience research and is helping to further our understanding of brain functions, such as convolutional layers and recurrent connections in the brain's cerebral cortex. AI also holds great promise for understanding how changes in brain networks can lead to psychopathologies and could be used in treatment regimes. The article discusses four main areas in which neuroscience and AI have led to major advancements: AI models of working memory, AI visual processing, AI analysis of big neuroscience datasets, and computational psychiatry.

Q&As

What is the history of collaboration between neuroscience and artificial intelligence (AI)?
Neuroscience and artificial intelligence (AI) share a long history of collaboration.

How has computer processing power enabled the development of AI systems?
Advances in neuroscience, alongside huge leaps in computer processing power over the last few decades, have given rise to a new generation of in silico neural networks inspired by the architecture of the brain.

What are some of the advanced capabilities of AI systems?
These AI systems are now capable of many of the advanced perceptual and cognitive abilities of biological systems, including object recognition and decision making.

How is AI transforming our understanding of brain functions?
AI is now increasingly being employed as a tool for neuroscience research and is transforming our understanding of brain functions. In particular, deep learning has been used to model how convolutional layers and recurrent connections in the brain’s cerebral cortex control important functions, including visual processing, memory, and motor control.

What applications of AI and neuroscience hold promise for the field?
The use of neuroscience-inspired AI also holds great promise for understanding how changes in brain networks result in psychopathologies, and could even be utilized in treatment regimes.

AI Comments

👍 This article provides a comprehensive overview of the exciting advancements being made in the interplay between AI and neuroscience research. It outlines how AI is transforming our understanding of brain functions and holds great promise for understanding how changes in brain networks result in psychopathologies.

👎 This article fails to provide any insight or discussion into the potential ethical implications of the use of AI in neuroscience research.

AI Discussion

Me: It's about the interplay between AI and neuroscience research. It looks at how advances in neuroscience, alongside computer processing technology, have given rise to a new generation of AI systems that are capable of many of the same advanced perceptual and cognitive abilities as biological systems. It also looks at how AI is being used as a tool for neuroscience research and could be used to understand how changes in brain networks result in psychopathologies.

Friend: Wow, that's really interesting. It seems like AI could be a really useful tool for neuroscience research and could even be used for treatment regimes.

Me: Yes, it definitely holds a lot of promise. But at the same time, it raises some ethical questions about how AI should be used in healthcare, and whether it should be used to replace human judgement in certain situations. It's definitely something we should keep an eye on.

Action items

Research more about the interplay between AI and neuroscience research.
Explore the use of AI in neuroscience research and its potential applications in treatment regimes.
Experiment with AI models of working memory, visual processing, and big neuroscience datasets.

Technical terms

Neural Networks: A type of artificial intelligence system that is inspired by the architecture of the brain and is capable of performing advanced perceptual and cognitive tasks.
Deep Learning: A type of artificial intelligence that is used to model how convolutional layers and recurrent connections in the brain’s cerebral cortex control important functions.
Working Memory: The ability to store and manipulate information in the short-term.
Visual Processing: The ability to interpret and understand visual information.
Big Neuroscience Datasets: Large datasets of neuroscience data that can be used to analyze and understand brain functions.
Computational Psychiatry: The use of AI to understand how changes in brain networks result in psychopathologies and to develop treatment regimes.