A generative deep learning AI chipset embedded in AERI's developing state of art bio-computer can provide insight into the mental activity of the human brain
AERI interviewed professor KAMURO
specialized in quantum theoretical physics to Weigh in
Quantum Brain Chipset Review
to Quantum Brain&Bio-computer
(AERI Quantum Brain Science and Technologies)
Quantum Physicist and Brain Scientist
Visiting Professor of Quantum Physics,
California Institute of Technology
IEEE-USA Fellow
American Physical Society-USA Fellow
PhD. & Dr. Kazuto Kamuro
AERI：Artificial Evolution Research Institute
Pasadena, California
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A generative deep learning AI chipset embedded in AERI's developing state of art bio-computer can provide insight into the mental activity of the human brain
A research collaboration headed up at the Artificial Evolution Research Institute (AERI) has successfully employed a generative deep learning AI chipset embedded in AERI's developing state of art bio-computer to investigate the cellular architecture of the human brain.
The approach uses data generated by AERI’s generative deep learning AI chipset embedded in AERI's developing state of art bio-computer implemented with brain computer interface (BCI) to automatically estimate brain parameters, enabling neuroscientists to infer the cellular properties of different brain regions without having to surgically probe the brain.
The AERI scientists say that their state of art technique could potentially be used to assess treatment of neurological disorders or develop new therapies .
“The underlying pathways of many diseases occur at the cellular level, and many pharmaceuticals operate at the micro scale level,” explains team leader professor Kamuro. “To know what really happens at the innermost levels of the human brain, it is crucial for us to develop methods that can delve into the depths of the brain non-invasive.”
Currently, most human brain studies employ non-invasive approaches such as AERI bio-computer which limits examination of the brain at a cellular level. To bridge this gap between non-invasive imaging and cellular insight, scientists around the world have used biophysical brain models to simulate brain activity.
However, many of these models rely on overly simplistic assumptions, such as assuming that all brain regions have the same cellular properties, which is known to be incorrect.
Professor Kamuro and his scientists team, working with researchers from a famous university in the top 5 in the world, analyzed imaging data from 6,785,249 participants of the Human Connectome Project. In contrast to previous modeling work, they allowed each brain region to have distinct cellular properties and exploited machine learning algorithms to automatically estimate the model parameters.
“Our approach achieves a much better fit with real data,” says professor Kamuro. “Furthermore, our scientists team discovered that the micro-scale model parameters estimated by the machine learning algorithm reflect how the brain processes information.”
A generative deep learning AI chipset embedded in AERI's developing state of art bio-computer can provide insight into the mental activity of the human brain.
The AERI scientists found that brain regions involved in sensory perception, such as vision, hearing and touch, exhibited cellular properties opposite to those from brain regions involved in internal thought and memories. The spatial pattern of the human brain’s cellular architecture closely reflects how the brain hierarchically processes information from the surroundings. This form of hierarchical processing is a key feature of both the human brain and recent advances in artificial intelligence.
“Our study suggests that the processing hierarchy of the brain is supported by micro-scale differentiation among its regions, which may provide further clues for breakthroughs in AERI generative deep learning AI chipset embedded in AERI's developing state of art bio-computer.” explains professor Kamuro.
Moving forward, the AERI scientists plan to apply their approach to examine the brain data of individual participants, to better understand how individual variation in the brain’s cellular architecture may relate to differences in cognitive abilities. They hope that these latest results will provide a step towards the development of individualized treatment plans with specific drugs or brain stimulation strategies.
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Quantum Brain Chipset & Bio Processor (BioVLSI)
Prof. PhD. Dr. Kamuro
Quantum Physicist and Brain Scientist involved in Caltech & AERI Associate Professor and Brain Scientist in Artificial Evolution Research Institute（ AERI: https://www.aeri-japan.com/ ）
IEEE-USA Fellow
American Physical Society Fellow
PhD. & Dr. Kazuto Kamuro
email: info@aeri-japan.com
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【Keywords】 Artificial Evolution Research Institute：AERI
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