Science, Space and Technology News 2024
A new “end-to-end” deep learning method for the prediction of behavioral states uses whole-cortex functional imaging that do not require preprocessing or pre-specified features. Developed by medical student AJIOKA Takehiro and a team led by Kobe University’s TAKUMI Toru, their approach also allows them to identify which brain regions are most relevant for the algorithm . The ability to extract this information lays the foundation for future developments of brain-machine interfaces.
For the production of brain-machine interfaces, it is necessary to understand how brain signals and affected actions relate to each other. This is called “neural decoding,” and most research in this field is done on the brain cells’ electrical activity, which is measured by electrodes implanted into the brain. On the other hand, functional imaging technologies, such asor calcium imaging, can monitor the whole brain and can make active brain regions visible by proxy data.
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