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Jeffrey D. Macklis is an American neuroscientist.He is the Max and Anne Wien Professor of Life Sciences in the Department of Stem Cell and Regenerative Biology and Center for Brain Science at Harvard University, Professor of Neurology [Neuroscience] at Harvard Medical School, and on the Executive Committee and a Member of the Principal Faculty of the Neuroscience / Nervous System Diseases ...
A deeper understanding of the brain's computation will inform design of sensorimotor devices for neural control and allow for more targeted future work on investigating neural function. [7] Using this knowledge, inorganic systems can be better engineered to better interact with the brain's endogenous system of computation.
Neurotechnology encompasses any method or electronic device which interfaces with the nervous system to monitor or modulate neural activity. [1] [2]Common design goals for neurotechnologies include using neural activity readings to control external devices such as neuroprosthetics, altering neural activity via neuromodulation to repair or normalize function affected by neurological disorders ...
Intraoperative neurophysiological monitoring (IONM) or intraoperative neuromonitoring is the use of electrophysiological methods such as electroencephalography (EEG), electromyography (EMG), and evoked potentials to monitor the functional integrity of certain neural structures (e.g., nerves, spinal cord and parts of the brain) during surgery.
Some brain implants involve creating interfaces between neural systems and computer chips. This work is part of a wider research field called brain–computer interfaces. (Brain–computer interface research also includes technology such as EEG arrays that allow interface between mind and machine but do not require direct implantation of a device.)
Neuromorphic engineering is an interdisciplinary subject that takes inspiration from biology, physics, mathematics, computer science, and electronic engineering [4] to design artificial neural systems, such as vision systems, head-eye systems, auditory processors, and autonomous robots, whose physical architecture and design principles are ...
[4] [43] The current state-of-the-art in secondary structure prediction uses a system called DeepCNF (deep convolutional neural fields) which relies on the machine learning model of artificial neural networks to achieve an accuracy of approximately 84% when tasked to classify the amino acids of a protein sequence into one of three structural ...
Neural engineering (also known as neuroengineering) is a discipline within biomedical engineering that uses engineering techniques to understand, repair, replace, or enhance neural systems. Neural engineers are uniquely qualified to solve design problems at the interface of living neural tissue and non-living constructs.