#brain-computer

[techvault24]

25 Cool Tools You Didn't Know About Before

[inventivaindia]

Elon Musk shows off Neuralink brain implant technology in a living pig

Elon Musk shows off Neuralink brain implant technology in a living pig

Elon Musk gave a peek at his brain computing startup, Neuralink, on Friday by showing off a surgically implanted electrical device in the skull of a living pig that broadcast the animal’s brain activity. 

Neuralink is working on a kind of brain-computer interface that it hopes will one day help restore brain functions in humans with disorders like blindness, seizures, and insomnia.

Musk’s…

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[scienza-magia]

Neuralink, interfaccia "neurale" con il computer di Elon Musk

Neuralink: ad agosto si scoprirà come Elon Musk collegherà il cervello umano con l'Intelligenza artificiale. Il papà di Tesla e SpaceX è pronto a svelare la sua nuova avventura dal sapore fantascientifico: ad agosto scopriremo cosa sta facendo con Neuralink ossia un'azienda che permetterà di trasmettere musica direttamente al cervello. Neuralink si farà e il prossimo 28 agosto Elon Musk svelerà al mondo nuove informazioni sul ''fantastico'' progetto che ha in mente. La conferma arriva direttamente da lui, CEO di Tesla e SpaceX, il quale con un tweet ha voluto precisare e soprattutto promettere che novità sul progetto Neurolink sono in arrivo e precisamente si saprà molto di più a fine agosto. Ma cosa è Neuralink e cosa punta ad ottenere Elon Musk con questo nuovo fantascientifico progetto? Vediamo di capirne di più. Neuralink: il nuovo prestigioso progetto di Elon Musk Elon Musk con Neuralink vuole creare un'interfaccia ''neurale'' ossia la possibilità da parte dell'uomo di avere il contatto e dunque far comunicare il cervello umano con un calcolatore ossia un computer super intelligente. Si era visto qualche anno fa l'affacciarsi sul mercato di una nuova società capitanata da Elon Musck e denominata appunto Neuralink. Read the full article

[m0nad4]

Mind over body: The search for stronger brain-computer interfaces

Summary: Machine learning algorithm allows a brain-computer interface to readjust itself continually in the background to ensure the system is always calibrated and ready to use.

When people suffer debilitating injuries or illnesses of the nervous system, they sometimes lose the ability to perform tasks normally taken for granted, such as walking, playing music or driving a car. They can imagine doing something, but the injury might block that action from occurring.

Brain-computer interface systems exist that can translate brain signals into a desired action to regain some function, but they can be a burden to use because they don’t always operate smoothly and need readjustment to complete even simple tasks.

Researchers at the University of Pittsburgh and Carnegie Mellon University are working on understanding how the brain works when learning tasks with the help of brain-computer interface technology. In a set of papers, the second of which was published today in Nature Biomedical Engineering, the team is moving the needle forward on brain-computer interface technology intended to help improve the lives of amputee patients who use neural prosthetics.

“Let’s say during your work day, you plan out your evening trip to the grocery store,” said Aaron Batista, associate professor of bioengineering in Pitt’s Swanson School of Engineering. “That plan is maintained somewhere in your brain throughout the day, but probably doesn’t reach your motor cortex until you actually get to the store. We’re developing brain-computer interface technologies that will hopefully one day function at the level of our everyday intentions.”

Batista, Pitt postdoctoral research associate Emily Oby and the Carnegie Mellon researchers have collaborated on developing direct pathways from the brain to external devices. They use electrodes smaller than a hair that record neural activity and make it available for control algorithms.

In the team’s first study, published last June in the Proceedings of the National Academy of Sciences, the group examined how the brain changes with the learning of new brain-computer interface skills.

“When the subjects form a motor intention, it causes patterns of activity across those electrodes, and we render those as movements on a computer screen. The subjects then alter their neural activity patterns in a manner that evokes the movements that they want,” said project co-director Steven Chase, a professor of biomedical engineering at the Neuroscience Institute at Carnegie Mellon.

In the new study, the team designed technology whereby the brain-computer interface readjusts itself continually in the background to ensure the system is always in calibration and ready to use.

“We change how the neural activity affects the movement of the cursor, and this evokes learning,” said Pitt’s Oby, the study’s lead author. “If we changed that relationship in a certain way, it required that our animal subjects produce new patterns of neural activity to learn to control the movement of the cursor again. Doing so took them weeks of practice, and we could watch how the brain changed as they learned.”

In a sense, the algorithm “learns” how to adjust to the noise and instability that is inherent in neural recording interfaces. The findings suggest that the process for humans to master a new skill involves the generation of new neural activity patterns. The team eventually would like this technology to be used in a clinical setting for stroke rehabilitation.

Such self-recalibration procedures have been a long-sought goal in the field of neural prosthetics, and the method presented in the team’s studies is able to recover automatically from instabilities without requiring the user to pause to recalibrate the system by themselves.

“Let’s say that the instability was so large such that the subject was no longer able to control the brain-computer interface,” said Yu. “Existing self-recalibration procedures are likely to struggle in that scenario, whereas in our method, we’ve demonstrated it can in many cases recover from even the most dramatic instabilities.”

Both research projects were performed as part of the Center for the Neural Basis of Cognition. This cross-institutional research and education program leverages the strengths of Pitt in basic and clinical neuroscience and bioengineering with those of Carnegie Mellon in cognitive and computational neuroscience.

Other Carnegie Mellon collaborators on the projects include co-director Byron Yu, professor of electrical and computer engineering and biomedical engineering, and also postdoctoral researchers Alan Degenhart and William Bishop, who led the conduct of the research.

https://neurosciencenews.com/bci-mobility-16210/

Source: University of Pittsburgh

[jahbillah]

On Dubbing With Your Mind World's first Brain-Computer codec is announced during the 3rd World Intelligence Congress at Tianjin. Before you start dubbing with your mind, this Brain–computer interface is designed for "medical treatment, education, self-discipline, security as well as games and entertainment.”

[evolving-science]

Writing Music with the Mind: New BCI Modality Offers the Power to Make Music as well as Play It

Brain-computer interfaces (BCIs) that allow people with severe neuromotor or motor disorders to communicate are becoming more and more common.