A robot controlled by a biological brain formed from cultured neurons has been developed by a team at the University of Reading.

This cutting edge research is the first step to examine how memories manifest themselves in the brain, and how a brain stores specific pieces of data. The key aim is that eventually this will lead to a better understanding of development and of diseases and disorders which affect the brain such as Alzheimer’s Disease, Parkinson’s Disease, stoke and brain injury.

The robot’s biological brain is made up of cultured neurons which are placed onto a multi electrode array (MEA). The MEA is a dish with approximately 60 electrodes which pick up the electrical signals generated by the cells. This is then used to drive the movement of the robot. Every time the robot nears an object, signals are directed to stimulate the brain by means of the electrodes. In response, the brain’s output is used to drive the wheels of the robot, left and right, so that it moves around in an attempt to avoid hitting objects. The robot has no additional control from a human or a computer, its sole means of control is from its own brain.

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Individuals with severe disabilities could lead more independent lives with the help of an assistive technology developed by engineers at the Georgia Institute of Technology.

To operate the Tongue Drive system, potential users only need to be able to move their tongues.

Maysam Ghovanloo, an assistant professor at the Georgia Tech School of Electrical and Computer Engineering, who helped develop the device, explained: “We chose the tongue to operate the system because unlike hands and feet, which are controlled by the brain through the spinal cord, the tongue is directly connected to the brain by a cranial nerve that generally escapes damage in severe spinal cord injuries or neuromuscular diseases.

“Tongue movements are also fast, accurate and do not require much thinking, concentration or effort.”

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Devices known as brain-machine interfaces could someday be used routinely to help paralysed patients and amputees control prosthetic limbs with just their thoughts. Researchers at the University of Florida have taken the concept a step further, developing a way for computerised devices to not only translate brain signals into movement, but also to evolve with the brain as it learns.

Instead of interpreting brain signals and routing them to a robotic hand or leg, this type of brain-machine interface would adapt to a person’s behavior over time and use the knowledge to help complete a task more efficiently.

Until now, brain-machine interfaces have been designed as one-way conversations between the brain and a computer, with the brain doing all the talking and the computer following commands. The system UF engineers created, allows the computer to have a say in that conversation.

Justin Sanchez, a UF assistant professor of pediatric neurology, and the study’s senior author, said: “In the grand scheme of brain-machine interfaces, this is a complete paradigm change.

“This idea opens up all kinds of possibilities for how we interact with devices. It’s not just about giving instructions but about those devices assisting us in a common goal. You know the goal, the computer knows the goal and you work together to solve the task.”

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Scientists at Carnegie Mellon University have developed a computational model that can predict the unique human brain activation patterns associated with names for things that can be seen, heard, felt, tasted or smelt.

Previously researchers used functional magnetic resonance imaging (fMRI) to detect which areas of the brain are activated when a person thinks about a specific word. A Carnegie Mellon team has taken the next step by predicting these activation patterns for concrete nouns - things that are experienced through the senses - for which fMRI data does not yet exist.

The work could eventually lead to the use of brain scans to identify thoughts and could have applications in the study of autism, disorders of thought such as paranoid schizophrenia, and semantic dementias such as Pick’s disease.

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