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Cambridge University releases a brain-training app that improves concentration to ritalin



January 22, 2019 21:07:09

If you're ever convinced yourself that your lack of attention needs serious medication, think again: a simple brain-training app from Cambridge University just might be the ticket.

Key points:

  • Ritalin is medication prescribed to those who suffer from ADHD
  • Researchers created a game that was found to significantly improve attention
  • They plan to expand this research for patients with severe neurological diseases

The university's Behavior and Clinical Neuroscience Institute has developed and tested "Decoder", an app which activates a frontal-parietal network in the brain that is designed to improve attention and concentration.

In a study published in the scientific journal, Frontiers in Behavioral Neuroscience, researchers – led by the Department of Psychiatry's Professor Barbara Sahakian – found that the app's use on an iPad for eight hours over the course of a month resulted in neurological improvements in healthy trial participants that were comparable to those taking stimulants such as methylphenidate (Ritalin) or nicotine.

"Many people tell me that they have trouble focusing their attention." Decoder should help them improve their ability to do this, "Professor Sahakian said.

What is the game?

Decoder, developed in collaboration with a games developer, gets users to assume the role of an intelligence officer tasked with breaking up the global crime gangs (users are able to choose a character and their backstory).

To meet the objective, users have to identify different combinations of number strings in missions littered with distraction.

Winning each mission means users of unlock letters

With each location, the difficulty of each mission is matched to a user's performance in real time.

How did the study work?

To quantify the app's outcomes, Cambridge researchers divided 75 healthy young adults into three groups, of which one would play the app, bingo, or no game at all.

The Cambridge Neuropsychological Test Automated Battery's (CANTAB) Rapid Visual Information Processing Test The Cambridge Neuropsychological Test Automated Battery's (CT) Rapid Visual Information Processing Test (RVP) – a test recommended to assess the alteration of people with Alzheimer's disease, depression, schizophrenia, and other neurological diseases.

The test on screen showed a centered white box containing digits from two to nine that appear in a "psuedo-random order" at the rate of 100 digits per minute.

Those tested were asked to detect digit sequences (such as 2-4 or 6-8), and then hit a button once detected as soon as they could – and multiple sequences could appear at the same time.

And what were the results?

Those who had played Decoder "showed better detection of target sequences" and were faster at hitting the targets, too.

Additionally, researchers found that "the subjective measures of enjoyment, motivation, alertness and positive mood remained at high levels in those who played decoder after every hour of gameplay".

Researchers were also careful to ensure that attention improvements in their trial participants one kind of attention did not impair their ability to shift attention.

To measure this, they had participants take the Trail Making Test, a neurospsychological test taking participants to 25 non-sequential dots as quickly as possible.

"Importantly, training of sustained attention / concentration did not impair performance on the Trail Making Test Indeed, if anything, gameplay had a beneficial effect on this form of attention also," they wrote.

While the "more challenging" version is now available on iPhones, and on Android later in 2019, researchers at Cambridge hope their app may be able to help those with chronic neurological disorders.

"While healthy young adults have been used as a measure to evaluate whether it can improve attentional performance, a key cognitive domain that is impaired in ADHD, schizophrenia and brain injury, They wrote.



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First posted

January 22, 2019 20:55:33

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