Cognitive psychology and artificial intelligence

#Cognitive psychology and artificial intelligence software
#Cognitive psychology and artificial intelligence simulator

We need a strategy that adjusts the training - which can involve many tasks that interfere with each other - according to the participant's changing responses,' said Asst Prof Asplund, who is also from Yale-NUS College.ДЄs such, the research team conducted a pilot study using CURATE.AI to create individualised training profiles. 'The stark differences show clearly that a one-size-fits-all training regimen based on static repetition is not suitable to optimise learning. In addition, the same participant's improvement often varied from day to day. Most participants improved over time, but their respective rates of improvement were highly varied. For instance, for a task requiring a reaction to a warning signal, the best performer could respond two times faster than the worst performer. Even with the same activity sequences and control settings, the participants performed differently.

#Cognitive psychology and artificial intelligence software

Tasks in the software include managing fuel tank levels, tracking a target using a joystick, adjusting a radio in response to verbal commands, and responding to indicator lights and gauges.ДЄ group of 28 participants were tested on how well they were able to perform multiple tasks required by the software simultaneously.

#Cognitive psychology and artificial intelligence simulator

The team employed a flight operations simulator software developed by the United States Air Force and National Aeronautics and Space Administration. To derive how optimal cognitive performance can be achieved, the NUS research team first examined how people perform tasks. Harnessing AI to optimise cognitive performance This calibration is then used to create an individualised CURATE.AI profile, which can map and pinpoint the best possible training regimen to boost the person's performance to its optimum. It works by using a person's own data, such as training intensity and corresponding task performance scores, to calibrate the person's unique response. This is where CURATE.AI can come in to plug the gap,' shared Prof Ho, who is the Director of N.1, and also a Provost's Chair Professor from the Biomedical Engineering and Pharmacology departments at NUS, as well as a member of the Biomedical Institute for Global Health Research and Technology (BIGHEART) at NUS.Д¬URATE.AI is an artificial intelligence platform developed by a team of engineers led by Prof Ho. What is lacking is approaches that can properly attune each user's performance to drive rapid training improvement. Harnessing technology to enhance learning is a good way to address the challenges confounding conventional learning approaches. 'Everyone is unique, so when it comes to training or learning, performance outcomes will certainly vary substantially from person to person. More recently, the field of digital therapeutics has emerged, with mobile applications being explored as replacements for drug treatments. Over the years, several approaches to improve cognitive performance have been studied, ranging from drug treatments to video games and mental exercises. In addition, the best trajectory of improvement will be specific to the individual, and the task needs to be adjusted to fit the individual. While such approaches can result in improved performance, they may not achieve optimal outcomes in every participant. Traditional learning approaches often rely on repetition, where participants are continuously trained under the same level of intensity, or steadily increasing intensity levels over time. Limitations of traditional cognitive training Asplund from the N.1 Institute for Health (N.1) of NUS, which was formerly the Singapore Institute for Neurotechnology (SINAPSE), was published in the journal Advanced Therapeutics on. The research, led by Professor Dean Ho and Assistant Professor Christopher L. The results of the study provide evidence that the CURATE.AI platform has the potential to enhance learning, and paves the way for promising applications for personalised digital therapy, including the prevention of cognitive decline. Such dynamic AI-guided personalisation overcomes the current limited improvement produced by using traditional training methods which often involve repetitive behavioural exercises.