Neurotechnology uses images of the brain to improve, repair or in some way alter brain function and, ultimately, cognitive or motor skills in the human being. Advances in basic cognitive neuroscience have helped to develop non-invasive devices that have facilitated the adoption of neurotechnology in an increasingly wide range of clinical settings, in addition to opening a vast market for domestic non-clinical use.

MNeuronic has introduced an innovative component in the real-time analysis of the electroencephalographic signal (EEG) that renders the devices more efficient in terms of precision and user-friendliness

MNeuronic  (A Mnemonic system based on Stimulation-free Neuroimaging) finished on 30 June 2018, a proof of concept project funded by the European Commission’s European Research Council (ERC), led by Salvador Soto-Faraco, head of the Multisensory Research Group (MRG) at the Center for Brain and Cognition (CBC) and ICREA research professor with the Department of Information and Communication Technologies (DTIC) at UPF. MNeuronic has introduced an innovative component in the real-time analysis of the electroencephalographic signal (EEG) that renders the devices more efficient in terms of precision and user-friendliness.  

MNeuronic is based on the real-time processing of the natural oscillations in brain activity

This progress is due to the fact that, unlike any existing technology, MNeuronic’s decoding and classification algorithms of neural activity have included a proactive approach that allows predicting brain states, instead of the reactive approach of existing systems. MNeuronic is based on the real-time processing of the natural oscillations in brain activity.

As professor Soto-Faraco, principal investigator of the project explains: “our non-invasive technological setting is at a level of technological preparation (known by the initials TRL in English) that will soon allow the presentation of the system to potential investors and companies in the sector, in addition to protecting the technology with a patent, which is currently being studied”.

The technology implemented by MNeuronic can be used as a component for Brain-Computer Interaction (BCI) devices which are typically developed for a wide variety of applications, such as cognitive training, assisted learning, motion control systems (such as  wheelchairs), neurocognitive rehabilitation, control over tremors, “neurogaming” and, in general, to improve well-being and quality of life.

“We have managed to advance significantly in the right direction, validating the system to match the encoding of memories to the electrophysiology of the user so that it can be demonstrated to potential customers”

The team of researchers, comprising doctors in physics, computer science, bioengineering, neuropsychology and psychology, is currently working to apply the technology to improve the encoding of memory in humans. As professor Soto-Faraco points out: “we have managed to advance significantly in the right direction, validating the system to match the encoding of memories to the electrophysiology of the user so that it can be demonstrated to potential customers. In this sense, we have tested a prototype in healthy adults and we are thinking of implementing this prototype in a clinical population, which we expect to perform in collaboration with a clinical centre in Brescia (Italy), an institution which is at the forefront of research into dementia”, adds Soto-Faraco.

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