{"id":314078,"date":"2026-03-05T09:57:07","date_gmt":"2026-03-05T09:57:07","guid":{"rendered":"https:\/\/www.newsbeep.com\/nz\/314078\/"},"modified":"2026-03-05T09:57:07","modified_gmt":"2026-03-05T09:57:07","slug":"open-data-to-help-create-adaptive-systems-for-stroke-recovery","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/nz\/314078\/","title":{"rendered":"Open Data To Help Create Adaptive Systems For Stroke Recovery"},"content":{"rendered":"

Thursday, 5 March 2026, 9:12 pm
Press Release: Skoltech<\/a><\/p>\n

A team of researchers from Skoltech, the Federal Center
\nfor Brain and Neurotechnologies (FMBA of Russia), Lomonosov
\nMoscow State University, and other leading organizations has
\nreleased a dataset that will enable deeper study of how the
\nbrain recovers after a stroke. The work, accepted for
\npublication in the journal Scientific Data (Nature
\nPublishing Group), is the first in the world to combine
\nlong-term recordings of brain activity obtained using two
\nadvanced methods \u2014 electroencephalography (EEG) and
\nfunctional near-infrared spectroscopy (fNIRS). The data are
\nopenly available, allowing scientists worldwide to
\naccelerate the development of personalized rehabilitation
\nmethods and brain-computer interfaces.<\/p>\n

Stroke remains
\none of the leading causes of disability worldwide, with
\nmotor impairments having the greatest impact on patients\u2019
\nquality of life. To make rehabilitation more effective, it
\nis essential to understand exactly how the brain regains
\ncontrol over movement. Since stroke is fundamentally a
\ndisruption of cerebral blood supply, methods that assess
\nbrain blood flow play a key role.<\/p>\n

One such method is
\nfunctional near-infrared spectroscopy (fNIRS). This
\nnon-invasive technology uses sensors placed on the head that
\nemit infrared light (760\u2013850 nm), penetrating the cortex
\nto a depth of up to 4 centimeters. By measuring how light is
\nabsorbed by tissues, it is possible to calculate the
\nconcentration of both oxygenated and deoxygenated
\nhemoglobin. Unlike functional MRI, fNIRS equipment is
\nportable, easy to use, and significantly cheaper. This
\nenables continuous monitoring of patients during
\nrehabilitation, rather than only at periodic
\nintervals.<\/p>\n

Advertisement – scroll to continue reading<\/p>\n

Electroencephalography (EEG) has been used
\nfor stroke prognosis and rehabilitation, but it remains
\npoorly understood how sensorimotor rhythms and cortical
\npotentials change precisely when a patient attempts to move
\ntheir hand. This limits the use of such signals in clinical
\nsettings and in the development of brain-computer interfaces
\nthat could aid rehabilitation.<\/p>\n

\u201cWe combined EEG and
\nfNIRS to get a more comprehensive picture. EEG captures fast
\nelectrical activity of neurons, while fNIRS shows how blood
\nvessels respond \u2014 where blood flows, where the brain
\nconsumes more oxygen. This is a slower but equally important
\nprocess. Together, the two methods provide a fuller
\nunderstanding of how the brain recovers and allow us to
\nstudy neurovascular coupling \u2014 how neuronal activity
\nrelates to blood flow,\u201d commented the paper\u2019s lead
\nauthor, Junior Research Scientist Alexandra Medvedeva at the
\nNeuro Center of Skoltech.<\/p>\n

The study involved 16
\npatients with hemiparesis \u2014 partial weakness or impairment
\nof muscles on one side of the body \u2014 aged 42 to 71, who
\nwere observed over 84 rehabilitation sessions at the Federal
\nCenter for Brain and Neurotechnologies. All data \u2014
\nincluding fNIRS and EEG signals, clinical assessments
\n(Fugl-Meyer scale, ARAT), and demographic information \u2014
\nhave been made openly available on the Figshare platform.
\nThis allows researchers around the world to begin analysis
\nwithout waiting to collect their own data.<\/p>\n

\u201cOur
\ndataset has practical value in several key areas. For
\nexample, it enables analysis of how brain activity changes
\nas a patient learns to move their hand again. The paper
\npresents a case where, during movement of the paralyzed
\nhand, the damaged hemisphere activated first, followed
\nseconds later by the healthy hemisphere. Understanding such
\npatterns will help clinicians predict how effectively
\nrehabilitation will progress for a particular patient and
\nadjust treatment programs accordingly,\u201d added co-author
\nLev Yakovlev, a senior research scientist at the Neuro
\nCenter of Skoltech.<\/p>\n

The combination of the two methods
\nalso reveals whether the healthy hemisphere reorganizes to
\nsupport the damaged one \u2014 and how this process relates to
\nprogress in restoring sensorimotor skills. This knowledge is
\nessential for learning to adjust therapy and avoid
\nreinforcing incorrect compensatory
\nmovements.<\/p>\n

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