Thursday, 5 March 2026, 9:12 pm
Press Release: Skoltech
A team of researchers from Skoltech, the Federal Center
for Brain and Neurotechnologies (FMBA of Russia), Lomonosov
Moscow State University, and other leading organizations has
released a dataset that will enable deeper study of how the
brain recovers after a stroke. The work, accepted for
publication in the journal Scientific Data (Nature
Publishing Group), is the first in the world to combine
long-term recordings of brain activity obtained using two
advanced methods — electroencephalography (EEG) and
functional near-infrared spectroscopy (fNIRS). The data are
openly available, allowing scientists worldwide to
accelerate the development of personalized rehabilitation
methods and brain-computer interfaces.
Stroke remains
one of the leading causes of disability worldwide, with
motor impairments having the greatest impact on patients’
quality of life. To make rehabilitation more effective, it
is essential to understand exactly how the brain regains
control over movement. Since stroke is fundamentally a
disruption of cerebral blood supply, methods that assess
brain blood flow play a key role.
One such method is
functional near-infrared spectroscopy (fNIRS). This
non-invasive technology uses sensors placed on the head that
emit infrared light (760–850 nm), penetrating the cortex
to a depth of up to 4 centimeters. By measuring how light is
absorbed by tissues, it is possible to calculate the
concentration of both oxygenated and deoxygenated
hemoglobin. Unlike functional MRI, fNIRS equipment is
portable, easy to use, and significantly cheaper. This
enables continuous monitoring of patients during
rehabilitation, rather than only at periodic
intervals.
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Electroencephalography (EEG) has been used
for stroke prognosis and rehabilitation, but it remains
poorly understood how sensorimotor rhythms and cortical
potentials change precisely when a patient attempts to move
their hand. This limits the use of such signals in clinical
settings and in the development of brain-computer interfaces
that could aid rehabilitation.
“We combined EEG and
fNIRS to get a more comprehensive picture. EEG captures fast
electrical activity of neurons, while fNIRS shows how blood
vessels respond — where blood flows, where the brain
consumes more oxygen. This is a slower but equally important
process. Together, the two methods provide a fuller
understanding of how the brain recovers and allow us to
study neurovascular coupling — how neuronal activity
relates to blood flow,” commented the paper’s lead
author, Junior Research Scientist Alexandra Medvedeva at the
Neuro Center of Skoltech.
The study involved 16
patients with hemiparesis — partial weakness or impairment
of muscles on one side of the body — aged 42 to 71, who
were observed over 84 rehabilitation sessions at the Federal
Center for Brain and Neurotechnologies. All data —
including fNIRS and EEG signals, clinical assessments
(Fugl-Meyer scale, ARAT), and demographic information —
have been made openly available on the Figshare platform.
This allows researchers around the world to begin analysis
without waiting to collect their own data.
“Our
dataset has practical value in several key areas. For
example, it enables analysis of how brain activity changes
as a patient learns to move their hand again. The paper
presents a case where, during movement of the paralyzed
hand, the damaged hemisphere activated first, followed
seconds later by the healthy hemisphere. Understanding such
patterns will help clinicians predict how effectively
rehabilitation will progress for a particular patient and
adjust treatment programs accordingly,” added co-author
Lev Yakovlev, a senior research scientist at the Neuro
Center of Skoltech.
The combination of the two methods
also reveals whether the healthy hemisphere reorganizes to
support the damaged one — and how this process relates to
progress in restoring sensorimotor skills. This knowledge is
essential for learning to adjust therapy and avoid
reinforcing incorrect compensatory
movements.
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