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, published 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.
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.
