Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.
The ability to concentrate is essential in everyday life as well as in meditation practice. However, scientists still do not fully understand which physiological changes most accurately reflect a state of deep concentration.
Modern research shows that the ability to focus attention can be developed and improved through training. It constantly changes depending on a person's physical and mental state, level of fatigue, and surrounding environment. Mindfulness and meditation practices can help people maintain focus for longer, cope with stress more effectively, and recognise when their attention begins to wander. Understanding how the brain regulates attention could make learning more effective, boost productivity, and enable the development of technologies that adapt to a person's state in real time.
Electroencephalography (EEG), which records the electrical activity of the brain, is most commonly used to study concentration. However, there is not yet a reliable indicator by which the concentration state can be determined. Researchers believe that other body signals, such as heart rate, breathing, and even a video recording of a face, can also provide useful information.
At the same time, scientists lack open datasets that combine all of these measurements. Such datasets would make it possible to compare how the brain, heart, and other physiological processes change during focused attention and to identify more reliable markers of concentration.
A team of researchers, including Elena Artemenko from HSE University–St Petersburg, has created a multimodal dataset containing simultaneous EEG, ECG, and video recordings collected during tasks involving both focused attention and mind wandering. The dataset is designed to help scientists better understand what happens in the human brain during deep concentration.
The study involved 49 volunteers. Half of the participants had more than one year of experience with yoga and meditation practices, while the other half had no prior experience with self-regulation techniques and served as the control group.
Each participant completed five stages of the experiment, with a total duration of approximately 45 minutes. First, participants rested; they were then asked to perform an internal concentration task by focusing on an imagined point in the centre of their forehead, followed by an external concentration task in which they had to identify a target character within a visually complex scene. Finally, they were instructed to let their thoughts wander freely. After the experiment, each participant was asked to provide a subjective assessment of the quality of their concentration.
Throughout the experiment, the researchers recorded participants' brain activity using EEG, monitored heart function with ECG, and captured video of each participant's face. All of this data was recorded simultaneously, allowing researchers to obtain a comprehensive picture of what happens to the body and brain during concentration, rest, or meditation.
The results showed that the state of focused attention differs markedly from the state in which thoughts freely shift from one topic to another. These differences were more pronounced in participants with long-term experience in yoga and meditation, making their level of concentration easier to identify from EEG data. The most informative signals came from the frontal regions of the brain, which are associated with attention control. However, the researchers emphasise that there is still no single biomarker capable of accurately measuring the level of concentration across individuals, and the newly created dataset will help identify such reliable markers in future studies.
Elena Artemenko
'We hope that the dataset we have created will find applications across several fields of science. It will help researchers not only explore the fundamental mechanisms of concentration and attention, but also develop new technologies for rehabilitating patients after stroke and traumatic brain injury, as well as create systems for assessing attention in educational and professional settings,' said study co-author Elena Artemenko, Deputy Head of the Laboratory for Social and Cognitive Informatics.
According to the researchers, such projects are especially important because modern science increasingly advances through collaboration between different laboratories and open exchange of data. The more scientists can work with a single high-quality database, the faster they will be able to find new answers to questions about how the human brain works.
The study was conducted with support from HSE University's Basic Research Programme.
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