Summary: Researchers are studying the synchronization of brain regions to help control brain-machine interfaces.
Source: FPU Barcelona
Just a few decades ago, the possibility of connecting the brain to a computer to convert neural signals into concrete actions would have seemed like science fiction.
But in recent years, some scientific advances have been made in this regard, thanks to so-called BCIs (Bran-Computer Interfaces) which establish communication bridges between the human brain and computers.
A recent UPF study continues to move in this direction and provides new insights to pursue this desired neuroscientific step.
The results of the UPF Center for Brain and Cognition (CBC) study are the subject of an article published on February 7 in the journal in Euroentitled “Long-range alpha-synchronization as control signal for BCI: A feasibility study”, co-authored by Martín Esparza-Iaizzo (UPF and University College of London), Salvador Soto-Faraco (UPF and ICREA), Irene Vigué-Guix (UPF), Mireia Torralba Cuello (UPF) and Manuela Ruzzoli (Basque Center for Cognition, Brain and Language).
One of the main challenges in neuroscience today is identifying brain signals that are robust enough to control devices in real time. Neuroscientists have already made devices that can be controlled by the mind using only the activity of one or more regions of the brain.
However, it is not yet possible to do this via communication and synchronization of the different regions of the brain. The article published by in Euro makes important contributions to progress towards this goal.
Brain activity during visuospatial attention tasks
This study is based on the analysis of the cerebral activity of 10 people during a visual-spatial attention task, carrying out up to 200 measurements per subject, and is based on the concept of cross-laterality: what what we see on the right of the visual field is represented in the left hemisphere of the brain and, conversely, what we see on the left is represented in the right hemisphere.
Levels of the brain signal known as the alpha band decrease in the hemisphere in which the images we observe are represented. Researchers compare variations in alpha band levels to plates on a balance. It is precisely on the side of the balance where the weight is the most loaded that their plates descend the most, while, on the less heavy side, they tend upwards.
The same goes for the alpha band levels: it is precisely in the hemisphere on the side where the images are represented that the alpha band levels decrease the most, while they rise in the opposite hemisphere. It should be kept in mind that the alpha band inhibits the excitability of neurons, therefore it causes a state of relaxation of the neuronal populations. It is therefore not surprising that their level is lower in the hemisphere of the brain that processes images.
It should also be noted that the brain is divided into different regions which communicate by synchronizing its neuronal fluctuations, for example in the alpha domain. Specifically, one of the goals of the research was to analyze whether the long-distance synchronization of the alpha band between brain regions exhibits lateralized patterns and this was confirmed by the study authors.
Specifically, looking to the right, communication between the frontal and parietal regions of the left hemisphere increases, and looking to the left, communication between these same regions in the right hemisphere increases.
To date, signals from the alpha band with which the frontal and parietal regions of the brain communicate can only be fully captured by aggregating data from different measurements and not by a single trial. Therefore, another of the objectives of the study was precisely to examine how to capture these neural patterns at a single test level, which would allow the generation of a control signal to activate devices via real-time brain-computer interfaces. .
To achieve this, the principal researcher, Martín Esparza-Iaizzo, explains that his study makes contributions from a methodological point of view: “The novelty of the study is that, unlike previous studies, it uses measures of synchrony between the zones parietal and frontal at the level of each individual trial, and not in aggregated data”,
However, he warns that the limits of current electroencephalographs to achieve this goal have been noted:
“Current encephalography has limitations in terms of spatial resolution, and in terms of noise, due to respiration, cardiac activity, etc.”
However, the results of this research provide a good basis for future research. In this sense, Esparza-Iaizzo concludes: “What our study presents is a good methodology to demonstrate that indeed, for the moment, synchrony cannot be introduced into the world of systems operating in real time. We hope this will serve as a paradigm for future attempts.
About this neurotechnology research news
Author: Press office
Source: FPU Barcelona
Contact: Press office – UPF Barcelona
Picture: Image is in public domain
Original research: Access closed.
“Long-range alpha-synchronization as a control signal for BCI: a feasibility study” by Martín Esparza-Iaizzo et al. in Euro
Long-range alpha synchronization as a control signal for BCI: a feasibility study
Changes in spatial attention are associated with variations in alpha band activity (α, 8–14 Hz), particularly in interhemispheric disequilibrium. The underlying mechanism is attributed to local α-synchronization, which regulates local inhibition of neuronal excitability, and fronto-parietal synchronization reflecting long-distance communication.
The direction-specific nature of this neural correlate highlights its potential as a control signal in brain-computer interfaces (BCIs). In the present study, we explored whether long-range α-synchronization exhibits lateralized patterns dependent on voluntary orientation of attention and whether these neural patterns can be captured at a single trial level to provide a control signal. for active BCI. We collected electroencephalography (EEG) data from a cohort of healthy adults (n=10) while performing a covert visuospatial attention task (CVSA).
The data show a lateralized pattern of α-band phase coupling between the frontal and parieto-occipital regions after target presentation, reproducing previous results. This pattern, however, was not evident during the cue-to-target orientation interval, the ideal time window for BCI. Moreover, trial-by-trial decoding of attention direction from locked synchronization with support vector machines (SVMs) was at the level of chance.
The present results suggest that the EEG may not be able to detect long-range α synchronization in attentional orientation based on a single trial and, therefore, highlight the limitations of this metric as a reliable signal for BCI control.