Summary: A simple movement like the push of a button can send ripples of activity through neurons spanning the entire brain, a new study reports.
Source: University of Oregon
Even a simple movement like pressing a button sends ripples of activity through neural networks stretching across the brain, according to new research from the University of Oregon.
The finding highlights just how complex the human brain is, challenging the simplified textbook image of separate brain areas dedicated to specific functions.
“It’s really well known that the primary motor cortex controls movement output,” said Alex Rockhill, a graduate student in the lab of human physiology professor Nicki Swann. “But there’s a lot more to movement than just this area of the brain.”
Rockhill is the first author of a new paper from the lab, published in December in the Neural Engineering Journal.
Swann and his team study brain networks in humans through collaboration with physicians and researchers at Oregon Health & Science University. The OHSU team uses a technique called intracranial EEG to determine where seizures may start in patients with treatment-resistant epilepsy. They surgically implant an array of electrodes into patients’ brains to identify precisely when and where a seizure occurs and eventually remove the affected brain area.
Intracranial EEG can also provide valuable information about other brain activities. It’s a “gold standard” technique, Swann said. But it’s a tool that researchers rarely have access to, because electrode implantation is a very intensive process. Participants in Swann’s study agreed to let his team study their brains while they are already hooked up to electrodes for the seizure study.
Swann and his colleagues gave study participants a simple movement-related task: press a button. They recorded the activity of thousands of neurons throughout the brain as the participants performed the task. Next, they tested whether they could train a computer to identify whether particular patterns of brain activity were being captured while the participant was at rest or in motion.
In certain areas of the brain, the signals were evident. These were areas previously related to movement, where most neurons are likely focused on this behavior. But the researchers also found brain signals predicting movement throughout the brain, including in areas not specifically dedicated to it.
In many parts of the brain, “we can predict with greater than chance accuracy whether or not that data came from movement,” Swann said.
“We found that there is a spectrum of brain areas, from primary motor areas where you can decode that the person is moving 100% of the time, to other areas that can be decoded 75% of the time,” Rockhill added.
In some of the areas that are not specialized in movement, “some of the neurons may fire, but they may be overwhelmed by neurons that are not related to movement,” he said.
Their findings complement a study published in 2019 in the journal Naturein which other researchers have shown similar large-scale brain networks related to movement in mice.
“This paper showed that movement is all over the brain, and our paper shows that’s true in humans as well,” Swann said.
The phenomenon is probably not limited to movement either. Other systems, like vision and touch, also likely span more of the brain than previously thought.
Now the team is working on developing new tasks that involve different types of movement, to see how these manifest in the brain. And they plan to continue to expand the collaboration with OHSU, involving more researchers in the project and gaining a deeper understanding of the intricacies of the brain.
“There are a lot of opportunities now that we have this new collaboration,” Swann said. “We are truly fortunate to have the opportunity to collect such interesting data working with the team at OHSU and their incredible patients.”
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About this neuroscience research news
Author: Laurel Hammer
Source: University of Oregon
Contact: Laurel Hamers – University of Oregon
Picture: Image is in public domain
Original research: Access closed.
“Stereo-EEG Recordings Extend Known Distributions of Canonical Motion-Related Oscillations” by Alexander P Rockhill et al. Neural Engineering Journal
Summary
Stereo-EEG recordings extend known distributions of motion-related canonical oscillations
Purpose. Previous electrophysiological research has characterized canonical oscillatory patterns associated with movement, primarily from recordings from the primary sensorimotor cortex. Less work has attempted to decode movement based on electrophysiological recordings from a wider range of brain areas such as those sampled by stereoelectroencephalography (sEEG), particularly in humans. We sought to identify and characterize different movement-related oscillations in a relatively large sample of brain areas in humans and whether they extend beyond brain areas previously associated with movement.
Approach. We used a linear support vector machine to decode motion-time-locked time-frequency spectrograms, and we validated our results with cluster permutation tests and common spatial pattern decoding.
Principle results. We were able to accurately classify sEEG spectrograms during a keypress motion task with respect to the interval between trials. Specifically, we found these previously described patterns: beta desynchronization (13–30 Hz), beta synchronization (bounce), alpha modulation before motion (8–15 Hz), broadband gamma increase after motion (60– 90Hz). and event potential. These oscillatory patterns have recently been observed in a wide range of brain areas accessible with sEEG that are not accessible with other electrophysiological recording methods. For example, the presence of beta desynchronization in the frontal lobe was more widespread than previously described, extending outside the primary and secondary motor cortices.
Importance. Our classification revealed important time-frequency patterns that have also been observed in previous studies using noninvasive electroencephalography and electrocorticography, but here we identified these patterns in brain regions that had not previously been associated At the move. This provides new evidence for the anatomical extent of the system of putative motor networks that exhibit each of these oscillatory patterns.
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