Summary: A simple movement like pushing a button can send waves of activity across neurons that cover the entire brain, new research reports.
Source: University of Oregon
Even a simple movement like pushing a button sends waves of activity through networks of neurons in the brain, new University of Oregon research shows.
The discovery highlights how complex the human brain is, challenging the simplistic textbook view of distinct brain regions dedicated to specific tasks.
“It’s really well known that the primary motor cortex controls movement,” said graduate student Alex Rockhill in Nicky Swann’s Laboratory of Human Physiology Professor. But there’s more to moving than just this area of the brain.
Rockhill is the first author of a new paper from the lab, published in December. Journal of Neural Engineering.
Swann and her team are studying brain networks in humans in collaboration with doctors and researchers at Oregon Health & Science University. The OHSU team is using a technique called intracranial EEG to determine where seizures begin in patients with treatment-resistant epilepsy. They surgically implant multiple electrodes into patients’ brains to pinpoint when and where seizures occur and to remove the affected area of the brain.
Intracranial EEG also provides valuable insight into other brain activity. According to Swann, it is the “gold standard” method. But researchers rarely have access to it, because implanting electrodes is a very difficult process. Participants in the Swann study consented to have their groups studied while they were connected to electrodes for seizure research.
Swann and her colleagues gave study participants a simple movement-related task: pushing a button. They recorded the activity of thousands of neurons throughout the brain while the participants performed the task. Then, they tested whether they could train a computer to recognize whether the participant had certain patterns of brain activity while at rest or while moving.
In some areas of the brain, the symptoms were clear. Those were the areas previously associated with movement, where most of the neurons were probably focused on that behavior. But the researchers found brain signals that predict activity throughout the brain, including areas not dedicated to the brain.
In many parts of the brain, “we can predict with greater accuracy than chance whether the information is during activity or not during activity,” Swann said.
“We found that there is a spectrum of primary motor areas where you can decode whether the person is walking 100 percent of the time,” Rockhill added.
In some areas that aren’t specific to movement, he says, “some neurons may be firing, but they may be overwhelmed by neurons unrelated to movement.”
Their findings complement a 2019 study published in the journal NatureOther researchers have shown similar distant brain networks related to movement in mice.
“That paper shows that activity is ubiquitous in the brain, and our paper shows that’s true in humans as well,” Swan said.
The phenomenon is probably not limited to movement. Other systems, such as vision and touch, probably extend further into the brain than previously thought.
Now the team is developing new tasks that involve different types of activity to see how it looks in the brain. And they plan to expand the collaboration with OHSU by involving more researchers in the project and gaining a deeper understanding of the complexities of the brain.
“Now that we have this new partnership, we have a lot of opportunity,” Swan said. “We are truly fortunate to have the opportunity to collect such exciting data in collaboration with the OHSU team and their patients.”
So neuroscience research news
Author: Laurel hammers
Source: University of Oregon
Contact: Laurel Hammers – University of Oregon
Image: The image is in the public domain.
Preliminary study: Closed access.
“Stereo-EEG recordings extend well-known canonical activity-related oscillation distributions.” by Alexander P. Rockhill et al Journal of Neural Engineering
Stereo-EEG recordings extend well-known canonical activity-related oscillation distributions.
Purpose. Previous electrophysiological studies have identified canonical patterns of movement-related oscillations, mostly from recordings in the primary sensorimotor cortex. Less work has attempted to resolve activity based on electrophysiological recordings. We aimed to identify and characterize different movement-related oscillations across a relatively broad sample of brain areas in humans and beyond those brain areas previously associated with movement.
Approach. We used a linear support vector machine to solve time-locked moving time-frequency spectrograms and confirmed our results by cluster permutation experiment and normal spatial pattern solving.
Main results. We were able to correctly segment the sEEG spectrograms during key press activity from the inter-trial interval. Specifically, we found these previously described patterns: beta (13–30 Hz) synchronization, beta synchronization (reactivation), pre-movement alpha (8–15 Hz) modulation, post-movement broadband gamma (60–90 Hz). Increase and event-related capacity. These oscillatory patterns have been newly demonstrated in vast areas of the brain accessible by sEEG that are inaccessible with other electrophysiological recording methods. For example, the presence of beta detachment in the frontal lobe is more widespread than previously described and extends beyond the primary and secondary motor cortices.
Importance. Our classification reveals prominent time-frequency patterns that have been used in previous studies using noninvasive electroencephalography and electrocorticography, but here we identify these patterns in brain regions unrelated to activity. This provides new evidence for the anatomical scope of the putative motor networks that display each of these oscillatory patterns.