High-frequency EEG patterns in the motor cortex can predict upcoming movements

overview: Spatially organized recruitment of neural activity throughout the motor cortex informs the details of planned movements.

sauce: University of Chicago

Dr. Nicholas G. Hatsopoulos, professor of biological biology and anatomy at the University of Chicago, has long been interested in space. Specifically, the physical space occupied by the brain.

“Inside our heads, the brain is all crumpled up. Flattening out the human cerebral cortex into a single 2D sheet would take up 2.5 square feet of space, roughly the size of four sheets of paper. You might think that the brain utilizes all its space when organizing patterns of activity, but know that one patch of the brain controls the arm and another the leg. Except how the brain uses its spatial organization has been largely ignored.”

Now, in a new study published January 16 Proceedings of the National Academy of Sciences, Hatsopoulos and his team have found evidence that the brain does use the spatial organization of high-frequency propagating waves of neuronal activity during exercise.

The existence of propagating waves of neuronal activity is well established, but traditionally associated with common behavioral states in animals (such as wakefulness or sleep). This study is the first evidence that spatially organized recruitment of neuronal activity across the motor cortex can inform details of planned movements.

The team hopes this work will help researchers and engineers learn how to decipher motion information to build better brain-machine interfaces.

To conduct the study, researchers recorded activity from a multi-electrode array implanted in the primary motor cortex of macaque monkeys while the monkeys performed a task that required moving a joystick. We then looked for wave-like patterns of activity, especially those with high amplitude.

“We focused on high-frequency band signals given their rich information, ideal spatial coverage, and ease of signal acquisition at all electrodes,” said Hatsopoulos Lab, lead author of the study. says Wei Liang, a graduate student at

They found these propagating waves, composed of hundreds of neuronal activity, moving in different directions across the cortical surface, based on which direction the monkey pressed the joystick.

“It’s like a series of dominoes falling,” says Hatsopoulos. “All the wave patterns we’ve seen in the past didn’t tell us what the animals were doing. It just happened. Because we’re looking at the patterns of propagating waves, and they show that the direction in which the waves travel can tell us something about what the animal is going to do.”

The results provide a new way of looking at cortical function. “This shows that space matters,” he says Hatsopoulos. “It turns out that there are spatially organized patterns that carry information, rather than just looking at what populations of neurons do and care about. This is a very different way of thinking about things.” am.”

The study was challenging due to the fact that they were studying activity patterns from individual movements rather than averaging recordings over repeated trials, which can be very noisy. We were able to develop computational methods to clean up the data to clarify the signal being recorded without losing important information.

“Averaging across trials, information is lost,” says Hatsopoulos. “If we want to implement this system as part of a brain-machine interface, we cannot average trials. there is.”

Knowing that these waves contain information about movement opens the door to a new dimension of understanding how the brain moves the body, adding to the computational systems that will drive future brain-machine interfaces. can provide information.

“Spatial dimensions, which have been largely ignored so far, are new angles that can be used to understand cortical function,” says Hatsopoulos. “When we try to understand the computations that the cerebral cortex is doing, we have to consider how the neurons are arranged spatially.”

Future studies will explore whether similar waveform patterns can be seen in more complex movements such as continuous movement, as opposed to simple point-to-point reach, and whether brain wave-like electrical stimulation can be used in monkeys. We plan to investigate whether we can bias movement.

Funding: The study “Spatiotemporal activity pattern propagation across the macaque motor cortex carries kinematic information” was supported by the National Institutes of Health (R01 NS111982). Other authors include his Karthikeyan Balasubramanianb and Vasileios Papadourakis from the University of Chicago.

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About this movement and neuroscience research news

author: Alison Caldwell
sauce: University of Chicago
contact: Alison Caldwell – University of Chicago
image: image is public domain

Original research: open access.
“Transmitting spatiotemporal activity patterns across the motor cortex of macaques conveys kinematic informationby Wei Liang et al. PNAS

overview

Transmitting spatiotemporal activity patterns across the motor cortex of macaques conveys kinematic information

Propagation of spatiotemporal neural patterns is widely evident across sensory, motor, and association cortical regions. However, it remains unclear whether neurotransmission properties carry information about specific behavioral details.

Here, we provide the first evidence of a link between the direction of cortical propagation on a trial-by-trial basis and specific behavioral properties of upcoming movements.

We recorded local field potentials (LFPs) from multi-electrode arrays implanted in the primary motor cortex of two rhesus monkeys while performing a two-dimensional reach task. Propagation patterns were extracted from the information-rich high gamma-band (200–400 Hz) envelope of the LFP amplitude.

We find that the exact direction of the propagation pattern varies systematically according to the initial migration direction, allowing for kinematic predictions.

Moreover, the properties of these propagation patterns provided additional predictive capabilities beyond the LFP amplitude itself.