A new method for analyzing data in the brain has been developed by Prof. Dr. Ilka Diester of the University of Freiburg and colleagues. The method detects short beta wave bursts in real time within neural frequency bands of around 20 Hertz; the researchers have shown how rats can increase the occurrence of these bursts.

Neural oscillations — also known as brain waves — are important carriers of information in the brain. Researchers are increasingly coming to view them less as sustained oscillations and more as transient bursts.

Until now, there has been no method for measuring such short-lived bursts in real time or for examining how they influence the behavior of living things.

Beta Wave Bursts

In humans, monkeys, and rodents, it is possible to detect short bursts of up to 150 milliseconds of beta waves — a specific section of the brainwave spectrum — within a frequency range of 15 hertz to 30 hertz[1]. Researchers up to now connected these events with memory, motion, and perception.

During what is known as neuro-feedback training, rats always receive a reward when their brain produces a burst in the beta frequency range. This increases not only the recurrence of beta frequency bursts, but the total amplitude of this frequency range as well.

[caption id=“attachment_102417” align=“aligncenter” width=“700”]LFP beta-burst detection model LFP signals from the motor cortex of a freely moving rat were measured and fed into the real-time digital signal processing unit (DSP, red outline). Upon detection of an LFP beta-burst, the rat was rewarded with sucrose water. The activity of the rat was videotaped in synchronization with the electrophysiological data, and videos were analysed offline by a machine learning algorithm to detect movements indicative of beta bursts (orange outline). Black arrows: online analysis. White arrows: offline analysis.
Credit: Karvat, G., et al. CC-BY[/caption]

Through their work, Diester and her team have been able to predict beta range bursts in rats based on the rats movements — particularly in the front half of the rats' bodies. This new method paves the way for investigating the role of beta bursts in specific behaviors.

Because beta frequencies play a significant role in motion control, the method also opens new approaches in neuroprosthetics —the development and application of electronic implants for the restoration of damaged nerve function.

Digital Signal Processing

One challenge was the detection of such short-lived peaks. It needs to use minimal pre-processing and delay, as well as high time and frequency resolutions.

The new approach involves a real-time digital signal processing (DSP) method, capable of detecting short- and narrow-band bursts, based on 32 digital finite-impulse-response bandpass filters.

At the Institute of Biology III and BrainLinks-BrainTools, Diester leads a working group that is using optophysiology — or new types of optical tools — to investigate the functioning of neural circuitry. The researchers are probing the neural underpinnings of motor and cognitive control as well as interactions between the prefrontal and motor cortex, which are both parts of the cerebral cortex.

The work was supported by the Deutsche Forschungsgemeinschaft (DFG) through the Clusters of Excellence BrainLinks-BrainTools, the ERC Starting grant OptoMotorPath, and the BW Foundation (RatTrack).

[1] Karvat, G., Schneider, A., Alyahyay, M. et al. Real-time detection of neural oscillation bursts allows behaviourally relevant neurofeedback. Commun Biol 3, 72 (2020). https://doi.org/10.1038/s42003-020-0801-z


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