Neural oscillations as important information carrier in the brain, are increasingly interpreted as transient bursts rather than as sustained oscillations. Short (<150 ms) bursts of betawaves (15-30 Hz) have been documented in humans, monkeys and mice. These events were correlated with memory, movement and perception, and were even suggested as the primary ingredient of all beta-band activity. However, a method to measure these short-lived events in real-time and to investigate their impact on behaviour is missing. Here we present a real-time data analysis system, capable to detect short narrowband bursts, and demonstrate its usefulness to increase the beta-band burst-rate in rats. This neurofeedback training induced changes in overall oscillatory power, and bursts could be decoded from the movement of the rats, thus enabling future investigation of the role of oscillatory bursts.
The increasing awareness of the impact of spontaneous movements on neuronal activity has raised the need to track behavior. We present FreiPose, a versatile learning-based framework to directly capture 3D motion of freely definable points with high precision (median error < 3.5% body length, 41.9% improvement compared to state-of-the-art) and high reliability (82.8% keypoints within < 5% body length error boundary, 72.0% improvement). The versatility of FreiPose is demonstrated in two experiments: (1) By tracking freely moving rats with simultaneous electrophysiological recordings in motor cortex, we identified neuronal tuning to behavioral states and individual paw trajectories. (2) We inferred time points of optogenetic stimulation in rat motor cortex from the measured pose across individuals and attributed the stimulation effect automatically to body parts. The versatility and accuracy of FreiPose open up new possibilities for quantifying behavior of freely moving animals and may lead to new ways of setting up experiments.
The activity state of neuronal populations is key to understanding information processing in the brain. Most of our knowledge about sensory processing and perception comes from studying local changes in firing rates and local field potentials (LFP) evoked by external stimuli. However, most of the cortical activity is generated intrinsically, can originate spontaneously in almost any cortical area, and spreads globally. The relationship between spontaneous activity and perception is largely unclear. Here we show that high levels of spontaneous activity in the beta-band (15-30 Hz) predict reduced detection, and that this influence can be overridden by stimulus-intensity adjustment. We found that vibrotactile stimulation of the forepaw of behaving rats evokes a robust modulation of event related field potentials and firing rates, reflected in power in low (3-10 Hz) and high (95-120 Hz) frequencies of the LFP, independent of detection. Only beta shows higher power prior and during undetected stimuli, and anti-correlates with firing rate. LFP oscillations in 15-120 Hz appear as short-high-power bursts, and by applying burst-rate detection algorithm in real-time, we found that changing the vibration amplitude according to beta-burst-rate can adjust beta's impact on detection bi-directionally. This result is supported by the finding that while in all bands bursts indicate transient synchronization of cell assemblies, only beta bursts are followed by a reduction in firing rate. Our results reveal that beta-bursts reflect increased spontaneous synchrony and predict reduced detection, suggesting a dynamic state that competes with the detection of external stimuli.
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