EEG Bursts Reveal Distinct Brain Rhythms Behind Parkinson’s and Freezing of Gait

One of the most unsettling experiences in Parkinson’s disease is not tremor or stiffness, but the sudden, inexplicable moment when the feet seem glued to the floor. This phenomenon, known as freezing of gait, strikes without warning, robs people of mobility, and dramatically raises the risk of falls. Despite decades of research, the brain mechanisms behind freezing remain stubbornly elusive. Now, a large multi-site study published in the Journal of Neurology offers a fresh clue, suggesting that the answer may lie not in how strongly the brain oscillates, but in the precise timing of its rhythmic bursts.

The research, led by Matthew Leedom and Arun Singh of the University of South Dakota together with colleagues at Oregon Health & Science University and other institutions, analyzed resting-state electroencephalography recordings from 237 participants across three study sites. The cohort included 88 healthy controls and 149 people with Parkinson’s disease, all assessed in their clinically defined ON-medication state while taking their usual dopaminergic medication. Among the patients, 73 experienced freezing of gait and 76 did not, allowing the team to ask a deceptively simple question: do the brains of people with Parkinson’s, and specifically those with freezing, generate neural rhythms differently?

To answer it, the researchers abandoned the traditional approach of measuring average spectral power. Conventional EEG analysis averages oscillatory activity over time, which can obscure the fact that brain rhythms do not behave like continuous signals. Beta activity, the frequency range most closely tied to Parkinson’s motor symptoms, actually arrives in short, intermittent packets known as bursts. By detecting these bursts directly, the team could quantify how often they occurred, how long they lasted, how strong they were, and how much of the recording time the brain spent in a burst state, metrics that capture the temporal architecture of neural synchrony rather than its blunt average.

The technical execution was carefully harmonized. Because the three sites used different EEG systems with different sampling rates, the analysis was restricted to a common set of 11 electrodes spanning frontal, central, parietal, and occipital regions. The primary focus fell on the midline fronto-central Cz electrode, a location relevant to lower limb control and gait. Signals were filtered into four frequency bands, theta from 4 to 8 hertz, alpha from 8 to 13 hertz, low beta from 13 to 20 hertz, and high beta from 20 to 30 hertz, and a burst was defined as any moment when the amplitude envelope of the filtered signal exceeded the 75th percentile threshold for that participant, channel, and band. Rigorous artifact removal, independent component analysis, and false discovery rate correction for multiple comparisons guarded against spurious findings.

The headline result was strikingly frequency-specific. People with Parkinson’s disease showed significantly altered low-beta burst dynamics at the mid-frontal region: their low-beta bursts were more frequent, but shorter in duration, compared with healthy controls. Both effects survived statistical correction, with corrected p-values of 0.004 for burst rate and duration. Crucially, burst amplitude and the total proportion of time spent in a burst did not differ between groups, indicating that the disease changes the temporal organization of beta activity, its rhythm of firing and resting, rather than simply cranking up oscillatory power. Exploratory topographic maps showed that these low-beta abnormalities extended beyond the mid-frontal electrode across several central and posterior channels, consistent with the idea that beta bursts are network-level events involving distributed cortical regions rather than isolated local oscillations.

That pattern contrasts intriguingly with earlier invasive findings. Recordings from the subthalamic nucleus, a deep brain target for stimulation therapy, have typically linked prolonged beta bursts to greater motor impairment, particularly when patients are off medication. The current cortical findings, gathered at rest while patients were medicated, instead suggest a fragmentation of beta activity, more bursts that terminate quickly, possibly reflecting dopaminergic modulation, residual disease-related dysfunction, or compensatory cortical reorganization. The authors are careful to note that without simultaneous cortical-subthalamic recordings or direct ON-OFF medication comparisons, the precise mechanism remains an open question.

When the team turned to freezing of gait, the picture changed. In three-group comparisons across healthy controls, patients without freezing, and patients with freezing, low-beta burst rate and duration differed across groups, but when the analysis was restricted to Parkinson’s patients alone and adjusted for disease duration and motor severity on the MDS-UPDRS scale, no significant differences emerged between those with and without freezing. In other words, the low-beta burst abnormalities appear to mark Parkinson’s disease and general motor-network dysfunction rather than freezing specifically. Some apparent freezing-related differences in the unadjusted data likely reflected the fact that patients with freezing tend to have longer disease duration and more severe motor symptoms.

Instead, the strongest signal tied to freezing came from an entirely different frequency band. Theta burst amplitude at the mid-frontal electrode correlated positively with freezing severity, measured with site-standardized questionnaire scores. Both the median theta burst amplitude and the 90th percentile amplitude, capturing the strongest theta events, showed significant correlations with severity, with Spearman’s rho of 0.22 and corrected p-values of 0.032 and 0.028 respectively. No beta-band metric survived correction in these severity analyses. This dissociation is physiologically compelling: theta activity in mid-frontal cortex has long been linked to cognitive control and conflict monitoring, and freezing episodes are most likely to occur in situations demanding heightened executive control, such as turning, navigating doorways, or dual-tasking. Elevated theta burst amplitude could reflect greater recruitment of cognitive control networks as a compensatory response to failing automatic motor control, or alternatively a maladaptive state of network instability and excessive conflict monitoring. Because the data were cross-sectional and collected at rest, the study cannot definitively distinguish between these interpretations.

The findings carry practical implications. Burst-based EEG metrics may serve as complementary biomarkers that capture aspects of Parkinson’s pathophysiology invisible to conventional spectral analysis. A low-beta burst timing signature could help characterize motor-network dysfunction, while theta burst amplitude might offer a continuous, quantitative index of the cognitive-motor burden underlying freezing severity, potentially useful for tracking disease progression or evaluating therapies. Notably, the continuous severity measure proved more sensitive than the categorical freezing-versus-non-freezing classification, hinting that neural dysfunction accumulates along a spectrum rather than switching on at a diagnostic threshold.

The study also has honest limitations. Harmonizing to 11 channels limited spatial resolution and ruled out source localization, resting-state recordings may miss the dynamic processes that unfold during actual walking and freezing episodes, and the timing of patients’ last medication dose was not uniformly standardized across sites, leaving open whether medication itself shaped the burst patterns. FOG severity was measured with different questionnaires at different sites, requiring within-site normalization, and the operational definition of bursts via an amplitude threshold, while consistent with prior work, should not be taken to represent discrete biological events in every instance. Still, the scale of the cohort, the multi-site harmonization, and the clean frequency-specific dissociation make this one of the most systematic examinations of cortical burst dynamics in Parkinson’s disease to date. The next step, the authors suggest, is to combine standardized medication manipulations, higher-density recordings, and tasks that provoke freezing in the laboratory, bringing science closer to the moment when the brain’s rhythm of rhythm itself explains why feet freeze.

Subject of Research: Frequency-specific EEG burst dynamics in Parkinson's disease and freezing of gait

Article Title: Frequency-Specific EEG burst dynamics in Parkinson’s Disease and freezing of gait

Article References: Frequency-Specific EEG burst dynamics in Parkinson’s Disease and freezing of gait. (n.d.). https://doi.org/10.1007/s00415-026-14149-6

Image Credits: AI Generated

DOI: 10.1007/s00415-026-14149-6

Keywords: Parkinson's disease, freezing of gait, EEG, beta bursts, theta oscillations, neural oscillations, basal ganglia, motor networks, cognitive control, biomarkers, neurophysiology, Journal of Neurology