Summary: Aging and Parkinson’s disease force the brain into “overdrive” to maintain balance, paradoxically leading to a higher risk of falling. While young adults recover from balance disturbances with an efficient, two-wave neural response, older populations show massive brain and muscle activity even for minor slips.
This increased neural engagement suggests that the brain is working harder but producing less robust physical recoveries. Furthermore, the study found that this “stiffening” of opposing muscles—a common compensatory tactic—actually correlates with worse overall balance performance.
Key Facts
- Neural Inefficiency: Older adults and those with Parkinson’s show larger brain responses for small balance threats than young adults do for major ones.
- The Stiffening Trap: When recovering balance, these populations often activate opposing muscles simultaneously, leading to joint stiffness that hinders recovery.
- Brain-Balance Tradeoff: Higher brain activity during balance tasks is a direct indicator of a reduced ability to physically recover from a fall.
- Predictive Testing: Researchers believe monitoring muscle activity during a “rug-pull” test could serve as a non-invasive way to measure brain engagement and predict fall risk.
Source: SfN
Lena Ting, from Emory University, and colleagues explored how brain and muscle activity during balance recovery change due to aging and Parkinson’s.
Previously, Ting’s research group revealed that when they pulled a rug out from under young adults to trigger balance recovery, these individuals experienced an immediate involuntary brainstem and muscle response followed by a second wave of activity in the brain and muscle in more difficult balance disturbances.
In this new study on older adults with and without Parkinson’s, published in eNeuro, the researchers discovered that these populations have larger brain responses and more muscle signals even when balance disturbances are small.
Says Ting, “Balance recovery takes more energy and engagement from the brain in these populations. We found that, when people require more brain activity to balance, they have less robust ability to recover their balance.”
The researchers also discovered that when older people activated a muscle to recover their balance, the opposing muscles would stiffen up. The degree to which people stiffened their muscles was also linked to worse balance performance.
The researchers emphasize that their technical approach could have clinical implications as a more precise way to gauge whether someone is at risk for poor balance recovery.
Ting notes that they still have more work to do in optimizing the approach, but adds, “We may be able to determine whether someone has increased brain activity simply by assessing muscle activity after pulling a rug out from under you.” This method could help identify at-risk people before they fall, who may benefit from balance training and exercise.
Key Questions Answered:
A: It’s a matter of neural efficiency. This study shows that when your brain has to work at 100% just to handle a small slip, it has no “reserve” left for major disturbances, leading to a less robust recovery.
A: Surprisingly, no. The researchers found that when people stiffen their opposing muscles to stabilize themselves, it actually makes their balance performance worse. Fluidity, not stiffness, is key to recovery.
A: Yes. By measuring how your muscles react to a sudden floor shift, scientists can now “see” how hard your brain is working. This could help identify at-risk individuals years before a dangerous fall occurs.
Editorial Notes:
- This article was edited by a Neuroscience News editor.
- Journal paper reviewed in full.
- Additional context added by our staff.
About this neurology and aging research news
Author: SfN Media
Source: SfN
Contact: SfN Media – SfN
Image: The image is credited to Neuroscience News
Original Research: Closed access.
“Cortically Mediated Muscle Responses to Balance Perturbations Increase with Perturbation Magnitude in Older Adults with and without Parkinson’s Disease” by Scott E. Boebinger, Aiden M. Payne, Jifei Xiao, Giovanni Martino, Michael R. Borich, J. Lucas McKay and Lena H. Ting. eNeuro
DOI:10.1523/ENEURO.0423-25.2026
Abstract
Cortically Mediated Muscle Responses to Balance Perturbations Increase with Perturbation Magnitude in Older Adults with and without Parkinson’s Disease
We lack a mechanistic understanding of how cortical contributions to balance control change in aging and Parkinson’s disease (PD). Balance is governed by brainstem circuits, with higher-order centers like the cortex or basal ganglia becoming engaged as challenge increases or balance health declines.
We previously showed that parallel sensorimotor feedback loops engaging brainstem and cortical circuitry contribute to muscle activity for balance control in young adults (YAs).
Here, we analyze data from male and female older adults (OAs) with and without PD, decomposing perturbation-evoked tibialis anterior and medial gastrocnemius muscle activity into hierarchical components based on latencies of feedback control loops.
We found that balance-correcting muscle activity followed a stereotypical waveform of long-latency responses (LLRs): LLR1 began ∼120ms and LLR2 occurred ∼210ms, respectively, consistent with subcortical and cortical feedback latencies.
Both LLRs increased with balance challenge and could be explained by center of mass kinematics. Perturbation-evoked antagonist muscle activity consisted of destabilizing and stabilizing components categorized based on whether they resist the kinematic errors that drive their activation.
The destabilizing component occurred at ∼180ms and was negatively correlated with clinical measures of balance ability in the OA but not PD group. Exploratory comparisons showed OA and PD groups had larger LLR2s at lower challenge levels than YAs, consistent with greater cortical engagement during balance with aging.
These findings demonstrate that a neuromechanical model can decompose perturbation-evoked muscle activity into hierarchical components related to clinical balance ability and identify mechanistic changes in the neural control of balance without direct brain measurements.
