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CONTROL Walking Study

Cerebral Networks of Locomotor Learning and Retention in Older Adults

Status
Completed
Phases
Phase 1
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT03790657
Enrollment
72
Registered
2018-12-31
Start date
2019-08-01
Completion date
2024-08-01
Last updated
2025-09-22

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Aging

Keywords

aging, walking, brain, electrical stimulation

Brief summary

Older adults often experience substantial deficits in walking ability, especially for walking tasks that are more complex such as obstacle crossing. This is due in part to changes in the brain that make performance of physical and cognitive tasks more difficult. Rehabilitation can help to improve walking ability, but effective rehabilitation is time consuming and expensive. New approaches are needed to improve the efficiency of rehabilitation so that gains in walking ability are widely attainable. A promising strategy is to focus on enhancing motor learning, which is defined as improved ability to perform a motor task due to practice or experience. The investigators will investigate the use of non-invasive brain stimulation to increase motor learning and retention of the newly learned walking skills. The investigators will also use neuroimaging to assess brain characteristics that explain how motor learning works. The knowledge gained from this study is expected to contribute to better understanding of mechanistic targets and intervention approaches to improve rehabilitation of walking.

Detailed description

Aging often leads to substantial declines in walking function, especially for walking tasks that are more complex such as obstacle crossing. This is due in part to a lack of continued practice of complex walking (sedentary lifestyle) combined with age-related deficits of brain structure and the integrity of brain networks. Neurorehabilitation can contribute to recovery of lost walking function in older adults, but major and persistent improvements are elusive. A cornerstone of neurorehabilitation is motor learning, defined as an enduring change in the ability to perform a motor task due to practice or experience. Unfortunately, in most clinical settings, the time and cost demands of delivering a sufficiently intensive motor learning intervention is not feasible. There is a need for research to develop strategies for enhancing motor learning of walking (locomotor learning) in order to improve the effectiveness of neurorehabilitation. The objective of this study is to use non-invasive brain stimulation to augment locomotor learning and to investigate brain networks that are responsible for locomotor learning in mobility-compromised older adults. The investigators have shown that frontal brain regions, particularly prefrontal cortex, are crucial to control of complex walking tasks. The investigators' neuroimaging and neuromodulation studies also show that prefrontal cortex structure and network connectivity are important for acquisition and consolidation of new motor skills. However, a major gap exists regarding learning of walking tasks. The proposed study is designed to address this gap. The investigators' pilot data from older adults shows that prefrontal transcranial direct current stimulation (tDCS) administered during learning of a complex obstacle walking task contributes to multi-day retention of task performance. In the proposed study the investigators will build upon this pilot work by conducting a full scale trial that also investigates mechanisms related to brain structure, functional activity, and network connectivity. The investigators will address the following specific aims: Specific Aim 1: Determine the extent to which prefrontal tDCS augments the effect of task practice for retention of performance on a complex obstacle walking task. Specific Aim 2: Determine the extent to which retention of performance is associated with individual differences in baseline and practice-induced changes in brain measures (including gray matter volume and brain network segregation). Specific Aim 3: Investigate the extent to which tDCS modifies resting state network segregation. The investigators anticipate that prefrontal tDCS will augment retention of locomotor learning, and that the data will provide the first evidence of specific brain mechanisms responsible for locomotor learning/retention in older adults with mobility deficits. This new knowledge will provide a clinically feasible intervention approach as well as reveal mechanistic targets for future interventions to enhance locomotor learning and retention.

Interventions

BEHAVIORALpractice of a complex walking task

walking over obstacles

mild electrical stimulation delivered to the frontal region of the brain

30 seconds of mild electrical stimulation delivered to the frontal region of the brain

Sponsors

VA Office of Research and Development
Lead SponsorFED

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
DOUBLE (Subject, Outcomes Assessor)

Masking description

Participants will not be told which dosage group they are assigned to. Outcomes Assessors will not be told which dosage group the participant was randomized to.

Intervention model description

Participants will randomized to one of two dosages of transcranial direct current stimulation (tDCS): Dosage A or Dosage B

Eligibility

Sex/Gender
ALL
Age
65 Years to No maximum
Healthy volunteers
Yes

Inclusion criteria

* age 65 years or older * preferred 10m walking speed \< 1.1 m/s * self-report of some difficulty with walking tasks, such as becoming tired when walking a quarter mile, or when climbing two flights of stairs, or when performing household chores. * Willingness to be randomized to either study group and to participate in all aspects of study assessment and intervention

Exclusion criteria

* Diagnosed neurological disorder or injury of the central nervous system, or observation of symptoms consistent with such a condition (Alzheimer's, Parkinson's, stroke, etc.) * Contraindications to non-invasive brain stimulation (e.g., metal in head, wound on scalp) * Contraindications to magnetic resonance imaging (e.g., metal in body, claustrophobia, etc). * Use of medications affecting the central nervous system * severe arthritis, such as awaiting joint replacement * severe obesity (body mass index \> 35) * current cardiovascular, lung or renal disease; diabetes; terminal illness * myocardial infarction or major heart surgery in the previous year * cancer treatment in the past year, except for nonmelanoma skin cancers and cancers having an excellent prognosis (e.g., early stage breast or prostate cancer) * current diagnosis of schizophrenia, other psychotic disorders, or bipolar disorder * uncontrolled hypertension at rest (systolic \> 180 mmHg and/or diastolic \> 100 mmHg) * bone fracture or joint replacement in the previous six months * current participation in physical therapy for lower extremity function or cardiopulmonary rehabilitation * current enrollment in any clinical trial * difficulty communicating with study personnel, and/or non-English speaking * planning to relocate out of the area during the study period * clinical judgment of investigative team regarding safety or non-compliance

Design outcomes

Primary

MeasureTime frameDescription
Walking Speed Change From BaselineMeasured at follow up visit (approximately three weeks after baseline)Change in the fastest safe walking speed over a complex walking course

Secondary

MeasureTime frameDescription
Prefrontal Cortex Gray Matter Volume Change From BaselineMeasured at follow up visit (approximately three weeks after baseline)Change in the volume of gray matter in the prefrontal cortex, as measured by MRI
Brain Resting State Network Segregation (Z-transformed Correlation Coefficient)Measured at follow up visit (approximately three weeks after baseline)Resting-state functional MRI was used to measure the segregation of large-scale brain networks. Connectivity strength was quantified using Fisher z-transformed correlation coefficients, averaged across regions of interest within each network. Results are reported as mean z-scores for each group. Higher values reflect greater segregation (i.e., stronger within-network compared to between-network connectivity).

Countries

United States

Participant flow

Pre-assignment details

Participants were screened to ensure they met all inclusion/exclusion criteria, did not have major disease or injury affecting brain function or walking function, were medically stable, and could safely participate in the study protocol.

Participants by arm

ArmCount
Active tDCS
20 minutes of mild electrical stimulation delivered to the frontal region of the brain during practice of a complex walking task
32
Sham tDCS
30 seconds of mild electrical stimulation delivered to the frontal region of the brain during practice of a complex walking task
36
Total68

Withdrawals & dropouts

PeriodReasonFG000FG001
Overall StudyAdverse Event11
Overall StudyWithdrawal by Subject11

Baseline characteristics

CharacteristicActive tDCSSham tDCSTotal
Age, Continuous72.97 years
STANDARD_DEVIATION 5.65
75.83 years
STANDARD_DEVIATION 8.06
74.49 years
STANDARD_DEVIATION 7.03
Ethnicity (NIH/OMB)
Hispanic or Latino
2 Participants2 Participants4 Participants
Ethnicity (NIH/OMB)
Not Hispanic or Latino
30 Participants34 Participants64 Participants
Ethnicity (NIH/OMB)
Unknown or Not Reported
0 Participants0 Participants0 Participants
Montreal Cognitive Assessment26.41 units on a scale
STANDARD_DEVIATION 1.88
26.58 units on a scale
STANDARD_DEVIATION 2.6
26.5 units on a scale
STANDARD_DEVIATION 2.29
Race (NIH/OMB)
American Indian or Alaska Native
0 Participants1 Participants1 Participants
Race (NIH/OMB)
Asian
1 Participants0 Participants1 Participants
Race (NIH/OMB)
Black or African American
1 Participants2 Participants3 Participants
Race (NIH/OMB)
More than one race
0 Participants0 Participants0 Participants
Race (NIH/OMB)
Native Hawaiian or Other Pacific Islander
0 Participants0 Participants0 Participants
Race (NIH/OMB)
Unknown or Not Reported
0 Participants0 Participants0 Participants
Race (NIH/OMB)
White
30 Participants33 Participants63 Participants
Sex: Female, Male
Female
8 Participants17 Participants25 Participants
Sex: Female, Male
Male
24 Participants19 Participants43 Participants
Walking speed1.25 meters per second
STANDARD_DEVIATION 0.23
1.19 meters per second
STANDARD_DEVIATION 0.19
1.22 meters per second
STANDARD_DEVIATION 0.21

Adverse events

Event typeEG000
affected / at risk
EG001
affected / at risk
deaths
Total, all-cause mortality
0 / 320 / 36
other
Total, other adverse events
1 / 321 / 36
serious
Total, serious adverse events
0 / 320 / 36

Outcome results

Primary

Walking Speed Change From Baseline

Change in the fastest safe walking speed over a complex walking course

Time frame: Measured at follow up visit (approximately three weeks after baseline)

ArmMeasureValue (MEAN)Dispersion
Active tDCSWalking Speed Change From Baseline0.033 meters per secondStandard Deviation 0.097
Sham tDCSWalking Speed Change From Baseline0.041 meters per secondStandard Deviation 0.104
Secondary

Brain Resting State Network Segregation (Z-transformed Correlation Coefficient)

Resting-state functional MRI was used to measure the segregation of large-scale brain networks. Connectivity strength was quantified using Fisher z-transformed correlation coefficients, averaged across regions of interest within each network. Results are reported as mean z-scores for each group. Higher values reflect greater segregation (i.e., stronger within-network compared to between-network connectivity).

Time frame: Measured at follow up visit (approximately three weeks after baseline)

Population: A total of 65 participants underwent MRI imaging, of which only 50 participants were included. Eight participants were missing either baseline or post-assessment scan. Four participants did not complete all necessary scanning sequences.

ArmMeasureValue (MEAN)Dispersion
Active tDCSBrain Resting State Network Segregation (Z-transformed Correlation Coefficient)-.0017 z-transformed correlation coefficientStandard Deviation 0.0253
Sham tDCSBrain Resting State Network Segregation (Z-transformed Correlation Coefficient)-.0002 z-transformed correlation coefficientStandard Deviation 0.0215
Secondary

Prefrontal Cortex Gray Matter Volume Change From Baseline

Change in the volume of gray matter in the prefrontal cortex, as measured by MRI

Time frame: Measured at follow up visit (approximately three weeks after baseline)

Population: Some participants did not complete the MRI assessment at baseline or at follow-up due to technical or logistical difficulties.

ArmMeasureValue (MEAN)Dispersion
Active tDCSPrefrontal Cortex Gray Matter Volume Change From Baseline-14.66 cubic millimetersStandard Deviation 81.75
Sham tDCSPrefrontal Cortex Gray Matter Volume Change From Baseline-3.45 cubic millimetersStandard Deviation 90.6

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026