Julia receives NSF CAREER Award (“Adaptation and learning processes in human locomotion”).
The NSF CAREER program provides 5 year awards to tenure-track Assistant Professors to support outstanding research projects and career development activities, including education and outreach initiatives. Read the full abstract.
Journal of Experimental Biology doi:10.1242/jeb.140723 (
Neuromuscular effort predicts walk-run transition speed in normal and adapted human gaits
Jan Stenum1 and Julia T Choi 1
1 Department of Kinesiology, University of Massachusetts, Amherst, Massachusetts
Often, humans and other animals move in a manner that minimizes energy costs. It is more economical to walk at slow speeds, and to run at fast speeds. Here we asked whether humans select a gait that minimizes neuromuscular effort under novel and unfamiliar conditions, by imposing interlimb asymmetry during split-belt treadmill locomotion. The walk-run transition speed changed markedly across different gait conditions: forward, backward, hybrid (one leg forward, one leg backward), and forward with speed differences (one leg faster than the other). Most importantly, we showed that the human walk-run transition speed across conditions was predicted by changes in neuromuscular effort (i.e., summed leg muscle activations). Our results for forward gait and forward gait with speed-differences suggest that human locomotor patterns are optimized under both familiar and novel gait conditions by minimizing the motor command for leg muscle activations.
Journal of Physiology (OI: 10.1113/JP271996
Error signals driving locomotor adaptation: Cutaneous feedback from the foot is used to adapt movement during perturbed walking
Julia T Choi 1,2, Peter Jensen 2, Jens Bo Nielsen 2 and Laurent J Bouyer3
1 Department of Kinesiology, University of Massachusetts, Amherst, Massachusetts
2 Neural Control of Movement Research Group, Department of Neuroscience and Pharmacology & Department of Nutrition, Exercise and Sport, University of Copenhagen, Denmark
3 Department of Rehabilitation, Université Laval & Center for Interdisciplinary Research in Rehabilitation and Social Integration, Québec City, Canada
Locomotor patterns must be adapted to external forces encountered during daily activities. The contribution of different sensory inputs to detecting perturbations and adapting movements during walking is unclear. Here we examined the role of cutaneous feedback in adapting walking patterns to force perturbations. Forces were applied to the ankle joint during the early swing phase using an electrohydraulic ankle-foot orthosis. Repetitive 80 Hz electrical stimulation was applied to disrupt cutaneous feedback from the superficial peroneal nerve (foot dorsum) and medial plantar nerve (foot sole) during walking (Choi et al. 2013). Sensory tests were performed to measure cutaneous touch threshold and perceptual threshold of force perturbations. Ankle movement were measured while subjects walked on the treadmill over three periods: baseline (1 min), adaptation (1 min) and post-adaptation (3 min). Subjects (n = 10) showed increased touch thresholds measured with Von Frey monofilaments and increased force perception thresholds with stimulation. Stimulation reduced the magnitude of walking adaptation to force perturbation. In addition, we compared the effects of interrupting cutaneous feedback using anaesthesia (n = 5) instead of repetitive nerve stimulation. Foot anaesthesia reduced ankle adaptation to external force perturbations during walking. Our results suggest that cutaneous input plays a role in force perception, and may contribute to the ‘error’ signal involved in driving walking adaptation when there is a mismatch between expected and actual force.
Locomotor sequence learning in visually guided walking
Julia T Choi 1,2, Peter Jensen 2 and Jens Bo Nielsen 2
1 Department of Kinesiology, University of Massachusetts, Amherst, Massachusetts
2 Neural Control of Movement Research Group, Department of Neuroscience and Pharmacology & Department of Nutrition, Exercise and Sport, University of Copenhagen, Denmark
Voluntary limb modifications must be integrated with basic walking patterns during visually guided walking. Here we tested whether voluntary gait modifications can become more automatic with practice. We challenged walking control by presenting visual stepping targets that instructed subjects to modify step length from one trial to the next. Our sequence learning paradigm is derived from the serial reaction-time (SRT) task that has been used in upper limb studies. Both random and ordered sequences of step lengths were used to measure sequence-specific and sequence non-specific learning during walking. In addition, we determined how age (i.e., healthy young adults vs. children) and biomechanical factors (i.e., walking speed) affected the rate and magnitude of locomotor sequence learning. The results showed that healthy young adults (age 24 ± 5 years, N = 20) could learn a specific sequence of step lengths over 300 training steps. Younger children (age 6-10 years, N = 8) have lower baseline performance, but their magnitude and rate of sequence learning was the same compared to older children (11-16 years, N = 10) and healthy adults. In addition, learning capacity may be more limited at faster walking speeds. To our knowledge, this is the first study to demonstrate that spatial sequence learning can be integrated with a highly automatic task like walking. These findings suggest that adults and children use implicit knowledge about the sequence to plan and execute leg movement during visually guided walking.
39th Annual Meeting of the American Society of Biomechanics (August 2015)
Walk-run transitions are dependent on interlimb coupling
Jan Stenum and Julia T. Choi
Department of Kinesiology, University of Massachusetts, Amherst MA
Walk-run transition in adult humans has been studied during forward gaits. However, it is unknown how contralateral leg movement affects walk-run transitions. We examined walk-run transitions on a split-belt treadmill where the speed and direction of each belt can be controlled independently. We hypothesize that walk-run transitions are dependent on contralateral leg movements. A split-belt treadmill was used to test 4 different gait conditions: forward, split-belt (i.e., constant speed difference of 0.5 m/s between belts), hybrid (i.e., left leg moved backward and right leg moved forward) and backwards. Here we define preferred walk-run transition speed as the speed where a subject is equally likely to choose walk and run. We found that walk-run transition occurred at different speeds across four conditions. On average, subjects transitioned at 2.00 ± 0.20 m/s in the forward condition. When one leg moved faster than the other in the split condition, the transition speed on the fast leg increased to 2.36 ± 0.20 m/s. The transition speed was 1.47 ± 0.15 m/s in the backward condition. When one leg walked forward, and one backward in the hybrid condition, both legs transitioned to running together at a lower speed. The average walk-to-run transition speed in hybrid locomotion was 1.17 ± 0.16 m/s. We did not observe walking on one leg, and running on the other leg during hybrid locomotion for the tested speed combinations. In sum, walk-run transition speed is dependent on interlimb speed and direction differences. To our knowledge, this is the first study to investigate the effects of interlimb coupling on human walk-run transitions.
Cerebral Cortex 2015 Jul;25(7):1981-6.
Disruption of Locomotor Adaptation with Repetitive Transcranial Magnetic Stimulation Over the Motor Cortex
Julia T. Choi1,3, Laurent J. Bouyer2 and Jens Bo Nielsen3
1University of Copenhagen, Denmark, 2Université Laval and Center for Interdisciplinary Research in Rehabilitation and Social Integration, Québec City, Canada, and 3 University of Massachusetts Amherst, Amherst, MA, USA
Locomotor patterns are adapted on a trial-and-error basis to account for predictable dynamics. Once a walking pattern is adapted, the new calibration is stored and must be actively de-adapted. Here, we tested the hypothesis that storage of newly acquired ankle adaptation in walking is dependent on corticospinal mechanisms. Subjects were exposed to an elastic force that resisted ankle dorsiflexion during treadmill walking. Ankle movement was adapted in <30 strides, leading to after-effects on removal of the force. We used a crossover design to study the effects of repetitive transcranial magnetic stimulation (TMS) over the primary motor cortex (M1), compared with normal adaptation without TMS. In addition, we tested the effects of TMS over the primary sensory cortex (S1) and premotor cortex (PMC) during adaptation. We found that M1 TMS, but not S1 TMS and PMC TMS, reduced the size of ankle dorsiflexion after-effects. The results suggest that suprathreshold M1 TMS disrupted the initial processes underlying locomotor adaptation. These results are consistent with the hypothesis that corticospinal mechanisms underlie storage of ankle adaptation in walking.
Annual Massachusetts Statewide Undergraduate Research Conference (April 2015)
Gait Adaptation on a Portable and Passive Split-Belt Treadmill
Brian J. Young1, Frank Sup1,2 and Julia T. Choi1
Departments of 1Kinesiology and 2Mechanical and Industrial Engineering, University of Massachusetts, Amherst, MA
Walking requires precise coordination of movement between two legs. Interlimb coordination is often disrupted after damage to the central nervous system (e.g., stroke), resulting in walking patterns that are slowed, asymmetric and inefficient. Previous studies have shown that training with powered split-belt treadmills can lead to a more symmetric walking pattern post-adaptation in stroke subjects. The focus of this study is to test a novel gait training platform (1st generation passive split-belt treadmill) that could drive adaptation of walking symmetry. We examined healthy adults (18-40 yrs old) walking on a passive split-belt treadmill (no motors to drive the belt). The adaptation phase on the passive split-belt treadmill lasted for 5 minutes. To evaluate the presence of after-effects, participants walked over-ground before and after the adaptation phase on the passive split- belt treadmill. Motion capture, electromyography, and force platform data were recorded in all trials. Adaptation was measured by changes in spatial and temporal gait parameters (e.g., step length, stance time, swing time), joint kinematics (e.g., hip, knee, ankle angle) and leg muscle activations (e.g., EMG). The results will inform about the potential for using the passive split-belt treadmill as a rehabilitation tool. The passive split-belt would be a more affordable option compared to a powered split-belt treadmill. Having access to rehabilitation in the home is important and would allow patients to continue training for longer periods of time and maximize gait improvements.
Program No. 831.07. Neuroscience 2014 Abstracts. Washington, DC: Society for Neuroscience, 2014.
Locomotor Sequence Learning in Visually Guided Walking
Julia T Choi 1,2, Peter Jensen 2,, and Jens Bo Nielsen 2
1University of Massachusetts, Amherst, MA USA; 2University of Copenhagen, Denmark
We tested whether spatial sequence learning can be integrated with a highly automatic task like walking. Based on the serial reaction response task, introduced by Nissen and Bullemer (1987), we developed a visuo-locomotor task where subjects controlled step length to hit visual targets displayed on a monitor while walking on a treadmill (Fig 1a). Subject performed a total of 7 blocks that each consisted of 100 steps (Fig 1b), without explicit knowledge of the sequence. In random blocks, the targets appeared randomly at locations that required different step lengths (i.e., short, normal, long). In sequence blocks, subjects were presented with a repeating sequence (i.e., short-long-normal-long-short-normal). The first random block (R1) was used to familiarize the subject to the task. The second random block (R2) provided a measure of final baseline performance. In subsequent training blocks (S1-3), subjects were presented with a repeating sequence. The last random block (R3) was used to measure overall improvement achieved. None of the subjects gave accurate descriptions of the repeating sequence when asked at the end of the experiment. Implicit sequence-specific learning was calculated as the difference in performance between the last training block (S3) and the last random block (R3); non-specific learning was calculated as the difference between blocks R2 and R3. We tested 6 healthy control subjects walking at 2.3 ± 0.2 km/h. Group averaged number of hits increased over the three training blocks, but decreased again in the last random block (*P < 0.05). Performance changes were also measured using endpoint error. We analyzed step frequency, and found that cadence was maintained across 7 blocks of testing. The difference in performance on re-introduction of the random sequence indicates sequence-specific effects rather than non-specific effects. In other words, subjects used knowledge about the step length sequence to plan and execute the movement (rather than simply reacting to the visual stimuli). The results suggest that step-by-step gait modifications can be optimized through visuo-locomotor training.
World Congress of Biomechanics (Boston, MA, 2014)
Adapting Gait Symmetry With Visually Guided Locomotor Training: ‘Virtual’ Split-Belt Adaptation
Julia T Choi 1,2, Peter Jensen 1, and Jens Bo Nielsen 1
1University of Massachusetts, Amherst, MA USA; 2University of Copenhagen, Denmark
Visually guided movements must be constantly adapted to maintain accuracy (e.g., foot placement). Here we applied principles of visuomotor adaptation to drive inter-limb adaptation of joint kinematics in a walking task that demands voluntary control of endpoint (i.e., foot) position. We hypothesized that step length symmetry can be adapted and stored after training with mismatched visual feedback on two legs (i.e., ‘virtual’ split-belt adaptation). 8 healthy subjects (7M/1F, 26±6 yrs) were tested. We created a computer task where subjects modified step length trial-by-trial to hit virtual targets while walking on a treadmill (Fig. 1A). The relationship between screen-space and treadmill-space was defined by a visuomotor gain for each leg. Each test consisted of the baseline period (same gain on both legs), adaptation period (one high, one low gain) and post-adaptation period (same gain on both legs). During the adaptation period, the leg adapted with the higher gain appeared to move fast, and the other leg appeared to move slowly on display. The ‘fast leg’ and ‘slow leg’ both adapted to maintain accuracy of foot placement relative to the targets. Figure 1B shows that step length gradually became more asymmetric during adaptation. The fast leg shortened step length (to correct overshoot), and the slow leg lengthened step length (to correct undershoot). In the post-adaptation period, step length asymmetry persisted (after-effect) despite the fact that the gains have returned to normal. The presence of an after-effect indicates storage of a new inter-limb visuomotor calibration. The after-effect in step length was washed out after one minute of post-adaptation walking. Step length adaptation was achieved by changing the range of limb excursion on the leading leg and trailing leg. Longer step lengths were associated with more hip flexion and knee extension on the leading leg, and more hip extension on the trailing leg. The opposite was true for shorter step lengths. The results suggest that visually guided inter-limb adaptation can alter joint kinematics and step length, a major determinant of gait stability and energetic costs. This may open up new opportunities to correct abnormal, asymmetric walking patterns in people with neurological damage (e.g., stroke).
We just got a Bertec split-belt treadmill in the lab. The two belts can be controlled independently, allowing us to adapt two legs to walk at different speeds. The treadmill is instrumented to measure forces and moments.
We will integrate this device with a motion capture system to study how people control and adapt walking patterns. We are also developing software to provide visual feedback during walking.