Goal-directed walking involves regulating foot placements to achieve specific tasks. This requires visuomotor integration. Perceptual, cognitive, and contextual salience guide attention and motor planning for navigation. Here, we quantified how perceptual salience informs lateral foot placement while walking. Participants walked along prescribed virtual paths (straight or winding), thus keeping contextual salience (the task itself) constant. We manipulated perceptual salience by systematically altering environment richness (rich vs. sparse) and path color contrast (high vs. low). We quantified head pitch angle to approximate gaze direction. We quantified lateral stepping regulation from a goal equivalent manifold framework. Our guiding hypothesis was that stepping arises from continuous decision-making action-perception processes: each step taken affects the decision of where to step next. This generated three testable predictions. First, that contextual salience alone (merely "seeing" the path) is sufficient for people to regulate stepping. However, while substantial between-path differences largely supported this, within-path differences in both head angle and stepping demonstrated that visual information (perceptual salience) also informs stepping. Second, we predicted perceptual salience of task-relevant visual information (here, of the path itself) is sufficient to guide stepping. However, while changing path color contrast did elicit more and greater changes than manipulating environmental richness, path visual saliency alone was not sufficient. Third, we predicted perceptual salience from peripheral vision also contributes to stepping. This prediction was supported, though less strongly than manipulating path visual saliency or contextual salience (straight vs. winding paths). Thus, both contextual and perceptual salience interact to influence step-to-step control of walking.NEW & NOTEWORTHY To walk in the real world, humans must navigate their environment (avoid obstacles, etc.) to reach their destination. People do this by taking steps, where each step affects the next. Here, we demonstrate how visual information contributes to such "embodied decision-making" during naturalistic walking. Context (the task), and both central and peripheral visual perception guide locomotor control of walking, down to the level of choosing where to take our next step.

Effectively navigating daily environments necessitates achieving adaptability while maintaining stability. This requires integrating sensory feedback, primarily from the visual system, to maintain balance and maneuverability as we walk. This study examined the impact of visual information salience on lateral balance and stepping. Twenty-eight healthy adults (16F/12M; 26.16±4.23 years) participated. Participants walked along each of two virtual paths (Straight vs. Winding), having each of two path color contrasts (High vs. Low), in each of two environments with differing visual richness (Rich vs. Sparse). We quantified stepping errors as the percentage of steps landing outside designated path boundaries. We computed means ( μ ) and standard deviations ( σ ) of the minimum mediolateral margins of stability ( MoS L ), and we computed lateral Probability of Instability ( PoI L ) to assess participants’ risk of taking unstable ( MoS L < 0) steps. On Straight paths, participants made more stepping errors on Low (vs. High) contrast paths for both environments, and exhibited decreased σ ( MoS L ) in Sparse (vs. Rich) environments on paths of both visual contrasts. On Winding paths, participants made the most stepping errors on Low Contrast paths in Sparse environments. They walked with smaller μ ( MoS L ) and exhibited higher PoI L on Low Contrast paths in both environments, and they exhibited higher PoI L in Sparse environments on paths of both visual contrasts. The effects of diminished visual information were far more pronounced on Winding paths (vs. Straight), hindering performance and balance maintenance, as these conditions challenged both mechanical and sensory mechanisms underlying balance control.

Most often, gait biomechanics is studied during straight-ahead walking. However, real-life walking imposes various lateral maneuvers people must navigate. Such maneuvers challenge people's lateral balance and can induce falls. Determining how people regulate their stepping movements during such complex walking tasks is therefore essential. Here, 24 adults (12F/12M; Age 25.8±3.5yrs) walked on wide or narrow virtual paths that were either straight, slowly-winding, or quickly-winding. From each trial, we computed time series of participants' step widths and their lateral body positions relative to their path. We applied our Goal Equivalent Manifold framework - an analysis of how task-level redundancy impacts motor regulation - to quantify how participants adjusted their step width and lateral position from step to step as they walked on these paths. On the narrower paths, participants walked with narrower steps and less lateral position and step width variability. They did so by correcting step-to-step deviations in lateral position more, while correcting step-to-step deviations in step width less. On the winding paths, participants took both narrower and more variable steps. Interestingly, on slowly-winding paths, participants corrected step-to-step deviations in step width more by correcting step-to-step deviations in lateral position less: i.e., they prioritized maintaining step width over position. Conversely, on quickly-winding paths, participants strongly corrected step-to-step deviations in both step width and lateral position: i.e., they prioritized maintaining both approximately equally, consistent with trying to maximize their maneuverability. These findings have important implications for persons who have elevated fall risk.

BACKGROUND:Older adults have difficulty maintaining side-to-side balance while navigating daily environments. Losing balance in such circumstances can lead to falls. We need to better understand how older adults adapt lateral balance to navigate environment-imposed task constraints. RESEARCH QUESTION:How do older adults adjust mediolateral balance while walking along continually-narrowing paths, and what are the stability implications of these adjustments? METHODS:Eighteen older (71.6±6.0 years) and twenty younger (21.7±2.6 years) healthy adults traversed 25 m-long paths that gradually narrowed from 45 cm to 5 cm. Participants switched onto an adjacent path when they chose. We quantified participants' lateral center-of-mass dynamics and lateral Margins of Stability (MoSL) as paths narrowed. We quantified lateral Probability of Instability (PoIL) as the probability that participants would take a laterally unstable (MoSL<0) step as they walked. We also extracted these outcomes where participants switched paths. RESULTS:As paths narrowed, all participants exhibited progressively smaller average MoSL and increasingly larger PoIL. However, their MoSL variability was largest at both the narrowest and widest path sections. Older adults exhibited consistently both larger average and more variable MoSL across path widths. Taken into account together, these resulted in either comparable or somewhat larger PoIL as paths narrowed. Older adults left the narrowing paths sooner, on average, than younger. As they did so, older adults exhibited significantly larger average and more variable MoSL, but somewhat smaller PoIL than younger. SIGNIFICANCE:Our results directly challenge the predominant interpretation that larger average MoSL indicate "greater stability", which we argue is inconsistent with the principles underlying its derivation. In contrast, analyzing step-to-step gait dynamics, together with estimating PoIL allows one to properly quantify instability risk. Furthermore, the adaptive strategies uncovered using these methods suggest potential targets for future interventions to reduce falls in older adults.

A simple lateral dynamic walker, with swing leg dynamics and three adjustable input parameters, is used to study how motor regulation affects frontal-plane stepping. Motivated by experimental observations and phenomenological models, we imposed task-level multi-objective regulation targeting the walker’s optimal lateral foot placement at each step. The regulator prioritizes achieving step width and lateral body position goals to varying degrees by choosing a mixture parameter. Our model thus integrates a lateral mechanical template , which captures the fundamental mechanics of frontal-plane walking, with a lateral motor regulation template , an empirically verified model of how humans manipulate lateral foot placements in a goal-directed manner. The model captures experimentally observed stepping fluctuation statistics and demonstrates how linear empirical models of stepping dynamics can emerge from first-principles nonlinear mechanics. We find that task-level regulation gives rise to a goal-equivalent manifold in the system’s extended state space of mechanical states and inputs, a subset of which contains a continuum of period-1 gaits forming a semistable set: perturbations off of any of its gaits result in transients that return to the set, though typically to different gaits.

Background:Walking requires frequent maneuvers to navigate changing environments with shifting goals. Humans accomplish maneuvers and simultaneously maintain balance primarily by modulating their foot placement, but a direct trade-off between these two objectives has been proposed. As older adults rely more on foot placement to maintain lateral balance, they may be less able to adequately adapt stepping to perform lateral maneuvers.Research Question:How do older adults adapt stepping to enact lateral lane-change maneuvers, and how do physical and perceived ability influence their task performance?Methods:Twenty young (21.7 ± 2.6 yrs) and 18 older (71.6 ± 6.0 yrs) adults walked on a motorized treadmill in a virtual environment. Following an audible and visual cue, participants switched between two parallel paths, centered 0.6m apart, to continue walking on their new path. We quantified when participants initiated the maneuver following the cue, as well as their step width, lateral position, and stepping variability ellipses at each maneuver step.Results:Young and older adults did not differ in when they initiated the maneuver, but participants with lower perceived ability took longer to do so. Young and older adults also did not exhibit differences in step width or lateral positions at any maneuver step, but participants with greater physical ability reached their new path faster. While only older adults exhibited stepping adaptations prior to initiating the maneuver, both groups traded-off stability for maneuverability to enact the lateral maneuver.Significance:Physical and perceived balance ability, rather than age per se, differentially influenced maneuver task performance. Humans must make decisions related to the task of walking itself and do so based on both physical and perceived factors. Understanding and targeting these interactions may help improve walking performance among older adults.

People with balance impairments often struggle performing turns or lateral maneuvers, which can increase risk of falls and injuries. Here we asked how people’s mediolateral balance is impacted when walking on non-straight winding paths. Twenty-four healthy adults (12F / 12M; 25.8±3.5 yrs) participated. Each walked on each of six paths projected onto a treadmill, comprised of three pseudo-random path oscillation frequency combinations (straight, slowly-winding, quickly-winding), each presented at either wide or narrow width. We quantified stepping errors as the percent of steps taken off each path. We quantified minimum mediolateral Margin of Stability (MoSL) at each step and calculated means (μ) and standard deviations (σ) for each trial. We calculated lateral Probability of Instability (PoIL) as participants’ statistical risk of taking unstable (MoSL < 0) steps. On narrower paths, participants made more stepping errors and walked with smaller μ(MoSL) for all path frequencies (p < 0.001), and exhibited increased PoIL on the straight and slowly-winding paths (p < 0.001). On winding paths, participants made progressively more stepping errors and walked with smaller μ(MoSL) as oscillation frequency increased on narrow paths (all p < 0.001) and on the wide quickly-winding paths (all p < 0.001). They also consistently walked with larger σ(MoSL), and increased PoILon higher sinuosity paths of both widths (all p < 0.001). Though many took numerous unstable steps, no participant fell. Our results demonstrate healthy adults’ ability both to trade off increased risk of lateral instability for greater maneuverability, and to employ highly-versatile stepping strategies to maintain balance while walking.

People rarely walk in straight lines. Instead, we make frequent turns or other maneuvers. Spatiotemporal parameters fundamentally characterize gait. For straight walking, these parameters are well-defined for the task of walking on a straight path. Generalizing these concepts to non-straight walking, however, is not straightforward. People follow non-straight paths imposed by their environment (sidewalk, windy hiking trail, etc.) or choose readily-predictable, stereotypical paths of their own. People actively maintain lateral position to stay on their path and readily adapt their stepping when their path changes. We therefore propose a conceptually coherent convention that defines step lengths and widths relative to predefined walking paths. Our convention simply re-aligns lab-based coordinates to be tangent to a walker's path at the mid-point between the two footsteps that define each step. We hypothesized this would yield results both more correct and more consistent with notions from straight walking. We defined several common non-straight walking tasks: single turns, lateral lane changes, walking on circular paths, and walking on arbitrary curvilinear paths. For each, we simulated idealized step sequences denoting "perfect" performance with known constant step lengths and widths. We compared results to path-independent alternatives. For each, we directly quantified accuracy relative to known true values. Results strongly confirmed our hypothesis. Our convention returned vastly smaller errors and introduced no artificial stepping asymmetries across all tasks. All results for our convention rationally generalized concepts from straight walking. Taking walking paths explicitly into account as important task goals themselves thus resolves conceptual ambiguities of prior approaches.

Walking humans often navigate complex, varying walking paths. To reduce falls, we must first determine how older adults purposefully vary their steps in contexts that challenge balance. Here, 20 young (21.7±2.6 yrs) and 18 older (71.6±6.0 yrs) healthy adults walked on virtual paths that slowly narrowed (from 45 cm to as narrow as 5 cm). Participants could switch onto an “easier” path whenever they chose. We applied our Goal Equivalent Manifold framework to quantify how participants adjusted their lateral stepping variability and step-to-step corrections of step width and lateral position as these paths narrowed. We also extracted these characteristics at the locations where participants switched paths. As paths narrowed, all participants reduced their lateral stepping variability, but older adults less so. To stay on the narrowing paths, young adults increasingly corrected step-to-step deviations in lateral position more, by correcting step-to-step deviations in step width less. Conversely, as older adults also increasingly corrected lateral position deviations, they did so without sacrificing correcting step-to-step deviations in step width, presumably to preserve balance. While older adults left the narrowing paths sooner, several of their lateral stepping characteristics remained similar to those of younger adults. Older adults largely maintained overall walking performance per se, but they did so by changing how they balanced the competing stepping regulation requirements intrinsic to the task: maintaining position vs. step width. Thus, balancing how to achieve multiple concurrent stepping goals while walking provides older adults the flexibility they need to appropriately adapt their stepping on continuously narrowing walking paths.

In biotin synthase reactions carried out in vitro, we observed efficient transfer of 35S to biotin from partially purified E. coli biotin synthase (product of the bioB gene) labelled by biosynthetic incorporation of [35S]-cysteine. Mass spectrometry was consistent with covalent alteration of the protein in the assay. These results suggest that BioB protein is a reagent, not a catalyst.

Walking humans display great versatility when achieving task goals, like avoiding obstacles or walking alongside others, but the relevance of this to fall avoidance remains unknown. We recently demonstrated a functional connection between the motor regulation needed to achieve task goals (e.g., maintaining walking speed) and a simple walker's ability to reject large disturbances. Here, for the same model, we identify the viability kernel-the largest state-space region where the walker can step forever via at least one sequence of push-off inputs per state. We further find that only a few basins of attraction of the speed-regulated walker's steady-state gaits can fully cover the viability kernel. This highlights a potentially important role of task-level motor regulation in fall avoidance. Therefore, we posit an adaptive hierarchical control/regulation strategy that switches between different task-level regulators to avoid falls. Our task switching controller only requires a target value of the regulated observable-a "task switch"-at every walking step, each chosen from a small, predetermined collection. Because humans have typically already learned to perform such goal-directed tasks during nominal walking conditions, this suggests that the "information cost" of biologically implementing such controllers for the nervous system, including cognitive demands in humans, could be quite low.

To successfully traverse their environment, humans often perform maneuvers to achieve desired task goals while simultaneously maintaining balance. Humans accomplish these tasks primarily by modulating their foot placements. As humans are more unstable laterally, we must better understand how humans modulate lateral foot placement. We previously developed a theoretical framework and corresponding computational models to describe how humans regulate lateral stepping during straight-ahead continuous walking. We identified goal functions for step width and lateral body position that define the walking task and determine the set of all possible task solutions as Goal Equivalent Manifolds (GEMs). Here, we used this framework to determine if humans can regulate lateral stepping during non-steady-state lateral maneuvers by minimizing errors consistent with these goal functions. Twenty young healthy adults each performed four lateral lane-change maneuvers in a virtual reality environment. Extending our general lateral stepping regulation framework, we first re-examined the requirements of such transient walking tasks. Doing so yielded new theoretical predictions regarding how steps during any such maneuver should be regulated to minimize error costs, consistent with the goals required at each step and with how these costs are adapted at each step during the maneuver. Humans performed the experimental lateral maneuvers in a manner consistent with our theoretical predictions. Furthermore, their stepping behavior was well modeled by allowing the parameters of our previous lateral stepping models to adapt from step to step. To our knowledge, our results are the first to demonstrate humans might use evolving cost landscapes in real time to perform such an adaptive motor task and, furthermore, that such adaptation can occur quickly-over only one step. Thus, the predictive capabilities of our general stepping regulation framework extend to a much greater range of walking tasks beyond just normal, straight-ahead walking.

To successfully traverse their environment, humans must often perform maneuvers to achieve desired task goals while simultaneously maintaining balance. Humans accomplish these tasks primarily by modulating their foot placements. As humans are more unstable laterally, we must better understand how humans modulate lateral foot placement. We previously developed a theoretical framework and corresponding computational models to describe how humans regulate lateral stepping during straight-ahead continuous walking. This framework yields goal functions for step width and lateral body position that define the walking task and determine the set of all possible task solutions as Goal Equivalent Manifolds (GEMs). Here, we used this framework to determine if humans can regulate lateral stepping during non-steady-state lateral maneuvers by minimizing errors in accordance with these goal functions. Twenty young healthy adults each performed four lateral lane-change maneuvers in a virtual reality environment. Within our general lateral stepping regulation framework, we first re-examined the requirements of such transient walking tasks. Doing so yielded new theoretical predictions regarding how steps during any such maneuver should be regulated to minimize error costs, consistent with the goals required at each step and with how these costs are adapted at each step during the maneuver. Humans performed the experimental lateral maneuvers in a manner consistent with our theoretical predictions. Furthermore, their stepping behavior was well modeled by merely adapting the parameters of our previous lateral stepping models from step to step. To our knowledge, our results are the first to demonstrate humans can use evolving cost landscapes in real time to perform such an adaptive motor task and, furthermore, that such adaptation can occur quickly – over only one step. Thus, the predictive capabilities of our general stepping regulation framework extend to a much greater range of walking tasks beyond just normal, straight-ahead walking. AUTHOR SUMMARY When we walk in the real world, we rarely walk continuously in a straight line. Indeed, we regularly have to perform other tasks like stepping aside to avoid an obstacle in our path (either fixed or moving, like another person coming towards us). While we have to be highly maneuverable to accomplish such tasks, we must also remain stable to avoid falling while doing so. This is challenging because walking humans are inherently more unstable side-to-side. Sideways falls are particularly dangerous for older adults as they can lead to hip fractures. Here, we establish a theoretical basis for how people can accomplish such maneuvers. We show that humans execute a simple lateral lane-change maneuver consistent with our theoretical predictions. Importantly, we show that they can do so using simple adaptations of the same step-to-step regulation strategies they use to walk in a straight line. Moreover, these same control processes also explain how humans trade-off side-to-side stability to gain the maneuverability they need to perform such lateral maneuvers.

People walk in complex environments where they must adapt their steps to maintain balance and satisfy changing task goals. How people do this is not well understood. We recently developed computational models of lateral stepping, based on Goal Equivalent Manifolds that serve as motor regulation templates, to identify how people regulate walking movements from step-to-step. In normal walking, healthy adults strongly maintain step width, but also lateral position on their path. Here, we used this framework to pose empirically-testable hypotheses about how humans might adapt their lateral stepping dynamics when asked to prioritize different stepping goals. Participants walked on a treadmill in a virtual-reality environment under 4 conditions: normal walking and, while given direct feedback at each step, walking while trying to maintain constant step width, constant absolute lateral position, or constant heading (direction). Time series of lateral stepping variables were extracted, and variability and statistical persistence (reflecting step-to-step regulation) quantified. Participants exhibited less variability of the prescribed stepping variable compared to normal walking during each feedback condition. Stepping regulation results supported our models' predictions: to maintain constant step width or position, people either maintained or increased regulation of the prescribed variable, but also decreased regulation of its complement. Thus, people regulated lateral foot placements in predictable and systematic ways determined by specific task goals. Humans regulate stepping movements to not only "just walk" (step without falling), but also to achieve specific goal-directed tasks within a specific environment. The framework and motor regulation templates presented here capture these important interactions.

Background: Daily walking paths exhibit varying environment features and require continuous adjustments to locomotor trajectories. Humans maintain lateral balance while navigating paths by modifying stepping in accordance with changing side-to-side path limitations (e.g. path width, lateral location). These processes are influenced by one's actual physical ability to maintain balance, as well as their self-perceived balance ability. Older adults experience decreases in each of these abilities, which may alter their capacity to execute appropriate lateral stepping adaptations. Research Question: How do age, physical and self-perceived balance abilities interact to influence lateral stepping adaptations of older adults walking in complex environments with dynamic lateral path features? Methods: Twenty young (age mean +/- SD: 21.7 &+/- 2.6) and 18 older adults (age mean +/- SD: 71.6 &+/- 6.0) walked on an instrumented treadmill in a virtual-reality system. Participants adjusted lateral stepping during two competing lateral balance sub-tasks that manipulated either path width or location. Participants began walking on a gradually-narrowing path (sub-task A), then decided when/ how to laterally maneuver to an adjacent path (sub-task B). Recorded path characteristics were used to quantify spatial thresholds for stepping error onset and sub-task exchange. Results: Older adults made sub-task A stepping errors on wider paths and exchanged sub-tasks earlier. These differences were not directly attributed to age. Statistical path analyses revealed that physical balance ability mediated age effects on stepping error onset, while self-perceived balance ability mediated age effects on sub-task exchange. Both age groups exchanged sub-tasks when stepping accuracy likelihoods were similar and high, similar to 90 %. Significance: This work demonstrates important mechanisms for how age, via degradation of physical and self-perceived balance abilities, indirectly and differentially influences navigation of competing lateral balance tasks. Mediating physical and perceptual factors are potential targets for improving older adults' navigation of complex environments.

Dual-task research is limited in its transferability to authentic contexts because laboratory conditions do not replicate real-world physical activity and decision-making scenarios. Creating valid, reliable methodologies to assess physiological and behavioral responses under varying physical and cognitive demands using virtual reality (VR) environment addresses this limitation. This study determined the feasibility of using VR to investigate the effects of dual-tasking on healthy young adults' cognitive performance. Three dual-tasking conditions (i.e., standing, preferred-paced walking, and fast-paced walking, each with blocked congruent and incongruent tasks) were developed. Using a within-subjects, randomized design, thirty-two young adults (17 female, mean age = 21.03 ± 2.86) were randomly assigned to a starting condition but experienced all three conditions. Physiological responses of heart rate (HR) and accelerometry data measured energy expenditure as the physical demand. Behavioral responses of reaction time and error rate quantified cognitive performance. Results indicated that (a) each condition verified independent physiological and behavioral responses; (b) reaction time and error rate during preferred walking or fast-paced walking dual-tasking conditions was significantly lower than standing condition; and surprisingly, (c) congruent tasks showed lower reaction time than the incongruent tasks. These findings suggest that it is feasible to use VR to assess the effects of dual-task conditions. Specifically, walking can optimize the motor-cognitive dual-task performance, compared to standing. These findings may be attributed to the dose-response effects of exercise intensity. Future studies should incorporate advanced technology such as the VR exercise.

Much remains unknown about how considerations such as stability and energy minimization shape the way humans walk. While active neuromotor control keeps humans upright, they also need to choose from multiple stepping regulation strategies to achieve one or more task goals, such as maintaining a desired speed or direction. Experiments on human treadmill walking motivate an important question: why do humans prefer one task-level regulation strategy over another-perhaps to enhance their ability to reject large disturbances? Here, we study the relationship between task-level regulation and global stability in a powered compass walker on a treadmill, with added step-to-step speed and position regulators. For treadmill walking, we find that speed regulation greatly enlarges and regularizes the unregulated walker's stability region, i.e. its basin of attraction, much more than position regulation. Thus, our results suggest a possible explanation for the experimental finding that humans strongly prioritize regulating speed from one stride to the next, even as they walk economically on average. Furthermore, our work suggests a functional connection between task-level motor regulation and global stability-and, thus, perhaps even fall risk.

Biological systems must contend with intrinsic redundancy and noise. Biomechanical templates and optimality criteria can define desired mean behaviors. But these systems must also perform tasks with extrinsic task-level redundancy. Here, we describe simple models to define regulation templates for how humans adjust stepping movements from each step to the next.

Gait variability is generally associated with falls, but specific connections remain disputed. To reduce falls, we must first understand how older adults maintain lateral balance while walking, particularly when their stability is challenged. We recently developed computational models of lateral stepping, based on Goal Equivalent Manifolds, that separate effects of step-to-step regulation from variability. These show walking humans seek to strongly maintain step width, but also lateral position on their path. Here, 17 healthy older (ages 60+) and 17 healthy young (ages 18-31) adults walked in a virtual environment with no perturbations and with laterally destabilizing perturbations of either the visual field or treadmill platform. For step-to-step time series of step widths and lateral positions, we computed variability, statistical persistence and how much participants directly corrected deviations at each step. All participants exhibited significantly increased variability, decreased persistence and tighter direct control when perturbed. Simulations from our stepping regulation models indicate people responded to the increased variability imposed by these perturbations by either maintaining or tightening control of both step width and lateral position. Thus, while people strive to maintain lateral balance, they also actively strive to stay on their path. Healthy older participants exhibited slightly increased variability, but no differences from young in stepping regulation and no evidence of greater reliance on visual feedback, even when subjected to substantially destabilizing perturbations. Thus, age alone need not degrade lateral stepping control. This may help explain why directly connecting gait variability to fall risk has proven difficult.

Background: Persons with lower limb amputation often experience decreased physical capacity, difficulty walking, and increased fall risk. To either prevent or recover from a loss of balance, one must effectively regulate their stepping movements. It is therefore critical to identify how well persons with amputation regulate stepping. Here, we used a multi-objective control framework based on Goal Equivalent Manifolds to identify how persons with transtibial amputation (TTA) regulate lateral stepping while walking without and with lateral perturbations. Research question: When walking in destabilizing environments, do otherwise healthy persons with TTA exhibit greater difficulty regulating lateral stepping due to impaired control? Or do they instead continue to use similar strategies to regulate lateral stepping despite their amputation? Methods: Eight persons with unilateral TTA and thirteen able-bodied (AB) controls walked in a virtual environment under three conditions: no perturbations, laterally oscillating visual field, and laterally oscillating treadmill platform. We analyzed step-to-step time series of step widths and absolute lateral body positions. We computed means, standard deviations and Detrended Fluctuation Analysis scaling exponents for each time series and computed how much participants directly corrected step width and position deviations at each step. We compared our results to computational predictions to identify the underlying causes of our experimental findings. Results: All participants exhibited significantly increased variability, decreased scaling exponents, and tighter direct control when perturbed. Simulations from our stepping regulation models revealed that people responded to the increased variability produced by the imposed perturbations by tightening their control of both step width and lateral position. Participants with TTA exhibited only a few minor differences from AB in lateral stepping regulation, even when subjected to substantially destabilizing lateral perturbations. Significance: Since control of stepping is intrinsically multi-objective, developing effective interventions to reduce fall risk in persons with amputation will likely require strategies that adopt multi-objective approaches.