Journal of Neurophysiology

Postural control depends on the ability to adapt motor responses to changing environmental and physiological conditions. Neuromuscular fatigue (NMF) is known to alter balance and muscle activation patterns, yet its effects on motor adaptation during whole-body postural tasks and on the persistence of learned strategies remain unclear. This study investigated whether localized NMF of the ankle dorsiflexors influences adaptation to a novel postural perturbation task and whether learning under fatigue induces persistent changes during subsequent re-exposure. Twenty-five healthy young adults were assigned to either a fatigue (FAT) or no-fatigue (NoFAT) group and completed two experimental sessions separated by 48-72 h allowing recovery from acute fatigue for fatigued group. Participants adapted to repeated mechanical perturbations while standing upright, while ground reaction forces and electromyographic activity of lower-limb muscles were recorded. NMF did not impair overall adaptation performance, as both groups exhibited similar reductions in performance error across practice. However, participants exposed to fatigue exhibited altered postural recovery dynamics, characterized by a reduced return toward the initial posture following perturbation release. These differences persisted during re-exposure on the subsequent day, despite the absence of acute fatigue. In parallel, NMF modified muscle activation and coactivation patterns involving both fatigued and non-fatigued muscles, several of which were retained during re-exposure. These findings indicate that the central nervous system preserves successful adaptation to postural perturbations under fatigue by reorganizing neuromuscular coordination and stabilization strategies. Learning under fatigue therefore influences not only immediate motor execution, but also shapes the longer-term representation of postural control strategies.

We investigated the dimensions of output zones affecting specific combinations of forelimb muscles in the precentral "motor" cortex of macaque monkeys. Single-pulse intracortical microstimulation (S-ICMS) was used to evoke subthreshold effects in multiple wrist and finger muscles. Results indicate that each motor cortex site represents a different combination of muscles. The effects evoked from cortical sites separated by several hundred microns invariably involved different profiles of muscle activity. The muscle fields of remote CM cells were rarely identical, while the fields of neighboring CM cells were often similar. Given the number of unrecorded muscles, we conclude that primate motor cortex is a mosaic of output sites representing forelimb muscles in different combinations.

Humans consistently decrease the amount of force they produce during isometric finger pressing in the absence of visual feedback, a phenomenon often called force drift. This decrease in force production has been attributed to limitations in working memory and/or adaptive neural control processes that minimize energy consumption. In this study, we investigated a potential peripheral reason for such force drifts: increases in the coefficient of friction between the fingertip and the surface it contacts due to changes in fingertip contact area as the fingertip hydrates under prolonged pressure. We investigated this possibility by eliciting force drifts from participants performing isometric pressing tasks against smooth glass, which shows the phenomenon of increasing contact area during prolonged contact, and a polymer which does not exhibit this phenomenon. We confirmed that the coefficient of friction only increased on the glass plate, however we did not observe a difference in force drifts between these two surfaces, although we found some evidence that force drift could be associated with coefficient of friction. Our findings suggest that factors other than peripheral changes in coefficient of friction are the primary drivers of force drifts.

The human sensorimotor system is remarkably effective at automatically parsing total movement error into its constituent parts, the error component due to a perturbation, or externally-generated error (EGE), versus the error component due to motor noise, or internally-generated error (IGE). Participants robustly, and implicitly, adapt to minuscule (2{degrees}) EGEs in the form of randomized visuomotor rotations while ignoring identically-sized errors caused by IGE. This error parsing, and its associated perceptual processes, directly contrasts previous work showing that humans must observe rotations that are > 1.5x the standard deviations of their motor variability, or [≥] 4{degrees}, before explicitly reporting their presence. While the combined results suggest a dissociation between perception for action--which allows for precise and automatic error parsing--and perception for conscious detection, this must be inferred across studies using different methodologies. Here, we combined a within-subjects study design and computational modeling to shed light on the principles underlying implicit adaptation to a perturbation and explicit perturbation detection. Neuro-typical adults participated in two experiments consisting of pseudo-randomized rotations during reaches to a single target, with one session requiring explicit reports after each reach of whether a perturbation was detected. Participants demonstrated a clear dissociation between implicit responses to a perturbation and explicit detection, with robust adaptation to 1{degrees} EGEs, but an inability to reliably report the presence of an EGE until it reached [~] 4{degrees}. For the adaptation task, a model that assumes the participant compares proprioceptive and visual cues to detect a perturbation and corrects for a proportion of this error best fit the data. For signal-detection, a Bayesian causal-inference model in which sensory cues are optimally integrated with a prior on their cause best fit those data. These results indicate that implicit adaptation is dissociated from explicit perturbation detection and the sensorimotor system applies distinct computational strategies to these behaviors.

Multiple learning signals can shape motor output, including reward and punishment (via value-based reinforcement learning) and sensorimotor error (via motor adaptation). However, it is unclear if action values, learned via reinforcement learning, interact with error-based motor learning. Here, we asked if the learned value of competing motor goals influences how the motor system learns from sensorimotor errors linked to those goals. We designed a paradigm that required participants (N = 85) to learn about the value associated with different movement targets prior to undergoing implicit visuomotor adaptation at or nearby those same targets. We observed two classes of related effects: repulsion and suppression. When adaptation brought the limb toward targets associated with low-value, learning was attenuated compared to when adaptation brought the limb away from targets associated with low-value, indicating a "repelling" effect of low-value actions. Moreover, adaptation was suppressed in all directions when low-value targets were themselves the goal of movement. These findings were asymmetric with respect to valence: we did not observe comparable attraction effects when adaptation brought the limb toward targets associated with high-value, nor did we see overall enhancement of adaptation when targets associated with high-value acted as movement goals. Additional analyses and experiments demonstrated that these effects did not reflect generic biases and were driven by relative rather than absolute goal values. Repulsion and suppression effects were tied to movement directions rather than the targets themselves. These results point to a novel interaction between reinforcement learning and motor memory -- a kind of "instrumental-motor transfer." Significance StatementIn order to ensure our motor behavior yields our desired outcomes, we must not only learn which actions lead to which outcomes (via reinforcement learning) but also how to precisely execute those actions to achieve the desired outcome (by calibrating our actions via implicit motor adaptation. While it is clear that reinforcement learning and motor adaptation operate at different levels of an action selection hierarchy, it is unclear if they interact. Knowing if and how these processes interact is critical for understanding the fundamental algorithms and various neural circuits underlying real-world motor behavior. Here, we show a novel interaction between the two processes where implicit adaptation is suppressed when adaptation would bring the hand toward a previously punished movement goal.

Despite extensive research on vestibular function in microgravity, particularly during orbital and parabolic flight exposure, several gaps remain regarding the spontaneous behavior of vestibular organs under non-terrestrial gravitoinertial conditions. In particular, semicircular canal function, typically assessed through vestibulo-ocular reflex (VOR) recordings, has yielded inconsistent findings, with reports describing either no effect or reduced performance in microgravity. Moreover, many of these studies are limited by methodological constraints that reduce the interpretability of their conclusions. To clarify these discrepancies, we evaluated horizontal and vertical VOR responses during parabolic flights to assess semicircular canal function under transient weightlessness. Participants were passively rotated at a constant frequency and amplitude during normogravity and microgravity phases, centered along the head vertical or inter-aural axis. Eye movements were recorded binocularly using infrared eye-tracking in darkness to eliminate visual influences, while participants were tightly restrained to minimize proprioceptive variability. Results show a reduction in VOR gain during microgravity in both axes, despite consistent rotational stimulation across gravity conditions. In addition, VOR gain remained reduced after parabolas in the horizontal plane, whereas vertical VOR performance was preserved. These are the first results to demonstrate an immediate alteration of semicircular canal function in weightlessness. Possible sources of the reduction in VOR performance in 0g are discussed. We also propose that the observed post-flight effects reflect a down-weighting of semicircular canal inputs during multisensory integration.

ObjectiveAging is associated with changes in cortical excitability and altered responsiveness to benzodiazepines, but the effects of benzodiazepine challenge on motor cortical paired-pulse physiology in older adults remain incompletely understood. We examined whether intravenous midazolam differentially modulates corticospinal excitability and short-interval paired-pulse transcranial magnetic stimulation (TMS) responses in younger and older adults. MethodsFifteen younger adults (18-35 years) and fifteen older adults (50-69 years) underwent single-pulse and paired-pulse TMS of the left primary motor cortex at baseline and during intravenous midazolam administration. Single-pulse motor evoked potential (MEP) amplitude was used to assess corticospinal excitability. Short-interval paired-pulse responses were quantified as the ratio of conditioned to unconditioned MEP amplitude. ResultsAt baseline, younger adults showed greater corticospinal excitability than older adults, reflected by larger single-pulse MEP amplitudes (adjusted p = 0.04). Younger adults demonstrated paired-pulse inhibition at baseline, reflected by a conditioned/unconditioned MEP ratio below 1.0 (ratio = 0.73; adjusted p < 0.01), whereas older adults did not show inhibition and instead had a mean ratio above 1.0 (ratio = 1.25). Midazolam reduced single-pulse MEP amplitudes in both groups. During midazolam administration, paired-pulse inhibition was no longer observed in younger adults, and older adults continued to show no evidence of inhibition. ConclusionsYounger and older adults differed in baseline corticospinal excitability and in short-interval paired-pulse TMS responses. Intravenous midazolam reduced corticospinal excitability and altered paired-pulse response patterns, eliminating baseline paired-pulse inhibition in younger adults while producing little measurable change in older adults. These findings suggest that aging may modify the net motor cortical response to benzodiazepine challenge. The results should be interpreted in relation to the paired-pulse stimulation parameters used and support further studies using complementary approaches to characterize age-related differences in inhibitory and facilitatory motor cortical circuits.

Whether and how various visual sensory areas contribute to the perceived location of visual stimuli remains unknown. To test the role of neurons in extrastriate area V4 in generating alterations in spatial perception during saccadic eye movements (saccades), we examined perisaccadic mislocalization--the perceptual phenomenon in which visual stimuli appearing around the time of a saccade are perceived at a different position than their actual location. We designed and implemented a combined behavioral and electrophysiological framework in non-human primates to directly relate trial-by-trial spatial perception reports during saccades to neuronal firing rates in V4 populations. We measured monkeys perception of stimulus location behaviorally and found perisaccadic mislocalization opposite to the saccade direction. We also quantified population responses by computing the center of mass of firing rate activity across probe locations for V4 neurons with receptive fields close to the saccade target. While perisaccadic neuronal responses showed shifts toward the saccade target, these shifts did not systematically vary with the magnitude of perceptual mislocalization across trials. In conclusion, receptive field shifts based on the perisaccadic firing rate of V4 neurons are not sufficient to account for the magnitude of perceptual mislocalization in each trial, suggesting that more complex neural representation of perisaccadic visual information may be critical for linking extrastriate neural activity to saccade-induced perception.

Although muscle spindle sensory signals have been extensively studied, little is known about how and why muscle spindle firing is modulated by the central nervous system during movement. Specialized motor neurons to the muscle spindle, i.e. gamma motor neurons, can profoundly alter spindle firing during behavior, but technological limitations hinder our ability to record gamma motor and muscle spindle sensory signals during most behaviors. We used a biophysical model of a muscle spindle within a muscle-tendon unit to simulate how gamma drive may modulate muscle spindle Ia firing during locomotion. Based on a few available recordings from decerebrate animals, we demonstrate that our model, tuned to passive stretch conditions, can reproduce profound changes in muscle spindle firing in response to identical joint motions in locomotor vs. relaxed stretch conditions. Our model can discover phasic patterns of two types of gamma motor neuron drive based on recorded muscle spindle Ia firing and joint motion. By simulating perturbations, we conclude that: 1) sinusoidal activation of static gamma motor neurons during locomotion, encoding intended movement, modulates muscle spindle signals such that they act as sensorimotor feedback signals based on errors from the intended muscle fascicle length; 2) phasic on/off activation of dynamic gamma motor neurons during locomotion acts as an event detector, heightening muscle spindle Ia responses to discrete perturbations. As such, their muscle-within-muscle structure allows the muscle spindle to act as a highly tunable physical internal model of muscle state to guide movement. Our model supports proposed but as-yet-untested theories of muscle spindle function and offers a framework for extending the testing of muscle spindle function to active, behavioral conditions.

High-frequency "ripple" oscillations support learning and memory across species, yet it has been argued that putative ripples in awake human recordings are false positives produced when algorithms misread aperiodic (1/f) fluctuations as ripple-band oscillations. We show that this conclusion arises from an artifact of evaluating detection algorithms on surrogate data containing only aperiodic activity. Ripple detectors are adaptive, setting their threshold from the amplitude statistics of the signal, so applying them to surrogate data that contains only aperiodic activity lowers the threshold and inflates false positives (median 62%). Adding real ripple-band events back to the surrogate corrects this threshold shift and eliminates most false detections across multiple standard algorithms. Using multivariate classifiers, we show aperiodic fluctuations can reproduce the power of ripples but not their timing or spectral content. These findings indicate care needs to be taken when using surrogates to evaluate ripple detection algorithms. Thus, under realistic signal properties, human hippocampal ripples remain distinguishable from aperiodic activity.

Interception of moving objects requires the nervous system to compensate for sensory delays and uncertainty, yet how behavior is controlled remains debated. Key questions concern whether predictive processes play any role at all and, if so, whether they rely on simple motion extrapolation or incorporate internalized physical priors, such as gravity. Another open question is whether observers adopt a single control strategy or flexibly switch between predictive and reactive control - or between different predictive strategies - depending on task demands. To address these questions, we developed a virtual interception task in which participants intercepted moving targets under systematically varied conditions. We manipulated gravity (1g vs. 0g), visual availability (occluded vs. non-occluded), target velocity, and the initial spatial configuration of the ball and paddle (same vs. opposite side). Results indicate that interception is supported by predictive mechanisms across conditions. Behavioral patterns during occluded 0g trials suggest that participants extrapolate target motion using expectations consistent with gravity. Target velocity, visual occlusion, and task geometry modulated movement strategies, indicating that predictive control is flexibly adapted to task demands. These findings support the view that interception relies on predictive internal models incorporating structured physical priors while revealing flexible, context-dependent adaptations to sensory and task constraints.

It has been demonstrated that people who stutter exhibit atypical motor control not only in speech tasks but also movements in the non-speech effector system, such as finger or arm motion. Notably, studies have reported that people who stutter show limited sensorimotor adaptation (i.e., updating subsequent movements in response to sensory errors) in both speech auditory-motor (i.e., updating speech movements in response to altered auditory feedback) and upper limb visuo-motor (i.e., updating arm movements in response to altered visual feedback) tasks. Given that speech auditory-motor adaptation is mostly if not entirely implicit (i.e., participants are unaware of the learning), it is thought that people who stutter have limited implicit adaptation in the speech effector system. It remains unclear however, whether such limited implicit learning also extends to upper limb visuomotor adaptation. Here, we examined implicit visuomotor learning in adults who stutter through the means of arm reaching adaptation to clamped visual feedback which provides a cursor that is fixed in direction (8{degrees} counterclockwise from targets) regardless of the participants actual hand location. All participants gradually adjusted their reach angle towards the clockwise direction, adapting in response to clamped feedback, but adults who stutter showed less adaptation compared to adults who do not stutter. In addition, computational modeling suggests that this implicit adaptation difficulties in stuttering individuals may reflect reduced error sensitivity. Together, our findings suggest that implicit sensorimotor learning difficulties in adults who stutter may generalize across multiple effector systems, providing important implications for understanding sensorimotor mechanisms underlying stuttering. Significance statementBy employing the clamped visual feedback paradigm during arm reaching movements, we demonstrated that adults who stutter showed less implicit visuomotor adaptation compared to adults who do not stutter. This study provides the first evidence that implicit sensorimotor adaptation limitations in developmental stuttering generalize across multiple effector systems. Our findings not only add to a growing body of evidence that stuttering is associated with domain-general sensorimotor difficulties but also point to specific underlying processes that may lead to stuttering.

Advances in intracortical brain-computer interface (BCI) technology have enabled increasingly sophisticated communication paradigms, including for decoding intended speech and touch typing. However, the methods by which intracortical neural population dynamics are engaged during practice-related skill acquisition in humans remain poorly understood. Here, we examined learning-related changes in neural activity during motor skill acquisition in a right-handed BCI clinical trial participant with tetraplegia, with intracortical microelectrode arrays placed in the bilateral dorsal precentral gyri (Brodmann area 6d), who learned how to type using a BCI-enabled typing interface. While decoder performance remained stable across sessions, typing speed improved with practice, indicating practice-related skill acquisition. Over weeks, low-dimensional neural population activity became progressively more compact, and this compaction was strongly associated with faster typing, independent of decoder accuracy. Although this compaction was observed bilaterally in 6d, firing-rate modulation and cross-session generalization were selectively enhanced in left 6d. Moreover, neural population changes across sessions were largely accounted for by canonical correlation analysis in right 6d, but only partially accounted for in left 6d. Together, these findings demonstrate that human intracortical neuro-motor skill acquisition related to intended typing engages shared bilateral population-level dynamics, with additional learning-related changes selectively expressed in dominant dorsal premotor cortex.

In animal learning research, learning is often represented by plotting a behavioral measure as a function of training trials. A particularly clear case is habituation, a basic form of learning in which repeated presentation of a stimulus produces a decrement in responding. Although retention tests provide the strongest basis for evaluating durable habituation once short-lived performance effects have dissipated, the pattern of response change across stimulus repetitions, or habituation curve, remains theoretically and empirically relevant because it is used to characterize determinants of habituation, individual and clinical profiles, and functional forms, including linear, curvilinear, asymptotic, and mixed incremental-decremental patterns of responding. However, group averaged curves may conceal substantial individual heterogeneity. Here, we analyzed archived human eyeblink habituation data from 157 participants to ask whether the curve shape selected for the group average reflects the curve shapes observed at the individual level. Five candidate functions were fitted separately to each participant and to the corresponding group average. No single function characterized most individuals. More importantly, the model selected for the group average differed from the most frequent individual model in all four groups. When data were pooled across groups, the average favored a dual-process form, a shape that matched the individual plurality in none of them. Simulation analyses showed that averaging heterogeneous individual trajectories can itself produce a group curve that favors a more complex model. Our findings show that group averaged habituation curves should not be treated as direct descriptions of the typical individual trajectory.

Resistance training lasting a few weeks increases maximal force mainly through neural adaptations that enhance the drive from the nervous system to muscle. While these adaptations have been well documented at the motor unit (MU) level during submaximal force contractions, the mechanisms underlying force increases during maximal voluntary contractions are poorly understood. This is due to a classic technical limitation in tracking MUs longitudinally during maximal force tasks. Here, we solved this technical challenge, enabling the investigation of MU adaptations during MVCs in both the trained and untrained limbs following unilateral resistance training. High-density surface electromyography was recorded from the biceps brachii of both limbs before and after a 4-week unilateral resistance-training intervention, and the same MUs were longitudinally tracked across sessions during MVCs by concatenation of three MVC trials of ~5-s each.Unilateral training increased maximal force in the trained limb (+16%) and induced strength transfer to the untrained limb (+8%). In both limbs, maximal contractions after training were characterized by greater EMG amplitude, faster muscle-fiber conduction velocity, and higher MU discharge rates, indicating enhanced neural drive to the motoneuron pool. These adaptations were strongly associated with improvements in maximal force (R2 > 0.7 for all). Importantly, longitudinal MU tracking revealed a non-uniform adaptation across the MU pool: MUs with higher baseline conduction velocity, indicative of higher recruitment threshold, exhibited the largest pre-post increases in discharge rate, whereas lower-threshold units showed smaller changes. Collectively, these findings demonstrate that gains in maximal force and their transfer to the untrained limb are primarily mediated by enhanced rate coding of higher-threshold MUs during MVCs.

AO_SCPLOWBSTRACTC_SCPLOWWe are constantly exploring the world around us through touch. Active touch depends on coordination of movement and force, yet the forces used during natural exploration and their relationship with perception is largely unexplored. Here we measured exploration forces together with fingertip motion while 17 participants explored 14 textures and rated their perceived hardness, slipperiness, or roughness. Exploration strategies differed systematically across tasks: hardness judgments involved relatively stationary pressing with larger and more variable normal forces, whereas slipperiness and roughness judgments relied more on sweeping movements. Within tasks, interaction forces covaried with perceptual ratings: harder textures elicited larger maximum tangential forces, consistent with diagonal pressing, while more slippery textures were explored with faster fingertip motion and lower forces. Estimated dynamic friction was negatively correlated with perceived slipperiness but not roughness. At the same time perceived roughness was strongly related to vibrations in the force, indicating distinct physical bases for these perceptual dimensions. These results show that humans actively tailor contact mechanics to perceptual goals during active exploration, supporting a sensorimotor account of texture perception. SO_SCPLOWIGNIFICANCEC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWSTATEMENTC_SCPLOWTouch is usually studied as if the skin passively receives information, but in everyday life we actively move and press against objects to recognize them and learn what they feel like. This study measured both fingertip motion and contact forces while people freely explored textures and judged hardness, slipperiness, and roughness - the three of the most salient dimensions of tactile experience. The results show that people adjust how they move and press depending on what they want to perceive, and that different physical signals - friction and vibration - support different texture judgments. This work helps explain touch as an active sensorimotor process, with implications for neuroscience, haptics, robotics, and neuroprosthetics.

Because of the uncertainties present in the any sensory inflows, we experienced perceptual biases that often contaminate sensorimotor transformations. How these biases can be prevented through perceptual learning or adaptation is an open question in inference theories of perception and motor control. We revisited this debate using a classic example of low-level perceptual bias, the aperture problem in motion perception and its consequences for smooth pursuit. In a visuomotor tracking paradigm, participants pursued left-, right-tilted, or upright Gabor patches moving horizontally. As expected, initial pursuit direction was biased toward the oblique directions. This initial pursuit error remained unchanged when participants repeatedly tracked a single tilted Gabor during training sessions conducted over several days. By contrast, post-training error correction became faster for the trained Gabor orientation, but not for its untrained, mirror-symmetric counterpart. This change in dynamics was explained by the emergence of a delayed compensatory pursuit response, best revealed after training with an upright Gabor, a stimulus that would normally elicit unbiased tracking. This corrective eye movement was selective for both shape and motion features. It lagged by [~]40 msec after pursuit onset suggesting that it was triggered by the biased motor command itself rather than by visual reafference. These results support a dissociation between low-level sensory computations, which cannot be modified over short timescales, and internal models of sensorimotor transformation, which can be rapidly updated to compensate for irreducible but predictable sensory-driven perceptual biases.

Some blind individuals use echolocation, a skill that allows them to better navigate their environment using echoes from self-generated mouth clicks reflected off surrounding surfaces. Echolocation involves a complex interplay of sensory accumulation, information processing, dynamic prediction, motor planning and execution in real-time. Computational modeling offers a valuable approach to understanding the cognitive and neural mechanisms underlying echolocation performance, in particular the temporal dynamics of the process. We present a computational model of human echolocation behavior based on a Kalman filter, where we treat the echolocator as an active sensor that maintains an internal belief about the target's location and continuously refines it via echo feedback. The model, based on observations of echolocation in blind human experts, simulates the use of mouth clicks and returning echoes to localize and orient toward a target under varying conditions. In the experiment, the target is placed at a random azimuth in the frontal plane. An echolocator aims a series of mouth clicks in various directions and infers the target azimuth using acoustic information received from the click echoes. The system integrates three major components: (1) a simulation of echoacoustic interaural time differences (ITD) to estimate the relative head-target angle; (2) a Kalman filter that processes these ITDs to iteratively update probabilistic beliefs about target location and associated uncertainty; and (3) a motor control system that modulates head movements with the current belief state. The Kalman filter serves as a representation of the internal state of the observer, where its beliefs drive the direction of head rotation, and its uncertainty estimates drive head velocity adjustments. Model performance demonstrates that simple predictive computational approaches can reproduce key aspects of echo-guided sensorimotor learning, providing a framework that may be leveraged to develop biologically plausible models, advance understanding of best practices, and potentially improve intervention strategies.

Motion perception depends on estimating the relative timing of sensory events under internal uncertainty. Although perceptual uncertainty is commonly represented by a single internal noise parameter, its structure, sources, and temporal organisation remain poorly understood. Here, I investigated the computational structure of internal uncertainty in phase-based tactile motion perception using continuous amplitude-modulated vibrations delivered simultaneously to two fingertips. Motion discrimination accuracy, response latency, confidence, and confidence entropy exhibited systematic phase-dependent changes, revealing distinct behavioural signatures of temporal uncertainty. Computational analyses demonstrated that tactile motion perception is not explained by a single source of landmark timing uncertainty. Instead, behavioural performance was best accounted for by two additive uncertainty components: an amplitude-dependent component associated with extracting temporal landmarks from the vibration envelope, and an amplitude-independent component shared across stimulus conditions. This dual uncertainty framework consistently explained the frequency dependence of motion perception, the reduced uncertainty observed for sharper vibration envelopes, and the previously reported enhancement of motion perception with exponential compared with sinusoidal modulation. An independent temporal order judgement experiment further validated the uncertainty parameter inferred from motion discrimination, demonstrating that sharpening temporal landmarks reduced timing uncertainty by 35%. Finally, manipulating the initial stimulus state showed that perceptual choices followed the temporal sequence and correspondence of landmark events rather than the initial evolution of the vibration envelopes, providing independent support for landmark-based computations. these findings demonstrate that tactile motion perception is governed by multiple computational sources of landmark timing uncertainty and establish phase-based tactile motion as a tractable paradigm for independently measuring, manipulating, and modelling the computational structure of perceptual uncertainty underlying sensory decisions.

Older adults sustain disproportionately severe injuries from trip-induced falls during obstacle crossing. Such falls depend partly on forward momentum when the foot crosses the obstacle. MOSAP, an index of passive dynamic gait stability, reflects this momentum. We quantified MOSAP and a synergy index from uncontrolled manifold analysis of step length and extrapolated center of mass in 25 young (21.6 {+/-} 3.5 yr) and 23 older adults (68 {+/-} 4.3 yr) during unobstructed and obstructed walking, to test whether MOSAP increases during obstacle crossing and whether it is actively stabilized at each step. Both groups increased MOSAP progressively over two approach steps by reducing forward momentum and shifting the center of mass posteriorly. Older adults showed greater increases at the crossing steps. The synergy index was positive for all steps, showing that deviations in step length and extrapolated center of mass covaried to stabilize MOSAP at step-specific values. The synergy index was not influenced by age. We conclude that adults actively recruit passive body mechanics while approaching and crossing obstacles to reduce the risk of a trip becoming a fall. Older adults amplify this strategy to compensate for diminished neuromuscular corrective capabilities.