Journal of Neurophysiology

Bimanual coordination is essential for many skilled everyday actions and requires maintaining specific spatiotemporal relationships between the two hands according to task demands. However, the contribution of the primary motor cortices (M1s) to learning such relationships is only partially understood. Conventional bimanual tasks necessarily engage both M1s in controlling the moving hands, making learning-related changes difficult to distinguish from those associated with movement execution. To reduce this effector-related confound, we used a unimanual and bimanual rhythmic coordination paradigm in which participants learned the same novel 90-degree relative-phase relationship by coordinating either hand with a virtual partner and compared these conditions with conventional bimanual practice. In three experiments, performance accuracy and stability improved during practice and improved further after a 6-h retention interval with comparable time-dependent changes across unimanual and bimanual trained groups. In Experiment 2, motor-evoked potentials measured before and after training revealed an overall increase in corticospinal excitability across both M1s under unimanual and bimanual training. In Experiment 3, bidirectional dual-site paired-pulse stimulation revealed effector-dependent changes in interhemispheric inhibition, in which bimanual practice produced no reliable directional modulation, whereas unimanual practice produced asymmetric changes that depended on the trained hand. Neither corticospinal excitability nor interhemispheric inhibition showed a consistent relationship with behavioral improvement. Together, these findings demonstrate comparable behavioral learning of a novel spatiotemporal coordination relationship across bimanual and unimanual contexts, while showing that behavioral improvement is not straightforwardly reflected in M1 neurophysiological changes. Causal intervention studies are therefore needed to determine whether and when M1 contributes directly to acquisition of novel coordination relationships.

The control of visually guided bimanual movements is thought to represent a compromise between the drive for synchrony that characterizes many bimanual movements and the competing demands that characterize the constituent unimanual movements. As a result, while visually guided bimanual movements are found to be ostensibly synchronized, they also demonstrate subtle asynchronies. Here, we conducted a fine-grained analysis of bimanual reaching movements focusing on their relative synchrony as movements unfold and the relationship with gaze behavior. Our novel analysis revealed that participants frequently shifted their gaze laterally several times during bimanual reaches and that these gaze shifts were systematically associated with changes in the speed ratio of the two limbs. More specifically, we observed a strong association between gaze shifts and the speed ratio shifting toward the limb on the attended side. This pattern of behavior was seen regardless of hand dominance and target difficulty, suggesting that it may reflect a common visuomotor strategy during bimanual reaching.

The vestibular system consists of peripheral end organs that provide the brain with temporally precise information about head position in space required for motor coordination and postural stability. Irregular vestibular afferents of the inner ear are particularly sensitive to rapid changes in acceleration, or jerk, which is necessary for making quick, corrective movements and postural adjustments. Vestibular short-latency evoked potentials (VsEPs) are waveforms that provide a measure of synchronous irregular afferent activity originating from peripheral (early peaks) and central (later peaks) vestibular pathways. These VsEPs are elicited by head jerk stimuli, commonly used preclinically. Previous studies have shown that early VsEP waves are dependent upon jerks of an adequate intensity, number, and duration. However, less is known about jerk characteristics necessary for generation of reliable VsEP signals centrally (later peaks). The present study examines the precise temporal dynamics of peripheral and central vestibular centers across a broad range of mechanical vestibular load in rats. We found differential changes in synchrony and timing driven by jerk repetition, intensity, and duration between early and late VsEP waves representing distinct anatomical components of the vestibular circuit. Our results suggest that central components are uniquely sensitive to jerk duration, intensity, and repetition, indicating a disconnect between peripheral and central neuronal recruitment, adaptive plasticity, and time-frequency dynamics. This work provides a foundation for using VsEP to assess jerk-induced physiological vestibular dysfunction and to understand how central relays differentially adapt to variations of mechanical vestibular stress compared with the precise, high-fidelity transmission observed in the periphery.

Standing balance relies on the continuous detection of body motion across a wide range of amplitudes and frequencies. According to Weber's law, sensory discrimination should degrade in proportion to stimulus amplitude, yet vestibular self-motion perception deviates from this prediction. Whether this deviation extends to the vestibular control of posture remains unknown. To test this hypothesis, we delivered amplitude-increasing electrical vestibular stimulation (EVS, 0-2 mA) at four frequencies (0.1, 0.2, 0.5, and 1 Hz) to 10 healthy young adults, and quantified balance discrimination thresholds (DTs) from the gain and inter-trial variability of the lateral ground reaction force, using signal detection theory. Balance control DTs increased sublinearly with EVS amplitude at all frequencies, deviating from Weber's law. Both balance-correcting response gain and variability accounted for this deviation: gain decreased more slowly than the strictly inverse relationship that would have alone produced strict adherence to Weber's law, while variability exhibited an initial increase followed by saturation at higher EVS amplitudes, a signal-dependent structure necessary to reproduce the observed DT pattern. EVS frequency modulated the shape of this deviation but affected neither overall DT nor the signal-to-noise ratio of the balance-correcting response, which instead remained similar across frequencies. This study revealed a particular property of postural control discrimination by extending the psychophysical and neural deviations from Weber's law previously reported for vestibular perception. Overall, these results provide a better understanding of the balance control discrimination process and provide potential additional assessment criteria for vestibular impairments.

Post-stroke gait impairment is associated with altered muscle coordination. Understanding how functional muscle coordination contributes to joint control is essential for clarifying the mechanisms of gait impairment after stroke. Functional muscle network approaches quantify how muscle interactions contribute to joint kinematics. We investigated how gait-related functional muscle networks are reorganized after stroke and how this reorganization relates to motor impairment and gait dysfunction. Thirty-five participants with subacute stroke and 25 healthy controls underwent gait analysis using surface electromyography and lower-limb kinematics. We quantified functionally similar (redundant information), complementary (synergistic information), and independent (unique information) muscle interactions underlying joint kinematics. Participants with stroke exhibited greater redundant information and lower independent information than healthy controls. Stroke-specific functional muscle network modules emerged through merging modules observed in healthy controls. Stroke-specific module activation was also associated with motor impairment and gait performance. Overall, these findings identify a shift toward more redundant muscle coordination and stroke-specific reorganization of functional network modules, providing new insights into post-stroke gait dysfunction.

We explored the role of proprioceptive feedback from Ia afferents in intra-muscle synergies stabilizing muscle force with the help of muscle vibration, which is known to increase presynaptic inhibition of those afferents to alpha-motoneurons. Healthy young adults performed an accurate three-finger force production task by pressing with the index, middle and ring fingers of the dominant (right) hand. This was done without vibration and with vibration applied to the extrinsic finger flexors, extensors, both muscles, the palm, or biceps brachii. High-density electromyography was used to identify motor units in both finger flexors and extensors. The raster plots of motor units were converted into firing frequency functions and then subjected to principal component analysis to extract stable motor unit groups (MU-modes). The uncontrolled manifold (UCM) analysis was used to quantify the variance components affecting and not affecting force, and the synergy index in the MU-mode space. Contrary to our expectations, the synergy index did not drop under any vibration condition and showed an increase during vibration applied simultaneously to both flexor and extensor muscles. This was primarily associated with a drop in the component of variance affecting the force magnitude. The results speak against an important role of monosynaptic Ia-afferent projections to alpha-motoneurons in the formation of intra-muscle synergies. They suggest that muscle vibration can play the role of a noisy signal decreasing performance-affecting variance via stochastic resonance effects.

Serial dependence, whereby current perception is systematically biased toward the most recent sensory experience, has been demonstrated across multiple sensory modalities. However, whether serial dependence occurs during active haptic perception remains unknown. Moreover, because haptic perception of object geometry depends on hand movements for sensory acquisition (i.e., active touch), it remains unclear whether serial dependence, if any, originates from perceptual processing, movement, or both. Here, we investigated whether active haptic perception exhibits attractive serial dependence using a newly developed haptic device that let participants explore virtual slopes of different heights. Participants reported perceived slope heights, and we recorded their kinematics. Perceptual judgments were systematically attracted toward the most recently experienced slope, demonstrating serial dependence during active haptic perception. By contrast, none of the kinematic parameters exhibited corresponding serial dependence. These findings show that serial dependence extends to the somatosensory perceptual domain and suggest that the observed perceptual bias was not mediated by systematic changes in hand movements.

Humans exhibit head movements synchronized with musical rhythms, frequently observed during instrument playing or dancing (e.g., hip hop). We conjectured that vestibular input from head movements could aid motor execution anticipatory of musical rhythms, known as sensorimotor synchronization (SMS). To examine this, we applied subthreshold galvanic vestibular stimulation (GVS) simultaneously with musical beats while healthy adults performed SMS to those beats. We designed a GVS waveform where the current rose steeply before each beat onset, which was expected to trigger intense vestibular afferent firing before the beats (as actual head movements would). Participants flexed their index finger in synchrony with the beats of syncopated auditory rhythms. In GVS trials, the SMS timing variability was significantly lower than in trials without GVS, suggesting that vestibular input stabilizes SMS to musical beats. Additionally, a control experiment using a waveform with a gradually increasing current revealed no significant difference in SMS variability between trials with and without GVS. This study provides causal evidence that the vestibular system is involved in synchronized movement to music. In addition, the results suggest that a specific parameter of the GVS waveform could influence predictive motor execution anticipatory of upcoming auditory events.

The results in this article demonstrate that the central nervous system CNS plans trajectories in the vertical plane by minimizing a Generalized Dynamic Jerk GJerk cost function, which we have proposed as an advancement of the traditional Minimum Jerk cost function. While the traditional Jerk cost function generates smooth trajectories by minimizing the third derivative of joint angle over time, it neglects real dynamic constraints most notably the effect of gravity. According to our engineering interpretation, the arm functions as a constrained manipulator where gravity acts as a non-linear, state-dependent bias; thus, the asymmetry in velocity profiles is not an anomaly but an optimal adaptation to the gravitational field. Consequently, it predicts mathematically symmetrical upward and downward movements, even in contexts where gravitational forces play a decisive role. The proposed GJerk cost function extends the classical framework by incorporating position-dependent dynamic coefficients into the cost function, thereby embedding gravitational effects directly within the planning process. As a result, the generated movements are not only smooth in a mathematical sense but also physically and mechanically consistent with the actual torque and energy demands imposed by the musculoskeletal system. The GJerk cost function reduces angular change in high-gravitational-torque regions because it makes the joint configuration with the highest gravitational torque more expensive within the cost function, prompting the planner to choose a slower and more conservative movement. This does not physically dissipate energy, but it acts as a behavioral damping mechanism, similar to how humans naturally slow down when approaching a high load or potentially dangerous configuration. In this way, the GJerk cost function reduces abrupt changes in joint kinetic energy and prevents sudden jumps in acceleration, ultimately producing a smoother and more stable trajectory that aligns with both biomechanical reality and observed human behavior. Within this framework, upward movements become inherently more costly than downward ones, penalizing configurations that require large torques to counteract gravity. This induces a biomechanically meaningful asymmetry, ensuring the resulting trajectories reflect the body's true mechanical constraints rather than mere geometric smoothness. Our empirical results demonstrate that the GJerk cost function provides a more realistic and physiologically grounded account of motor planning in the vertical plane, linking smoothness optimization with genuine dynamic requirements and offering a closer approximation to biological motor behavior

How cognitive control influences the correction of motor errors is an important question. In this study, we examined how the slow and fast processes that constitute motor adaptation are modulated by cognitive load. To address this question, we used a novel approach that differed from traditional dual-task experiments that have assessed the role of fast processes by decreasing attention to the motor adaptation task. Here, cognitive load was manipulated using a decision-making task with easy and hard difficulty levels, while simultaneously adapting to a perturbation and maintaining attention on the task. Our results showed that the hard decision-making task increased cognitive load relative to the easy task, resulting in attenuated steady-state learning. The relative contributions of the fast and slow components were assessed using a dual state-space model, which showed that the former was larger under the high-load condition, whereas the latter was larger under the easy-load condition, consistent with a competition model in which a shared error signal is partitioned between the two processes. We also showed that the effect of cognitive load on fast processes was not attributable to increased reaction times or task performance. Taken together, these results support the notion that faster explicit motor adaptation processes derive from cognitive processes involved in action selection.

Primates use eye movements to explore and gather information about their external, visual world. Similarly, even when there is nothing to see spontaneous eye movements reflect the structure and the exploration of internal, conceptual knowledge. However, it remains unclear what mechanism links eye movements to this internal search process. One possibility is that eye movements reflect visual imagery or visual exploration strategies used to explore conceptual knowledge. On the other hand, eye movements may reflect attentional movements in the conceptual space, which are independent from visual experience. Early blind individuals are a useful testbed for this hypothesis in that they never had access to functional vision, thus ruling out the influence of imagery or recycling of visual exploration strategies. To this end, we asked early blind individuals to perform a random number generation task while recording their eye movements. Using electrooculography (EOG), we found that eye movements track the exploration of the mental number line in both sighted and blind: participants moved their eyes to the right for positive changes in magnitude in the number sequence and to the left for negative changes, with eye movement amplitude scaling with the magnitude difference. Furthermore, sighted and early blind participants showed a similar temporal profile, with the effect peaking around 750 ms before number onset. These findings support the hypothesis that internally generated shifts of attention, rather than eye movements per se, drive the exploration of conceptual spaces.

Dexterous hand control is essential for daily activities and a top restoration priority for people with tetraplegia, yet neurophysiological datasets suitable for studying and decoding naturalistic hand behavior remain scarce. Most available recordings constrain movements to a small number of degrees of freedom or cover only a single stereotypical grasp-and-hold structure. Moreover, previous brain-computer interface (BCI) studies have largely relied on signals from a single cortical area, even though dexterous hand control is distributed across an interconnected frontoparietal network. To address these limitations, we designed a paradigm that elicits rich hand movements across 40 distinct hand-object interaction conditions. We recorded simultaneous frontoparietal activity with hand kinematics from a rhesus macaque performing them. Neural activity was recorded from the primary motor cortex, anterior intraparietal area, and ventral premotor cortex using microelectrode arrays spanning 1,920 channels, while a multi-camera markerless motion-capture system acquired video from which kinematics were extracted offline. The dataset comprises data from 20 sessions, including processed neural features, synchronized 3D coordinates of hand and elbow keypoints, and trial-level metadata including task conditions and event timing. We further provide technical validation, including a neural decoding benchmark with multiple algorithms for continuous keypoint coordination reconstruction. We found that cross-day and cross-task decoding performance varied among algorithms. Variation in channel availability leads to different performance degradation curves in different algorithms. This task-rich dataset offers a valuable resource for investigating the neural mechanisms of dexterous hand control and for advancing the performance of motor BCIs.

Most animals move intermittently. Of these, animals that fly and swim move in two stages: during active propulsion, when they beat their wings or swing their tails, and right after, when they glide or coast through the air or water. The kinematics of active movements are typically well studied, but the coasting period afterwards is less understood. We used larval zebrafish as a model of intermittent locomotion. Larval zebrafish swim in discrete bouts lasting ~200 ms, coast for short durations and distances, and then are largely stationary for ~800 ms. We find that larval zebrafish do not coast like a passive object. While they coast for distances that are correlated with the prior swim's strength, as expected from physics, they seem to be able to modulate the mechanics of their coasting: the time constant is not a constant, but varies from coast-to-coast. Furthermore, the time constant is correlated with the duration of the interval between swim bouts. This suggests that larval zebrafish can either shorten or extend their coasting duration, and that coasting inhibits the initiation of the next swim. Finally, the time constant changes quickly, while other swimming kinematics (e.g., distance swum) are autocorrelated over the course of at least several seconds. Altogether, this suggests that fish, and perhaps other animals that move intermittently, actively modulate their post-propulsion movement, possibly to gather sensory feedback in the absence of blurry visual feedback associated with fast locomotion.

Computer mouse weight has been proposed to influence human motor performance, but existing evidence comes largely from small, short-duration controlled studies, leaving its relationship to performance during naturalistic gameplay unresolved. We analyzed one-week skill improvement in Aimlabs, a popular first-person shooter aim-training and assessment platform, among 9,067 players whose telemetry recorded a mouse-model change (switchers) during self-directed game use, using a 21-day baseline and 7-day follow-up; 4,991 players with a single mouse model (non-switchers) observed over matched pseudo-anchor intervals provided a secondary contextual comparison. Post-switch mouse weight was represented by eight bands spanning 35-124 g. The primary multivariable generalized additive regression model accounted for baseline skill, pre- and post-switch practice intensity, and pre- and post-switch mouse sensitivity, and allowed the association between weight band and improvement to vary with baseline skill, post-switch practice, and post-switch sensitivity. For each weight band, predicted mean one-week improvement was standardized to the observed distribution of these covariates among switchers and reported in percentile-rank points. Statistical significance was evaluated using 1,000 permutations in which observed mouse weights were randomly reassigned among switchers without replacement and the model was refitted to generate empirical null distributions for the weight-related test statistics. Predicted improvement differed significantly across the eight weight bands (p = 0.001). Pairwise comparisons identified significant differences between bands (p < 0.05), but no single band was associated with significantly greater predicted improvement than all seven others. In this large naturalistic cohort, predicted improvement was highest for players with 35-44 g mice, followed by 45-54 and 55-64 g, and several pairwise comparisons showed significantly greater improvement in lighter than in heavier weight bands. Across the examined baseline-skill profiles, the lowest predicted improvements occurred in either the 85-99 or 115-124 g band. Predicted improvement differed across weight bands at the 25th-percentile and median baseline-skill values (p = 0.002 and p = 0.003) but not at the 75th percentile (p = 0.153). However, the weight-band x baseline-skill interaction was not significant (p = 0.181), indicating that the analysis did not establish that weight-related differences varied by skill level.

Feedforward control is impaired after stroke, but whether practice improves it in the chronic stage remains unclear. In fast single-joint movements, feedforward control scales initial acceleration to movement amplitude. Feedback-error-learning theory predicts that fast practice should promote recalibration. We tested whether speed-emphasized reach training improved this scaling in the more-affected arm. Thirty-six individuals with mild-to-moderate chronic stroke completed 2,080 reaches over four sessions emphasizing Speed (n = 17) or Accuracy (n = 19). At baseline, 3 days, and 1 month after training, participants performed single-joint elbow movements of three amplitudes without online visual feedback. The slope relating initial peak acceleration to target amplitude quantified feedforward scaling. At baseline, scaling was reduced on the more-affected side for extension and flexion. Speed training increased flexion scaling at 3 days, with 14 of 17 participants improving. The group-by-session interaction showed a greater increase after Speed than Accuracy training. Scaling declined by 1 month; no training-related changes occurred for extension. Peak acceleration occurred within 100 ms. Time to peak velocity, an index of pulse width, showed no group-specific training effect. Thus, speed-emphasized training produced a short-term improvement in early flexion acceleration scaling that transferred to an untrained single-joint task and was consistent with improved feedforward control. Transfer primarily reflected acceleration pulse-height rather than pulse-width modulation.

Cortical proprioceptive processing to passive movements can be quantified with evoked and induced responses in magnetoencephalographic (MEG) signals. We examined how intensity of proprioceptive stimulation (i.e., tendon-tap evoked movement) scales cortical processing of proprioceptive afference from the knee joint, and whether it affects stimulus-to-stimulus response variability. Twenty-one healthy volunteers (28.2{+/-}5 yr, 10 females) underwent a total of 100 right patellar tendon taps (5.0--6.0s inter-stimulus interval) evoked by a novel MEG-compatible stimulator under higher and lower intensity conditions. Strength of cortical evoked and induced MEG and electromyographic responses from the vastus lateralis and medialis muscles were quantified, and their variability were assessed using a matched sliding-window coefficient of variation (CoV). Higher intensity stimulation elicited significantly stronger cortical evoked (~11%) and induced (~17% for beta suppression and ~18% for beta rebound) responses, and muscular response (~27%) than lower intensity stimulation (p<0.05). The stimulus intensity did not affect response variability, with comparable CoV values between higher and lower intensity condition (p>0.05), but the muscular responses showed greater variability than the cortical ones in both intensity conditions (CoV: ~30% vs. ~10%, p<0.001). In addition, the variability in cortical and muscular responses were not significantly correlated (p>0.05). Our results indicate that patellar tendon-tap intensity scaled cortical and muscular response gain, but did not measurably alter response variability. The distinct variability profiles of cortical evoked fields and stretch-reflex muscular response suggest that proprioceptive afference evoked by tendon-tap is transformed differently across cortical and spinal levels.

Motor imagery and overt action are proposed to share common planning mechanisms while relying on distinct processes during movement performance. To investigate how repetition affects physical and imagined movements, participants physically or mentally drew paths while avoiding barriers. The barrier orientations were either repeated or different across consecutive trials, and the modality (execution or imagery) of the trials either changed or remained the same for two consecutive trials. Reaction time and movement time were analysed as measures of movement planning and task performance, respectively. Imagined movements produced longer reaction times and movement times than physical movements. Repetition of orientation reduced reaction times in both physical and imagined trials, indicating that trajectory repetition facilitated movement preparation. In contrast, previous trial type influenced reaction times only for physical movements, which were only initiated faster when preceded by another physical trial. Different effects emerged for movement time. Physical movements were faster when the same trajectory was repeated no matter the previous trial type, whereas imagined movements were unaffected by orientation and instead showed shorter durations when preceded by another imagined trial. The findings indicate that physical and imagined movements rely on more similar trajectory representations during the planning stage, but diverge during task performance. While physical movements appear to benefit from the persistence of previously generated movement trajectories, imagined trials seems more influenced by modality-specific cognitive processes. These results provide behavioural support for the Motor-Cognitive model and contribute to understanding how movement repetition influences overt and imagined actions.

Background: Paretic-arm nonuse and trunk compensation after stroke are often interpreted as impairment or learned behavior but may also reflect task-dependent optimization. We previously showed that gravitational shoulder effort and force reserve shape these behaviors. Here, we tested whether endpoint precision is an additional constraint. Methods: Twenty-two individuals with stroke and 22 matched controls performed a seated Proximal Arm Nonuse reaching task toward small (2 cm) and large (12 cm) targets. Stroke participants were tested at normal arm weight and with the paretic arm mechanically lightened; controls were tested at normal arm weight and while holding a dumbbell corresponding to 85% of maximal voluntary shoulder force. Results: In stroke participants, trunk compensation was 15% lower for the large target than for the small target, independently of arm weight condition (F(1,13)=8.166, p=.013, pes=.39). Target size did not significantly affect trunk compensation in controls or anterior deltoid activation in either group. In stroke participants, movement time was 24% longer for the small target than for the large target (F(1,13)=8.533, p=.012, pes=.40). In controls, the small target increased movement time only when the arm was weighted (F(1,18)=14.9, p=.001, pes=.45), not at normal arm weight (F(1,18)=0.158, p=.695, pes=.01). Conclusions: Endpoint precision altered reaching after stroke partly independently of gravitational shoulder effort. Trunk compensation after stroke was therefore modulated by task demands rather than fixed by impairment, a pattern consistent with, although not a direct demonstration of, an optimal-control account. Rehabilitation should evaluate compensation by its functional role and the cost of suppressing it, not only by its deviation from typical kinematics, and should treat target size as an adjustable parameter of the task. Clinical Trial: NCT04747587. https://clinicaltrials.gov/study/NCT04747587

Background: Immediate transcranial evoked potentials (iTEPs) are ultra-early electroencephalographic responses elicited by single-pulse transcranial magnetic stimulation (TMS) of the primary motor cortical hand area (M1-HAND). Their characteristic latency, waveform, and sensitivity to short-interval intracortical inhibition suggest a close relationship to the cortical generators of indirect corticospinal volleys (I-waves). Here, we tested the hypothesis that iTEPs constitute a fundamental physiological response of human motor cortex and therefore generalize across motor representations, including the leg representation (M1-LEG). Methods: Single-pulse TMS was delivered over the motor cortical representation of the right tibialis anterior (TA) in 16 healthy volunteers. In a subset of participants (n=10), stimulus-response curves and paired-pulse short-interval intracortical inhibition (SICI) measures were obtained. Results: TMS of M1-LEG elicited reproducible iTEPs consisting of a slow positive deflection with superimposed high-frequency peaks with topographic maxima in electrodes adjacent to the stimulation site. M1-LEG iTEPs emerged close to active motor threshold and increased in prevalence and amplitude with increasing stimulation intensity. Paired-pulse stimulation produced consistent SICI of the second and third iTEP peaks. M1-LEG stimulation also evoked conventional later TEPs with latencies and polarities closely resembling those recorded after M1-HAND stimulation. Conclusions: TMS of the human M1-LEG elicits robust iTEPs that closely resemble those recorded from M1-HAND in their timing, intensity dependence, and sensitivity to intracortical inhibition. These findings indicate that iTEPs are not specific to M1-HAND but reflect a general physiological response of human motor cortex closely linked to corticospinal I-wave generation. This broadens their utility as a non-invasive probe of excitatory and inhibitory circuit dynamics throughout the human motor system.

Mistakes make up our daily lives. Once a mistake has been committed, it is common to pause before you continue. This slowing is called post-error slowing (PES). Although several theories have been proposed to account for PES in humans, findings across cognitive tasks show variation in how PES occurs, and it is unclear how this phenomenon may translate across modalities to a key model organism of human cognition, macaque monkeys. To determine whether monkeys exhibit PES, we tested three rhesus macaque monkeys in components of cognitive sequential decision-making tasks that used either eye tracking or touch screens to report responses. Here we show that monkeys exhibit non-adaptive, error type-dependent PES across modalities. Task structure and context also modulated PES in the eye tracking task, and no modality improved task performance following PES. These results suggest that monkey PES is a combination of cognitive and non-cognitive related responses to error that are modulated by task structures such as error type and task context. Overall, the flexibility in monkey PES is comparable to that of humans, further supporting the importance of monkeys as a translational model in investigating the mechanisms of PES.