Effect of a single session of sensorimotor rhythm neurofeedback training on the putting performance of professional golfers.

Sensorimotor rhythm (SMR) activity has been associated with automaticity and flow in motor execution. Studies have revealed that neurofeedback training (NFT) of the SMR can improve sports performance; however, few studies have adequately explored the effects of a single session of such NFT or examined the possible mechanisms underlying these effects on sports performance. This study recruited 44 professional golfers to address these gaps in the literature. A crossover design was employed to determine the order of the participation in the NFT and no-training control conditions. The participants were asked to perform 60 10-foot putts while electroencephalograms (EEGs) were recorded before and after the tasks. In pre-and post-tests, visual analog scales were used to assess the psychological states associated with SMR activities including the levels of attention engagement, conscious motor control, and physical relaxation. The results revealed that a single NFT session effectively increased SMR power and improved putting performance compared with the control condition. The subjective assessments also revealed that the participants reported lower attention engagement, less conscious control of the motor details and were more relaxed in the putting task, suggesting that SMR NFT promoted effortless and quiescent mental states during motor preparation for a putting task. This study aligns with theoretical hypotheses and extends current knowledge by revealing that a single session of SMR NFT can effectively enhance SMR power and improve putting performance in professional golfers. It also provides preliminary evidence of the possible underlying mechanisms that drive the effect of SMR NFT on putting performances.

Basal forebrain functional connectivity as a mediator of associations between cardiorespiratory fitness and cognition in healthy older women.

Age-related cholinergic dysfunction within the basal forebrain (BF) is one of the key hallmarks for age-related cognitive decline. Given that higher cardiorespiratory fitness (CRF) induces neuroprotective effects that may differ by sex, we investigated the moderating effects of sex on the associations between CRF, BF cholinergic function, and cognitive function in older adults. 176 older adults (68.5 years) were included from the Nathan Kline Institute Rockland Sample. Functional connectivity (rsFC) of the BF subregions including the medial septal nucleus/diagonal band of Broca (MS/DB) and nucleus basalis of Meynert (NBM) were computed from resting-sate functional MRI. Modified Astrand-Ryhming submaximal cycle ergometer protocol was used to estimate CRF. Trail making task and inhibition performance during the color word interference test from the Delis-Kaplan Executive Function System and Rey Auditory Verbal Learning Test were used to examine cognitive function. Linear regression models were used to assess the associations between CRF, BF rsFC, and cognitive performance after controlling for age, sex, and years of education. Subsequently, we measured the associations between the variables in men and women separately to investigate the sex differences. There was an association between higher CRF and greater rsFC between the NBM and right middle frontal gyrus in older men and women. There were significant associations between CRF, NBM rsFC, and trail making task number-letter switching performance only in women. In women, greater NBM rsFC mediated the association between higher CRF and better trail making task number-letter switching performance. These findings provide evidence that greater NBM rsFC, particularly in older women, may be an underlying neural mechanism for the relationship between higher CRF and better executive function.

A mental workload and biomechanical assessment during split-belt locomotor adaptation with and without optic flow.

Adaptive human performance relies on the central nervous system to regulate the engagement of cognitive-motor resources as task demands vary. Despite numerous studies which employed a split-belt induced perturbation to examine biomechanical outcomes during locomotor adaptation, none concurrently examined the cerebral cortical dynamics to assess changes in mental workload. Additionally, while prior work suggests that optic flow provides critical information for walking regulation, a few studies have manipulated visual inputs during adaption to split-belt walking. This study aimed to examine the concurrent modulation of gait and Electroencephalography (EEG) cortical dynamics underlying mental workload during split-belt locomotor adaptation, with and without optic flow. Thirteen uninjured participants with minimal inherent walking asymmetries at baseline underwent adaptation, while temporal-spatial gait and EEG spectral metrics were recorded. The results revealed a reduction in step length and time asymmetry from early to late adaptation, accompanied by an elevated frontal and temporal theta power; the former being well corelated to biomechanical changes. While the absence of optic flow during adaptation did not affect temporal-spatial gait metrics, it led to an increase of theta and low-alpha power. Thus, as individuals adapt their locomotor patterns, the cognitive-motor resources underlying the encoding and consolidation processes of the procedural memory were recruited to acquire a new internal model of the perturbation. Also, when adaption occurs without optic flow, a further reduction of arousal is accompanied with an elevation of attentional engagement due to enhanced neurocognitive resources likely to maintain adaptive walking patterns.

NeuroLISP: High-level symbolic programming with attractor neural networks.

Despite significant improvements in contemporary machine learning, symbolic methods currently outperform artificial neural networks on tasks that involve compositional reasoning, such as goal-directed planning and logical inference. This illustrates a computational explanatory gap between cognitive and neurocomputational algorithms that obscures the neurobiological mechanisms underlying cognition and impedes progress toward human-level artificial intelligence. Because of the strong relationship between cognition and working memory control, we suggest that the cognitive abilities of contemporary neural networks are limited by biologically-implausible working memory systems that rely on persistent activity maintenance and/or temporal nonlocality. Here we present NeuroLISP, an attractor neural network that can represent and execute programs written in the LISP programming language. Unlike previous approaches to high-level programming with neural networks, NeuroLISP features a temporally-local working memory based on itinerant attractor dynamics, top-down gating, and fast associative learning, and implements several high-level programming constructs such as compositional data structures, scoped variable binding, and the ability to manipulate and execute programmatic expressions in working memory (i.e., programs can be treated as data). Our computational experiments demonstrate the correctness of the NeuroLISP interpreter, and show that it can learn non-trivial programs that manipulate complex derived data structures (multiway trees), perform compositional string manipulation operations (PCFG SET task), and implement high-level symbolic AI algorithms (first-order unification). We conclude that NeuroLISP is an effective neurocognitive controller that can replace the symbolic components of hybrid models, and serves as a proof of concept for further development of high-level symbolic programming in neural networks.

Tunable Neural Encoding of a Symbolic Robotic Manipulation Algorithm.

We present a neurocomputational controller for robotic manipulation based on the recently developed "neural virtual machine" (NVM). The NVM is a purely neural recurrent architecture that emulates a Turing-complete, purely symbolic virtual machine. We program the NVM with a symbolic algorithm that solves blocks-world restacking problems, and execute it in a robotic simulation environment. Our results show that the NVM-based controller can faithfully replicate the execution traces and performance levels of a traditional non-neural program executing the same restacking procedure. Moreover, after programming the NVM, the neurocomputational encodings of symbolic block stacking knowledge can be fine-tuned to further improve performance, by applying reinforcement learning to the underlying neural architecture.

Compositional memory in attractor neural networks with one-step learning.

Compositionality refers to the ability of an intelligent system to construct models out of reusable parts. This is critical for the productivity and generalization of human reasoning, and is considered a necessary ingredient for human-level artificial intelligence. While traditional symbolic methods have proven effective for modeling compositionality, artificial neural networks struggle to learn systematic rules for encoding generalizable structured models. We suggest that this is due in part to short-term memory that is based on persistent maintenance of activity patterns without fast weight changes. We present a recurrent neural network that encodes structured representations as systems of contextually-gated dynamical attractors called attractor graphs. This network implements a functionally compositional working memory that is manipulated using top-down gating and fast local learning. We evaluate this approach with empirical experiments on storage and retrieval of graph-based data structures, as well as an automated hierarchical planning task. Our results demonstrate that compositional structures can be stored in and retrieved from neural working memory without persistent maintenance of multiple activity patterns. Further, memory capacity is improved by the use of a fast store-erase learning rule that permits controlled erasure and mutation of previously learned associations. We conclude that the combination of top-down gating and fast associative learning provides recurrent neural networks with a robust functional mechanism for compositional working memory.

Effect of Self-Controlled Practice on Neuro-Cortical Dynamics During the Processing of Visual Performance Feedback.

Evidence has accumulated that learners participating in self-controlled practice can both acquire skills and process task-relevant information more effectively than those participating in externally controlled practice. However, the impact of self-controlled practice on neuro-cognitive information processing during visual performance-related feedback has received limited investigation. We expected that individuals participating in self-controlled practice would exhibit elevated neuro-cognitive information processing, as assessed via electroencephalography (EEG), compared with those engaged with externally controlled practice. Participants practiced a golf-putting task under self-controlled or externally controlled (yoked) conditions while EEG data were recorded. Results indicated that EEG theta power was maintained at an elevated level during the feedback period in the self-controlled group relative to the yoked group. The yoked group did not display increases in theta power until the time at which the ball stopped. Both groups displayed similar improvement over the course of the experiment. Correlational analyses revealed that performance improvement within each group was related differently to EEG theta power. Specifically, the self-controlled group displayed positive relationships between theta power and performance improvement, while the yoked group displayed negative relationships. These results have implications regarding the relative effectiveness of self-controlled and externally controlled practice and the instances in which they may provide the most benefit.

Self-Controlled Practice to Achieve Neuro-Cognitive Engagement: Underlying Brain Processes to Enhance Cognitive-Motor Learning and Performance.

While self-controlled practice has been shown to be an effective practice methodology, the neuro-cognitive correlates of its effectiveness are unclear. We investigated whether learners participating in self-controlled practice exhibit increased neuro-cognitive engagement compared to externally controlled practice. Two groups (self-controlled and yoked) of 16 participants practiced and performed a golf putting task over 3 days. Working memory engagement, central executive activity, and cortical activation were assessed via electroencephalography as indicators of neuro-cognitive engagement. The self-controlled group exhibited more consistent working memory engagement, and greater central executive activity, compared to the yoked group during practice. Relationships were also observed between neuro-cognitive engagement during self-controlled practice and performance improvement, indicating that self-controlled practice uniquely benefitted from increased neuro-cognitive engagement.

A Comparison of Mental Workload in Individuals with Transtibial and Transfemoral Lower Limb Loss during Dual-Task Walking under Varying Demand.

OBJECTIVES: This study aimed to evaluate the influence of lower limb loss (LL) on mental workload by assessing neurocognitive measures in individuals with unilateral transtibial (TT) versus those with transfemoral (TF) LL while dual-task walking under varying cognitive demand. METHODS: Electroencephalography (EEG) was recorded as participants performed a task of varying cognitive demand while being seated or walking (i.e., varying physical demand). RESULTS: The findings revealed both groups of participants (TT LL vs. TF LL) exhibited a similar EEG theta synchrony response as either the cognitive or the physical demand increased. Also, while individuals with TT LL maintained similar performance on the cognitive task during seated and walking conditions, those with TF LL exhibited performance decrements (slower response times) on the cognitive task during the walking in comparison to the seated conditions. Furthermore, those with TF LL neither exhibited regional differences in EEG low-alpha power while walking, nor EEG high-alpha desynchrony as a function of cognitive task difficulty while walking. This lack of alpha modulation coincided with no elevation of theta/alpha ratio power as a function of cognitive task difficulty in the TF LL group. CONCLUSIONS: This work suggests that both groups share some common but also different neurocognitive features during dual-task walking. Although all participants were able to recruit neural mechanisms critical for the maintenance of cognitive-motor performance under elevated cognitive or physical demands, the observed differences indicate that walking with a prosthesis, while concurrently performing a cognitive task, imposes additional cognitive demand in individuals with more proximal levels of amputation.

A programmable neural virtual machine based on a fast store-erase learning rule.

We present a neural architecture that uses a novel local learning rule to represent and execute arbitrary, symbolic programs written in a conventional assembly-like language. This Neural Virtual Machine (NVM) is purely neurocomputational but supports all of the key functionality of a traditional computer architecture. Unlike other programmable neural networks, the NVM uses principles such as fast non-iterative local learning, distributed representation of information, program-independent circuitry, itinerant attractor dynamics, and multiplicative gating for both activity and plasticity. We present the NVM in detail, theoretically analyze its properties, and conduct empirical computer experiments that quantify its performance and demonstrate that it works effectively.

Motor Performance, Mental Workload and Self-Efficacy Dynamics during Learning of Reaching Movements throughout Multiple Practice Sessions.

The human capability to learn new motor skills depends on the efficient engagement of cognitive-motor resources, as reflected by mental workload, and psychological mechanisms (e.g., self-efficacy). While numerous investigations have examined the relationship between motor behavior and mental workload or self-efficacy in a performance context, a fairly limited effort focused on the combined examination of these notions during learning. Thus, this study aimed to examine their concomitant dynamics during the learning of a novel reaching skill practiced throughout multiple sessions. Individuals had to learn to control a virtual robotic arm via a human-machine interface by using limited head motion throughout eight practice sessions while motor performance, mental workload, and self-efficacy were assessed. The results revealed that as individuals learned to control the robotic arm, performance improved at the fastest rate, followed by a more gradual reduction of mental workload and finally an increase in self-efficacy. These results suggest that once the performance improved, less cognitive-motor resources were recruited, leading to an attenuated mental workload. Considering that attention is a primary cognitive resource driving mental workload, it is suggested that during early learning, attentional resources are primarily allocated to address task demands and not enough are available to assess self-efficacy. However, as the performance becomes more automatic, a lower level of mental workload is attained driven by decreased recruitment of attentional resources. These available resources allow for a reliable assessment of self-efficacy resulting in a subsequent observable change. These results are also discussed in terms of the application to the training and design of assistive technologies.

Cerebral cortical networking for mental workload assessment under various demands during dual-task walking.

While several studies have examined attentional reserve (via event-related potentials) and mental effort (via EEG spectral content) from various cortical regions during dual-task walking, none have assessed changes in the magnitude of interregional (cortico-cortical) communication as a measure of mental workload. Therefore, by deploying a traditional montage of electrode sites centered over the motor planning region as well as a more comprehensive graph theory-based approach encompassing the entire scalp, this study aimed to systematically examine changes in the magnitude of functional connectivity underlying cortico-cortical communication to assess changes in mental workload under various levels of challenge. Specifically, the Weighted Phase Lag Index (WPLI) was computed to assess the changes in magnitude of functional connectivity as participants performed a cognitive task under two demands (low and high) and two conditions (seated and walking). The results revealed enhanced fronto-centro-temporo-parietal theta connectivity during dual-task walking relative to being seated as well as a reduced inhibition of fronto-centro-temporo-parieto-occipital alpha networking as the demand on the secondary cognitive task increased. Collectively, these findings may reflect greater recruitment of task relevant processes to respond to increased cognitive-motor demands and thus an elevation of mental workload in an effort to maintain performance under varying levels of challenge. This work has the potential to inform future mental workload assessment applications in patient populations, including those who employ prostheses during cognitive-motor performance under various task demands.

Sleep health and its association with performance and motivation in tactical athletes enrolled in the Reserve Officers' Training Corps.

OBJECTIVE: To examine habitual sleep health and investigate how habitual sleep duration impacts performance and motivation in Reserve Officers' Training Corps (ROTC) tactical athletes. DESIGN: Observational. SETTING: A large, state university. PARTICIPANTS: Fifty-four young tactical athletes enrolled in ROTC. MEASUREMENTS: Participants wore wrist actigraph devices and completed sleep diaries for 7 days prior to completing a cognitive/motor test battery. RESULTS: The mean objective total sleep time of the participants was 6.17 ±â€¯0.69 hours, with only 7.4% of participants averaging ≥7 hours of sleep per day. A mean sleep quality rating between "Poor" and "Fair" was reported by 22.2% of participants. The mean Epworth Sleepiness Scale rating was 8.80 ±â€¯3.24, with 27.8% of participants reporting scores >10. Controlling for age and gender, the average objective total sleep duration was significantly associated with performance on the Symbol Digit Modalities Test (P = .026) and with motivation levels to perform the cognitive/motor battery (P = .016), but not with performance on the Psychomotor Vigilance Test, Flanker task, Trail Making Test, or Standing Broad Jump. CONCLUSIONS: ROTC tactical athletes habitually sleep less than the recommended 7 hours per day with roughly one-fourth reporting excessive daytime sleepiness and one-fifth reporting poor sleep quality, which may increase their risk for future adverse health outcomes. Longer sleep durations were associated with higher motivation levels and better cognitive processing speed performance; however, they were not associated with executive function, psychomotor vigilance, or broad jump performance.

Effects of sleep extension on cognitive/motor performance and motivation in military tactical athletes.

OBJECTIVE: Investigate the immediate and residual impacts of sleep extension in tactical athletes. METHODS: A randomized controlled trial (Sleep extension = EXT vs Control = CON) was conducted on 50 (EXT: 20.12 ± 2.01 years vs CON: 19.76 ± 1.09 years) tactical athletes enrolled in the Reserve Officers' Training Corps (ROTC). Participants wore actigraphs for 15 consecutive nights and completed a cognitive/motor battery after seven habitual sleep nights, after four sleep extension nights, and after the resumption of habitual sleep for four nights. The CON group remained on habitual sleep schedules for the entire study. RESULTS: During the intervention, the EXT group significantly increased mean sleep time (1.36 ± 0.71 h, p < 0.001). After sleep extension, there were significant between-group differences on the mean score change since baseline in Psychomotor Vigilance Test (PVT) reaction time (p = 0.026), Trail Making Test (TMT) - B time (p = 0.027), standing broad jump (SBJ) distance (p < 0.001), and motivation levels [to perform the cognitive tasks (p = 0.003) and the SBJ (p = 0.009)]; with the EXT group showing a greater enhancement in performance/motivation. After resuming habitual sleep schedules, significant between-group differences on the mean score change since baseline persisted on SBJ distance (p = 0.001) and motivation to perform the SBJ (p = 0.035), with the EXT showing greater enhancement in performance/motivation. CONCLUSION: Increasing sleep duration in military tactical athletes resulted in immediate performance benefits in psychomotor vigilance, executive functioning, standing broad jump distance, and motivation levels. Benefits on motor performance were evident four days after resumption of habitual sleep schedules. Military tactical athletes aiming to optimize their overall performance should consider the impact of longer sleep durations when feasible.

Semantic Memory Activation After Acute Exercise in Healthy Older Adults.

OBJECTIVES: A growing body of research suggests that regular participation in long-term exercise is associated with enhanced cognitive function. However, less is known about the beneficial effects of acute exercise on semantic memory. This study investigated brain activation during a semantic memory task after a single session of exercise in healthy older adults using functional magnetic resonance imaging (fMRI). METHODS: Using a within-subjects counterbalanced design, 26 participants (ages, 55-85 years) underwent two experimental visits on separate days. During each visit, participants engaged in 30 min of rest or stationary cycling exercise immediately before performing a Famous and Non-Famous name discrimination task during fMRI scanning. RESULTS: Acute exercise was associated with significantly greater semantic memory activation (Famous>Non-Famous) in the middle frontal, inferior temporal, middle temporal, and fusiform gyri. A planned comparison additionally showed significantly greater activation in the bilateral hippocampus after exercise compared to rest. These effects were confined to correct trials, and as expected, there were no differences between conditions in response time or accuracy. CONCLUSIONS: Greater brain activation following a single session of exercise suggests that exercise may increase neural processes underlying semantic memory activation in healthy older adults. These effects were localized to the known semantic memory network, and thus do not appear to reflect a general or widespread increase in brain blood flow. Coupled with our prior exercise training effects on semantic memory-related activation, these data suggest the acute increase in neural activation after exercise may provide a stimulus for adaptation over repeated exercise sessions. (JINS, 2019, 25, 557-568).

Fronto-parietal mirror neuron system modeling: Visuospatial transformations support imitation learning independently of imitator perspective.

Although the human mirror neuron system (MNS) is critical for action observation and imitation, most MNS investigations overlook the visuospatial transformation processes that allow individuals to interpret and imitate actions observed from differing perspectives. This problem is not trivial since accurately reaching for and grasping an object requires a visuospatial transformation mechanism capable of precisely remapping fine motor skills where the observer's and imitator's arms and hands may have quite different orientations and sizes. Accordingly, here we describe a novel neural model to investigate the dynamics between the fronto-parietal MNS and visuospatial processes during observation and imitation of a reaching and grasping action. Our model encompasses i) the inferior frontal gyrus (IFG) and inferior parietal lobule (IPL), regions that are postulated to produce neural drive and sensory predictions, respectively; ii) the middle temporal (MT) and middle superior temporal (MST) regions that are postulated to process visual motion of a particular action; and iii) the superior parietal lobule (SPL) and intra-parietal sulcus (IPS) that are hypothesized to encode the visuospatial transformations enabling action observation/imitation based on different visuospatial viewpoints. The results reveal that when a demonstrator executes an action, an imitator can reproduce it with similar kinematics, independently of differences in anthropometry, distance, and viewpoint. As with prior empirical findings, similar model synaptic activity was observed during both action observation and execution along with the existence of both view-independent and view-dependent neural populations in the frontal MNS. Importantly, this work generates testable behavioral and neurophysiological predictions. Namely, the model predicts that i) during observation/imitation the response time increases linearly as the rotation angle of the observed action increases but remain similar when performing both clockwise and counterclockwise rotation and ii) IPL embeds essentially view-independent neurons while SPL/IPS includes both view-independent and view-dependent neurons. Overall, this work suggests that MT/MST visuomotion processes combined with the SPL/IPS allow the MNS to observe and imitate actions independently of demonstrator-imitator spatial relationships.

Biomechanical and neurocognitive performance outcomes of walking with transtibial limb loss while challenged by a concurrent task.

Individuals who have sustained loss of a lower limb may require adaptations in sensorimotor and control systems to effectively utilize a prosthesis, and the interaction of these systems during walking is not clearly understood for this patient population. The aim of this study was to concurrently evaluate temporospatial gait mechanics and cortical dynamics in a population with and without unilateral transtibial limb loss (TT). Utilizing motion capture and electroencephalography, these outcomes were simultaneously collected while participants with and without TT completed a concurrent task of varying difficulty (low- and high-demand) while seated and walking. All participants demonstrated a wider base of support and more stable gait pattern when walking and completing the high-demand concurrent task. The cortical dynamics were similarly modulated by the task demand for both groups, to include a decrease in the novelty-P3 component and increase in the frontal theta/parietal alpha ratio power when completing the high-demand task, although specific differences were also observed. These findings confirm and extend prior efforts indicating that dual-task walking can negatively affect walking mechanics and/or neurocognitive performance. However, there may be limited additional cognitive and/or biomechanical impact of utilizing a prosthesis in a stable, protected environment in TT who have acclimated to ambulating with a prosthesis. These results highlight the need for future work to evaluate interactions between these cognitive-motor control systems for individuals with more proximal levels of lower limb loss, and in more challenging (ecologically valid) environments.

Changes in Mental Workload and Motor Performance Throughout Multiple Practice Sessions Under Various Levels of Task Difficulty.

The allocation of mental workload is critical to maintain cognitive-motor performance under various demands. While mental workload has been investigated during performance, limited efforts have examined it during cognitive-motor learning, while none have concurrently manipulated task difficulty. It is reasonable to surmise that the difficulty level at which a skill is practiced would impact the rate of skill acquisition and also the rate at which mental workload is reduced during learning (relatively slowed for challenging compared to easier tasks). This study aimed to monitor mental workload by assessing cortical dynamics during a task practiced under two difficulty levels over four days while perceived task demand, performance, and electroencephalography (EEG) were collected. As expected, self-reported mental workload was reduced, greater working memory engagement via EEG theta synchrony was observed, and reduced cortical activation, as indexed by progressive EEG alpha synchrony was detected during practice. Task difficulty was positively related to the magnitude of alpha desynchrony and accompanied by elevations in the theta-alpha ratio. Counter to expectation, the absence of an interaction between task difficulty and practice days for both theta and alpha power indicates that the refinement of mental processes throughout learning occurred at a comparable rate for both levels of difficulty. Thus, the assessment of brain dynamics was sensitive to the rate of change of cognitive workload with practice, but not to the degree of difficulty. Future work should consider a broader range of task demands and additional measures of brain processes to further assess this phenomenon.

Combined assessment of attentional reserve and cognitive-motor effort under various levels of challenge with a dry EEG system.

A novel ERP approach was proposed to index variations in mental workload, particularly in attentional reserve, which is complementary to EEG spectral content thought to reflect mental effort. To our knowledge, no study has assessed mental effort and attentional reserve simultaneously in EEG gel-based and, importantly, dry systems, which are particularly well suited for real-world settings. Therefore, by systematically considering ERP, EEG spectral, and importantly the combination of both, this study examined if a small set of dry EEG electrodes could detect changes in both spectral and ERP metrics to assess the mental workload under various challenges with a similar fidelity to their gel-based counterparts in a laboratory setting. By employing both EEG gel-based and dry systems, the ERP and spectral markers were computed while participants executed a visuomotor task under three levels of challenge. For both EEG systems, more challenging levels of difficulty were associated with concomitant changes in ERP amplitude, and spectral power reflected a reduction of the attentional reserve and an increase in cognitive-motor effort, respectively. Those variations in attentional reserve and cognitive-motor effort collectively indexed mental workload with nearly identical fidelity for both gel-based and dry EEG systems. These findings promise to assess the mental workload in situations where the use of dry EEG systems could be advantageously employed to examine human cognitive-motor performance.

Measurement of attentional reserve and mental effort for cognitive workload assessment under various task demands during dual-task walking.

Previous work focused on cognitive workload assessment suggests EEG spectral content and component amplitudes of the event-related potential (ERP) waveform may index mental effort and attentional reserve, respectively. Although few studies have assessed attentional reserve and mental effort during upper-extremity performance, none have employed a combined approach to measure cognitive workload during locomotion. Therefore, by systematically considering ERPs, spectral content and importantly their combination, this study aimed to examine whether concurrent changes in spectral content and ERPs could collectively serve as an index of cognitive workload during locomotion. Specifically, ERP and EEG biomarkers were assessed as participants performed a cognitive task under two levels of difficulty (easy or hard) and two conditions (seated or walking). Changes in attentional reserve and mental effort appeared to collectively index cognitive workload under varying demands due to changes in task difficulty or performance conditions. This work can inform cognitive workload assessment in patient populations with gait deficiencies for future applications.