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1. Eye-Tracking in Physical Human–Robot Interaction: Mental Workload and Performance Prediction

   https://doi.org/10.1177/00187208231204704  

   Upasani, Satyajit ; Srinivasan, Divya ; Zhu, Qi ; Du, Jing ; Leonessa, Alexander ( October 2023 , Human Factors: The Journal of the Human Factors and Ergonomics Society)

   In Physical Human–Robot Interaction (pHRI), the need to learn the robot’s motor-control dynamics is associated with increased cognitive load. Eye-tracking metrics can help understand the dynamics of fluctuating mental workload over the course of learning.

   The aim of this study was to test eye-tracking measures’ sensitivity and reliability to variations in task difficulty, as well as their performance-prediction capability, in physical human–robot collaboration tasks involving an industrial robot for object comanipulation.

   Participants (9M, 9F) learned to coperform a virtual pick-and-place task with a bimanual robot over multiple trials. Joint stiffness of the robot was manipulated to increase motor-coordination demands. The psychometric properties of eye-tracking measures and their ability to predict performance was investigated.

   Stationary Gaze Entropy and pupil diameter were the most reliable and sensitive measures of workload associated with changes in task difficulty and learning. Increased task difficulty was more likely to result in a robot-monitoring strategy. Eye-tracking measures were able to predict the occurrence of success or failure in each trial with 70% sensitivity and 71% accuracy.

   The sensitivity and reliability of eye-tracking measures was acceptable, although values were lower than those observed in cognitive domains. Measures of gaze behaviors indicative of visual monitoring strategies were most sensitive to task difficulty manipulations, and should be explored further for the pHRI domain where motor-control and internal-model formation will likely be strong contributors to workload.

   Future collaborative robots can adapt to human cognitive state and skill-level measured using eye-tracking measures of workload and visual attention.

    

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2. Neuroplasticity enables bio-cultural feedback in Paleolithic stone-tool making

   https://doi.org/10.1038/s41598-023-29994-y  

   Hecht, Erin Elisabeth ; Pargeter, Justin ; Khreisheh, Nada ; Stout, Dietrich ( February 2023 , Scientific Reports)

   Stone-tool making is an ancient human skill thought to have played a key role in the bio-cultural co-evolutionary feedback that produced modern brains, culture, and cognition. To test the proposed evolutionary mechanisms underpinning this hypothesis we studied stone-tool making skill learning in modern participants and examined interactions between individual neurostructural differences, plastic accommodation, and culturally transmitted behavior. We found that prior experience with other culturally transmitted craft skills increased both initial stone tool-making performance and subsequent neuroplastic training effects in a frontoparietal white matter pathway associated with action control. These effects were mediated by the effect of experience on pre-training variation in a frontotemporal pathway supporting action semantic representation. Our results show that the acquisition of one technical skill can produce structural brain changes conducive to the discovery and acquisition of additional skills, providing empirical evidence for bio-cultural feedback loops long hypothesized to link learning and adaptive change.

    

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3. Age-related enhancement in visuomotor learning by a dual-task

   https://doi.org/10.1038/s41598-022-09553-7  

   Wang, Tony S. L. ; Martinez, Miles ; Festa, Elena K. ; Heindel, William C. ; Song, Joo-Hyun ( April 2022 , Scientific Reports)

   Many daily activities require performance of multiple tasks integrating cognitive and motor processes. While the fact that both processes go through deterioration and changes with aging has been generally accepted, not much is known about how aging interacts with stages of motor skill acquisition under a cognitively demanding situation. To address this question, we combined a visuomotor adaptation task with a secondary cognitive task. We made two primary findings beyond the expected age-related performance deterioration. First, while young adults showed classical dual-task cost in the early motor learning phase dominated by explicit processes, older adults instead strikingly displayed enhanced performance in the later stage, dominated by implicit processes. For older adults, the secondary task may have facilitated a shift to their relatively intact implicit learning processes that reduced reliance on their already-deficient explicit processes during visuomotor adaptation. Second, we demonstrated that consistently performing the secondary task in learning and re-learning phases can operate as an internal task-context and facilitate visuomotor memory retrieval later regardless of age groups. Therefore, our study demonstrated age-related similarities and differences in integrating concurrent cognitive load with motor skill acquisition which, may in turn, contributes to the understanding of a shift in balance across multiple systems.

    

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4. Somatosensory changes associated with motor skill learning

   https://doi.org/10.1152/jn.00497.2019  

   Mirdamadi, Jasmine Lauren ; Block, Hannah J ( January 2020 , Journal of Neurophysiology)

   Trial-and-error motor adaptation has been linked to somatosensory plasticity and shifts in proprioception (limb position sense). The role of sensory processing in motor skill learning is less understood. Unlike adaptation, skill learning involves the acquisition of new movement patterns in the absence of perturbation, with performance limited by the speed-accuracy tradeoff. We investigated somatosensory changes during motor skill learning at the behavioral and neurophysiological level. Twenty-eight healthy young adults practiced a maze-tracing task, guiding a robotic manipulandum through an irregular 2D track featuring several abrupt turns. Practice occurred on days 1 and 2. Skill was assessed before practice on day 1 and again on day 3, with learning indicated by a shift in the speed-accuracy function between these assessments. Proprioceptive function was quantified with a passive two-alternative forced choice task. In a subset of 15 participants, we measured short latency afferent inhibition (SAI) to index somatosensory projections to motor cortex. We found that motor practice enhanced the speed-accuracy skill function (F 4,108 = 32.15, p < 0.001) and was associated with improved proprioceptive sensitivity at retention (t 22 = 24.75, p = 0.0031). Further, SAI increased after training (F 1,14 = 5.41, p = 0.036). Interestingly, individuals with larger increases in SAI, reflecting enhanced somatosensory afference to motor cortex, demonstrated larger improvements in motor skill learning. These findings suggest that SAI may be an important functional mechanism for some aspect of motor skill learning. Further research is needed to test what parameters (task complexity, practice time, etc) are specifically linked to somatosensory function. 

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5. Peak frequency of the sensorimotor mu rhythm varies with autism-spectrum traits

   https://doi.org/10.3389/fnins.2022.950539  

   Strang, Caroline C. ; Harris, Alison ; Moody, Eric J. ; Reed, Catherine L. ( August 2022 , Frontiers in Neuroscience)

   Autism spectrum disorder (ASD) is a neurodevelopmental syndrome characterized by impairments in social perception and communication. Growing evidence suggests that the relationship between deficits in social perception and ASD may extend into the neurotypical population. In electroencephalography (EEG), high autism-spectrum traits in both ASD and neurotypical samples are associated with changes to the mu rhythm, an alpha-band (8–12 Hz) oscillation measured over sensorimotor cortex which typically shows reductions in spectral power during both one’s own movements and observation of others’ actions. This mu suppression is thought to reflect integration of perceptual and motor representations for understanding of others’ mental states, which may be disrupted in individuals with autism-spectrum traits. However, because spectral power is usually quantified at the group level, it has limited usefulness for characterizing individual variation in the mu rhythm, particularly with respect to autism-spectrum traits. Instead, individual peak frequency may provide a better measure of mu rhythm variability across participants. Previous developmental studies have linked ASD to slowing of individual peak frequency in the alpha band, or peak alpha frequency (PAF), predominantly associated with selective attention. Yet individual variability in the peak mu frequency (PMF) remains largely unexplored, particularly with respect to autism-spectrum traits. Here we quantified peak frequency of occipitoparietal alpha and sensorimotor mu rhythms across neurotypical individuals as a function of autism-spectrum traits. High-density 128-channel EEG data were collected from 60 participants while they completed two tasks previously reported to reliably index the sensorimotor mu rhythm: motor execution (bimanual finger tapping) and action observation (viewing of whole-body human movements). We found that individual measurement in the peak oscillatory frequency of the mu rhythm was highly reliable within participants, was not driven by resting vs. task states, and showed good correlation across action execution and observation tasks. Within our neurotypical sample, higher autism-spectrum traits were associated with slowing of the PMF, as predicted. This effect was not likely explained by volume conduction of the occipitoparietal PAF associated with attention. Together, these data support individual peak oscillatory alpha-band frequency as a correlate of autism-spectrum traits, warranting further research with larger samples and clinical populations. 

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