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Physical Hazards of Space Exploration and the Biological Bases of Behavioral Health and Performance in Extreme Environments
Published in Lauren Blackwell Landon, Kelley J. Slack, Eduardo Salas, Psychology and Human Performance in Space Programs, 2020
Julia M. Schorn, Peter G. Roma
Sensorimotor systems are responsible for the control, execution, and inhibition of motor behaviors. This affects many basic aspects of team performance in space, as motor actions enable individuals to move within the habitat or planetary surface, operate life-support systems, pick up and control objects, etc. Specifically, these motor behaviors are critical for all physical mission tasks, including piloting and landing, extra-vehicular activities (EVA), and telerobotics operations, as well as activities of daily living and self-care (e.g., food preparation and consumption, hygiene). Physical performance processes rely heavily on the motor cortex that projects to the basal ganglia, the brainstem, and the spinal cord, which terminate on motoneurons that innervate muscles to initiate movement (Lemon, 2008). Neurotransmitters glutamate (excitatory) and gamma-amino butyric acid (GABA; inhibitory) work together to release acetylcholine and promote muscle activity and movement (Grillner, 2015; Sian, Youdim, Riederer, & Gerlach, 1999).
Visual Perception and Human–Computer Interaction in Surgical Augmented and Virtual Reality Environments
Published in Terry M. Peters, Cristian A. Linte, Ziv Yaniv, Jacqueline Williams, Mixed and Augmented Reality in Medicine, 2018
Roy Eagleson, Sandrine de Ribaupierre
Interactive, 3D, immersive AR/VR environments, by their nature, invite the user’s motor system response within the environment. Sensory-motor control, for the most part, involves feedback-based dynamics. Human control does not seem to require “absolute” coordinates for control but instead can guide interactions based on the relative spatial, relational information provided by the sensory system. However, by the nature of the production of the final motor system output, all relative inputs must be resolved into a single controlled output. Consequently, any inconsistent or incomplete sensory estimates must somehow be reconciled. In some cases, inconsistent input channels can be ignored but in most cases will lead to errors in the output, or worse, to a breakdown of the entire task, or in many cases, headaches or serious “simulator sickness.”
Therapeutic Applications of BCI Technologies
Published in Chang S. Nam, Anton Nijholt, Fabien Lotte, Brain–Computer Interfaces Handbook, 2018
A rationale for feedback that actually moves the affected limb is the suggestion that closing the sensorimotor loop produces Hebbian plasticity owing to the pairing of intention and proprioceptive feedback (Gomez-Rodriguez et al. 2011). Although Gomez-Rodriguez et al. (2011) proposed that closing the sensorimotor loop using within-trial activation of an orthosis might prove beneficial for stroke recovery, their study only involved showing that haptic feedback facilitated classification of the EEG. Buch et al. (2008) reported that magnetoencephalography (MEG)-based BCI training paired with post-trial activation of an orthosis had no significant effect on hand function, although patients successfully learned to control the device. Using a pre–post design, Shindo et al. (2011) reported some improvement in function after EEG-based BCI operation of an orthosis. Young et al. (2015) reported an improvement in a self-reported measure of strength after training with a BCI system that produced functional electrical stimulation of the hand and tongue. No information was provided about the specific EEG features used for training. Ang et al. (2014) found no significant difference between outcome measures for stroke patients receiving BCI-controlled robotic therapy and those receiving standard robotic therapy. Ramos-Murguialday et al. (2013) reported a significant improvement in functioning of stroke patients after training with an SMR-controlled orthosis as compared to a sham control group. Both groups also received behaviorally oriented physiotherapy. Information that would characterize the EEG features used by patients for orthosis control was not provided. Ramos-Murguialday et al. (2013) suggested that BCI training may have primed the effects of physiotherapy. Using a head-mounted neurochip in monkeys, Lucas and Fetz (2013) showed that making invasive stimulation of the primary motor cortex contingent on activation of a muscle resulted in reorganization of cortical outputs. The Lucas and Fetz (2013) study illustrates the bidirectional nature of the sensorimotor loop and provides an alternative method for creating associations between motor cortex and muscles.
Effects of strength exercise on the knee and ankle proprioception of individuals with knee osteoarthritis
Published in Research in Sports Medicine, 2018
Zhangqi Lai, Yu Zhang, Seullee Lee, Lin Wang
Proprioception is a component of the sensorimotor system and is defined as the perception of the position and movement of an extremity or a joint in space (Knoop et al., 2011; Wang, Li, Xu, & Hong, 2008). Knee proprioception is mainly modulated by receptors in the structures of the knees and influenced by receptors in other organ systems (e.g. visual and vestibular systems). Studies on balance and proprioception in individuals with KOA have shown that impaired balance increases the risk of falls and decreases proprioceptive accuracy (Felson et al., 2009; Khalaj, Abu Osman, Mokhtar, Mehdikhani, & Wan Abas, 2014; Lund et al., 2008).
Working memory network plasticity after exercise intervention detected by task and resting-state functional MRI
Published in Journal of Sports Sciences, 2021
Lina Zhu, Xuan Xiong, Xiaoxiao Dong, Yi Zhao, Adam Kawczyński, Aiguo Chen, Wei Wang
Voxelwise resting connectivity analyses showed that the exercise intervention caused connectivity increases in the left HIP–left lingual gyrus, left HIP–left STG, and left HIP–left MFG, as well as decreases in the left cerebellum posterior lobe–right MTG. Extensive research has pointed out that the above regions are critical nodes of the WM network. The HIP has a crucial role in support of memory encoding and retrieval by the WM network (Baddeley et al., 2010, 2011). Enhancement in FC between the HIP and prefrontal cortex has been reported to result in better N-back task performance (Laroche et al., 2000; Preston & Eichenbaum, 2013). Meta-analysis research concluded that the functional topography of the cerebellum is mainly involved in sensorimotor, language, spatial memory, and WM (Stoodley & Schmahmann, 2009; Stoodley et al., 2012). A training study indicated that cognitive training could increase neural activity in cerebellar circuits in children with ADHD (Hoekzema et al., 2010). Recently, new research characterized differential FC patterns from hippocampal segments (anterior-vs-posterior; left-vs-right) and related them to specific cognitive functions that assessed the correlations on memory task performance; these studies found that better topographical memory was associated with stronger coupling from the left anterior HIP to the lingual gyrus, a region implicated in visual processing (Sormaz et al., 2017). These pieces of evidence may signify a reorganization of the HIP-prefrontal cortex-visual cortex-cerebellum connectivity, which is involved in changes in WM performance. The right MTG showed higher connectivity in deaf signers than in hearing nonsigners (Malaia et al., 2014). The decreased connectivity between the left HIP and right MTG in our results may suggest normalization of brain networks in deaf children.
Sleep restriction impairs maximal jump performance and joint coordination in elite athletes
Published in Journal of Sports Sciences, 2019
Cheri D. Mah, Aaron J. Sparks, Michael A. Samaan, Richard B. Souza, Anthony Luke
The sensorimotor system determines the motor patterns required to successfully achieve a dynamic task even under a non-optimal condition or state (Latash, Scholz, & Schoner, 2002). Joint coordination variability is a quantitative method of assessing the sensorimotor system’s ability to accomplish a particular goal by either increasing or decreasing the use of a degree of freedom (i.e. muscle, joint) (Bernstein, 1967; Hamill, Van Emmerik, Heiderscheit, & Li, 1999). Vector coding, a method of assessing joint position data, has been used to assess joint coordination variability during sidestep cutting (Pollard, Heiderscheit, Van Emmerik, & Hamill, 2005; Pollard, Stearns, Hayes, & Heiderscheit, 2015; Samaan, Hoch, Ringleb, Bawab, & Weinhandl, 2015), running (Gribbin et al., 2016; Heiderscheit, Hamill, & Van Emmerik, 2002), walking (Gribbin et al., 2016; Smith, Popovich, & Kulig, 2014; Barrett, Noordegraaf, & Morrison, 2008; Chang, Van Emmerik, & Hamill, 2008; Miller, Chang, Baird, Van Emmerik, & Hamill, 2010; Samaan, Teng et al., 2015), and free-throw shooting (Mullineaux & Uhl, 2010). Vector coding provides an understanding of the underlying motor strategies required to successfully perform these dynamic tasks. Vector coding has been demonstrated to be a sensitive measure to assess subtle changes in motion patterns during dynamic activity compared to traditional kinematic analyses (Smith et al., 2014; Samaan, Teng et al., 2015). To our knowledge, no other studies have examined traditional kinematic analyses or vector coding on dynamic movements following sleep loss. Additionally, the maximal vertical jump is a dynamic task that has been studied extensively to examine the neuromuscular system and associated mechanics (Bobbert, 2014; Jaric & Markovic, 2009). Moreover, a reduction in the maximal vertical jump has been associated with sleep deprivation (Takeuchi, 1985). Understanding how sleep restriction affects biomechanics during a dynamic task may provide insights of the effects on neuromuscular coordination and ultimately how movement patterns are possibly altered in physical performance, which may have significant implications for injury risk.