We thank Mr. Zhengyang Wang for reshaping the scripts, shooting and editing the video, and Mr. Ziyuan Ye for editing the video. This study got support from CIT Endowment &#38; National Science Foundation (to JCD),&#160;Boswell fellowship (to QL) and High-level University Fund (No. G02386301, G02386401), Guangdong Natural Science Foundation Joint Fund (No. 2019A1515111038).&#160;

The development and application of the protocol were approved by the California Institute of Technology Institutional Review Board (IRB) and the Southern University of Science and Technology IRB. The subject provided informed consent prior to any procedures being performed.
1. System preparation and setup
<ol>
	<li>The recommended basic hardware is a&#160;2 GHz dual-core processor and 4 GB of system memory.</li>
	<li>Build the gaming platform under the Unity platform, while using C# programi...

<ol>
	<li>Franklin, D. W., Wolpert, D. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Computational+Mechanisms+of+Sensorimotor+Control.">Computational Mechanisms of Sensorimotor Control.</a> Neuron. 72 (3), 425-442 (2011).</li><li>Bays, P. M., Wolpert, D. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Computational+principles+of+sensorimotor+control+that+minimize+uncertainty+and+variability.">Computational principles of sensorimotor control that minimize uncertainty and variability.</a> The Journal of Physiology. 578 (2), 387-396 (2007).</li><li>Desmurget, M., Grafton, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Forward+modeling+allows+feedback+control+for+fast+reaching+movements.">Forward modeling allows feedback control for fast reaching movements.</a> Trends in Cognitive Sciences. 4 (11), 423-431 (2000).</li><li>Sanger, T. D., Merzenich, M. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Computational+Model+of+the+Role+of+Sensory+Disorganization+in+Focal+Task-Specific+Dystonia.">Computational Model of the Role of Sensory Disorganization in Focal Task-Specific Dystonia.</a> Journal of Neurophysiology. 84 (5), 2458-2464 (2000).</li><li>Mohler, H., Okada, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Benzodiazepine+receptor:+demonstration+in+the+central+nervous+system.">Benzodiazepine receptor: demonstration in the central nervous system.</a> Science. 198 (4319), 849-851 (1977).</li><li>Muller, L., Chavane, F., Reynolds, J., Sejnowski, T. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cortical+travelling+waves:+mechanisms+and+computational+principles.">Cortical travelling waves: mechanisms and computational principles.</a> Nature Reviews Neuroscience. 19 (5), 255-268 (2018).</li><li>Zhang, H., Watrous, A. J., Patel, A., Jacobs, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Theta+and+Alpha+Oscillations+Are+Traveling+Waves+in+the+Human+Neocortex.">Theta and Alpha Oscillations Are Traveling Waves in the Human Neocortex.</a> Neuron. 98 (6), 1269-1281 (2018).</li><li>Blinks, J. R., R&#252;del, R., Taylor, S. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Calcium+transients+in+isolated+amphibian+skeletal+muscle+fibres:+detection+with+aequorin.">Calcium transients in isolated amphibian skeletal muscle fibres: detection with aequorin.</a> The Journal of Physiology. 277 (1), 291-323 (1978).</li><li>Gallivan, J. P., Chapman, C. S., Wolpert, D. M., Flanagan, J. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Decision-making+in+sensorimotor+control.">Decision-making in sensorimotor control.</a> Nature Reviews Neuroscience. 19 (9), 519-534 (2018).</li><li>Sanger, T. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Basic+and+Translational+Neuroscience+of+Childhood-Onset+Dystonia:+A+Control-Theory+Perspective.">Basic and Translational Neuroscience of Childhood-Onset Dystonia: A Control-Theory Perspective.</a> Annual Review of Neuroscience. 41 (1), 41-59 (2018).</li><li>Todorov, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optimality+principles+in+sensorimotor+control.">Optimality principles in sensorimotor control.</a> Nature Neuroscience. 7 (9), 907-915 (2004).</li><li>Todorov, E., Jordan, M. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optimal+feedback+control+as+a+theory+of+motor+coordination.">Optimal feedback control as a theory of motor coordination.</a> Nature Neuroscience. 5 (11), 1226-1235 (2002).</li><li>Wolpert, D. M., Flanagan, J. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Computations+underlying+sensorimotor+learning.">Computations underlying sensorimotor learning.</a> Current Opinion in Neurobiology. 37, 7-11 (2016).</li><li>Kiper, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Computational+models+and+motor+learning+paradigms:+Could+they+provide+insights+for+neuroplasticity+after+stroke?+An+overview.">Computational models and motor learning paradigms: Could they provide insights for neuroplasticity after stroke? An overview.</a> Journal of the Neurological Sciences. 369, 141-148 (2016).</li><li>Cluff, T., Crevecoeur, F., Scott, S. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tradeoffs+in+optimal+control+capture+patterns+of+human+sensorimotor+control+and+adaptation.">Tradeoffs in optimal control capture patterns of human sensorimotor control and adaptation.</a> bioRxiv. , 730713 (2019).</li><li>Nakahira, Y., Liu, Q., Bernat, N., Sejnowski, T., Doyle, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Theoretical+foundations+for+layered+architectures+and+speed-accuracy+tradeoffs+in+sensorimotor+control.">Theoretical foundations for layered architectures and speed-accuracy tradeoffs in sensorimotor control.</a> 2019 American Control Conference (ACC). , 809-814 (2019).</li><li>K&#246;rding, K. P., Wolpert, D. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bayesian+integration+in+sensorimotor+learning.">Bayesian integration in sensorimotor learning.</a> Nature. 427 (6971), 244-247 (2004).</li><li>Chambers, C., Sokhey, T., Gaebler-Spira, D., Kording, K. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+development+of+Bayesian+integration+in+sensorimotor+estimation.">The development of Bayesian integration in sensorimotor estimation.</a> Journal of Vision. 18 (12), 8 (2018).</li><li>Karmali, F., Whitman, G. T., Lewis, R. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bayesian+optimal+adaptation+explains+age-related+human+sensorimotor+changes.">Bayesian optimal adaptation explains age-related human sensorimotor changes.</a> Journal of Neurophysiology. 119 (2), 509-520 (2017).</li><li>Gori, J., Rioul, O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Information-Theoretic+Analysis+of+the+Speed-Accuracy+Tradeoff+with+Feedback.">Information-Theoretic Analysis of the Speed-Accuracy Tradeoff with Feedback.</a> 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC). , 3452-3457 (2018).</li><li>Trendafilov, D., Polani, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Information-theoretic+Sensorimotor+Foundations+of+Fitts'+Law.">Information-theoretic Sensorimotor Foundations of Fitts' Law.</a> Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems. , 1-6 (2019).</li><li>Fitts, P. M., Peterson, J. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Information+capacity+of+discrete+motor+responses.">Information capacity of discrete motor responses.</a> Journal of Experimental Psychology. 67 (2), 103-112 (1964).</li><li>Fitts, P. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+information+capacity+of+the+human+motor+system+in+controlling+the+amplitude+of+movement.">The information capacity of the human motor system in controlling the amplitude of movement.</a> Journal of Experimental Psychology. 47 (6), 381-391 (1954).</li><li>Nakahira, Y., Matni, N., Doyle, J. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hard+limits+on+robust+control+over+delayed+and+quantized+communication+channels+with+applications+to+sensorimotor+control.">Hard limits on robust control over delayed and quantized communication channels with applications to sensorimotor control.</a> 2015 54th IEEE Conference on Decision and Control (CDC). , 7522-7529 (2015).</li><li>. Neural Correlates of Sensorimotor Control in Human Cortex: State Estimates and Reference Frames Available from: <a target="_blank" href="https://resolver.caltech.edu/CaltechTHESIS:05302019-163325527">https://resolver.caltech.edu/CaltechTHESIS:05302019-163325527</a> (2019)</li><li>Miall, R. C., Wolpert, D. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Forward+Models+for+Physiological+Motor+Control.">Forward Models for Physiological Motor Control.</a> Neural Networks. 9 (8), 1265-1279 (1996).</li><li>Battaglia-Mayer, A., Caminiti, R., Lacquaniti, F., Zago, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiple+Levels+of+Representation+of+Reaching+in+the+Parieto-frontal+Network.">Multiple Levels of Representation of Reaching in the Parieto-frontal Network.</a> Cerebral Cortex. 13 (10), 1009-1022 (2003).</li><li>Scott, S. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optimal+feedback+control+and+the+neural+basis+of+volitional+motor+control.">Optimal feedback control and the neural basis of volitional motor control.</a> Nature Reviews Neuroscience. 5 (7), 532-545 (2004).</li><li>Saunders, J. A., Knill, D. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Humans+use+continuous+visual+feedback+from+the+hand+to+control+fast+reaching+movements.">Humans use continuous visual feedback from the hand to control fast reaching movements.</a> Experimental Brain Research. 152 (3), 341-352 (2003).</li><li>Insperger, T., Milton, J., St&#233;p&#225;n, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Acceleration+feedback+improves+balancing+against+reflex+delay.">Acceleration feedback improves balancing against reflex delay.</a> Journal of The Royal Society Interface. 10 (79), 20120763 (2013).</li><li>Birbaumer, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Breaking+the+silence:+Brain-computer+interfaces+(BCI)+for+communication+and+motor+control.">Breaking the silence: Brain-computer interfaces (BCI) for communication and motor control.</a> Psychophysiology. 43 (6), 517-532 (2006).</li><li>Liu, Q., Farahibozorg, S., Porcaro, C., Wenderoth, N., Mantini, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Detecting+large-scale+networks+in+the+human+brain+using+high-density+electroencephalography.">Detecting large-scale networks in the human brain using high-density electroencephalography.</a> Human Brain Mapping. 38 (9), 4631-4643 (2017).</li><li>Nicolelis, M. A. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Brain-machine+interfaces+to+restore+motor+function+and+probe+neural+circuits.">Brain-machine interfaces to restore motor function and probe neural circuits.</a> Nature Reviews Neuroscience. 4 (5), 417-422 (2003).</li><li>Nordin, A. D., Hairston, W. D., Ferris, D. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Faster+Gait+Speeds+Reduce+Alpha+and+Beta+EEG+Spectral+Power+From+Human+Sensorimotor+Cortex.">Faster Gait Speeds Reduce Alpha and Beta EEG Spectral Power From Human Sensorimotor Cortex.</a> IEEE Transactions on Biomedical Engineering. 67 (3), 842-853 (2020).</li><li>Hallett, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transcranial+magnetic+stimulation+and+the+human+brain.">Transcranial magnetic stimulation and the human brain.</a> Nature. 406 (6792), 147-150 (2000).</li><li>Madhavan, S., Weber, K. A., Stinear, J. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Non-invasive+brain+stimulation+enhances+fine+motor+control+of+the+hemiparetic+ankle:+implications+for+rehabilitation.">Non-invasive brain stimulation enhances fine motor control of the hemiparetic ankle: implications for rehabilitation.</a> Experimental Brain Research. 209 (1), 9-17 (2011).</li><li>Denoyelle, N., Pouget, F., Vi&#233;ville, T., Alexandre, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> VirtualEnaction: A Platform for Systemic Neuroscience Simulation. , (2014).</li><li>Butti, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Virtual+Reality+Social+Prediction+Improvement+and+Rehabilitation+Intensive+Training+(VR-SPIRIT)+for+paediatric+patients+with+congenital+cerebellar+diseases:+study+protocol+of+a+randomised+controlled+trial.">Virtual Reality Social Prediction Improvement and Rehabilitation Intensive Training (VR-SPIRIT) for paediatric patients with congenital cerebellar diseases: study protocol of a randomised controlled trial.</a> Trials. 21 (1), 82 (2020).</li><li>McCall, J. V., Ludovice, M. C., Blaylock, J. A., Kamper, D. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Platform+for+Rehabilitation+of+Finger+Individuation+in+Children+with+Hemiplegic+Cerebral+Palsy.">A Platform for Rehabilitation of Finger Individuation in Children with Hemiplegic Cerebral Palsy.</a> 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR). , 343-348 (2019).</li><li>Demers, M., Levin, M. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Kinematic+Validity+of+Reaching+in+a+2D+Virtual+Environment+for+Arm+Rehabilitation+After+Stroke.">Kinematic Validity of Reaching in a 2D Virtual Environment for Arm Rehabilitation After Stroke.</a> IEEE Transactions on Neural Systems and Rehabilitation Engineering. 28 (3), 679-686 (2020).</li><li>Zbytniewska, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Design+and+Characterization+of+a+Robotic+Device+for+the+Assessment+of+Hand+Proprioceptive,+Motor,+and+Sensorimotor+Impairments.">Design and Characterization of a Robotic Device for the Assessment of Hand Proprioceptive, Motor, and Sensorimotor Impairments.</a> 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR). , 441-446 (2019).</li><li>Delp, S. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=OpenSim:+Open-Source+Software+to+Create+and+Analyze+Dynamic+Simulations+of+Movement.">OpenSim: Open-Source Software to Create and Analyze Dynamic Simulations of Movement.</a> IEEE Transactions on Biomedical Engineering. 54 (11), 1940-1950 (2007).</li><li>Gray, W. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Plateaus+and+Asymptotes:+Spurious+and+Real+Limits+in+Human+Performance.">Plateaus and Asymptotes: Spurious and Real Limits in Human Performance.</a> Current Directions in Psychological Science. 26 (1), 59-67 (2017).</li></ol>

In this paper, we have presented a free, open-source gaming platform, WheelCon, for studying the effects of delay, quantization, disturbance, and layered feedback loops in human sensorimotor control. We have shown the hardware, the software, and the GUI. The settings of a single sensorimotor control loop with delay and quantization have been implemented, which allows us to measure the effects of delay, quantization, and disturbance in sensorimotor control. The experimental results are well in line with the prediction fro...

The human sensorimotor control system is extremely robust1, although the sensing is distributed, variable, sparse, quantized, noisy and delayed2,3,4; the computing in the central nervous system is slow5,6,7; and the muscle actuation fatigues and saturates8. Many computational theoretical models have been proposed to explain the complicated human sensorimotor control process4,9,10,11,12,13,14, which is a tradeoff process in human reach and response15,16. For example, feedback control theory predicts the optimal control policy12, Bayesian theory models sensorimotor learning17,18,19 and information theory sensorimotor foundation20,21. In contrast to the abundance of theoretical models, experimental platforms capable of manipulating important components of multiple feedback loops lack development. This is in part due to the fact that designing a platform to bridge and test these aspects of sensorimotor control requires a diverse range of expertise, extending from motor control theory, signal processing, and interaction, all the way to computer graphics and programming. Researchers often develop their own custom hardware/software systems to characterize human sensorimotor control performance, which can limit the ability to compare/contrast and integrate datasets across research groups. The development of an easy-to-use and validated system could broaden the quantitative characterization of sensorimotor control.
In this paper, we present the WheelCon platform, a novel, free and open-source platform to design video games for a virtual environment that noninvasively simulates a Fitts&#8217; Law reaching game and a mountain bike task with downing a steep, twisting and bumpy trail. The Fitts&#8217; law for reaching task quantifies the tradeoff between speed and accuracy in which the time required for reaching a target of width at distance scales as22,23. The &#39;mountain-bike task&#39; is a combination of a pursuit and compensatory tracking task, which are two classic components of research on human sensorimotor performance, especially in terms of studying feedback loops.
WheelCon contains the highly demanded basic components presented in each theory: delay, quantization, noise, disturbance, and multiple feedback loops. It is a potential tool for studying the following diverse questions in human sensorimotor control:
&#8226; How the human sensorimotor system deals with the delay and quantization in neural signaling, which is fundamentally constrained by the limited resources (such as the space and metabolic costs) in the brain24,25; &#8226; How neural correlation in the human cortex with sensorimotor control26; &#8226; How humans handle the unpredictable, external disturbances in sensorimotor control27; &#8226; How the hierarchical control loops layered and integrated within human sensorimotor system16,28,29; &#8226; The consequence of the delay and quantization in human visual feedback30 and reflex feedback31 in sensorimotor control; &#8226; The optimal policy and strategy for sensorimotor learning under delay and quantization16,17,24,29.
WheelCon integrates with a steering wheel and can simulate game conditions that manipulate the variables in these questions, such as signaling delay, quantization, noise, and disturbance, while recording the dynamic control policy and system errors. It also allows researchers to study the layered architecture in sensorimotor control. In the example of riding a mountain bike, two control layers are involved in this task: the high-layer plan and the low-layer reflex. For visible disturbances (i.e., the trail), we plan before the disturbance arrives. For disturbances unknown in advance (i.e., small bumps), the control relies on delayed reflexes. Feedback control theory proposes that effective layered architectures can integrate the higher layers&#39; goals, plans, decisions with the lower layers&#39; sensing, reflex, and action24. WheelCon provides experimental tools to induce distinctive disturbances in the plan and reflex layers separately for testing such a layered architecture (Figure 1).
We provide a cheap, easy to use and flexible to program platform, WheelCon that bridges the gap between theoretical and experimental studies on neuroscience. To be specific, it can be used for examining the effects of delay, quantization, disturbance, potentially speed-accuracy tradeoffs. The variables that can be manipulated in control loops are shown in Table 1. It can also be applied for studying decision making and multiplexing ability across different control layers in human sensorimotor control. Moreover, WheelCon is compatible with noninvasive neural recordings, such as electroencephalography (EEG), to measure the neural response during sensorimotor control32,33,34,35, and the non-invasive brain stimulation techniques, such as Transcranial Electrical Stimulation (tES) and Transcranial Magnetic Stimulation (TMS), to manipulate the neural activity36,37.

<table>
	<tbody>
		<tr>
			<td>Gaming Wheel</td>
			<td>Logitech</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Windows 10 OS</td>
			<td>Microsoft</td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

wheelcon: a wheel control-based gaming platform for studying human sensorimotor control

Feedback control theory has been extensively implemented to theoretically model human sensorimotor control. However, experimental platforms capable of manipulating important components of multiple feedback loops lack development. This paper describes WheelCon, an open-source platform aimed at resolving such insufficiencies. Using only a computer, a standard display, and inexpensive gaming steering wheel equipped with a force feedback motor, WheelCon safely simulates the canonical sensorimotor task of riding a mountain bike down a steep, twisting, bumpy trail. The platform provides flexibility, as will be demonstrated in the demos provided, so that researchers may manipulate the disturbances, delay, and quantization (data rate) in the layered feedback loops, including a high-level advanced plan layer and a low-level delayed reflex layer. In this paper, we illustrate WheelCon&#39;s graphical user interface (GUI), the input and output of existing demos, and how to design new games. In addition, we present the basic feedback model and the experimental results from the demo games, which align well with the model&#39;s prediction. The WheelCon platform can be downloaded at https://github.com/Doyle-Lab/WheelCon. In short, the platform is featured to be cheap, simple to use, and flexible to program for effective sensorimotor neuroscience research and control engineering education.

Modelling Feedback Control
We show a simplified feedback control model shown in Figure 1. The system dynamics is given by:
<img alt="Equation 1" src="/files/ftp_upload/61092/61092equ01.jpg" />
where x(t) is the error at time t, r(t) is the trail disturbance w(t), is the bump disturbance, and u(...

Watch this Scientific Journal Video about WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control at JoVE.com

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

WheelCon is a novel, free and open-source platform to design video games that noninvasively simulates mountain biking down a steep, twisting, bumpy trail. It contains components presenting in human sensorimotor control (delay, quantization, noise, disturbance, and multiple feedback loops) and allows researchers to study the layered architecture in sensorimotor control.

Feedback control theory has been extensively implemented to theoretically model human sensorimotor control. However, experimental platforms capable of ...

Human sensory motor control system is extremely robust, although the sensing is distributed, sparse, quantized, noisy, and delayed. The computing in the central nervous system is slow, the muscle actuation fatigues and saturates. To study this causal factors and its consequence on the system performance of sensory motor control, it is important to develop an easy-to-use experimental platform which manipulate these factors and record the performance.Here we presents a gaming platform called the WheelCon, which is a free and open source platform to design video games for our virtual environment that simulates riding a mountain bike down a steep, twisted, bumpy trail. WheelCon integrates with a steering wheel as it can manipulate the variables in the human sensory motor control system, such as signaling delay, quantization, noise, and the disturbance while recording the motor control trajectory and aerodynamics. It also allows research to study the layer the architects in sensory motor control, including the higher layer's goals, plans, decisions, and the lower layer's sensing, reflex and action.On the computer running Windows 10, go to the WheelCon webpage, click Clone or download, then click Download ZIP in the popup dialog. Extract all the files to the local hard drive. Go to the manufacturer's website and download the corresponding driver for your racing wheel model.Mount the racing wheel securely at sitting level in front of a monitor. Connect the wheel's USB cable to the PC and the power adapter to an outlet. To test the program, double-click wheelcon.exe in the Excutable Output file's folder. Configure the settings according to monitor setup and click Play. Seat the subject down comfortably behind the wheels.Make sure the subject is allowed adequate range of motion when handling the wheel. Click Fitt's Law Task. Click on the text box and type a name for the output file, include subject and task information.Click Select File, then select Fitt's Law. txt as input. Click Begin Game.Instruct the subject to track the gray zone with the green line by turning the steering wheel. This game serves to familiarize the subject with the setup. Click Mountain Bike Task.Type the output file name and select Vision_Delay.txt. Click Begin Game to start testing. In this game, the length of the look-ahead window changes to provide advanced warning, no warning or a visual delay.Click Mountain Bike Task, type the output file name and select Action_Delay.txt. Click Begin Game to start testing. In this game, a delay is added between the subject's wheel turning and the green line's movement.The delay starts at zero seconds and increases by 0.15 seconds until it reaches 0.75 seconds. Click Mountain Bike Task, type the output file name and select Vision Quantization.txt. Click Begin Game to start testing.In this game, the visual data rate is manipulated. When visual data is low, the trail can only appear in a few loose gray locations. As the visual data rate increases, the gray zone can appear in more potential locations and its movement becomes more continuous.Click Mountain Bike Task, type the output file name and select Action Quantization.txt. Click Begin Game to start testing. In this game, action data rate is manipulated.When data rate is at its slowest, the gray line can only go at one speed. As data rate increases, controlling wheel speed becomes finer. Click Mountain Bike Task, type the output file name and select Bump Trail.txt.Click Begin Game to start testing. In this game, disturbances are added either as a torque on the wheel, simulating a bump, a sudden turn on the trail or the two types of disturbances combined. To retrieve test results go to the Executable Output file's folder, and look for the file with previously specified file names.From left to right, each row in the output file specifies time, trial position, bump size, action data rate, action delay, visual delay, visual data rate, tracking error, and steering wheel angle. To develop a new input file, open the WheelCon Mntn Bike Trail Design Code. m in the Source Code folder with Matlab.Selecting this section of the code for the desired game parameters, press Control plus T to uncomment, then press Run. The input file will be regenerated in the same folder. As the figure suggests, in games with either visual or action delays, the subject's error increased with bigger delays.Limiting data rates in either visual input or action output resulted in larger errors. This figure shows the aerodynamics during trials with either only bumps, only turns or the two combined. As you're watching this video, you should be familiar with how to apply WheelCon to a human sensory motor control study.

wheelcon-wheel-control-based-gaming-platform-for-studying-human

Research

JoVE Journal

Neuroscience

4.8K vistas.  Southern University of Science and Technology. El sistema de control del motor sensorial humano es extremadamente robusto, aunque la detección está distribuida, escasa, cuantificada, ruidosa y retrasada. La computación en el sistema nervioso central es lenta, la acción muscular se fatiga y se satura. Para estudiar estos factores causales y sus consecuencias sobre el rendimiento del sistema del control sensorial del motor, es importante desarrollar una plataforma experimental fácil de usar que manipule estos factores y registre el ren...