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      Perturbation Predictability Can Influence the Long-Latency Stretch Response

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          Abstract

          Perturbations applied to the upper limbs elicit short (M1: 25–50 ms) and long-latency (M2: 50–100 ms) responses in the stretched muscle. M1 is produced by a spinal reflex loop, and M2 receives contribution from multiple spinal and supra-spinal pathways. While M1 is relatively immutable to voluntary intention, the remarkable feature of M2 is that its size can change based on intention or goal of the participant (e.g., increasing when resisting the perturbation and decreasing when asked to let-go or relax following the perturbation). While many studies have examined modulation of M2 between passive and various active conditions, through the use of constant foreperiods (interval between warning signal and a perturbation), it has also been shown that the magnitude of the M2 response in a passive condition can change based on factors such as habituation and anticipation of perturbation delivery. To prevent anticipation of a perturbation, most studies have used variable foreperiods; however, the range of possible foreperiod duration differs between experiments. The present study examined the influence of different variable foreperiods on modulation of the M2 response. Fifteen participants performed active and passive responses to a perturbation that stretched wrist flexors. Each block of trials had either a short (2.5–3.5 seconds; high predictability) or long (2.5–10.5 seconds; low predictability) variable foreperiod. As expected, no differences were found between any conditions for M1, while M2 was larger in the active rather than passive conditions. Interestingly, within the two passive conditions, the long variable foreperiods resulted in greater activity at the end of the M2 response than the trials with short foreperiods. These results suggest that perturbation predictability, even when using a variable foreperiod, can influence circuitry contributing to the long-latency stretch response.

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          Primary motor cortex underlies multi-joint integration for fast feedback control

          A basic difficulty for the nervous system is integrating locally ambiguous sensory information to form accurate perceptions about the outside world 1–4 . This local-to-global problem is also fundamental to motor control of the arm since complex mechanical interactions between the shoulder and elbow allow a particular amount of motion at one joint to arise from an infinite combination of shoulder and elbow torques 5 (Fig. 1a). Here we show that a transcortical pathway through primary motor cortex (M1) resolves this ambiguity during fast feedback control. We demonstrate that single M1 neurons of behaving monkeys can integrate shoulder and elbow motion information into motor commands which appropriately counter the underlying torque within ~50 ms of a mechanical perturbation. Moreover, we reveal a causal link between M1 processing and multi-joint integration in humans by showing that shoulder muscle responses occurring ~50 ms after pure elbow displacement can be potentiated by transcranial magnetic stimulation. Our results show that M1 underlies multi-joint integration during fast feedback control, demonstrating that transcortical processing permits feedback responses to express a level of sophistication previously reserved for voluntary control and providing neurophysiological support for influential theories positing that voluntary movement is generated by the intelligent manipulation of sensory feedback 6,7 .
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            Optimal feedback control and the long-latency stretch response.

            There has traditionally been a separation between voluntary control processes and the fast feedback responses which follow mechanical perturbations (i.e., stretch "reflexes"). However, a recent theory of motor control, based on optimal control, suggests that voluntary motor behavior involves the sophisticated manipulation of sensory feedback. We have recently proposed that one implication of this theory is that the long-latency stretch "reflex", like voluntary control, should support a rich assortment of behaviors because these two processes are intimately linked through shared neural circuitry including primary motor cortex. In this review, we first describe the basic principles of optimal feedback control related to voluntary motor behavior. We then explore the functional properties of upper-limb stretch responses, with a focus on how the sophistication of the long-latency stretch response rivals voluntary control. And last, we describe the neural circuitry that underlies the long-latency stretch response and detail the evidence that primary motor cortex participates in sophisticated feedback responses to mechanical perturbations.
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              Rapid motor responses are appropriately tuned to the metrics of a visuospatial task.

              Considerable research has established that rapid motor responses (traditionally called reflexes), can be modified by a subject's voluntary goals. Here, we expand on past observations using verbal instructions by defining the voluntary goal via visual target position. This approach allowed us to objectively enforce task adherence and explore a richer set of variables, such as target direction and distance, metrics that modify voluntary control and that--according to our hypothesis--will influence rapid motor responses. Our first experiment tested whether upper-limb responses are categorically modulated by target direction by placing targets such that the same perturbation could push the hand into one target and out of the other, a spatial analogue to "resist/yield" verbal instructions. Consistent with these classical results, we found that the short-latency rapid response (R1, 20-45 ms) was not modulated by target direction, whereas long-latency rapid responses (R2/R3, 45-105 ms) were modified in a manner approaching the voluntary response (VOL, 120-180 ms). Our second experiment tested whether upper-limb responses are continuously modulated by target distance by distributing five targets along one axis centered on the hand. Here, the long-latency and voluntary response mirrored the task demands by increasing activity in a graded fashion with increasing target distance. Our final experiment explored how upper-limb responses incorporate two-dimensional spatial information by placing targets radially around the hand. Notably, long-latency responses exhibited smooth tuning functions to target direction that were similar to those observed for the voluntary response. Taken together, these results illustrate the flexibility of long-latency rapid responses and emphasize their similarity to later voluntary responses.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                11 October 2016
                2016
                : 11
                : 10
                : e0163854
                Affiliations
                [001]School of Kinesiology, University of British Columbia, Vancouver, Canada
                Ehime University Graduate School of Medicine, JAPAN
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: CJF RC.

                • Data curation: CJF RC.

                • Formal analysis: CJF.

                • Funding acquisition: CJF IMF RC.

                • Methodology: CJF RC.

                • Software: CJF RC.

                • Supervision: IMF RC.

                • Validation: CJF RC.

                • Visualization: CJF.

                • Writing – original draft: CJF.

                • Writing – review & editing: CJF IMF DM RC.

                Article
                PONE-D-16-17952
                10.1371/journal.pone.0163854
                5058553
                27727293
                07f4ad53-9e96-49e6-8e63-9885e538bdba
                © 2016 Forgaard et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 3 May 2016
                : 15 September 2016
                Page count
                Figures: 2, Tables: 1, Pages: 12
                Funding
                This work was supported by NSERC Discovery Grants awarded to Romeo Chua (6051) and Ian Franks (434), and an NSERC Doctoral Fellowship awarded to CJF.
                Categories
                Research Article
                Biology and Life Sciences
                Anatomy
                Musculoskeletal System
                Limbs (Anatomy)
                Arms
                Wrist
                Medicine and Health Sciences
                Anatomy
                Musculoskeletal System
                Limbs (Anatomy)
                Arms
                Wrist
                Research and Analysis Methods
                Bioassays and Physiological Analysis
                Electrophysiological Techniques
                Muscle Electrophysiology
                Electromyography
                Biology and Life Sciences
                Neuroscience
                Reflexes
                Biology and Life Sciences
                Anatomy
                Brain
                Motor Cortex
                Medicine and Health Sciences
                Anatomy
                Brain
                Motor Cortex
                Biology and Life Sciences
                Anatomy
                Musculoskeletal System
                Joints (Anatomy)
                Medicine and Health Sciences
                Anatomy
                Musculoskeletal System
                Joints (Anatomy)
                Physical Sciences
                Physics
                Classical Mechanics
                Motion
                Torque
                Engineering and Technology
                Electronics
                Oscilloscopes
                Engineering and Technology
                Electrical Engineering
                Electrical Circuits
                Custom metadata
                Data are available through the UBC Dataverse hdl:11272/10368.

                Uncategorized
                Uncategorized

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