Temporal Components of the Motor Patterns Expressed by the Human Spinal Cord Reflect Foot Kinematics

Ivanenko, Yuri P.; Grasso, R.; Zago, Myrka; Molinari, Marco; Scivoletto, Giorgio; Castellano, V.; Macellari, Velio; Lacquaniti, Francesco

doi:10.1152/jn.00223.2003

Cited by 152 publications

(160 citation statements)

References 46 publications

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“…Consistent with some of the primitives ideas, we and others (Davis and Vaughan, 1993;Olree and Vaughan, 1995;Ivanenko et al, 2003Ivanenko et al, , 2004 have shown that muscle activity during human locomotion is driven by a few (approximately five) temporal activation components. Each activation component describes a short period of synchronous activation or relaxation of a particular set of muscles, and it represents a characteristic timing rather than a characteristic muscle synergy associated with each movement component.…”

Section: Introductionsupporting

confidence: 87%

Coordination of Locomotion with Voluntary Movements in Humans

et al. 2005

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Muscle activity occurring during human locomotion can be accounted for by five basic temporal activation patterns in a variety of locomotion conditions. Here, we examined how these activation patterns interact with muscle activity required for a voluntary movement. Subjects produced a voluntary movement during locomotion, and we examined the resulting kinematics, kinetics, and EMG activity in 16 -31 ipsilateral limb and trunk muscles during the tasks. There were four voluntary tasks added to overground walking (ϳ5 km/h) in which subjects kicked a ball, stepped over an obstacle, or reached down and grasped an object on the floor (weight support on either the right or the left foot). Statistical analyses of EMG waveforms showed that the five basic locomotion patterns were invariantly present in each task, although they could be differently weighted across muscles, suggesting a characteristic locomotion timing of muscle activations. We also observed a separate activation that was timed to the voluntary task. The coordination of locomotion with the voluntary task was accomplished by combining activation timings that were associated separately with the voluntary task and locomotion. Activation associated with the voluntary tasks was either synchronous with the timing for locomotion or had additional activations not represented in the basic locomotion timing. We propose that this superposition of an invariant locomotion timing pattern with a voluntary activation timing may be consistent with the proposal suggesting that compound movements are produced through a superposition of motor programs.

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Section: Introductionsupporting

confidence: 87%

Coordination of Locomotion with Voluntary Movements in Humans

et al. 2005

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“…30,36 Furthermore, it has been recently reported that, while with training (body weight support), footmotion of SCI patients tends to recover the shape and the step-by-step reproducibility that characterize normal gait, the specific activation of individual muscles often differs substantially from the normal ones and include the activation of several trunk muscles which are not included in ASIA key muscles evaluation. 40 On the other hand, a subset of seven subjects, who performed at lower WISCI levels (4-11) than expected with LEMS of an average of 26, had associated problems of age, weak upper extremities, pain, balance problems and overweight. The effect of age is particularly worthy to note: Burns et al 41 and Penrod et al 42 reported that subjects over 50 years with ASIA C within a week of injury when compared to younger individuals, did much poorer in recovery of walking function, and speculated that this may have been due to associated medical problems.…”

Section: Discussionmentioning

confidence: 82%

“…Mean length of stay was 98.7768.13 days. A nontraumatic etiology was present in the majority of the patients (177/284): inflammatory (40), vascular (36), neoplastic (39), degenerative (62); traumatic lesions (107/284): car accident (38), motorcycle accident (15), sport accident (7), acts of violence (6), suicide attempts (6), accidental falls (31). Lesion level: 81 had cervical lesions, 148 thoracic lesions and 55 had lumbar-sacral lesions Ambulates in parallel bars, with braces and physical assistance of two persons, less than 10 m. 02…”

Section: Demographicsmentioning

confidence: 99%

Walking index for spinal cord injury (WISCI): criterion validation

et al. 2004

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Study design: Retrospective examination. Objectives: To compare the Walking Index for Spinal Cord Injury (WISCI) and current scales for their sensitivity to walking changes in subjects with a spinal cord lesion (SCL) and further validate the WISCI for use in clinical trails. Setting: A large rehabilitation hospital in the center of Italy. Patients and methods: Retrospective review was performed on 284 patient records with an SCL. Measurements included neurological evaluation with Lower Extremity Motor Scores (LEMS) according to the American Spinal Injury Association (ASIA) and walking status assessed by Barthel Index (BI (0-15)), Rivermead Mobility Index (RMI (three levels)), Functional Independence Measure (FIM (1-7)), Spinal Cord Independence Measure (SCIM (0-8)), and WISCI (0-20). The WISCI is a 21-level hierarchical scale which incorporates gradations of physical assistance and devices required for walking. Improvement in walking is based on the change of scores from admission to discharge. Statistical analysis included Spearman rank correlation and w 2 test; Po0.05. Results: There was a significant positive correlation between WISCI and other scales (WISCI and BI r ¼ 0.67, Po0.001; WISCI and RMI r ¼ 0.67, Po0.001; WISCI and SCIM r ¼ 0.97, Po0.001; WISCI and FIM r ¼ 0.7, Po0.001). The initial ASIA grade was predictive of mobility outcome on the WISCI: of the 78 ASIA A patients, only five achieved independent walking versus 4/17 ASIA B (P ¼ 0.02), 56/109 ASIA C (Po0.001) and 39/44 ASIA D (Po0.001). The correlation of LEMS to the WISCI was 0.58 (Po0.001). At discharge, patients were distributed into 12 WISCI levels versus four FIM, three BI, two RMI and five SCIM levels. The most frequent WISCI levels at discharge were 13 (walker, no braces or assistance), 16 (two crutches, no braces or assistance) and 20 (no devices or assistance). Conclusions: Similar correlation between the WISCI and the other scales indicates that all these measures address the same concept, mobility, which is a measure of concurrent validity. The correlation is not 100% because of conceptual differences (the WISCI incorporates gradations of physical assistance and devices required for walking while most of the other scales focus on burden of care or mobility in the environment). The WISCI is more detailed and appears more sensitive to walking recovery than the other scales, as demonstrated by our patients' score distribution at discharge. Within each of the most frequent WISCI levels (13,16,20) LEMS and other walking features varied; therefore the scale would benefit from further refinement based on speed, distance and energy cost.

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“…Our decomposition algorithm is similar to other procedures used to analyze the muscle activity patterns, such as principal component analysis or factor analysis (Patla, 1985;Davis and Vaughan, 1993;Olree and Vaughan, 1995;Merkle et al, 1998;Weijs et al, 1999;Ivanenko et al, 2003Ivanenko et al, , 2004Krishnamoorthy et al, 2003), independent component analysis (McKeown, 2000;Hart and Giszter, 2004), and non-negative matrix factorization (Tresch et al, 1999;Saltiel et al, 2001;Ting and Macpherson, 2005), all of which allow complex spatiotemporal patterns to be expressed as combinations of a limited number of components; however, these other procedures decompose the time-varying multidimensional muscle activity into combinations of synchronous synergies (vectors with the same dimension as the number of muscles) multiplied by a set of time-varying coefficients (vectors with the same dimension as the number of samples). Here, instead, the decomposition of the muscle patterns into time-varying syn- Figure 11.…”

Section: Discussionmentioning

confidence: 99%

Control of Fast-Reaching Movements by Muscle Synergy Combinations

et al. 2006

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How the CNS selects the appropriate muscle patterns to achieve a behavioral goal is an open question. To gain insight into this process, we characterized the spatiotemporal organization of the muscle patterns for fast-reaching movements. We recorded electromyographic activity from up to 19 shoulder and arm muscles during point-to-point movements between a central location and 8 peripheral targets in each of 2 vertical planes. We used an optimization algorithm to identify a set of time-varying muscle synergies, i.e., the coordinated activations of groups of muscles with specific time-varying profiles. For each one of nine subjects, we extracted four or five synergies whose combinations, after scaling in amplitude and shifting in time each synergy independently for each movement condition, explained 73-82% of the data variation. We then tested whether these synergies could reconstruct the muscle patterns for point-to-point movements with different loads or forearm postures and for reversal and via-point movements. We found that reconstruction accuracy remained high, indicating generalization across these conditions. Finally, the synergy amplitude coefficients were directionally tuned according to a cosine function with a preferred direction that showed a smaller variability with changes of load, posture, and endpoint than the preferred direction of individual muscles. Thus the complex spatiotemporal characteristics of the muscles patterns for reaching were captured by the combinations of a small number of components, suggesting that the mechanisms involved in the generation of the muscle patterns exploit this low dimensionality to simplify control.

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Temporal Components of the Motor Patterns Expressed by the Human Spinal Cord Reflect Foot Kinematics

Cited by 152 publications

References 46 publications

Coordination of Locomotion with Voluntary Movements in Humans

Coordination of Locomotion with Voluntary Movements in Humans

Walking index for spinal cord injury (WISCI): criterion validation

Control of Fast-Reaching Movements by Muscle Synergy Combinations

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