Abstract
Neurophysiological experiments in walking cats have shown that a number of neural control mechanisms are involved in regulating the movements of the hind legs during locomotion. It is experimentally hard to isolate individual mechanisms without disrupting the natural walking pattern and we therefore introduce a different approach where we use a model to identify what control is necessary to maintain stability in the musculo-skeletal system. We developed a computer simulation model of the cat hind legs in which the movements of each leg are produced by eight limb muscles whose activations follow a centrally generated pattern with no proprioceptive feedback. All linear transfer functions, from each muscle activation to each joint angle, were identified using the response of the joint angle to an impulse in the muscle activation at 65 postures of the leg covering the entire step cycle. We analyzed the sensitivity and stability of each muscle action on the joint angles by studying the gain and pole plots of these transfer functions. We found that the actions of most of the hindlimb muscles display inherent stability during stepping, even without the involvement of any proprioceptive feedback mechanisms, and that those musculo-skeletal systems are acting in a critically damped manner, enabling them to react quickly without unnecessary oscillations. We also found that during the late swing, the activity of the posterior biceps/semitendinosus (PB/ST) muscles causes the joints to be unstable. In addition, vastus lateralis (VL), tibialis anterior (TA) and sartorius (SAT) muscle–joint systems were found to be unstable during the late stance phase, and we conclude that those muscles require neuronal feedback to maintain stable stepping, especially during late swing and late stance phases. Moreover, we could see a clear distinction in the pole distribution (along the step cycle) for the systems related to the ankle joint from that of the other two joints, hip or knee. A similar pattern, i.e., a pattern in which the poles were scattered over the s-plane with no clear clustering according to the phase of the leg position, could be seen in the systems related to soleus (SOL) and TA muscles which would indicate that these muscles depend on neural control mechanisms, which may involve supraspinal structures, over the whole step cycle.
Similar content being viewed by others
References
Bouyer L, Rossignol S (2003a) Contribution of cutaneous inputs from the hindpaw to the control of locomotion: I. Intact cats. J Neurophysiol 90: 3625–3639
Bouyer L, Rossignol S (2003b) Contribution of cutaneous inputs from the hindpaw to the control of locomotion: II. Spinal cats. J Neurophysiol 90: 3640–3653
Brown I, Scott S, Loeb G (1996) Mechanics of feline soleus: II. Design and validation of a mathematical model. J Muscle Res Cell Motil 17: 221–233
Brown T (1911) The intrinsic factors in the act of progression in the mammal. Proc R Soc Lond B 84: 308–319
Cheung V, d’Avella A, Tresch M, Bizzi E (2005) Central and sensory contributions to the activation and organization of muscle synergies during natural behaviors. J Neurosci 25: 6419–6434
Donelan J, Pearson K (2004) Contribution of force feedback to ankle extensor activity in decerebrate walking cats. J Neurophysiol 92: 2093–2104
Duenas S, Loeb G, Marks W (1990) Monosynaptic and dorsal root reflexes during locomotion in normal and thalamic cats. J Neurophysiol 63: 1467–1476
Duysens J, Van de Crommert H (1998) Neural control of locomotion, part 1: the central pattern generator from cats to humans. Gait Posture 7: 131–141
Ekeberg Ö, Pearson K (2005) Computer simulation of stepping in the hind legs of the cat: an examination of mechanisms regulating the stance-to-swing transition. J Neurophysiol 94: 4256–4268
Engberg I, Lundberg A (1969) An electromyographic analysis of muscular activity in the hindlimb of the cat during unrestrained locomotion. Acta Physiol Scand 75(4): 614–630
Forssberg H, Grillner S, Rossignol S (1975) Phase dependent reflex reversal during walking in chronic spinal cats. Brain Res 85: 103–107
Frigon A, Rossignol S (2006) Experiments and models of sensorimotor interactions during locomotion. Biol Cybern 95: 607–627
Fukuoka Y, Kimura H, Cohen A (2003) Adaptive dynamic walking of a quadruped robot on irregular terrain based on biological concepts. J Rob Res 22(3–4): 187–202
Goslow G, Reinking R, Stuart D (1973) The cat step cycle: hind limb joint angles and muscle lengths during unrestrained locomotion. J Morphol 141: 1–42
Grillner S, Zangger P (1975) How detailed is the central pattern generation for locomotion?. Brain Res 88: 367–371
Herzog W, Leonard T, Renaud J, Wallace J, Chaki G, Bornemisza S (1992) Force-length properties and functional demands of cat gastrocnemius, soleus and plantaris muscles. J Biomech 25(11): 1329–1335
Hoy M, Zernicke R (1985) Modulation of limb dynamics in the swing phase of locomotion. J Biomech 18(1): 49–60
Hultborn H (2006) Spinal reflexes, mechanisms and concepts: from Eccles to Lundberg and beyond. Prog Neurobiol 78: 215–232
Ijspeert A (2002) Locomotion, vertebrate. In: M A (eds) The handbook of brain theory and neural networks. MIT Press, Cambridge
Ivashko D, Prilutsky B, Markin S, Chapin J, Rybak I (2003) Modeling the spinal cord neural circuitry controlling cat hindlimb movement during locomotion. J Neurocomput 52–54: 621–629
Jiping H, Levine S, Loeb G (1991) Feedback gains for correcting small perturbations to standing posture. IEEE Trans Autom Control 36(3): 322–332
Kandel E, Schwartz J, Jessel T (2000) Principles of neural science, 4th edn. McGraw-Hill, New York
Kaya M, Herzog W (2003) Coordination of medial gastrocnemius and soleus forces during cat locomotion. J Exp Biol 206: 3645–3655
Kimura H, Fukuoka Y, Konage K (2001) Adaptive dynamic walking of a quadruped robot using a neural system model. J Adv Robot 15(8): 859–878
Krouchev N, Kalaska J, Drew T (2006) Sequential activation of muscle synergies during locomotion in the intact cat as revealed by cluster analysis and direct decomposition. J Neurophysiol 96(4): 1991–2010
Lieber R (1999) Skeletal muscle is a biological example of a linear electro-active actuator. In: Annual international symposium on smart structures and material, no. 3669-03 in SPIE
Loeb G (1995) Control implications of musculoskeletal mechanics. IEEE-EMBC and CMBEC, pp 1393–1394
MacKay-Lyons M (2002) Central pattern generation of locomotion: a review of the evidence. J Phys Ther 82(1): 69–83
Murphy P, Hammond G (1997) Reversal of fusimotor reflex responses during locomotion in the decerebrate cat. J Exp Physiol 82: 837–858
Orlovsky G, Feldman A (1972) Role of afferent activity in the generation of stepping movements. J Neurophysiol 4: 304–310
Pearson K, Ekeberg Ö, Buschges A (2006) Assessing sensory function in locomotor systems using neuro-mechanical simulations. Trends Neurosci 29(11): 625–631
Prochazka A (1989) Sensorymotor gain control: a basic strategy of gain control. Prog Neurobiol 33: 281–307
Proske U, Morgan D (1987) Tendon stiffness: methods of measurement and significance for the control of movement; review. J Biomech 20(1): 75–82
Rack P, Westbury D (1984) Elastic properties of the cat soleus tendon and their functional importance. J Physiol 347: 479–495
Rossignol S, Dubuc R, Gossard J (2006) Dynamic sensorimotor interactions in locomotion. Physiol Rev 86: 89–154
Rybak I, Stecina K, Shevtsova N, McCrea D (2006) Modelling spinal circuitry involved in locomotor pattern generation: insights from the effects of afferent stimulation. J Physiol 577: 641–658
Scott S, Brown I, Loeb G (1996) Mechanics of feline soleus: I. Effect of fascicle length and velocity on force output. J Muscle Res Cell Motil 17: 207–219
Shen L, Poppele R (1995) Kinematic analysis of cat hindlimb stepping. J Neurophysiol 74(6): 2266–2280
Shue G, Crago P, Chizeck H (1995) Muscle–joint models incorporating activation dynamics, moment–angle, and moment–velocity properties. IEEE Trans Biomed Eng 42(2): 212–223
Taylor A, Durbaba R, Ellaway P, Rawlinson S (2000) Patterns of fusimotor activity during locomotion in the decerebrate cat deduced from recordings from hindlimb muscle spindles. J Physiol 522(3): 515–532
Torres-Oviedo G, Macpherson J, Ting L (2006) Muscle synergy organization is robust across a variety of postural perturbations. J Neurophysiol 96: 1530–1546
Trank T, Chen C, Smith J (1996) Forms of forward quadrupedal locomotion: I. A comparison of posture, hindlimb kinematics, and motor patterns for normal and crouched walking. J Neurophysiol 76(4): 2316–2326
Windhorst U (2007) Muscle proprioceptive feedback and spinal networks. Brain Res Bull 73: 155–202
Yakovenko S, Gritsenko V, Prochazka A (2004) Contribution of stretch reflexes to locomotor control: a modeling study. J Biol Cybern 90: 146–155
Zajac F (1989) Muscle and tendon: properties, models, scaling and application to biomechanics and motor control. Crit Rev Biomed Eng 17(4): 359–411
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Harischandra, N., Ekeberg, Ö. System identification of muscle–joint interactions of the cat hind limb during locomotion. Biol Cybern 99, 125–138 (2008). https://doi.org/10.1007/s00422-008-0243-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00422-008-0243-z