Human locomotion

Interlimb coordination is the coordination of the left and right limbs. It could be classified into two types of action: bimanual coordination and hands or feet coordination. Such coordination involves various parts of the nervous system and requires a sensory feedback mechanism for the neural control of the limbs. A model can be used to visualize the basic features, the control centre of locomotor movements, and the neural control of interlimb coordination. This coordination mechanism can be altered and adapted for better performance during locomotion in adults and for the development of motor skills in infants. The adaptive feature of interlimb coordination can also be applied to the treatment for CNS damage from stroke and the Parkinson's disease in the future.

Types of interlimb coordination

Bimanual coordination

Bimanual coordination involves the coordination of two arms in bimanual action, which allows two hands to move simultaneously to do tasks.[1] Examples of bimanual coordination include clapping hands, opening the cap of a bottle with two hands or typing words on a keyboard with both hands.

Hands/ feet coordination

Hands/ feet coordination involves the coordination of the upper limbs and the lower limbs, including the ipsilateral side of the body (e.g. left hand and left foot), or the contralateral side (both sides of the limbs). Examples include walking and climbing.

Mechanisms of interlimb coordination

Nervous system involved in interlimb coordination

Different parts of the brain are included in such coordination, including the premotor cortex (PMC), the parietal cortex, the mesial motor cortices, the supplementary motor area, the cingulate motor cortex, the primary motor cortex cerebellum and the spinal cord.[2]

Sensory feedback mechanism

Sensory feedback mechanism is involved in interlimb coordination. The sensory receptors including muscle spindles, golgi tendon organs in the limbs will first be stimulated by the external stimuli (e.g. pressure of touching an object), then generate sensory feedbacks and send information to the nervous system through the afferent pathways.[3] After receiving the feedback, the central nervous system (CNS) will then generate an internal schema of the orientation and motion of the limbs,[4] which allows the nervous system to monitor the consequence of action so that efficient sensory regulation of the limbs could be made. This allows independent modification of the movements of the limb to better manipulate the tasks.

Types of sensory feedback mechanism

There are two types of sensory feedback, intrinsic and extrinsic pathways. Intrinsic feedback will be received only from the organism's own movement,[5] which means it is the internal physical feeling of the movement performed by the organism. For example, a person can feel its movement of making a fist without any external stimulus because it requires the folding of the fingers tightly into the centre of the palm and placing of the thumb over the folding fingers. In contrast, extrinsic feedback to be received must be provided from external sources from the environment. For instance, our fingers can detect heat from boiling water and pain from the poking of needle because the heat and pain receptors receive external stimuli from the surroundings.

Modelization of interlimb coordination

Basic features

The coordination of interlimb can be represented by an integrated model which contains a central pattern generator (CPG), nonlinear muscles, hexahedral geometry, and a representative proprioceptive sensory pathway. One-dimensional phase oscillators are used to stimulate the movement of agonist-antagonist muscle pairs. Different phases of the oscillators are responsible to demonstrate the movements between the limbs. A specific oscillator with respect to the specific muscle from a specific limb could show the progression and development of that limb through its movement, for instance, the progression and development of the step cycle of the left limb in walking motion. Reflex response (e.g. biceps contracts and triceps relaxes to bend the elbow) is also incorporated in the model using stereotypical spike trains to represent, such that the reflexive feedback mechanism can also be demonstrated during the movement of muscles.[6]

Control centre of locomotor movements

The spinal cord is the core of the neural control of locomotion. This organ is the integrative centre of the CNS for motor control, it is done by receiving sensory information from peripheral receptors to control and adjust movements.[7] The central pattern generator (CPG) from the model is simulated as a network of spinal neurons that controls the basic locomotor output.[8] An effective locomotion of the model must involve a flexible coordination of spinal cord neuronal networks, thus allowing various gait patterns and independent use of the limbs. This flexible coordination can be accomplished by integrating the intrinsic regulation mechanism of the spinal cord, somatosensory feedback from the limbs and various supraspinal pathways in the model.[9]

The mechanical linkages between the limbs and trunk is important for the stabilization of multi-limb coordination movements. In return, the CNS will receive information of mechanical state of the limbs and trunk as it interacts with the environment through somatosensory feedback from the periphery.[9]

Control of arm-leg coordination during human locomotion

Rhythmic movement of the arms during bipedal walking is generated by passive biomechanical linkages and neural commands generated by spinal locomotor CPGs that control rhythmic arm and leg movements.[10] Although movement of the arms is less important to maintain dynamic stability during bipedal walking, the arms remain rhythmically coordinated with the legs. The human CNS integrated new control mechanisms into circuits already present to meet the need for new functional demands.

The neural coupling between arms and legs can be presented by the association between electromyography (EMG) activity from the upper limb and leg kinematics. Muscles of the upper limb show rhythmic activity related to arm swing, even when the arm is paralyzed.[11] The EMG activity shows that coordination of arm-leg movement still provide stimulation to the limb regardless to the mobility of limbs.

Schematic representation of the neural control of interlimb coordination

Each limb has its own spinal locomotor CPG, a schematic representation can illustrate the interactions between parts of the CPG controlling flexor and extensor activity.[12]

A schematic representation of the locomotor central pattern generator in the mammalian nervous system

Adaptations of interlimb coordination

The control of interlimb coordination is precise and flexible, therefore humans can maintain dynamic stability in a continuously changing environment, such as changing speed, or transitioning from one gait pattern to another.[9]

Change in adult gait patterns

Recent studies found out that adaptive changes only occur in interlimb coordination but do not occur in intralimb coordination (coordination on the same limb but different joints).[13] A split-belt treadmill (a treadmill that contains two belts that can drive each leg at different speeds) was used in the experiment, this intervention alters the walking or running speed of the users. Participants were stimulated to walk at different speeds alternatively, and locomotor parameters were used to calculate the movement of limbs during the gait cycle. The subjects appeared to have new motor patterns after walking on the treadmill, which indicated that a new interlimb coordination pattern was adapted and stored in participants.[13]

Development of motor skills in infants

Age was found to be related to changes in interlimb coordination such as the correlation between limb positions or between limb velocities. Changes and improvements in interlimb coordination by age are recognized to be a major phenomenon in the development of gross motor skills in infants. It was also found that a combination of movement of the arms and legs might be a precursor to some goal-directed behaviors such as reaching and grasping with the arms while walking with legs by infants.[14]

CNS damage from stroke

Cerebral structures that are involved with stroke do not impair the adaptive ability of interlimb coordination and the storage of new interlimb relationships, and therefore patients of cerebral stroke are found to be able to adapt new mechanism of interlimb coordination.[15] Given that the coordination of the limbs can be adaptively change, it is expected there is a possibility that the asymmetric walking patterns as a result of CNS damage from stroke could be improved by long-term adaptive rehabilitation strategies using a split-belt treadmill.[13][15]

Parkinson's disease

Freezing of Gait (FOG) is a disabling symptom commonly found in Parkinson's Disease. FOG is a major contributor to fall risk in Parkinson's Disease patients and can only be partially relieved by medication. Parkinson's patients with FOG are known to have more difficulty with gait adaptation in their daily movements.[16] Further, asymmetry of gait has been implicated in FOG as patients with FOG often fail to complete asymmetric tasks such as turning. Split-belt treadmill training (SBT), but not regular tied-belt treadmill training (TBT) can be used as a rehabilitation method for people with FOG by practicing their ability to adapt their gait pattern to asymmetrical circumstances. SBT improved gait adaptation immediately after the training and more importantly, improvements were retained up till 24 hours. The advantage of SBT is that it modulates gait more implicitly without attention being consciously drawn to the adaptation task.[17][16] Furthermore, repeated adaptations of the gait pattern may improve the flexible adaptation of the movement to new tasks and may train motor switching, which could potentially improve motor performance in a more sustained manner. In addition, the cerebellar circuits became more involved in the processing of gait adaptation with repeated exposure to SBT,[18] which may possibly lead to improvement in balancing and hence reduce the risk of falling.[16]

References

  1. ↑ "Bimanual coordination | Action, Control, and Learning | Psychological and Brain Sciences". psychology.uiowa.edu. Retrieved 2022-04-18.
  2. ↑ Swinnen, S.P.; Vangheluwe, S.; Wagemans, J.; Coxon, J.P.; Goble, D.J.; Van Impe, A.; Sunaert, S.; Peeters, R.; Wenderoth, N. (2010). "Shared neural resources between left and right interlimb coordination skills: The neural substrate of abstract motor representations". NeuroImage. 49 (3): 2570–2580. doi:10.1016/j.neuroimage.2009.10.052. PMID 19874897. S2CID 17227329.
  3. ↑ Wilson, Natalie M.; Wright, Douglas E. (2014-01-01), Zochodne, Douglas W.; Malik, Rayaz A. (eds.), "Chapter 30 - Experimental motor neuropathy in diabetes", Handbook of Clinical Neurology, Diabetes and the Nervous System, Elsevier, 126: 461–467, doi:10.1016/b978-0-444-53480-4.00030-8, ISBN 9780444534804, PMID 25410239, retrieved 2022-04-18
  4. ↑ MacKinnon, Colum D. (2018-01-01), Day, Brian L.; Lord, Stephen R. (eds.), "Chapter 1 - Sensorimotor anatomy of gait, balance, and falls", Handbook of Clinical Neurology, Balance, Gait, and Falls, Elsevier, 159: 3–26, doi:10.1016/b978-0-444-63916-5.00001-x, ISBN 9780444639165, PMC 7069605, PMID 30482322
  5. ↑ Greenwald, Anthony G. (1970). "Sensory feedback mechanisms in performance control: With special reference to the ideo-motor mechanism". Psychological Review. 77 (2): 73–99. doi:10.1037/h0028689. ISSN 1939-1471. PMID 5454129.
  6. ↑ Proctor, J.; Kukillaya, R. P.; Holmes, P. (2010-11-13). "A phase-reduced neuro-mechanical model for insect locomotion: feed-forward stability and proprioceptive feedback". Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. 368 (1930): 5087–5104. Bibcode:2010RSPTA.368.5087P. doi:10.1098/rsta.2010.0134. ISSN 1364-503X. PMID 20921014. S2CID 8511489.
  7. ↑ Guertin PA. The mammalian central pattern generator for locomotion. Brain Research Reviews. 2009;62(1):45–56. doi:10.1016/j.brainresrev.2009.08.002
  8. ↑ Terjung, Ronald, ed. (2011-01-17). Comprehensive Physiology (1 ed.). Wiley. doi:10.1002/cphy.cp010226. ISBN 978-0-470-65071-4.
  9. 1 2 3 Frigon, Alain (2017-06-01). "The neural control of interlimb coordination during mammalian locomotion". Journal of Neurophysiology. 117 (6): 2224–2241. doi:10.1152/jn.00978.2016. ISSN 0022-3077. PMC 5454475. PMID 28298308.
  10. ↑ Dietz, Volker; Michel, Jan (2009). "Human Bipeds Use Quadrupedal Coordination during Locomotion". Annals of the New York Academy of Sciences. 1164 (1): 97–103. Bibcode:2009NYASA1164...97D. doi:10.1111/j.1749-6632.2008.03710.x. PMID 19645886. S2CID 33657268.
  11. ↑ Kuhtz-Buschbeck, Johann P.; Jing, Bo (2012-04-01). "Activity of upper limb muscles during human walking". Journal of Electromyography and Kinesiology. 22 (2): 199–206. doi:10.1016/j.jelekin.2011.08.014. ISSN 1050-6411. PMID 21945656.
  12. ↑ "Difference Between Flexor and Extensor Muscles". Compare the Difference Between Similar Terms. 7 April 2021.
  13. 1 2 3 Reisman, Darcy S.; Block, Hannah J.; Bastian, Amy J. (2005). "Interlimb Coordination During Locomotion: What Can be Adapted and Stored?". Journal of Neurophysiology. 94 (4): 2403–2415. doi:10.1152/jn.00089.2005. ISSN 0022-3077. PMID 15958603.
  14. ↑ Kanemaru N, Watanabe H, Taga G. 2012. Increasing selectivity of interlimb coordination during spontaneous movements in 2- to 4-month-old infants. Experimental Brain Research. 218(1):49–61. doi:10.1007/s00221-012-3001-3.
  15. 1 2 Reisman, D. S.; Wityk, R.; Silver, K.; Bastian, A. J. (2007-05-29). "Locomotor adaptation on a split-belt treadmill can improve walking symmetry post-stroke". Brain. 130 (7): 1861–1872. doi:10.1093/brain/awm035. ISSN 0006-8950. PMC 2977955. PMID 17405765.
  16. 1 2 3 Seuthe, Jana; D’Cruz, Nicholas; Ginis, Pieter; Becktepe, Jos Steffen; Weisser, Burkhard; Nieuwboer, Alice; Schlenstedt, Christian (2020). "The Effect of One Session Split-Belt Treadmill Training on Gait Adaptation in People With Parkinson's Disease and Freezing of Gait". Neurorehabilitation and Neural Repair. 34 (10): 954–963. doi:10.1177/1545968320953144. ISSN 1545-9683. PMID 32940131. S2CID 221770364.
  17. ↑ Bastian, Amy J (2008). "Understanding sensorimotor adaptation and learning for rehabilitation". Current Opinion in Neurology. 21 (6): 628–633. doi:10.1097/wco.0b013e328315a293. ISSN 1350-7540. PMC 2954436. PMID 18989103.
  18. ↑ Reisman, Darcy S.; Bastian, Amy J.; Morton, Susanne M. (2010-02-01). "Neurophysiologic and Rehabilitation Insights From the Split-Belt and Other Locomotor Adaptation Paradigms". Physical Therapy. 90 (2): 187–195. doi:10.2522/ptj.20090073. ISSN 0031-9023. PMC 2816031. PMID 20023001.
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