Literature DB >> 20358220

Reflexes and preflexes: on the role of sensory feedback on rhythmic patterns in insect locomotion.

J Proctor1, P Holmes.   

Abstract

Neuromuscular systems are stabilized and controlled by both feedforward and feedback signals. Feedforward pathways driven by central pattern generators (CPGs), in conjunction with preflexive mechanical reaction forces and nonlinear muscle properties, can produce stable stereotypical gaits. Feedback is nonetheless present in both slow and rapid running, and preflexive mechanisms can join with neural reflexes originating in proprioceptive sensors to yield robust behavior in uncertain environments. Here, we develop a single degree-of-freedom neuromechanical model representing a joint actuated by an agonist/antagonist muscle pair driven by motoneurons and a CPG in a periodic rhythm characteristic of locomotion. We consider two characteristic feedback modes: phasic and tonic. The former encodes states such as position in the timing of individual spikes, while the latter can transmit graded measures of force and other continuous variables as spike rates. We use results from phase reduction and averaging theory to predict phase relationships between CPG and motoneurons in the presence of feedback and compare them with simulations of the neuromechanical model, showing that both phasic and tonic feedback can shift motoneuronal timing and thereby affect joint motions. We find that phase changes in neural activation can cooperate with preflexive displacement and velocity effects on muscle force to compensate for externally applied forces, and that these effects qualitatively match experimental observations in the cockroach.

Mesh:

Year:  2010        PMID: 20358220     DOI: 10.1007/s00422-010-0383-9

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  12 in total

1.  Integration of intrinsic muscle properties, feed-forward and feedback signals for generating and stabilizing hopping.

Authors:  D F B Haeufle; S Grimmer; K-T Kalveram; A Seyfarth
Journal:  J R Soc Interface       Date:  2012-01-04       Impact factor: 4.118

2.  A dynamical systems analysis of afferent control in a neuromechanical model of locomotion: II. Phase asymmetry.

Authors:  Lucy E Spardy; Sergey N Markin; Natalia A Shevtsova; Boris I Prilutsky; Ilya A Rybak; Jonathan E Rubin
Journal:  J Neural Eng       Date:  2011-11-04       Impact factor: 5.379

3.  A dynamical systems analysis of afferent control in a neuromechanical model of locomotion: I. Rhythm generation.

Authors:  Lucy E Spardy; Sergey N Markin; Natalia A Shevtsova; Boris I Prilutsky; Ilya A Rybak; Jonathan E Rubin
Journal:  J Neural Eng       Date:  2011-11-04       Impact factor: 5.379

4.  Sex differences in leg dexterity are not present in elite athletes.

Authors:  Emily L Lawrence; Lorenzo Peppoloni; Francisco J Valero-Cuevas
Journal:  J Biomech       Date:  2017-09-14       Impact factor: 2.712

5.  The role of phase shifts of sensory inputs in walking revealed by means of phase reduction.

Authors:  Azamat Yeldesbay; Tibor Tóth; Silvia Daun
Journal:  J Comput Neurosci       Date:  2018-03-27       Impact factor: 1.621

Review 6.  Sensory feedback in cockroach locomotion: current knowledge and open questions.

Authors:  A Ayali; E Couzin-Fuchs; I David; O Gal; P Holmes; D Knebel
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2014-11-29       Impact factor: 1.836

Review 7.  Spikes alone do not behavior make: why neuroscience needs biomechanics.

Authors:  E D Tytell; P Holmes; A H Cohen
Journal:  Curr Opin Neurobiol       Date:  2011-06-15       Impact factor: 6.627

8.  Intersegmental coupling and recovery from perturbations in freely running cockroaches.

Authors:  Einat Couzin-Fuchs; Tim Kiemel; Omer Gal; Amir Ayali; Philip Holmes
Journal:  J Exp Biol       Date:  2015-01-15       Impact factor: 3.312

9.  A soft body as a reservoir: case studies in a dynamic model of octopus-inspired soft robotic arm.

Authors:  Kohei Nakajima; Helmut Hauser; Rongjie Kang; Emanuele Guglielmino; Darwin G Caldwell; Rolf Pfeifer
Journal:  Front Comput Neurosci       Date:  2013-07-09       Impact factor: 2.380

10.  Biologically-inspired adaptive obstacle negotiation behavior of hexapod robots.

Authors:  Dennis Goldschmidt; Florentin Wörgötter; Poramate Manoonpong
Journal:  Front Neurorobot       Date:  2014-01-29       Impact factor: 2.650

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