Neural bases of goal-directed locomotion in vertebrates—An overview

Grillner, Sten; Wallén, Peter; Saitoh, Ken-ichi; Kozlov, Alexander; Robertson, Brita

doi:10.1016/j.brainresrev.2007.06.027

Cited by 310 publications

(278 citation statements)

References 40 publications

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“…In many model systems, rhythmic locomotor activity is drug-induced. Although this approach has greatly facilitated investigation of CPG networks, their neuromodulation, and their development (1)(2)(3)(4), it also constrains the networks to operate over a relatively narrow range of possible output configurations, producing a single mode of operation dictated by the concentration and mixture of the drugs. This approach therefore precludes an appreciation of the complexity of naturally evoked and sustained motor network activity, which can operate like a rheostat over an almost infinitely wide range of frequencies and intensities.…”

Section: Discussionmentioning

confidence: 99%

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Development of a spinal locomotor rheostat

Zhang

Issberner

Sillar

2011

Proc. Natl. Acad. Sci. U.S.A.

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Locomotion in immature animals is often inflexible, but gradually acquires versatility to enable animals to maneuver efficiently through their environment. Locomotor activity in adults is produced by complex spinal cord networks that develop from simpler precursors. How does complexity and plasticity emerge during development to bestow flexibility upon motor behavior? And how does this complexity map onto the peripheral innervation fields of motorneurons during development? We show in postembryonic Xenopus laevis frog tadpoles that swim motorneurons initially form a homogenous pool discharging single action potential per swim cycle and innervating most of the dorsoventral extent of the swimming muscles. However, during early larval life, in the prelude to a free-swimming existence, the innervation fields of motorneurons become restricted to a more limited sector of each muscle block, with individual motorneurons reaching predominantly ventral, medial, or dorsal regions. Larval motorneurons then can also discharge multiple action potentials in each cycle of swimming and differentiate in terms of their firing reliability during swimming into relatively high-, medium-, or low-probability members. Many motorneurons fall silent during swimming but can be recruited with increasing locomotor frequency and intensity. Each region of the myotome is served by motorneurons spanning the full range of firing probabilities. This unfolding developmental plan, which occurs in the absence of movement, probably equips the organism with the neuronal substrate to bend, pitch, roll, and accelerate during swimming in ways that will be important for survival during the period of free-swimming larval life that ensues.motor system | central pattern generator | ontogeny A dult vertebrates navigate through their environment with incredible agility and flexibility, a feature of locomotory behavior that is often critical for survival. During locomotion, sensory information interacts with central pattern generator (CPG) networks in the spinal cord, which in turn provide command signals to motorneurons (MNs) to sequence and guide movements appropriately (1). CPGs develop before locomotion is possible (2-4). Initially, however, the output of immature CPGs lacks the precision and flexibility that typifies adult locomotion. Therefore, postembryonic development must involve a period during which the central motor control circuitry is modified to accommodate the behavioral requirements of later stages. Much is known about the molecular mechanisms responsible for the differentiation of neuronal components of the motor system, motor axon trajectories, and innervation patterns (5-7). However, how this links to the functional development of these components has not been fully resolved, although there is ample evidence that activity itself is influential as a developmental signal (8, 9).Recent evidence has revealed a topographic recruitment order for dorsoventrally arranged spinal premotor interneurons and MNs during changes in swimming speed in larval ...

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Section: Discussionmentioning

confidence: 99%

“…During locomotion, sensory information interacts with central pattern generator (CPG) networks in the spinal cord, which in turn provide command signals to motorneurons (MNs) to sequence and guide movements appropriately (1). CPGs develop before locomotion is possible (2)(3)(4).…”

mentioning

confidence: 99%

Development of a spinal locomotor rheostat

Zhang

Issberner

Sillar

2011

Proc. Natl. Acad. Sci. U.S.A.

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“…excitatory outputs of the cerebral cortex and thalamus, inhibitory outputs of the basal ganglia, and modulation of synaptic transmission and neuronal excitability by transmitters such as DA. This motif has been conserved in the evolution of vertebrates [19]. By comparison, variations in the expression of receptors and cytoarchitectonic features are minor.…”

Section: Discussionmentioning

confidence: 99%

“…The basal ganglia are a group of subcortical nuclei with highly conserved circuitry [19][20][21]. As shown in figure 1, unlike the cerebral cortex, which contains excitatory glutamatergic projection neurons, the basal ganglia contain g-aminobutyric acid (GABA) projection neurons [18].…”

Section: Dopamine and The Basal Gangliamentioning

confidence: 99%

Action, time and the basal ganglia

Yin

2014

Phil. Trans. R. Soc. B

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The ability to control the speed of movement is compromised in neurological disorders involving the basal ganglia, a set of subcortical cerebral nuclei that receive prominent dopaminergic projections from the midbrain. For example, bradykinesia, slowness of movement, is a major symptom of Parkinson's disease, whereas rapid tics are observed in patients with Tourette syndrome. Recent experimental work has also implicated dopamine (DA) and the basal ganglia in action timing. Here, I advance the hypothesis that the basal ganglia control the rate of change in kinaesthetic perceptual variables. In particular, the sensorimotor cortico-basal ganglia network implements a feedback circuit for the control of movement velocity. By modulating activity in this network, DA can change the gain of velocity reference signals. The lack of DA thus reduces the output of the velocity control system which specifies the rate of change in body configurations, slowing the transition from one body configuration to another.

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“…In biology, despite contributing to the mechanistic explanation of foraging behavior at the genetic [26][27][28][29], molecular [30], and neural levels [31,32], the study of foraging and its evolution has not sufficiently improved our understanding of this phenomenon to the point where it is reproducible in artificial legged animals. One reason for this failure may be that goal-directed behavior in higher animals has taken a very long evolutionary route, by gradually evolving from ancient instances in organisms that can be traced back to the first prokaryotes [30].…”

Section: Introductionmentioning

confidence: 99%

Evolution of sustained foraging in three-dimensional environments with physics

Chaumont¹,

Adami

2016

Genet Program Evolvable Mach

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Artificially evolving foraging behavior in simulated articulated animals has proved to be a notoriously difficult task. Here, we co-evolve the morphology and controller for virtual organisms in a three-dimensional physical environment to produce goal-directed locomotion in articulated agents. We show that following and reaching multiple food sources can evolve de novo, by evaluating each organism on multiple food sources placed on a basic pattern that is gradually randomized across generations. We devised a strategy of evolutionary ''staging'', where the best organism from a set of evolutionary experiments using a particular fitness function is used to seed a new set, with a fitness function that is progressively altered to better challenge organisms as evolution improves them. We find that an organism's efficiency at reaching the first food source does not predict its ability at finding subsequent ones because foraging efficiency crucially depends on the position of the last food source reached, an effect illustrated by ''foraging maps'' that capture the organism's controller state, body position, and orientation. Our best evolved foragers are able to reach multiple food sources over 90 % of the time on average, a behavior that is key to any biologically realistic simulation where a self-sustaining population has to survive by collecting food sources in three-dimensional, physical environments.Electronic supplementary material The online version of this article

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Neural bases of goal-directed locomotion in vertebrates—An overview

Cited by 310 publications

References 40 publications

Development of a spinal locomotor rheostat

Development of a spinal locomotor rheostat

Action, time and the basal ganglia

Evolution of sustained foraging in three-dimensional environments with physics

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