Modulation of Cellular and Synaptic Variability in the Lamprey Spinal Cord

Parker, Dianne; Bevan, Sarah

doi:10.1152/jn.00717.2006

Cited by 9 publications

(12 citation statements)

References 60 publications

(78 reference statements)

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“…Each of the 10,000 multicompartmental neurons have biophysically realistic properties and closely resemble their biological counterparts. One critical factor for the overall network function is the importance of the experimentally observed variability in neuronal size and membrane properties within each population (6,38,39). The asymmetric anteroposterior distribution of the axonal projections of the interneurons (see Fig.…”

Section: Discussionmentioning

confidence: 99%

Simple cellular and network control principles govern complex patterns of motor behavior

Kozlov

Huss²,

Lansner³

et al. 2009

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

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The vertebrate central nervous system is organized in modules that independently execute sophisticated tasks. Such modules are flexibly controlled and operate with a considerable degree of autonomy. One example is locomotion generated by spinal central pattern generator networks (CPGs) that shape the detailed motor output. The level of activity is controlled from brainstem locomotor command centers, which in turn, are under the control of the basal ganglia. By using a biophysically detailed, full-scale computational model of the lamprey CPG (10,000 neurons) and its brainstem/forebrain control, we demonstrate general control principles that can adapt the network to different demands. Forward or backward locomotion and steering can be flexibly controlled by local synaptic effects limited to only the very rostral part of the network. Variability in response properties within each neuronal population is an essential feature and assures a constant phase delay along the cord for different locomotor speeds.basal ganglia ͉ brainstem ͉ computational model ͉ lamprey ͉ spinal CPG V ertebrate behavior depends on different sets of neuronal networks specialized to coordinate different motor tasks like locomotion, breathing, and the expression of emotions (1-5). The activity of these networks is governed by brainstem command centers that are, in turn, under the control of the basal ganglia (1, 2). Although the critical role of these networks is well established, their intrinsic mode of operation has, for the most part, remained enigmatic. The lamprey nervous system provides one of the few examples in which detailed knowledge is available, not only of the different types of the participating neurons, but also their membrane properties and synaptic connectivity, particularly with regard to the spinal network (6, 7). Even with this knowledge at hand, it is very difficult, if not impossible, to establish, without the help of modeling, whether the experimental data available are actually sufficient to account for the dynamic operation of the networkand enable exploration of the particular role of different cellular and synaptic components to make predictions of their functional role. To achieve this, we report here a biophysically realistic model of the locomotor network and its control from the brain. The spinal network is composed of excitatory and inhibitory model neurons that, in considerable detail, behave as their biological counterparts. It proved to be important to introduce within each pool of model neurons the known biological variability in neuronal size and membrane properties. Thanks to recent developments in computer technology, we have been able to make a full-scale model of the network with 100 model neurons per segment, each of the Hodgkin-Huxley type-altogether 10,000 neurons connected via 760,000 synapses in the 100 segments. We represent the brainstem command system, as well as the forebrain control from the basal ganglia with an additional 3,500 neurons. Simulations limited to subsamples of neurons have previou...

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Section: Discussionmentioning

confidence: 99%

Simple cellular and network control principles govern complex patterns of motor behavior

Kozlov

Huss²,

Lansner³

et al. 2009

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

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“…For example, in a study that compared glutamate-evoked fictive activity in the isolated lamprey spinal cord with locomotor activity in swimming animals only regular activity was considered for analysis (it was stated that “the sequences selected for analysis in each preparation were those that appeared least variable”; Wallen and Williams, 1984). The selection was necessary because fictive activity is often irregular (Ayers et al, 1983; Parker et al, 1998; Parker and Bevan, 2007), and data are often searched for regions of regular activity or preparations are taken until one shows regular (“normal”) activity (it could be claimed that the quality of fictive activity shown is directly proportional to the number of experiments performed). This is a reflection of the belief that activity should be regular to resemble normal locomotion and that variability in the pattern is somehow abnormal, which counters the findings of the Hausdorff et al (1997).…”

Section: Complexity In Movement and Central Pattern Generating Networkmentioning

confidence: 99%

Dynamic systems approaches and levels of analysis in the nervous system

Parker¹,

Srivastava²

2013

Front. Physio.

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Various analyses are applied to physiological signals. While epistemological diversity is necessary to address effects at different levels, there is often a sense of competition between analyses rather than integration. This is evidenced by the differences in the criteria needed to claim understanding in different approaches. In the nervous system, neuronal analyses that attempt to explain network outputs in cellular and synaptic terms are rightly criticized as being insufficient to explain global effects, emergent or otherwise, while higher-level statistical and mathematical analyses can provide quantitative descriptions of outputs but can only hypothesize on their underlying mechanisms. The major gap in neuroscience is arguably our inability to translate what should be seen as complementary effects between levels. We thus ultimately need approaches that allow us to bridge between different spatial and temporal levels. Analytical approaches derived from critical phenomena in the physical sciences are increasingly being applied to physiological systems, including the nervous system, and claim to provide novel insight into physiological mechanisms and opportunities for their control. Analyses of criticality have suggested several important insights that should be considered in cellular analyses. However, there is a mismatch between lower-level neurophysiological approaches and statistical phenomenological analyses that assume that lower-level effects can be abstracted away, which means that these effects are unknown or inaccessible to experimentalists. As a result experimental designs often generate data that is insufficient for analyses of criticality. This review considers the relevance of insights from analyses of criticality to neuronal network analyses, and highlights that to move the analyses forward and close the gap between the theoretical and neurobiological levels, it is necessary to consider that effects at each level are complementary rather than in competition.

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“…As these conductances are targeted by neuromodulatory systems (e.g., cholinergic, Chevallier et al 2006;serotonergic, Kiehn 2000), they might provide some degree of variability in the bursting of motor axial networks, which is essential for an enhanced robustness and a larger working range (Parker and Bevan 2007).…”

Section: Stability Of Hemisegmental/segmental Burstingmentioning

confidence: 99%

Segmental Oscillators in Axial Motor Circuits of the Salamander: Distribution and Bursting Mechanisms

Ryczko

Charrier

Ijspeert

et al. 2010

Journal of Neurophysiology

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The rhythmic and coordinated activation of axial muscles that underlie trunk movements during locomotion are generated by specialized networks in the spinal cord. The operation of these networks has been extensively investigated in limbless swimming vertebrates. But little is known about the architecture and functioning of the axial locomotor networks in limbed vertebrates. We investigated the rhythm-generating capacity of the axial segmental networks in the salamander (Pleurodeles waltlii). We recorded ventral root activity from hemisegments and segments that were surgically isolated from the mid-trunk cord and chemically activated with bath-applied N-methyl-d-aspartate (NMDA). We provide evidence that the rhythmogenic capacity of the axial network is distributed along the mid-trunk spinal cord without an excitability gradient. We demonstrate that the burst generation in a hemisegment depends on glutamatergic excitatory interactions. Reciprocal glycinergic inhibition between opposite hemisegments ensures left-right alternation and lowers the rhythm frequency in segments. Our results further suggest that persistent sodium current contributes to the rhythmic regenerating process both in hemisegments and segments. Burst termination in hemisegments is not achieved through the activation of apamine-sensitive Ca(2+)-activated K(+) channels and burst termination in segments relies on crossed glycinergic inhibition. Together our results indicate that the basic design of the salamander axial network is similar to most of axial networks investigated in other vertebrates, albeit with some significant differences in the cellular mechanism that underlies segmental bursting. This finding supports the view of a phylogenetic conservation of basic building blocks of the axial locomotor network among the vertebrates.

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Modulation of Cellular and Synaptic Variability in the Lamprey Spinal Cord

Cited by 9 publications

References 60 publications

Simple cellular and network control principles govern complex patterns of motor behavior

Simple cellular and network control principles govern complex patterns of motor behavior

Dynamic systems approaches and levels of analysis in the nervous system

Segmental Oscillators in Axial Motor Circuits of the Salamander: Distribution and Bursting Mechanisms

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