A Model of Fast Hebbian Spike Latency Normalization

Einarsson, Hafsteinn; Gauy, Marcelo Matheus; Lengler, Johannes; Steger, Angelika

doi:10.3389/fncom.2017.00033

“…The static synapse model was used for simulations with self-inhibition via inhibitory interneurons. The synaptic delay was set to 1 s in all models [ 83 , 84 ].…”

Section: Methodsmentioning

confidence: 99%

Biological data questions the support of the self inhibition required for pattern generation in the half center model

Köhler

¹

,

Stratmann

²

,

Röhrbein

³

et al. 2020

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Locomotion control in mammals has been hypothesized to be governed by a central pattern generator (CPG) located in the circuitry of the spinal cord. The most common model of the CPG is the half center model, where two pools of neurons generate alternating, oscillatory activity. In this model, the pools reciprocally inhibit each other ensuring alternating activity. There is experimental support for reciprocal inhibition. However another crucial part of the half center model is a self inhibitory mechanism which prevents the neurons of each individual pool from infinite firing. Self-inhibition is hence necessary to obtain alternating activity. But critical parts of the experimental bases for the proposed mechanisms for self-inhibition were obtained in vitro, in preparations of juvenile animals. The commonly used adaptation of spike firing does not appear to be present in adult animals in vivo. We therefore modeled several possible self inhibitory mechanisms for locomotor control. Based on currently published data, previously proposed hypotheses of the self inhibitory mechanism, necessary to support the CPG hypothesis, seems to be put into question by functional evaluation tests or by in vivo data. This opens for alternative explanations of how locomotion activity patterns in the adult mammal could be generated.

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“…Other values were considered, and similar results were obtained with the only difference being the speed of weight change. Still, the pattern of activity remained the same for all the values we examined as can be seen in Fig 3. The weight matrix was normalised after each update-to avoid runaway plasticity as indicated by the findings of [55,56]-by the following rule:…”

Section: Connectivity and Plasticitymentioning

confidence: 99%

Computational modelling of the long-term effects of brain stimulation on the local and global structural connectivity of epileptic patients

Giannakakis

¹

,

Hutchings

²

,

Papasavvas

³

et al. 2020

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Computational studies of the influence of different network parameters on the dynamic and topological network effects of brain stimulation can enhance our understanding of different outcomes between individuals. In this study, a brain stimulation session along with the subsequent post-stimulation brain activity is simulated for a period of one day using a network of modified Wilson-Cowan oscillators coupled according to diffusion imaging based structural connectivity. We use this computational model to examine how differences in the interregion connectivity and the excitability of stimulated regions at the time of stimulation can affect post-stimulation behaviours. Our findings indicate that the initial inter-region connectivity can heavily affect the changes that stimulation induces in the connectivity of the network. Moreover, differences in the excitability of the stimulated regions seem to lead to different post-stimulation connectivity changes across the model network, including on the internal connectivity of non-stimulated regions.

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“…A natural extension of this 72 mutual inhibition network is to provide each half center with a network structure to 73 gradually accumulate activity over time, so that the half center becomes inhibited after 74 a certain amount of time depending on the level of excitation that is provided to the 75 network. As either of these two circuitry structures would have to form the foundation 76 for any circuitry model implementing the half center hypothesis, we here decided to 77 simulate these two network scenarios to explore what frequencies of alternating 78 oscillations they would be able to support, and under what conditions with respect to 79 the synaptic time constants. 80 Whereas our simulations show that both of these mechanisms could be made to work 81 to produce alternating oscillations, these cover only part of the frequency range 82 observed for locomotion and moreover require parameter settings for synaptic decay 83 time constants and recovery time constants from STD, which can be observed in some 84 in vitro preparations of juvenile spinal cord but that appear unlikely to be present in 85 vivo.…”

Section: Introductionmentioning

confidence: 99%

“…The static synapse model 366 static synapse was used for simulations with self-inhibition via inhibitory 367 interneurons. The synaptic delay was set to 1 s in all models [76,77].…”

mentioning

confidence: 99%

Biological data questions the support of the self inhibition required for pattern generation in the half center model

Köhler¹,

Stratmann²,

Röhrbein³

et al. 2019

Preprint

View full text Add to dashboard Cite

Locomotion control in mammals has been hypothesized to be governed by a central pattern generator (CPG) located in the circuitry of the spinal cord. The most common model of the CPG is the half center model, where two pools of neurons generate alternating, oscillatory activity. In this model, the pools reciprocally inhibit each other ensuring alternating activity. There is experimental support for reciprocal inhibition. However another crucial part of the half center model is a self inhibitory mechanism which prevents the neurons of each individual pool from infinite firing. Self-inhibition is hence necessary to obtain alternating activity. But critical parts of the experimental bases for the proposed mechanisms for self-inhibition were obtained in vitro, in preparations of juvenile animals. The commonly used adaptation of spike firing does not appear to be present in adult animals in vivo. We therefore modeled several possible self inhibitory mechanisms for locomotor control. Based on currently published data, previously proposed hypotheses of the self inhibitory mechanism, necessary to support the CPG hypothesis, seems to be put into question by functional evaluation tests or by in vivo data. This opens for alternative explanations of how locomotion activity patterns in the adult mammal could be generated. Author summaryLocomotion control in animals is hypothesized to be controlled through an intrinsic central pattern generator in the spinal cord. This was proposed over a hundred years ago and has subsequently been formed into a consistent theory, through experimentation and computer modeling. However, critical data that support the neuronal circuitry mechanisms underpinning this theory has been obtained in experiments that greatly differ from intact animals. We propose, after trying to fill in this critical part, that new ideas are required to explain locomotion of intact animals. 14 alternating oscillation in activity between the two half centers. The alternation would 15 ensure left right alternation and alternation between antagonists. This model would 16 explain locomotion in decerebrated animals [1], fictive locomotion [5] and locomotion 17 patterns in intact animals [6]. Neurophysiological evidence for a circuit fitting the half 18 center model was found [7] and subsequently substantiated by further findings [8-10]. 19The half center is a key component of computational and other models of the 20 CPG [5,6,[11][12][13][14]. Asymmetric half center models have been proposed to explain 21 alternation between flexor and extensor [15]. We focus on the symmetric case. 22Experimental studies show that reciprocal inhibition is necessary to ensure left right 23 alternation [16], hence reciprocal inhibition must be present in the CPG. 24However, it was already noted that two groups of neurons inhibiting each other are 25 not sufficient to generate oscillation [1,7]. We will formally demonstrate why this is the 26 case using a mean field model. Without a mechanism that stops neurons from indefinite 27 activity, one h...

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A Model of Fast Hebbian Spike Latency Normalization

Cited by 9 publications

References 92 publications

Biological data questions the support of the self inhibition required for pattern generation in the half center model

Biological data questions the support of the self inhibition required for pattern generation in the half center model

Computational modelling of the long-term effects of brain stimulation on the local and global structural connectivity of epileptic patients

Biological data questions the support of the self inhibition required for pattern generation in the half center model

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