Motoneurons regulate the central pattern generator during drug-induced locomotor-like activity in the neonatal mouse
Abstract
Motoneurons are traditionally viewed as the output of the spinal cord that do not influence locomotor rhythmogenesis. We assessed the role of motoneuron firing during ongoing locomotor-like activity in neonatal mice expressing archaerhopsin-3 (Arch), halorhodopsin (eNpHR), or channelrhodopsin-2 (ChR2) in Choline acetyltransferase expressing neurons (ChAT+) or the LIM-homeodomain transcription factor Isl1+ neurons. Illumination of the lumbar cord in mice expressing eNpHR or Arch in ChAT+ or Isl1+ neurons, depressed motoneuron discharge, transiently decreased the frequency, and perturbed the phasing of the locomotor-like rhythm. When the light was turned off motoneuron firing and locomotor frequency both transiently increased. These effects were not due to cholinergic neurotransmission, persisted during partial blockade of gap junctions and were mediated, in part, by AMPAergic transmission. In spinal cords expressing ChR2, illumination increased motoneuron discharge and transiently accelerated the rhythm. We conclude that motoneurons provide feedback to the central pattern generator (CPG) during drug-induced locomotor-like activity.
Article and author information
Author details
Funding
National Institutes of Health (NINDS Intramural program)
- Melanie Falgairolle
National Institutes of Health (NINDS Intramural program)
- Michael James O'Donovan
National Institutes of Health (NINDS Intramural program)
- Joshua G Puhl
National Institutes of Health (NINDS Intramural NRSA)
- Joshua G Puhl
National Institutes of Health (NINDS Intramural program)
- Wenfang Liu
National Institutes of Health (NINDS Intramural program)
- Avinash Pujala
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All experiments were carried out in compliance with the National Institutes of Neurological Disorders and Stroke Animal Care and Use Committee (Animal Protocol Number 1267-12 and 1267-15).
Copyright
This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
Metrics
-
- 2,427
- views
-
- 406
- downloads
-
- 47
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Neuroscience
Female sexual receptivity is essential for reproduction of a species. Neuropeptides play the main role in regulating female receptivity. However, whether neuropeptides regulate female sexual receptivity during the neurodevelopment is unknown. Here, we found the peptide hormone prothoracicotropic hormone (PTTH), which belongs to the insect PG (prothoracic gland) axis, negatively regulated virgin female receptivity through ecdysone during neurodevelopment in Drosophila melanogaster. We identified PTTH neurons as doublesex-positive neurons, they regulated virgin female receptivity before the metamorphosis during the third-instar larval stage. PTTH deletion resulted in the increased EcR-A expression in the whole newly formed prepupae. Furthermore, the ecdysone receptor EcR-A in pC1 neurons positively regulated virgin female receptivity during metamorphosis. The decreased EcR-A in pC1 neurons induced abnormal morphological development of pC1 neurons without changing neural activity. Among all subtypes of pC1 neurons, the function of EcR-A in pC1b neurons was necessary for virgin female copulation rate. These suggested that the changes of synaptic connections between pC1b and other neurons decreased female copulation rate. Moreover, female receptivity significantly decreased when the expression of PTTH receptor Torso was reduced in pC1 neurons. This suggested that PTTH not only regulates female receptivity through ecdysone but also through affecting female receptivity associated neurons directly. The PG axis has similar functional strategy as the hypothalamic–pituitary–gonadal axis in mammals to trigger the juvenile–adult transition. Our work suggests a general mechanism underlying which the neurodevelopment during maturation regulates female sexual receptivity.
-
- Neuroscience
Theoretical computational models are widely used to describe latent cognitive processes. However, these models do not equally explain data across participants, with some individuals showing a bigger predictive gap than others. In the current study, we examined the use of theory-independent models, specifically recurrent neural networks (RNNs), to classify the source of a predictive gap in the observed data of a single individual. This approach aims to identify whether the low predictability of behavioral data is mainly due to noisy decision-making or misspecification of the theoretical model. First, we used computer simulation in the context of reinforcement learning to demonstrate that RNNs can be used to identify model misspecification in simulated agents with varying degrees of behavioral noise. Specifically, both prediction performance and the number of RNN training epochs (i.e., the point of early stopping) can be used to estimate the amount of stochasticity in the data. Second, we applied our approach to an empirical dataset where the actions of low IQ participants, compared with high IQ participants, showed lower predictability by a well-known theoretical model (i.e., Daw’s hybrid model for the two-step task). Both the predictive gap and the point of early stopping of the RNN suggested that model misspecification is similar across individuals. This led us to a provisional conclusion that low IQ subjects are mostly noisier compared to their high IQ peers, rather than being more misspecified by the theoretical model. We discuss the implications and limitations of this approach, considering the growing literature in both theoretical and data-driven computational modeling in decision-making science.