Recruitment of Motoneurons

Thirumalai, Vatsala; Jha, Urvashi

doi:10.1007/978-3-031-07167-6_8

Cited by 4 publications

(3 citation statements)

References 129 publications

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“…The smallest neurons are presumably slow (S) -motoneurons. However, size alone is not a reliable indicator to separate these classes (42)(43)(44).…”

Section: Discussionmentioning

confidence: 99%

A size principle for bistability in mouse spinal motoneurons

Harris-Warrick,

Pecchi,

Drouillas

et al. 2023

Preprint

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Bistability in spinal motoneurons supports tonic spike activity in the absence of excitatory drive. Earlier work in adult preparations suggested that smaller motoneurons innervating slow antigravity muscle fibers are more likely to generate bistability for postural maintenance. However, whether large motoneurons innervating fast-fatigable muscle fibers display bistability related to postural tone is still controversial. To address this, we examined the relationship between soma size and bistability in lumbar ventrolateral α-motoneurons of ChAT-GFP and Hb9-GFP mice across different developmental stages: neonatal (P2-P7), young (P7-P14) and mature (P21-P25). We found that as neuron size increases, the prevalence of bistability rises. Smaller α-motoneurons lack bistability, while larger fast α-motoneurons (MMP-9+/Hb9+) with a soma area ≥ 400µm2exhibit significantly higher bistability. Ionic currents associated with bistability, including the persistent Nav1.6 current, thermosensitive Trpm5 Ca2+-activated Na+current and the slowly inactivating Kv1.2 current, also scale with cell size. Serotonin evokes full bistability in large motoneurons with partial bistable properties, but not in small motoneurons. Our study provides important insights into the neural mechanisms underlying bistability and how motoneuron size dictates this process.New and NoteworthyBistability is not a common feature of all mouse spinal motoneurons. It is absent in small, slow motoneurons but present in most large, fast motoneurons. This difference results from differential expression of ionic currents that enable bistability, which are highly expressed in large motoneurons but small or absent in small motoneurons. These results support a possible role for fast motoneurons in maintenance of tonic posture in addition to their known roles in fast movements.

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“…The smallest neurons are presumably slow (S) -motoneurons. However, size alone is not a reliable indicator to separate these classes (42)(43)(44).…”

Section: Discussionmentioning

confidence: 99%

A size principle for bistability in mouse spinal motoneurons

Harris-Warrick,

Pecchi,

Drouillas

et al. 2023

Preprint

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“…Though it is appreciated that bistability increases the information processing capacity of neurons, such as by allowing gating of synaptic inputs (Thirumalai and Jha, 2022), its implication for network computation or behavioural output is less well understood. This is true of Purkinje neurons as well - while it is established that these neurons are bistable and are important for motor behaviours (Engbers et al, 2013; Popa et al, 2018; Sengupta and Thirumalai, 2015), the role of bistability in Purkinje neuron computation or motor behaviour output has thus far not been clear.…”

Section: Discussionmentioning

confidence: 99%

A machine-learning tool to identify bistable states from calcium imaging data

Varma

Udupa

Sengupta

et al. 2022

Preprint

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The use of calcium imaging to map the activation of neurons in vivo during behavioral tasks has resulted in advancing our understanding of how nervous systems encode sensory input and generate appropriate output. In almost all of these studies, calcium imaging is used to infer spike times or probabilities since action potentials activate voltage-gated calcium channels and increase intracellular calcium levels. However, it is well known that neurons not only fire action potentials but convey information via intrinsic dynamics such as by generating bistable membrane potential states. While a number of tools for spike inference have been developed and are currently being used, no tool exists for converting calcium imaging signals to maps of cellular state in bistable neurons. Purkinje neurons (PNs), the GABA-ergic principal neurons of the cerebellum, exhibit membrane potential bistability, firing either tonically or in bursts. Several studies have implicated the role of a population code in cerebellar function, with bistability adding an extra layer of complexity to the code. In this manuscript we develop a tool, CaMLsort, which uses convolutional recurrent neural networks to classify calcium imaging traces as arising from either tonic or bursting cells. We validated the classifier using a number of different methods and we show that the tool performs well on simulated event rasters as well as real biological data that was previously not seen by the network. This tool offers a new way of analysing calcium imaging data from bistable neurons to understand how they participate in network computation and natural behaviors.

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“…Although it is appreciated that bistability increases the information processing capacity of neurons, such as by allowing gating of synaptic inputs (Thirumalai & Jha, 2022), its implication for network computation or behavioural output is less well understood. This is true of PNs as well.…”

Section: Bistability In Pn Populationsmentioning

confidence: 99%

A machine‐learning tool to identify bistable states from calcium imaging data

Varma,

Udupa,

Sengupta

et al. 2024

The Journal of Physiology

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Mapping neuronal activation using calcium imaging in vivo during behavioural tasks has advanced our understanding of nervous system function. In almost all of these studies, calcium imaging is used to infer spike probabilities because action potentials activate voltage‐gated calcium channels and increase intracellular calcium levels. However, neurons not only fire action potentials, but also convey information via intrinsic dynamics such as by generating bistable membrane potential states. Although a number of tools for spike inference have been developed and are currently being used, no tool exists for converting calcium imaging signals to maps of cellular state in bistable neurons. Purkinje neurons in the larval zebrafish cerebellum exhibit membrane potential bistability, firing either tonically or in bursts. Several studies have implicated the role of a population code in cerebellar function, with bistability adding an extra layer of complexity to this code. In the present study, we develop a tool, CaMLSort, which uses convolutional recurrent neural networks to classify calcium imaging traces as arising from either tonic or bursting cells. We validate this classifier using a number of different methods and find that it performs well on simulated event rasters as well as real biological data that it had not previously seen. Moreover, we find that CaMLsort generalizes to other bistable neurons, such as dopaminergic neurons in the ventral tegmental area of mice. Thus, this tool offers a new way of analysing calcium imaging data from bistable neurons to understand how they participate in network computation and natural behaviours. imageKey points Calcium imaging, compriising the gold standard of inferring neuronal activity, does not report cellular state in neurons that are bistable, such as Purkinje neurons in the cerebellum of larval zebrafish. We model the relationship between Purkinje neuron electrical activity and its corresponding calcium signal to compile a dataset of state‐labelled simulated calcium signals. We apply machine‐learning methods to this dataset to develop a tool that can classify the state of a Purkinje neuron using only its calcium signal, which works well on real data even though it was trained only on simulated data. CaMLsort (Calcium imaging and Machine Learning based tool to sort intracellular state) also generalizes well to bistable neurons in a different brain region (ventral tegmental area) in a different model organism (mouse). This tool can facilitate our understanding of how these neurons carry out their functions in a circuit.

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Recruitment of Motoneurons

Cited by 4 publications

References 129 publications

A size principle for bistability in mouse spinal motoneurons

A size principle for bistability in mouse spinal motoneurons

A machine-learning tool to identify bistable states from calcium imaging data

A machine‐learning tool to identify bistable states from calcium imaging data

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