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1. The Voltage-Gated Sodium Channel in Drosophila , Para, Localizes to Dendrites As Well As Axons in Mechanosensitive Chordotonal Neurons

   https://doi.org/10.1523/ENEURO.0105-23.2023  

   Ravenscroft, Thomas A.; Jacobs, Ashleigh; Gu, Mingxue; Eberl, Daniel F.; Bellen, Hugo J. (June 2023, eneuro)

   Abstract The fruit flyDrosophila melanogasterhas provided important insights into how sensory information is transduced by transient receptor potential (TRP) channels in the peripheral nervous system (PNS). However, TRP channels alone have not been able to completely model mechanosensitive transduction in mechanoreceptive chordotonal neurons (CNs). Here, we show that, in addition to TRP channels, the sole voltage-gated sodium channel (Na_V) inDrosophila, Para, is localized to the dendrites of CNs. Para is localized to the distal tip of the dendrites in all CNs, from embryos to adults, and is colocalized with the mechanosensitive TRP channels No mechanoreceptor potential C (NompC) and Inactive/Nanchung (Iav/Nan). Para localization also demarcates spike initiation zones (SIZs) in axons and the dendritic localization of Para is indicative of a likely dendritic SIZ in fly CNs. Para is not present in the dendrites of other peripheral sensory neurons. In both multipolar and bipolar neurons in the PNS, Para is present in a proximal region of the axon, comparable to the axonal initial segment (AIS) in vertebrates, 40–60 μm from the soma in multipolar neurons and 20–40 μm in bipolar neurons. Whole-cell reduction ofparaexpression using RNAi in CNs of the adult Johnston’s organ (JO) severely affects sound-evoked potentials (SEPs). However, the duality of Para localization in the CN dendrites and axons identifies a need to develop resources to study compartment-specific roles of proteins that will enable us to better understand Para’s role in mechanosensitive transduction. 

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2. Transcriptional expression changes during compensatory plasticity in the terminal ganglion of the adult cricket Gryllus bimaculatus

   https://doi.org/10.1186/s12864-021-08018-x  

   Prasad, Meera P.; Detchou, Donald K.; Wang, Felicia; Ledwidge, Lisa L.; Kingston, Sarah E.; Wilson Horch, Hadley (December 2021, BMC Genomics)

   Abstract Background Damage to the adult central nervous system often leads to long-term disruptions in function due to the limited capacity for neurological recovery. The central nervous system of the Mediterranean field cricket, Gryllus bimaculatus , shows an unusual capacity for compensatory plasticity, most obviously in the auditory system and the cercal escape system. In both systems, unilateral sensory disruption leads the central circuitry to compensate by forming and/or strengthening connections with the contralateral sensory organ. While this compensatory plasticity in the auditory system relies on robust dendritic sprouting and novel synapse formation, the compensatory plasticity in the cercal escape circuitry shows little obvious dendritic sprouting and instead may rely on shifts in excitatory and inhibitory synaptic strength. Results In order to better understand what types of molecular pathways might underlie this compensatory shift in the cercal system, we used a multiple k-mer approach to assemble a terminal ganglion transcriptome that included ganglia collected one, three, and 7 days after unilateral cercal ablation in adult, male animals. We performed differential expression analysis using EdgeR and DESeq2 and examined Gene Ontologies to identify candidates potentially involved in this plasticity. Enriched GO terms included those related to the ubiquitin-proteosome protein degradation system, chromatin-mediated transcriptional pathways, and the GTPase-related signaling system. Conclusion Further exploration of these GO terms will provide a clearer picture of the processes involved in compensatory recovery of the cercal escape system in the cricket and can be compared and contrasted with the distinct pathways that have been identified upon deafferentation of the auditory system in this same animal. 

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3. Adaptive load feedback robustly signals force dynamics in robotic model of Carausius morosus stepping

   https://doi.org/10.3389/fnbot.2023.1125171  

   Zyhowski, William P.; Zill, Sasha N.; Szczecinski, Nicholas S. (January 2023, Frontiers in Neurorobotics)

   Animals utilize a number of neuronal systems to produce locomotion. One type of sensory organ that contributes in insects is the campaniform sensillum (CS) that measures the load on their legs. Groups of the receptors are found on high stress regions of the leg exoskeleton and they have significant effects in adapting walking behavior. Recording from these sensors in freely moving animals is limited by technical constraints. To better understand the load feedback signaled by CS to the nervous system, we have constructed a dynamically scaled robotic model of the Carausius morosus stick insect middle leg. The leg steps on a treadmill and supports weight during stance to simulate body weight. Strain gauges were mounted in the same positions and orientations as four key CS groups (Groups 3, 4, 6B, and 6A). Continuous data from the strain gauges were processed through a previously published dynamic computational model of CS discharge. Our experiments suggest that under different stepping conditions (e.g., changing “body” weight, phasic load stimuli, slipping foot), the CS sensory discharge robustly signals increases in force, such as at the beginning of stance, and decreases in force, such as at the end of stance or when the foot slips. Such signals would be crucial for an insect or robot to maintain intra- and inter-leg coordination while walking over extreme terrain. 

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4. A Normative Theory for Causal Inference and Bayes Factor Computation in Neural Circuits

   Zhang, Wenhao; Wu, Si; Doiron, Brent; Lee, Tai Sing (January 2019, Advances in neural information processing systems)

   This study provides a normative theory for how Bayesian causal inference can be implemented in neural circuits. In both cognitive processes such as causal reasoning and perceptual inference such as cue integration, the nervous systems need to choose different models representing the underlying causal structures when making inferences on external stimuli. In multisensory processing, for example, the nervous system has to choose whether to integrate or segregate inputs from different sensory modalities to infer the sensory stimuli, based on whether the inputs are from the same or different sources. Making this choice is a model selection problem requiring the computation of Bayes factor, the ratio of likelihoods between the integration and the segregation models. In this paper, we consider the causal inference in multisensory processing and propose a novel generative model based on neural population code that takes into account both stimulus feature and stimulus reliability in the inference. In the case of circular variables such as heading direction, our normative theory yields an analytical solution for computing the Bayes factor, with a clear geometric interpretation, which can be implemented by simple additive mechanisms with neural population code. Numerical simulation shows that the tunings of the neurons computing Bayes factor are consistent with the "opposite neurons" discovered in dorsal medial superior temporal (MSTd) and the ventral intraparietal (VIP) areas for visual-vestibular processing. This study illuminates a potential neural mechanism for causal inference in the brain. 

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5. Investigating the role of low level reinforcement reflex loops in insect locomotion

   https://doi.org/10.1088/1748-3190/ac28ea  

   Goldsmith, C A; Quinn, R D; Szczecinski, N S (October 2021, Bioinspiration & Biomimetics)

   Abstract Insects are highly capable walkers, but many questions remain regarding how the insect nervous system controls locomotion. One particular question is how information is communicated between the ‘lower level’ ventral nerve cord (VNC) and the ‘higher level’ head ganglia to facilitate control. In this work, we seek to explore this question by investigating how systems traditionally described as ‘positive feedback’ may initiate and maintain stepping in the VNC with limited information exchanged between lower and higher level centers. We focus on the ‘reflex reversal’ of the stick insect femur-tibia joint between a resistance reflex (RR) and an active reaction in response to joint flexion, as well as the activation of populations of descending dorsal median unpaired (desDUM) neurons from limb strain as our primary reflex loops. We present the development of a neuromechanical model of the stick insect ( Carausius morosus ) femur-tibia (FTi) and coxa-trochanter joint control networks ‘in-the-loop’ with a physical robotic limb. The control network generates motor commands for the robotic limb, whose motion and forces generate sensory feedback for the network. We based our network architecture on the anatomy of the non-spiking interneuron joint control network that controls the FTi joint, extrapolated network connectivity based on known muscle responses, and previously developed mechanisms to produce ‘sideways stepping’. Previous studies hypothesized that RR is enacted by selective inhibition of sensory afferents from the femoral chordotonal organ, but no study has tested this hypothesis with a model of an intact limb. We found that inhibiting the network’s flexion position and velocity afferents generated a reflex reversal in the robot limb’s FTi joint. We also explored the intact network’s ability to sustain steady locomotion on our test limb. Our results suggested that the reflex reversal and limb strain reinforcement mechanisms are both necessary but individually insufficient to produce and maintain rhythmic stepping in the limb, which can be initiated or halted by brief, transient descending signals. Removing portions of this feedback loop or creating a large enough disruption can halt stepping independent of the higher-level centers. We conclude by discussing why the nervous system might control motor output in this manner, as well as how to apply these findings to generalized nervous system understanding and improved robotic control. 

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