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1. Synapses without tension fail to fire in an in vitro network of hippocampal neurons

   https://doi.org/10.1073/pnas.2311995120  

   Joy, Md Saddam; Nall, Duncan L.; Emon, Bashar; Lee, Ki Yun; Barishman, Alexandra; Ahmed, Movviz; Rahman, Saeedur; Selvin, Paul R.; Saif, M. Taher (December 2023, Proceedings of the National Academy of Sciences)

   Neurons in the brain communicate with each other at their synapses. It has long been understood that this communication occurs through biochemical processes. Here, we reveal that mechanical tension in neurons is essential for communication. Using in vitro rat hippocampal neurons, we find that 1) neurons become tout/tensed after forming synapses resulting in a contractile neural network, and 2) without this contractility, neurons fail to fire. To measure time evolution of network contractility in 3D (not 2D) extracellular matrix, we developed an ultrasensitive force sensor with 1 nN resolution. We employed Multi-Electrode Array and iGluSnFR, a glutamate sensor, to quantify neuronal firing at the network and at the single synapse scale, respectively. When neuron contractility is relaxed, both techniques show significantly reduced firing. Firing resumes when contractility is restored. This finding highlights the essential contribution of neural contractility in fundamental brain functions and has implications for our understanding of neural physiology. 

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2. A computational neural model that incorporates both intrinsic dynamics and sensory feedback in the Aplysia feeding network

   https://doi.org/10.1007/s00422-024-00991-2  

   Li, Yanjun; Webster-Wood, Victoria A; Gill, Jeffrey P; Sutton, Gregory P; Chiel, Hillel J; Quinn, Roger D (May 2024, Biological Cybernetics)

   Abstract Studying the nervous system underlying animal motor control can shed light on how animals can adapt flexibly to a changing environment. We focus on the neural basis of feeding control inAplysia californica. Using the Synthetic Nervous System framework, we developed a model ofAplysiafeeding neural circuitry that balances neurophysiological plausibility and computational complexity. The circuitry includes neurons, synapses, and feedback pathways identified in existing literature. We organized the neurons into three layers and five subnetworks according to their functional roles. Simulation results demonstrate that the circuitry model can capture the intrinsic dynamics at neuronal and network levels. When combined with a simplified peripheral biomechanical model, it is sufficient to mediate three animal-like feeding behaviors (biting, swallowing, and rejection). The kinematic, dynamic, and neural responses of the model also share similar features with animal data. These results emphasize the functional roles of sensory feedback during feeding. 

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3. Uncovering the electrical synapse proteome in retinal neurons via in vivo proximity labeling

   https://doi.org/10.1101/2024.11.26.625481  

   Tetenborg, Stephan; Shihabeddin, Eyad; Kumar, Elizebeth_Olive_Akansha Manoj; Sigulinsky, Crystal L; Dedek, Karin; Lin, Ya-Ping; Echeverry, Fabio A; Hoff, Hannah; Pereda, Alberto E; Jones, Bryan W; et al (November 2024, bioRxiv)

   Abstract Electrical synapses formed by Connexin 36 (Cx36) serve as a fast means for communication in the nervous systems. Only little is known about the protein complexes that constitute these synapses. In the present study, we applied different BioID strategies to screen the interactomes of Connexin 36 the major neuronal connexin and its zebrafish orthologue Cx35b in retinal neurons. Forin vivoproximity labeling in mice, we took advantage of the Cx36-EGFP strain and expressed a GFP-nanobody-TurboID fusion construct selectively in AII amacrine cells. Forin vivoBioID in zebrafish, we generated a transgenic line expressing a Cx35b-TurboID fusion under control of the Cx35b promoter. Both strategies allowed us to capture a plethora of molecules that were associated with electrical synapses and showed a high degree of evolutionary conservation in the proteomes of both species. Besides known interactors of Cx36 such as ZO-1 and ZO-2 we have identified more than 50 new proteins, such as scaffold proteins, adhesion molecules and regulators of the cytoskeleton. We further determined the subcellular localization of these proteins in AII amacrine and tested potential binding interactions with Cx36. Of note, we identified signal induced proliferation associated 1 like 3 (SIPA1L3), a protein that has been implicated in cell junction formation and cell polarity as a new scaffold of electrical synapses. Interestingly, SIPA1L3 was able to interact with ZO-1, ZO-2 and Cx36, suggesting a pivotal role in electrical synapse function. In summary, our study provides a first detailed view of the electrical synapse proteome in retinal neurons. 

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4. Optimizing Initial State of Detector Sensors in Quantum Sensor Networks

   https://doi.org/10.1145/3655028  

   Zhan, Caitao; Gupta, Himanshu; Hillery, Mark (June 2024, ACM Transactions on Quantum Computing)

   none (Ed.)

   In this article, we consider a network of quantum sensors, where each sensor is a qubit detector that “fires,” i.e., its state changes when an event occurs close by. The change in state due to the firing of a detector is given by a unitary operator, which is the same for all sensors in the network. Such a network of detectors can be used to localize an event, using a protocol to determine the firing sensor, presumably the one closest to the event. The determination of the firing sensor can be posed as aQuantum State Discriminationproblem, which incurs a probability of error depending on the initial state and the measurement operators used. In this article, we address the problem of determining the optimal initial global state of a network of detectors that incur a minimum probability of error in determining the firing sensor. For this problem, we derive necessary and sufficient conditions for the existence of an initial state that allows for perfect discrimination, i.e., zero probability of error. Using insights from this result, we derive a conjectured optimal solution for the initial state, provide a pathway to prove the conjecture, and validate the conjecture empirically using multiple search heuristics that seem to perform near-optimally. 

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5. HisCl1 regulates gustatory habituation in sweet taste neurons and mediates sugar ingestion in Drosophila

   https://doi.org/10.1101/2024.05.06.592591  

   Kim, Haein; Zhong, Ziqing; Cui, Xinyue; Sung, Hayeon; Agrawal, Naman; Jiang, Tianxing; Dus, Monica; Yapici, Nilay (May 2024, bioRxiv)

   SUMMARY Similar to other animals, the fly,Drosophila melanogaster, reduces its responsiveness to tastants with repeated exposure, a phenomenon called gustatory habituation. Previous studies have focused on the circuit basis of gustatory habituation in the fly chemosensory system^1,2. However, gustatory neurons reduce their firing rate during repeated stimulation³, suggesting that cell-autonomous mechanisms also contribute to habituation. Here, we used deep learning-based pose estimation and optogenetic stimulation to demonstrate that continuous activation of sweet taste neurons causes gustatory habituation in flies. We conducted a transgenic RNAi screen to identify genes involved in this process and found that knocking downHistamine-gated chloride channel subunit 1(HisCl1)in the sweet taste neurons significantly reduced gustatory habituation. Anatomical analysis showed thatHisCl1is expressed in the sweet taste neurons of various chemosensory organs. Using single sensilla electrophysiology, we showed that sweet taste neurons reduced their firing rate with prolonged exposure to sucrose. Knocking downHisCl1in sweet taste neurons suppressed gustatory habituation by reducing the spike frequency adaptation observed in these neurons during high-concentration sucrose stimulation. Finally, we showed that flies lackingHisCl1in sweet taste neurons increased their consumption of high-concentration sucrose solution at their first meal bout compared to control flies. Together, our results demonstrate that HisCl1 tunes spike frequency adaptation in sweet taste neurons and contributes to gustatory habituation and food intake regulation in flies. Since HisCl1 is highly conserved across many dipteran and hymenopteran species, our findings open a new direction in studying insect gustatory habituation. 

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