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1. Switching neuron contributions to second network activity

   https://doi.org/10.1152/jn.00373.2023  

   Fahoum, Savanna-Rae H.; Blitz, Dawn M. (February 2024, Journal of Neurophysiology)

   Network flexibility is important for adaptable behaviors. This includes neuronal switching, where neurons alter their network participation, including changing from single- to dual-network activity. Understanding the implications of neuronal switching requires determining how a switching neuron interacts with each of its networks. Here, we tested 1) whether “home” and second networks, operating via divergent rhythm generation mechanisms, regulate a switching neuron, and 2) if a switching neuron, recruited via modulation of intrinsic properties, contributes to rhythm or pattern generation in a new network. Small, well-characterized feeding-related networks (pyloric, ~1 Hz; gastric mill, ~0.1 Hz) and identified modulatory inputs make the isolated crab (Cancer borealis) stomatogastric nervous system (STNS) a useful model to study neuronal switching. In particular, the neuropeptide Gly1-SIFamide switches the lateral posterior gastric (LPG) neuron (2 copies) from pyloric-only to dual-frequency pyloric/gastric mill (fast/slow) activity via modulation of LPG intrinsic properties. Using current injections to manipulate neuronal activity, we found that gastric mill, but not pyloric, network neurons regulated the intrinsically generated LPG slow bursting. Conversely, selective elimination of LPG from both networks using photoinactivation revealed that LPG regulated gastric mill neuron firing frequencies but was not necessary for gastric mill rhythm generation or coordination. However, LPG alone was sufficient to produce a distinct pattern of network coordination. Thus, modulated intrinsic properties underlying dual-network participation may constrain which networks can regulate switching neuron activity. Further, recruitment via intrinsic properties may occur in modulatory states where it is important for the switching neuron to actively contribute to network output. 

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2. Multiple intrinsic membrane properties are modulated in a switch from single- to dual-network activity

   https://doi.org/10.1152/jn.00337.2022  

   Snyder, Ryan R.; Blitz, Dawn M. (November 2022, Journal of Neurophysiology)

   Neural network flexibility includes changes in neuronal participation between networks, such as the switching of neurons between single- and dual-network activity. We previously identified a neuron that is recruited to burst in time with an additional network via modulation of its intrinsic membrane properties, instead of being recruited synaptically into the second network. However, the modulated intrinsic properties were not determined. Here, we use small networks in the Jonah crab ( Cancer borealis) stomatogastric nervous system (STNS) to examine modulation of intrinsic properties underlying neuropeptide (Gly 1 -SIFamide)-elicited neuronal switching. The lateral posterior gastric neuron (LPG) switches from exclusive participation in the fast pyloric (∼1 Hz) network, due to electrical coupling, to dual-network activity that includes periodic escapes from the fast rhythm via intrinsically generated oscillations at the slower gastric mill network frequency (∼0.1 Hz). We isolated LPG from both networks by pharmacology and hyperpolarizing current injection. Gly 1 -SIFamide increased LPG intrinsic excitability and rebound from inhibition and decreased spike frequency adaptation, which can all contribute to intrinsic bursting. Using ion substitution and channel blockers, we found that a hyperpolarization-activated current, a persistent sodium current, and calcium or calcium-related current(s) appear to be primary contributors to Gly 1 -SIFamide-elicited LPG intrinsic bursting. However, this intrinsic bursting was more sensitive to blocking currents when LPG received rhythmic electrical coupling input from the fast network than in the isolated condition. Overall, a switch from single- to dual-network activity can involve modulation of multiple intrinsic properties, while synaptic input from a second network can shape the contributions of these properties. NEW & NOTEWORTHY Neuropeptide-elicited intrinsic bursting was recently determined to switch a neuron from single- to dual-network participation. Here we identified multiple intrinsic properties modulated in the dual-network state and candidate ion channels underlying the intrinsic bursting. Bursting at the second network frequency was more sensitive to blocking currents in the dual-network state than when neurons were synaptically isolated from their home network. Thus, synaptic input can shape the contributions of modulated intrinsic properties underlying dual-network activity. 

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3. Serotonin Strengthens a Developing Glutamatergic Synapse through a PI3K-Dependent Mechanism

   https://doi.org/10.1523/JNEUROSCI.1260-23.2023  

   Udoh, Uwemedimo G.; Bruno, John R.; Osborn, Paige O.; Pratt, Kara G. (January 2024, The Journal of Neuroscience)

   It is well established that, during neural circuit development, glutamatergic synapses become strengthened via NMDA receptor (NMDAR)-dependent upregulation of AMPA receptor (AMPAR)-mediated currents. In addition, however, it is known that the neuromodulator serotonin is present throughout most regions of the vertebrate brain while synapses are forming and being shaped by activity-dependent processes. This suggests that serotonin may modulate or contribute to these processes. Here, we investigate the role of serotonin in the developing retinotectal projection of theXenopustadpole. We altered endogenous serotonin transmission in stage 48/49 (∼10–21 days postfertilization)Xenopustadpoles and then carried out a set of whole-cell electrophysiological recordings from tectal neurons to assess retinotectal synaptic transmission. Because tadpole sex is indeterminate at these early stages of development, experimental groups were composed of randomly chosen tadpoles. We found that pharmacologically enhancing and reducing serotonin transmission for 24 h up- and downregulates, respectively, AMPAR-mediated currents at individual retinotectal synapses. Inhibiting 5-HT₂receptors also significantly weakened AMPAR-mediated currents and abolished the synapse strengthening effect seen with enhanced serotonin transmission, indicating a 5-HT₂receptor–dependent effect. We also determine that the serotonin-dependent upregulation of synaptic AMPAR currents was mediated via an NMDAR-independent, PI3K-dependent mechanism. Altogether, these findings indicate that serotonin regulates AMPAR currents at developing synapses independent of NMDA transmission, which may explain its role as an enabler of activity-dependent plasticity. 

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4. Minimal circuit motifs for second-order conditioning in the insect mushroom body

   https://doi.org/10.3389/fphys.2023.1326307  

   Jürgensen, Anna-Maria; Schmitt, Felix Johannes; Nawrot, Martin Paul (January 2024, Frontiers in Physiology)

   In well-established first-order conditioning experiments, the concurrence of a sensory cue with reinforcement forms an association, allowing the cue to predict future reinforcement. In the insect mushroom body, a brain region central to learning and memory, such associations are encoded in the synapses between its intrinsic and output neurons. This process is mediated by the activity of dopaminergic neurons that encode reinforcement signals. In second-order conditioning, a new sensory cue is paired with an already established one that presumably activates dopaminergic neurons due to its predictive power of the reinforcement. We explored minimal circuit motifs in the mushroom body for their ability to support second-order conditioning using mechanistic models. We found that dopaminergic neurons can either be activated directly by the mushroom body’s intrinsic neurons or via feedback from the output neurons via several pathways. We demonstrated that the circuit motifs differ in their computational efficiency and robustness. Beyond previous research, we suggest an additional motif that relies on feedforward input of the mushroom body intrinsic neurons to dopaminergic neurons as a promising candidate for experimental evaluation. It differentiates well between trained and novel stimuli, demonstrating robust performance across a range of model parameters. 

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5. Astrocytes as a mechanism for contextually-guided network dynamics and function

   Gong, L; Pasqualetti, F; Papuan, T; Ching, S (May 2024, PLOS computational biology)

   Astrocytes are a ubiquitous and enigmatic type of non-neuronal cell and are found in the brain of all vertebrates. While traditionally viewed as being supportive of neurons, it is increasingly recognized that astrocytes play a more direct and active role in brain function and neural computation. On account of their sensitivity to a host of physiological covariates and ability to modulate neuronal activity and connectivity on slower time scales, astrocytes may be particularly well poised to modulate the dynamics of neural circuits in functionally salient ways. In the current paper, we seek to capture these features via actionable abstractions within computational models of neuron-astrocyte interaction. Specifically, we engage how nested feedback loops of neuron-astrocyte interaction, acting over separated time-scales, may endow astrocytes with the capability to enable learning in context-dependent settings, where fluctuations in task parameters may occur much more slowly than within-task requirements. We pose a general model of neuron-synapse-astrocyte interaction and use formal analysis to characterize how astrocytic modulation may constitute a form of meta-plasticity, altering the ways in which synapses and neurons adapt as a function of time. We then embed this model in a bandit-based reinforcement learning task environment, and show how the presence of time-scale separated astrocytic modulation enables learning over multiple fluctuating contexts. Indeed, these networks learn far more reliably compared to dynamically homogeneous networks and conventional non-network-based bandit algorithms. Our results fuel the notion that neuron-astrocyte interactions in the brain benefit learning over different time-scales and the conveyance of task-relevant contextual information onto circuit dynamics. 

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