Frontiers in Neural Circuits

New tools in optogenetics and molecular biology have culminated in recent studies which mark immediate-early gene (IEG)-expressing neurons as memory traces or engrams. Although the activity-dependent expression of IEGs has been successfully utilised to label memory traces, their roles in engram specification is incompletely understood. Outstanding questions remain as to whether expression of IEGs can interplay with network properties such as functional connectivity and also if neurons expressing different IEGs are functionally distinct. We investigated the expression of Arc and c-Fos, two commonly utilised IEGs in memory engram specification, in cultured hippocampal neurons. After pharmacological induction of long-term potentiation (LTP) in the network, we noted an emergent network property of refinement in functional connectivity between neurons, characterized by a global down-regulation of network connectivity, together with strengthening of specific connections. Subsequently, we show that Arc expression correlates with the effects of network refinement, with Arc-positive neurons being selectively strengthened. Arc positive neurons were also found to be located in closer physical proximity to each other in the network. While the expression pattern of IEGs c-Fos and Arc strongly overlaps, Arc was more selectively expressed than c-Fos. These IEGs also act together in coding information about connection strength pruning. These results demonstrate important links between IEG expression and network connectivity, which serve to bridge the gap between cellular correlates and network effects in learning and memory.

Fundamental neural mechanisms such as activity dependent Hebbian and homeostatic neuroplasticity are driven by balanced excitatory - inhibitory synaptic transmission, and work in tandem to coordinate and regulate complex neural network dynamics in both healthy and perturbed conditions. These neuroplasticity processes shape neural network activity, as well as structural and functional aspects of network organization, information transmission and processing. While crucial for all aspects of network function, understanding how the brain utilizes plasticity mechanisms to retain or regain function during and after perturbation is often challenging. This is because these processes occur at varying spatiotemporal scales simultaneously across diverse circuits and brain regions and are thus highly complicated to distinguish from other underlying mechanisms. However, neuroplasticity and self-organizing properties of the brain are largely conserved in in vitro biological neural networks, and as such, these networks enable us to investigate both structural and functional plasticity responses to perturbation networks at the micro and mesoscale level. In this study, we selectively silenced excitatory synaptic transmission in in vitro neural networks to investigate the impact of the perturbation on structural and functional network organization and resilience. Our results demonstrate that selective inhibition of excitatory transmission leads to transient de-clustering of modular structure, increased path length and degree in perturbed networks. These changes indicate a transient loss of network efficiency; with the network subsequently reorganizing to a state of increased clustering and short path lengths following recovery. These findings highlight the remarkable capacity of neural networks to reconfigure their functional organization following perturbation. The ability to detect and decode such processes as they evolve highlights the robustness of our models to investigate certain dynamic network properties that are often not accessible by in vivo methods.

Neuronal network resilience, the ability of brain circuits to maintain and recover functional connectivity following perturbation, is fundamental to cognitive stability and adaptability. Using human cerebral organoids and multi-electrode arrays (MEAs), we investigated how mechanical stress disrupts network stability and identified key mechanisms regulating recovery. Blast overpressure exposure destabilized small-world network (SWN) organization, increasing network fragmentation and reducing overall integration. Merged SWNs, which exhibit high connectivity, were particularly vulnerable, while fragmented and single SWNs persisted for extended periods, indicating a shift toward less resilient network states. Optogenetic stimulation promoted network recovery, reducing the persistence of fragile states and facilitating transitions toward more cohesive network structures. GABAergic signaling emerged as a critical regulator of network resilience, with pharmacological inhibition exacerbating fragmentation and impairing network reorganization. These findings reveal fundamental principles of how inhibitory networks regulate circuit stability, with implications extending beyond mechanical injury to broader conditions characterized by network dysfunction, including anxiety, depression, PTSD, and neurodegenerative disorders. Understanding the mechanisms governing network adaptation and resilience could inform new therapeutic strategies aimed at stabilizing disrupted neural circuits across a range of neurological conditions. Significance statementNeuronal networks must dynamically adapt to maintain function in the face of disruption, yet the mechanisms that govern network resilience remain poorly understood. Using human cerebral organoids, we demonstrate that primary blast overpressure destabilizes small-world networks, increasing fragmentation and reducing overall connectivity. Critically, GABAergic signaling emerges as a key stabilizer, with inhibition of GABA receptors amplifying network fragmentation and impairing recovery. These findings provide fundamental insight into how neural circuits resist and recover from mechanical stress, bridging gaps between basic neuroscience, injury pathology, and potential therapeutic interventions. By identifying inhibitory signaling as a regulator of network resilience, our work informs not only traumatic brain injury treatment strategies but also broader efforts to restore functional connectivity in neurological disorders, from epilepsy to neurodegeneration.

Thalamocortical circuits play a fundamental role in cognitive functions, and neural synchronization, with disruptions implicated in disorders. Here, we investigated the neural dynamics of thalamocortical connectivity using computational modeling of rodent and primate thalamocortical loops. We incorporated distinct projections and varying network configurations and examined their impact on circuit synchrony, spiking patterns, and sleep spindle generation. Circuits included distinct core and matrix thalamocortical projections, with core pathways providing focal, driving input to middle cortical layers, while matrix pathways mediate widespread, modulatory signaling across superficial layers, and the presence of thalamic interneurons, which are scarce in rodents but comprise up to a third of the thalamic neurons in primates. In our simulations, these distinctions produced clear species-and loop architecture-dependent effects: rodent circuits were markedly more sensitive to parameter changes in core and matrix thalamocortical connectivity strength, while primate circuits maintained relatively stable spatiotemporal patterns across parameter variations, exhibiting greater stability and synchrony. Sleep spindle analysis likewise revealed species differences. Overall, across all thalamocortical configurations, rodent simulations produced spindles with greater spatiotemporal variability, showing irregular event structure and timing. In contrast, primate spindles were more uniform and coherent, with clearer and more consistent organization across neurons and time. These findings provide insights into species-specific differences in thalamocortical dynamics and have implications for modeling sensory and cognitive disruptions in disorders such as autism and schizophrenia. By incorporating distinct configurations, and interspecies differences, our model contributes to understanding how thalamocortical dysregulation may differentially impact spindle generation, network synchrony, and information processing across species.

AO_SCPLOWBSTRACTC_SCPLOWThe salamander is a key limbed vertebrate from which many major scientific questions can be addressed in the fields of motor control, evolutionary biology, and regeneration biology. An important gap of knowledge is the description of the electrophysiological properties of the neurons constituting their central nervous system. To our knowledge, some patch-clamp electrophysiological recordings were done in the spinal cord and recently in hindbrain slices, but not in any higher brain region. Here, we present a method to obtain patch-clamp recordings in slices of the telencephalon, diencephalon and rhombencephalon of salamanders. The method includes dissection of the brain, brain slice preparation, visual identification of neurons and patch-clamp recordings. We provide single cell recordings in the rhombencephalon, diencephalon and telencephalon of salamanders. This method should open new avenues to dissect the operation of salamander brain circuits at the cellular level. HO_SCPLOWIGHLIGHTSC_SCPLOW- Salamander brain slices of telencephalon, diencephalon, and rhombencephalon - Patch-clamp recordings in salamander brain slices - The salamander as a model to decipher tetrapod neural microcircuits

Levy flights (LF), a concept originating in statistical physics, describe random walks in which the step lengths follow a heavy-tailed probability distribution, often a power law. Unlike Brownian motion, where step lengths are constrained within a narrow range, LF are characterized by the coexistence of many short steps interspersed with occasional long jumps. Applying advanced computational techniques, we looked for LF-like patterns in high-resolution histological images of Macaca mulatta (Rhesus macaque) cortical area 4 from BrainMaps.org. Step-length distributions, derived from pairwise distances between neuronal somata, exhibited heavy-tailed behavior consistent with power-law models across all samples. Maximum likelihood estimation of power-law exponents ( values: 0.87-1.08) strongly supported the heavy-tailed nature of these patterns, showing a better fit with power-law models compared to exponential or normal distributions. Connectivity analyses revealed a dual organizational structure within cortical layers: densely interconnected local clusters coexisting with sparse long-range connections. k-Nearest neighbors graphs demonstrated small-world network properties, with average clustering coefficients ranging from 0.622 to 0.630 across samples. This consistent structural organization aligns with LF principles, wherein local processing is optimized alongside global integration for efficiency and functionality. The implications extend to developmental biology, as the emergence of LF-like patterns likely reflects intrinsic self-organizing processes during embryonic and fetal development. This LF-like organization provides a natural framework for designing artificial networks that optimize performance in tasks requiring both localized specialization and global integration. Moreover, understanding the developmental origins of these patterns could guide strategies for neural repair and regeneration in stroke or neurodegenerative diseases.

Cerebellar function, known to be important for motor learning and motor coordination, is mediated by efferent neurons that project to diverse motor areas. To understand cerebellar function, it is imperative to study how these efferent neurons integrate inputs from the principal neurons of the cerebellar cortex, the inhibitory Purkinje neurons (PNs). In zebrafish, PNs are bistable and we show here that bistability influences spike synchrony among PNs. Bistability also alters spike correlation with motor bouts. We asked how PN population synchrony influences Eurydendroid cells (ECs), which are postsynaptic targets of PNs and are the cerebellar efferent cells in zebrafish. Using optogenetics, we artificially modulated population synchrony of PNs over millisecond time scales and showed that under conditions of high synchrony, EC firing is briefly suppressed and entrained by PN spiking. However, the magnitude of such modulation is relatively small and indicates a strong combined influence of other synaptic inputs on EC spiking. Key PointsO_LICerebellar Purkinje neurons (PN) in larval zebrafish alter simple spike correlations with each other based on cellular state. C_LIO_LIThey also alter simple spike correlations with motor bouts as a function of state. C_LIO_LIWe altered PN population synchrony in a graded manner using optogenetics. C_LIO_LIPN targets are cerebellar efferent neurons, which in teleosts are called eurydendroid cells. C_LIO_LIWhen PN population is firing with high synchrony, eurydendroid cells are entrained better than when the PN input is asynchronous. C_LIO_LIThis can explain how PNs use bistability to modulate their influence on cerebellar output and ultimately, motor behavior. C_LI

Recent studies have shown that symbiotic bacteria can have drastic effects on host neurobiology, but few simple, accessible models currently exist in which to study these interactions. Hawaiian bobtail squid (Euprymna scolopes) participate in a binary symbiosis with the bacterium Vibrio fischeri, a population of which resides in a specialized hindgut-derived organ called the light organ. Upon colonization by V. fischeri, the light organ undergoes transcriptional changes that suggest neurons are impacted by the initiation of symbiosis, but the nascent light organs innervation has remained uncharacterized. Here, we show that the light organ-associated nervous system (LONS) in hatchling E. scolopes is a remarkably complex segment of the peripheral nervous system. The LONS is largely plexiform and originates from two primary nerves connected by a local commissure. The abundance of synapsin-like immunoreactivity (-lir) indicates that the lobe plexus is highly interconnected. We also highlight a small number of serotonin-lir neurites that innervate the anterior appendages whose developmental fate may be directly affected by symbiont-driven light organ morphogenesis. Finally, we present evidence that a limited but diverse population of neurons reside within the light organ and are often located near internal symbiont-interacting structures. This description of the E. scolopes LONS serves to provide a foundation from which to investigate how beneficial bacterial symbionts affect host peripheral neurobiology in a tractable model system.

Glutamatergic reticulospinal neurons in the gigantocellular reticular nucleus (GRN) of the medullary reticular formation can function as command neurons, transmitting motor commands to spinal cord circuits. Recent advances in our understanding of this neuron-dense region have been facilitated by the discovery of expression of the transcriptional regulator, Chx10, in excitatory reticulospinal neurons. Here, we address the capacity of local circuitry in the GRN to contribute to reticulospinal output. We define two sub-populations of Chx10-expressing neurons in this region, based on distinct electrophysiological properties and somata size (small and large), and show that these correspond to local interneurons and reticulospinal neurons, respectively. Using focal release of caged-glutamate combined with patch clamp recordings, we demonstrated that Chx10 neurons form microcircuits in which the Chx10 interneurons project to and facilitate the firing of Chx10 reticulospinal neurons. We discuss the implications of these microcircuits in terms of movement selection. SIGNIFICANCE STATEMENTReticulospinal neurons in the medullary reticular formation play a key role in movement. The transcriptional regulator Chx10 defines a population of glutamatergic neurons in this region, a proportion of which have been shown to be involved in stopping, steering, and modulating locomotion. While it has been shown that these neurons integrate descending inputs, we asked whether local processing also ultimately contributes to reticulospinal outputs. Here, we define Chx10-expressing medullary reticular formation interneurons and reticulospinal neurons, and demonstrate how the former modulate the output of the latter. The results shed light on the internal organization and microcircuit formation of reticular formation neurons.

Gymnotiform fish emit electric organ discharges (EODs) for both active electroreception and electrocommunication. EOD waveform and rhythm can be modified to cope with diverse environmental challenges. In pulse-type species, EODs are generated by a hierarchical electromotor network controlled by a medullary pacemaker nucleus (PN), which comprises intrinsic pacemaker cells (PM-cells) and projecting relay cells (R-cells). Active electroreception requires the emission of stereotyped EODs, an electromotor output that implies a functional PN configuration in which PM-cells rhythmically time EODs and R-cells transmit coordinated commands to downstream components of the electromotor system. To test whether electrical coupling (EC) between PN neurons supports this functional organization, intrinsic connectivity of the PN in Gymnotus omarorum was examined in brainstem slices using electrophysiology, immunohistochemistry, and dye-coupling analysis. Homotypic connections (PM-PM and R-R) exhibited low-magnitude, bidirectional EC with symmetrical, low-pass filter properties, supporting synchronous yet adaptable pacemaker activity and coordinated descending commands. Heterotypic connections (PM-R) also displayed bidirectional, symmetrical coupling but revealed direction-dependent filtering: an apparent high-pass behavior from PM- to R-cells and a low-pass behavior in the opposite direction. Together with precise PM-to-R discharge timing, direction-dependent filtering suggests a role of PM-cell axons in shaping signal flow. Dye coupling and immunohistochemical evidence further indicate that PN neurons are interconnected via gap junctions, likely formed by connexin 35. Thus, EC-based connectivity endows the PN with crucial functional attributes of its exploration mode of operation while preserving the capacity to organize communication signals under the influence of descending inputs, revealing remarkable functional versatility. Summary statementGap junction-mediated intrinsic connections within the electromotor nucleus of electric fish may sustain the emission of signals essential for sensory sampling as well as those supporting communication.

Heterosynaptic plasticity, along with Hebbian homosynaptic plasticity, is an important mechanism ensuring stable operation of learning neuronal networks. However, whether heterosynaptic plasticity occurs in the whole brain in vivo, and what role(s) in brain function in vivo it could play, remains unclear. Here, we used an optogenetics approach to apply a model of intracellular tetanization, which was established and employed to study heterosynaptic plasticity in brain slices, to study plasticity of response properties of neurons in mouse visual cortex in vivo. We show that optogenetically evoked high-frequency bursts of action potentials (optogenetic tetanization) in principal neurons of the visual cortex induce long-term changes of responses to visual stimuli. Optogenetic tetanization had distinct effects on responses to different stimuli: responses to optimal and orthogonal orientations decreased, response to null direction did not change, and responses to oblique orientations increased. As a result, direction selectivity of the neurons decreased, and orientation tuning became broader. Since optogenetic tetanization was a purely postsynaptic protocol, applied in the absence of sensory stimulation, and thus without association of presynaptic activity with bursts of action potentials, the observed changes were mediated by mechanisms of heterosynaptic plasticity. We conclude that heterosynaptic plasticity can be induced in vivo and propose that it may play important homeostatic roles in operation of neural networks by helping to prevent runaway dynamics of responses to visual stimuli and to keep the tuning of neuronal responses within the range optimized for encoding of multiple features in population activity.

The vast majority of cortical synapses are found in the neuropil which is implicated in multiple and diverse functions underlying brain computation. Unraveling the organizing principles of the cortical neuropil requires an intricate characterization of synaptic connections established by excitatory and inhibitory axon terminals, of intrinsic and extrinsic origin and from ascending projections that govern the function of cortical microcircuits through the release of neuromodulators either through point-to-point chemical synapses or diffuse volume transmission (VT). Even though neuromodulatory release has been studied for almost a century it is still not clear if one modality prevails upon the other. The hindlimb representation of the somatosensory cortex (HLS1) of two-week old Wistar rats has served as a model system to dissect the microcircuitry of neurons and their synaptic connections. In the present study, we quantified the fiber length per cortical volume and the density of varicosities for cholinergic, catecholaminergic and serotonergic neuromodulatory systems in the cortical neuropil using immunocytochemical staining and stereological techniques. Acquired data were integrated into a novel computational framework to reconcile the specific modalities and predict the effects of neuromodulatory release in shaping neocortical network activity. We predict that acetylcholine (ACh), dopamine (DA), serotonin (5-HT) release desynchronizes cortical activity by inhibiting slow oscillations (delta range), and that 5-HT triggers faster oscillations (theta). Moreover, we found that high levels (>40%) of neuromodulatory VT are sufficient to induce network desynchronization, but also that combining volume release with synaptic inputs leads to more robust and stable effects, meaning that lower levels of VT are needed to achieve the same outcome (10%).

Neuronal populations connected by gap junctions can be revealed via dye coupling of small molecules like neurobiotin and lucifer yellow. However, the extent of dye diffusion between neurons varies with connexin subtype, loading method, and neuromodulation. Due to the increasing availability of GCaMP transgenic animals, we explore the possibility of revealing gap junctional coupling using Ca2+ imaging in the Xenopus laevis tadpole motor system. Reliable axo-axonal electrical coupling was previously found in excitatory descending interneurons (dINs) using paired recordings but not with neurobiotin dye coupling. Here, we made whole-cell patch-clamp recordings with Ca2+-supplemented intracellular solution to load Ca2+ into GCaMP6s-expressing neurons, followed by Ca2+ imaging to detect potential Ca2+ diffusion across coupled neurons. Successful membrane breakthroughs led to transient fluorescence increases in the patched neuron. However, increasing the Ca2+ concentration promoted membrane resealing and rapid loss of whole-cell recordings. Regardless of recording duration, loading-triggered fluorescence only lasted up to three minutes, suggesting rapid Ca2+ clearance. Pharmacologically blocking sarcoplasmic /endoplasmic reticulum Ca2+-ATPases and plasma membrane Na+/Ca2+ exchangers did not prolong fluorescence, although sustained fluorescence was achieved with positive current injections. Counter to our expectations, fluorescence increases in Ca2+-loaded dINs did not spread to neighboring dINs. Robust intracellular Ca2+ regulation mechanisms, membrane resealing, and long dIN axons likely hindered intercellular Ca2+ diffusion. Therefore, this approach is not appropriate for revealing electrical coupling within this system.

Multi-electrode recording of neural activity in cultures offer opportunities for understanding how the structure of a network gives rise to function. Although it is hypothesized that network size is critical for determining the dynamics of activity, this relationship in human neural cultures remains largely unexplored. By applying new methods for analyzing neural activity to human iPSC derived cultures at either low-densities or high-densities, we uncovered the significant impacts that neuron number has on the individual neurophysiological properties of cells (such as firing rates), the collective behavior of the networks these cultures formed (as measured by entropy), and the relationship between the two. As a result, simply changing the densities of neurons generated dynamics and network behavior that differed not just in degree, but in kind. Beyond revealing the relationship between network structure and function, our findings provide a novel analytical framework to study diseases where network level activity is affected.

Distinct computations are performed at multiple brain regions during encoding of the spatial environments. Neural representations in the hippocampal, entorhinal and head direction (HD) networks during spatial navigation have been clearly documented, while the representational properties of the Subicular Complex (SC) network is rather unexplored, even though it has extensive anatomical connections with various brain regions involved in spatial information processing. Here, we report a global cue controlled highly coherent representation of the cue-conflict environment in the SC network, along with strong coupling between HD cells and Spatial cells. We propose that the attractor dynamics in the SC network might play a critical role in orientation of the spatial representations, thus providing a "reference map" of the environment for further processing at other networks.

Understanding how minimal perturbations influence cortical network dynamics remains a central challenge in neural engineering. While single-cell stimulation has been shown to affect population activity, the resulting variability is often treated as noise rather than an informative feature of network behavior. Here, we investigated how single-cell stimulation reflects heterogeneous modulation of neuronal recruitment and the extent to which these effects can be explained by the functional state of the stimulated cell. For this, we combined single-cell optogenetic stimulation with wide-field calcium imaging in cortical cultures. In each network, a single stimulation event was induced, and subsequent alterations in stimulus-coupled recruitment, synchrony, and pairwise correlations were quantified. Additionally, we evaluated whether the baseline functional state of the stimulated neurons, including their event activity levels and Pearson correlation structures, were linked to the observed network responses. Single cell stimulation induced effects were transient, and the network dynamics recovered over a few seconds within the responder population. Importantly, Our findings demonstrate that the observed direction and magnitude of recruitment changes were not significantly explained by the functional state of the stimulated neurons, indicating that these parameters do not capture the determinants of perturbation-induced network responses. This highlights a possibilities in the future approaches for characterizing network responsiveness and suggests that additional unobserved features govern the response of microcircuits to localized inputs.

The phenomenon of splitting was originally observed in hamsters which, after prolonged exposure to constant light, exhibit two rest/wake cycles within a subjective day. Splitting is a consequence of the left and right suprachiasmatic nuclei (SCN) falling out of synchrony. While it is known that split activity is characterized by an antiphase relationship between the left and right SCN and between the core and shell within each hemisphere, the role of the commissural projections that connect the right and left SCN is not known. In the present study, we investigate the impact of the inter-hemispheric connections on the split and unsplit dynamics of a computational model of the bilateral SCN. Our model has 4 nodes corresponding to each right and left core and shell. We simulated our bilateral model under different lighting conditions and measured its period and the phase relationships among the 4 nodes. To further characterize the dynamics of the system, we performed a bifurcation analysis. We found that the bilateral model automatically splits unless entrained by bright light/dark cycles, or unless it has excitatory inter-hemispheric connections. This suggests that excitatory cross-connections may be important for freerunning behavior. We found that constant light of varying intensities transitions the model between split and unsplit activity only in very limited conditions, but the strength and polarity of the contralateral connections play a much greater role in this dynamical transition. These findings suggest that splitting may involve plasticity of the inter-hemispheric connections of the SCN.

Computational simulations with data-driven physiological detail can foster a deeper understanding of the neural mechanisms involved in cognition. Here, we utilize the wealth of cellular properties from Hippocampome.org to study neural mechanisms of spatial coding with a spiking continuous attractor network model of medial entorhinal cortex circuit activity. The primary goal was to investigate if adding such realistic constraints could produce firing patterns similar to those measured in real neurons. Biological characteristics included in the work are excitability, connectivity, and synaptic signaling of neuron types defined primarily by their axonal and dendritic morphologies. We investigate the spiking dynamics in specific neuron types and the synaptic activities between groups of neurons. Modeling the rodent hippocampal formation keeps the simulations to a computationally reasonable scale while also anchoring the parameters and results to experimental measurements. Our model generates grid cell activity that well matches the spacing, size, and firing rates of grid fields recorded in live behaving animals from both published datasets and new experiments performed for this study. Our simulations also recreate different scales of those properties, e.g., small and large, as found along the dorsoventral axis of the medial entorhinal cortex. Computational exploration of neuronal and synaptic model parameters reveals that a broad range of neural properties produce grid fields in the simulation. These results demonstrate that the continuous attractor network model of grid cells is compatible with a spiking neural network implementation sourcing data-driven biophysical and anatomical parameters from Hippocampome.org. The software is released as open source to enable broad community reuse and encourage novel applications.

Electrical transmission is mediated by intercellular channels that cluster into structures known as gap junctions (GJ). In vertebrates, GJ channels are encoded by the gene family of connexin (Cx) proteins that assemble as hexamers, termed hemichannels, in the pre- and postsynaptic membranes, and that subsequently dock to form GJ channels. Auditory contacts on the fish Mauthner cells serve as model to study the properties and organization of vertebrate electrical synapses. Electrical transmission at these synapses is mediated by multiple co-existing GJs at which the presence of intercellular channels is regulated by a molecular scaffold. Zebrafish contain four homologs of the neuronal Cx36: Cx35.5 and Cx35.1 (gjd2a and b, respectively), and Cx34.1 and Cx34.7 (gjd1a and b). Cx mutations suggested that GJs are formed by heterotypic channels made of presynaptic Cx35.5 and postsynaptic Cx34.1. Using transgenic fish in which Cxs were tagged, we found that a second Cx, Cx34.7, is present together with Cx34.1 on the postsynaptic side at some but not all GJs at these terminals. When exogenously expressed, both Cx34.1 and Cx34.7 formed heterotypic functional channels with Cx35.5, each with substantially different voltage-dependent properties, indicating they can serve differential functions. However, we previously demonstrated that electrical transmission is lost in Cx34.1 but not Cx34.7 null mutants, suggesting that Cx34.7 cannot compensate for the loss of Cx34, despite the intrinsic ability of Cx34.1 and Cx34.7 to create functional channels. The findings reveal an unanticipated functional organization in the electrical synapse, where Cx34.1 is obligatory and Cx34.7 accessory, roles that appear to be defined by the postsynaptic molecular scaffold, with two postsynaptic Cxs possibly assembling under specific functional contexts. Thus, our results indicate that electrical synapses share an organizational motif with chemical synapses, akin to how they combine postsynaptic receptor types to modify synaptic function.

Molecular layer interneurons (MLIs) play a crucial role in modulating the output of the cerebellar cortex through their inhibition of Purkinje cells. MLIs also inhibit other MLIs synaptically and are coupled electrically through gap junctions. While synchronization of MLIs has been observed, comprehensive understanding of the role of gap junctional coupling in shaping MLI network activity is lacking. Dendro-dendritic gap junctional coupling in MLIs involves propagation of signals to and from the dendritic gap junction location which can lead to neural synchronization. However, how this is regulated by the intrinsic electrical properties of MLIs, including dendritic properties, is poorly understood. In this study, we apply conductance-based computational modelling to examine the effect of dendritic filtering on gap junctional coupling in pairs of ball-and-stick MLI models, demonstrating that gap junctional properties, rather than the active dendritic properties of MLIs, primarily dictate gap junction-driven synchronization. By systematically reducing the ball-and-stick model to a one-compartment MLI model, we additionally investigate the role of MLI gap junctional coupling in mediating MLI network synchrony. Our results reveal that transient AMPA input drives brief network-wide synchronization, whereas NMDA-mediated elevated firing enables gap junction-dependent oscillatory synchronization that is further enhanced by MLI-MLI inhibition in a positive feedback loop, producing pronounced peaks of network coactivity resembling sensory-evoked MLI activity observed in vivo. These findings provide important insights into network dynamics of MLIs and how gap junctions shape their activity, with broader implications for other neural networks that rely on gap junctional coupling.