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bioRxiv2022

Pairing cellular and synaptic dynamics into building blocks of rhythmic neural circuits

The purpose of this paper is trifold - to serve as an instructive resource and a reference catalog for biologically plausible modeling with i) conductance-based models, coupled with ii) strength-varying slow synapse models, culminating in iii) two canonical pair-wise rhythm-generating networks. We document the properties of basic network components: cell models and synaptic models, which are prerequisites for proper network assembly. Using the slow-fast decomposition we present a detailed analysis of the cellular dynamics including a discussion of the most relevant bifurcations. Several approaches to model synaptic coupling are also discussed, and a new logistic model of slow synapses is introduced. Finally, we describe and examine two types of bicellular rhythm-generating networks: i) half-center oscillators ii) excitatory-inhibitory pairs and elucidate a key principle - the network hysteresis underlying the stable onset of emergent slow bursting in these neural building blocks. These two cell networks are a basis for more complicated neural circuits of rhythmogenesis and feature in our models of swim central pattern generators.

neuroscience↗

bioRxiv2021

Functional architecture of neural circuits for leg proprioception in Drosophila

To effectively control their bodies, animals rely on feedback from proprioceptive mechanosensory neurons. In the Drosophila leg, different proprioceptor subtypes monitor joint position, movement direction, and vibration. Here, we investigate how these diverse sensory signals are integrated by central proprioceptive circuits. We find that signals for leg joint position and directional movement converge in second-order neurons, revealing pathways for local feedback control of leg posture. Distinct populations of second-order neurons integrate tibia vibration signals across pairs of legs, suggesting a role in detecting external substrate vibration. In each pathway, the flow of sensory information is dynamically gated and sculpted by inhibition. Overall, our results reveal parallel pathways for processing of internal and external mechanosensory signals, which we propose mediate feedback control of leg movement and vibration sensing, respectively. The existence of a functional connectivity map also provides a resource for interpreting connectomic reconstruction of neural circuits for leg proprioception.

neuroscience↗

bioRxiv2025

Neural Circuit Remodeling Underlying Enhanced Feeding During Pregnancy in Mice

Pregnancy represents a unique physiological state marked by substantial adaptations influencing both behavior and metabolism1. Alterations have been observed across multiple levels--from changes in cellular morphology, synaptic density, and neuroglial interactions to a brain-wide reduction in gray matter volume2-7. While these adaptations are thought to support offspring survival and promote maternal physiological and psychological well-being8, their functional significance remains largely unresolved. In particular, linking localized synaptic plasticity to a broader brain-wide circuit dynamics has posed a major challenge. Using virus-mediated screening in mice, we investigated the pregnancy-induced remodeling of the presynaptic landscape of paraventricular hypothalamic (PVH) oxytocin neurons, a central hub of maternal physiology9,10. Here we show a selective and reversible elimination of excitatory synaptic inputs from the medial preoptic nucleus to PVH oxytocin neurons, displaying region-, cell-type-, and pathway-specificity. This reduction in excitatory drive attenuated the anorexigenic activity of oxytocin neurons during feeding, thereby promoting the increased food intake characteristic of pregnancy. These data demonstrate that the selective suppression of anorexigenic PVH oxytocin neuron activity plays a critical role in appetite regulation during pregnancy. More broadly, our data identify a pregnancy-associated remodeling of hypothalamic neural circuits with direct physiological relevance.

neuroscience↗

bioRxiv2026

Ferulic acid eicosyl ester enhances cognitive flexibility and modulates arousal-related neural circuits in mice

Cognitive deficits are a major contributor to disability in numerous neuropsychiatric and neurodegenerative disorders, yet effective pharmacological treatments remain limited. Ferulic acid eicosyl ester (FAE-20), a natural constituent of the plant Rhodiola rosea, has previously been identified as an enhancer of simple forms of Pavlovian conditioning in flies, bees, and mice. Here, we investigated whether FAE-20 has further potential to enhance cognitive flexibility, working memory, or spatial learning in mice, and explored potential neurobiological mechanisms underlying such enhancement. Cognitive flexibility was assessed using the attentional set-shifting task (ASST). Subchronic FAE-20 treatment significantly improved ASST performance in both male and female young adult mice, indicating enhanced cognitive flexibility. In contrast, no effects were observed on spatial working memory, assessed by spontaneous alternations in the Y-maze, or on spatial learning in the Barnes maze in either young or aged mice. Notably, FAE-20 enabled spatial learning in the Barnes maze in a subgroup of aged mice that failed to learn the task under vehicle treatment. Histological analyses using c-Fos immunohistochemistry as a marker of neural activity and doublecortin expression and spine density as markers of hippocampal plasticity revealed sex-specific effects on components of the ascending arousal system. FAE-20 increased the activation of orexinergic neurons in the lateral hypothalamus of male mice, whereas it reduced the activity of cholinergic neurons in the laterodorsal tegmental nucleus of females. No effects were detected on hippocampal neurogenesis or dendritic spine density. These findings suggest that the cognitive effects of FAE-20 are selective, depending on the cognitive demands of the task and the baseline cognitive abilities of the animals, and may be mediated, at least in part, by modulation of arousal-related neural circuits. HighlightsO_LIFAE-20 enhanced cognitive flexibility in young adult mice C_LIO_LIEffects of FAE-20 were strongest in demanding cognitive tasks C_LIO_LIAged poor learners benefited from FAE-20 treatment C_LIO_LIFAE-20 activated hypothalamic orexin neurons in male mice C_LIO_LIFAE-20 modulated ascending arousal systems in a sex-specific manner C_LI

neuroscience↗

bioRxiv2021

Redundant neural circuits regulate olfactory masking

Olfactory masking is a complex olfactory response found in humans. However, the mechanisms whereby the presence of one odorant masks the sensory and behavioral responses elicited by another odorant are poorly understood. Here, we report that Caenorhabditis elegans displays olfactory masking and that the presence of a repulsive odorant, 2-nonanone, that signals threat strongly masks the attraction of other odorants, such as isoamyl alcohol (IAA) or benzaldehyde that signals food. Using a forward genetic screen, we found that several genes, osm-5, osm-1, and dyf-7, known to regulate the structure and function of sensory neurons played a critical role in olfactory masking. Loss of these genes mildly reduces the response to 2-nonanone and disrupts the masking effect of 2-nonanone. Restoring the function of OSM-5 in either AWB or ASH, two sensory neurons known to mediate 2-nonanone-evoked avoidance, is sufficient to rescue olfactory masking. AWB is activated by the removal of 2-nonanone stimulation or the onset of IAA; however, the mixture of 2-nonanone and IAA stimulates AWB similarly as 2-nonanone alone, masking the cellular effect of IAA. The latency of the AWB response is critical for the masking effect. Thus, our results identify redundant neural circuits that regulate the robust masking effect of a repulsive odorant and uncover the neuronal and cellular basis for this complex olfactory task. AUTHOR SUMMARYIn their natural environment, animals, including humans, encounter complex olfactory stimuli. However, regardless how complex the stimuli are, the behavioral output can only be one. Thus, how the brain processes multiple sensory cues to generate a coherent behavioral output is critical for the survival of the animal. In the present study, we combined molecular cellular genetics, optical physiology and behavioral analysis to study olfactory masking, a common olfactory phenomenon in which the presence of one odorant masks the stimulation of another odorant. Our results show that olfactory masking is regulated by redundant neuronal circuits, a mechanism that likely ensures the robust behavioral response to the sensory cue representing information critical for the survival.

neuroscience↗

bioRxiv2025

Barcoded Rabies In Situ Connectomics for high-throughput reconstruction of neural circuits

Sequencing of oligonucleotide barcodes holds promise as a high-throughput approach for reconstructing synaptic connectivity at scale (1). Rabies viruses can act as a vehicle for barcode transmission, thanks to their ability to spread between synaptically connected cells (2, 3). However, applying barcoded rabies viruses to map synaptic connections in vivo has proved challenging (4-7). Here, we develop Barcoded Rabies In Situ Connectomics (BRISC) for high-throughput connectivity mapping in the mouse brain. To ensure that the majority of post-synaptic "starter" neurons are uniquely labeled with distinct barcode sequences, we first generated libraries of rabies viruses with sufficient diversity to label >1000 neurons uniquely. To minimize the probability of barcode transmission between starter neurons, we developed a strategy to tightly control their density. We then applied BRISC to map inputs of single neurons in the primary visual cortex (V1). Using in situ sequencing, we read out the expression of viral barcodes in rabies-infected neurons, while preserving spatial information. We then matched barcode sequences between starter and presynaptic neurons, mapping the inputs of 385 neurons and identifying 7,814 putative synaptic connections. The resulting connectivity matrix revealed layer- and cell-type-specific local connectivity rules and topographic organization of long-range inputs to V1. These results show that BRISC can simultaneously resolve the synaptic connectivity of hundreds of neurons while preserving spatial information, enabling reconstruction of neural circuits at an unprecedented scale.

neuroscience↗

bioRxiv2021

Recurrent neural circuits overcome partial inactivation by compensation and re-learning

1Technical advances in artificial manipulation of neural activity have precipitated a surge in studying the causal contribution of brain circuits to cognition and behavior. However, complexities of neural circuits challenge interpretation of experimental results, necessitating theoretical frameworks for system-atic explorations. Here, we take a step in this direction, using, as a testbed, recurrent neural networks trained to perform a perceptual decision. We show that understanding the computations implemented by network dynamics enables predicting the magnitude of perturbation effects based on changes in the networks phase plane. Inactivation effects are weaker for distributed network architectures, are more easily discovered with non-discrete behavioral readouts (e.g., reaction times), and vary considerably across multiple tasks implemented by the same circuit. Finally, networks that can "learn" during inactivation recover function quickly, often much faster than the original training time. Our framework explains past empirical observations by clarifying how complex circuits compensate and adapt to perturbations.

neuroscience↗

bioRxiv2026

Sex differences in neural circuits driving binge drinking: A female-specific role for an amygdalo-striatal pathway

BackgroundRates of binge drinking have converged significantly between the sexes over recent decades, driven by increased rates of alcohol misuse in women. However, understanding of fundamental circuitry and neurobiology driving alcohol use in females, or how this may differ from male subjects remains underexplored. MethodsWe quantified c-Fos expression across 40 brain regions in alcohol naive, alcohol anticipating and binge drinking male and female mice. In vivo fiber photometry examined sex differences in basolateral amygdala (BLA) activity changes to alcohol intake. Chemogenetic BLA inhibition investigated a functional role in binge drinking. We then assessed sex differences in BLA efferent projection activation following binge drinking. Finally, we functionally interrogated the BLA to nucleus accumbens core (AcbC) projection in binge drinking. ResultsBinge drinking reduced network modularity (number of communities with similar activation patterns) in both sexes relative to alcohol naive and anticipating same-sex counterparts. Female binge drinking mice had increased BLA c-Fos expression compared to female naive and male binge drinking counterparts. In vivo fiber photometry revealed greater and more prolonged BLA responsivity at the onset of alcohol intake in females. Global BLA inhibition reduced reward intake in both sexes. However, the BLA to AcbC projection was preferentially activated in female binge drinking mice, and inhibition of this pathway reduced binge alcohol intake exclusively in females. ConclusionsWe identified sex differences in the neural circuits engaged in binge drinking, highlighting the BLA to AcbC projection may in part underpin sex differences in alcohol misuse. This provides further evidence of distinct neurobiological drivers of alcohol-related behaviors between the sexes.

neuroscience↗

bioRxiv2018

A Mechanism for Synaptic Copy between Neural Circuits

The brain has a central, short-term learning module, the hippocampus, which transfers what it has learned to long-term memory in cortex during non-REM sleep. The putative mechanism responsible for this type of memory consolidation invokes hierarchically nested hippocampal ripples (100-250 Hz), thalamo-cortical spindles (7-15 Hz), and cortical slow oscillations (< 1 Hz) to enable transfer. Suppression of, for instance, thalamic spindles has been shown to impair hippocampus-dependent memory consolidation. Cortical oscillations are central to information transfer in neural systems. Significant evidence supports the idea that coincident spike input can allow the neural threshold to be overcome, and spikes to be propagated downstream in a circuit. Thus, an observation of oscillations in neural circuits would be an indication that repeated synchronous spiking is enabling information transfer. However, for memory transfer, in which synaptic weights must be being transferred from one neural circuit (region) to another, what is the mechanism? Here, we present a synaptic transfer mechanism whose structure provides some understanding of the phenomena that have been implicated in memory transfer, including the nested oscillations at various frequencies. The circuit is based on the principle of pulse-gated, graded information transfer between neural populations.\n\nPACS numbers: 87.18.Sn,87.19.lj,87.19.lm,87.19.lq

neuroscience↗

bioRxiv2020

HySyn: A genetically-encoded synthetic synapse to rewire neural circuits in vivo

Here we introduce HySyn, a system designed to rewire neural connectivity in vivo by reconstituting a functional heterologous synapse. We demonstrate that genetically targeted expression of the two HySyn components, a Hydra-derived neuropeptide and its receptor, creates de novo neuromodulatory transmission in a mammalian neuronal tissue culture model and rewires a behavioral circuit in vivo in the nematode Caenorhabditis elegans. HySyn can interface with existing optogenetic, chemogenetic and pharmacological approaches to functionally probe synaptic transmission, dissect neuropeptide signaling, or modulate specific neural circuits.

neuroscience↗

bioRxiv2019

Corollary Discharge Promotes a Sustained Motor State in a Neural Circuit for Navigation

Animals exhibit behavioral and neural responses that persist on longer time scales than transient or fluctuating stimulus inputs. Here, we report that C. elegans uses feedback from the motor circuit to a sensory processing interneuron to sustain its motor state during thermotactic navigation. By imaging circuit activity in behaving animals, we show that a principal postsynaptic partner of the AFD thermosensory neuron, the AIY interneuron, encodes both temperature and motor state information. By optogenetic and genetic manipulation of this circuit, we demonstrate that the motor state representation in AIY is a corollary discharge signal. RIM, an interneuron that is connected with premotor interneurons, is required for this corollary discharge. Ablation of RIM eliminates the motor representation in AIY, allows thermosensory representations to reach downstream premotor interneurons, and reduces the animals ability to sustain forward movements during thermotaxis. We propose that feedback from the motor circuit to the sensory processing circuit underlies a positive feedback mechanism to generate persistent neural activity and sustained behavioral patterns in a sensorimotor transformation.

neuroscience↗

bioRxiv2018

Learning probabilistic representations with randomly connected neural circuits

The brain represents and reasons probabilistically about complex stimuli and motor actions using a noisy, spike-based neural code. A key building block for such neural computations, as well as the basis for supervised and unsupervised learning, is the ability to estimate the surprise or likelihood of incoming high-dimensional neural activity patterns. Despite progress in statistical modeling of neural responses and deep learning, current approaches either do not scale to large neural populations or cannot be implemented using biologically realistic mechanisms. Inspired by the sparse and random connectivity of real neuronal circuits, we present a new model for neural codes that accurately estimates the likelihood of individual spiking patterns and has a straightforward, scalable, efficiently learnable, and realistic neural implementation. This models performance on simultaneously recorded spiking activity of >100 neurons in the monkey visual and prefrontal cortices is comparable or better than that of current models. Importantly, the model can be learned using a small number of samples, and using a local learning rule that utilizes noise intrinsic to neural circuits. Slower, structural changes in random connectivity, consistent with rewiring and pruning processes, further improve the efficiency and sparseness of the resulting neural representations. Our results merge insights from neuroanatomy, machine learning, and theoretical neuroscience to suggest random sparse connectivity as a key design principle for neuronal computation.

neuroscience↗

bioRxiv2021

Multifunctional Cre-dependent transgenic mice for high-precision all-optical interrogation of neural circuits

Determining which features of the neural code drive perception and behavior requires the ability to simultaneous read out and write in neural activity patterns with high precision across many neurons. All-optical systems that combine two photon (2p) calcium imaging and targeted 2p photostimulation enable the activation of specific, functionally defined groups of neurons in behaving animals. However, these techniques do not yet have the ability to reveal how the specific distribution of firing rates across a relevant neural population mediates neural computation and behavior. The key technical obstacle is the inability to transform single-cell calcium signals into accurate estimates of firing rate changes and then write in these cell-specific firing rate changes to each individual neuron in a targeted population. To overcome this challenge, we made two advances: first we introduce a new genetic line of mice for robust Cre-dependent co-expression of a high-performance calcium indicator and a potent soma-targeted microbial opsin. Second, using this line, we developed a pipeline that enables the read-out and write-in of precise population vectors of neural activity across a targeted group of neurons. The combination of the new multifunctional transgenic line and the photostimulation paradigm offer a powerful and convenient platform for investigating the neural codes of computation and behavior. It may prove particularly useful for probing causal features of the geometry of neural representations where the ability to directly control the topology of population activity is essential.

neuroscience↗

bioRxiv2019

Neural circuit mechanism for generating categorical representations

Categorical neural responses underlie various forms of selection and decision-making. Such binary-like responses promote robust signaling of the winner in the presence of input ambiguity and neural noise. Here, we show that a donut-like inhibitory mechanism in which each competing option suppresses all options except itself, is highly effective at generating categorical neural responses. It surpasses motifs of feedback inhibition, recurrent excitation, and divisive normalization invoked frequently in decision-making models. We demonstrate experimentally not only that this mechanism operates in the midbrain spatial selection network in barn owls, but also that it is necessary for categorical signaling by it. The functional pattern of neural inhibition in the midbrain forms an exquisitely structured multi-holed donut consistent with this networks combinatorial inhibitory function for stimulus selection. Additionally, modeling reveals a generalizable neural implementation of the donut-like motif for categorical selection. Self-sparing inhibition may, therefore, be a powerful circuit module central to categorization.

neuroscience↗

bioRxiv2018

Neural circuit robustness to acute, global physiological perturbations

Neural function depends on underlying physiological processes that are highly sensitive to physical variables such as temperature. However, some robustness to perturbations in these variables manifests at the circuit level, suggesting that circuit properties are organized to tolerate consistent changes in underlying parameters. We show that a crustacean pacemaker circuit is robust to two global perturbations - temperature and pH - that differentially alter circuit properties. Consistent with high variability in underlying circuit parameters, we find that the critical temperatures and pH values where circuit activity breaks down vary widely across animals. Despite variability in critical points the network state transitions at these critical points are consistent, implying that qualitative circuit dynamics are preserved across animals, in spite of high quantitative parameter variability. Surprisingly, robustness perturbations in pH only moderately affect temperature robustness. Thus, robustness to a global perturbation does not necessarily imply sensitivity to other global perturbations.

bioinformatics↗

bioRxiv2024

Structured stabilization in recurrent neural circuits through inhibitory synaptic plasticity

In cortical circuits, inhibitory interneurons play a dual role: they regulate overall activity levels to prevent runaway excitation, and contribute to diverse computations. While unstructured inhibitory synaptic connections achieve the first role by homeostatically regulating firing rates, computational tasks often require structured excitatory-inhibitory (E/I) connectivity. Here, we consider a broad class of pairwise inhibitory spike-timing dependent plasticity (iSTDP) rules, demonstrating how inhibitory connections can self-organize to both stabilize excitation and generate functionally relevant connectivity motifs--a process we call "structured stabilization". We show that in both small E/I circuits and large spiking recurrent neural networks the choice of iSTDP rule can lead to either mutually connected E/I pairs, or to lateral inhibition, where an inhibitory neuron connects to an excitatory neuron that does not directly connect back to it. In a one-dimensional ring network with two inhibitory subpopulations following these distinct iSTDP rules, the effective connectivity within the excitatory units self-organizes into a Mexican-hat-like profile, with excitatory influence in the center and inhibitory influence away from the center. This leads to emergent network responses such as contextual modulation effects as in the visual cortex and spatially modular activity characteristic of developmental spontaneous activity. Our theoretical work introduces a family of rules that retains the broad applicability and simplicity of spike-timing-based plasticity, while stabilizing activity and promoting specific connectivity motifs which support emergent network computations. Significance StatementNeural circuits are faced with the dual challenge of keeping activity stable while modifying synaptic strengths during development and learning. A prominent mechanism to keep excitation in check is inhibitory synaptic plasticity. In recurrent circuit models, we show that plasticity rules based on spike timing at synapses from inhibitory to excitatory neurons can stabilize activity while reinforcing specific connectivity motifs. The shape of these rules dictates the resulting motifs, and determines whether inhibitory neurons form strong reciprocal connections with their excitatory partners or lateral connections onto excitatory neurons that do not connect back. In recurrent networks with local excitatory connectivity, these motifs generate surround suppression as in the visual cortex, and long-range spatial correlations characteristic of developmental spontaneous activity.

neuroscience↗

bioRxiv2025

Repetitive stimulation modifies network characteristics of neural organoid circuits

Neural organoids form complex networks but lack external stimuli and hierarchical structures crucial for refining functional microcircuits. In this study, we modeled the hierarchical and modular network organization by connecting multiple organoids and tested if the connection enhances the external stimuli-induced network refinement. We cultured networks of one, two, or three organoids on high-density microelectrode arrays, applied repetitive stimulation at two input locations from the microelectrodes, and monitored emergence of output signals that can decode the stimulus locations with machine learning algorithms. After two weeks of daily stimulation, networks of three organoids showed significantly higher stimulus decoding capability compared to the simpler one- or two-organoid networks. Long-term stimulation induced pronounced changes in the three-organoid networks response patterns, spontaneous activity, and inter- and intra-organoid functional connectivity. These findings underscore the importance of hierarchical network organization, e.g. creating distinct subnetworks with specialized roles, for stimuli-induced formation of circuits with robust input-output functionality.

bioengineering↗

bioRxiv2022

Insect asynchronous flight requires neural circuit de-synchronization by electrical synapses

Despite profound mechanistic insight into motor pattern generation, for asynchronous insect flight - the most prevalent form of flight employed by >600.000 species - architecture and function of the underlying central pattern generating (CPG) neural network remain elusive. Combining electro- and optophysiology, Drosophila genetics, and mathematical modelling, we uncover a miniaturized circuit solution of motoneurons interconnected by electrical synapses that, contrary to doctrine, serve to de-synchronize network activity. This minimal gap-junctional motoneuron network suffices to translate unpatterned premotor input into stereotyped firing sequences which are conserved across species and generate stable wingbeat power. Mechanistically, network de-synchronization requires weak electrical coupling in conjunction with specific postsynaptic excitability dynamics, revealing an unexpected, generic feature in the control of neural circuit dynamics by electrical synapses. One Sentence SummaryElectrical synapses de-synchronize neural network firing to enable stable wingbeat power during insect flight.

neuroscience↗