Frontiers in Neural Circuits

Background: Nervous system regeneration requires creation of new neurons and their integration into new and existing networks. How new neurons find their targets and reconnect in the environment of regenerating tissue remains a major gap in knowledge. The planarian Schmidtea mediterranea is well suited to the study of neural regeneration due to the remarkable ability of planarians to regenerate their entire body, including the nervous system. However, we have not yet been able to explore synaptogenesis in regeneration using planarians due to a lack of tools to study synapses. Here we investigate potential players in planarian synapse, focusing on the conserved syntaxin protein family, which functions in neurotransmitter vesicle fusion at the synapse. Results: We found that reduction of either syntaxin-1 (stx1) or syntaxin-binding protein 1-1 (stxbp1-1) decreased locomotion and impeded brain regeneration, specifically in synapse-rich regions. Conclusions: Our observations support STX-1 and STXBP1-1 as bona fide synapse components, providing a starting point for studies neuronal connectivity during homeostatic remodeling and regeneration.

Astrocytes actively regulate synaptic transmission and neuronal excitability, yet their role in orchestrating macroscopic cortical network regimes and slow-wave oscillations remains an active area of reasearch. This study investigates how bidirectional neuron astrocyte interactions shape emergent population dynamics using a computational network model of excitatory and inhibitory neurons coupled to an astrocyte. The results identify astrocytic feedback topology, rather than astrocytic coupling strength alone, as a key determinant of emergent cortical network dynamics. By systematically dissecting pathway-specific connectivity, it has been shown that the neuronal population driving astrocytic activation and the neuronal population receiving gliotransmission jointly determine whether the network occupies asynchronous irregular (AI), synchronous irregular (SI), synchronous regular(SR), asynchronous regular(AR) or quiescent regimes.Directing gliotransmission selectively onto excitatory neurons consistently promotes population synchrony regardless of the population influencing astrocytic dynamics, whereas selective modulation of inhibitory interneurons induces network quiescence via strong suppression. Under dual-target gliotransmission, network synchrony is dictated by the population driving astrocytic dynamics: excitatory-only drive promotes synchrony, while combined or inhibitory-specific drive preserves asynchronous states. Furthermore, the model reveals that astrocytic signaling kinetics provide an additional temporal control mechanism that regulates the frequency and persistence of self sustained up states.

The mouse superior colliculus (SC) regulates critical behaviors such as prey capture and visual threat avoidance, each of which depend on binocular visual processing. In contrast to our previous understanding, recent work has demonstrated widespread and diverse binocular interactions in the mouse SC. The SC receives direct input from contralaterally and ipsilaterally projecting retinal ganglion cells (contra- and ipsi-RGCs), but the ways in which eye-specific information is filtered in the SC remain unclear. Here, we utilized a trans-synaptic, intersectional viral tracing strategy to label SC neurons receiving input monocularly from contra-RGCs (SC-C), monocularly from ipsi-RGCs (SC-I), or binocularly from both (SC-B). We show that a surprising number of SC neurons receive ipsi-RGC input and that the proportions of SC-C, SC-I, and SC-B neurons are consistent throughout the SC. Morphometric analysis revealed few differences between neurons receiving different eye-specific patterns of input. Consistent with this, we show that SC-C, SC-I, and SC-B neurons are comprised of similar proportions of five morphologically distinct subtypes. And, the expression of candidate molecular markers appears similar across innervation patterns. Together, these data suggest that eye-specific information is widespread throughout the SC targeting overlapping populations of neurons.

The ventral lateral geniculate nucleus (GLv) is a conserved retinorecipient structure positioned between visual and premotor systems, yet its role in visuomotor transformations remains poorly understood. Here, we examined whether the pigeon GLv contains a spatially organized motor representation linking visual-field locations to orienting movements. Anatomical tracing identified descending projections from neurons in the GLv inner lamina (GLv-li) through pretectal and tegmental regions toward pontine targets. GLv-li projection neurons are GABAergic, yet electrical microstimulation of GLv-li in awake pigeons evoked rapid head movements followed by smaller eye movements. Each stimulation locus produced a reproducible characteristic motor vector whose direction and duration were largely insensitive to stimulation parameters, whereas movement amplitude and velocity approached site-specific plateaus. Movements initiated from different head positions were better explained by repetition of a fixed displacement than by convergence toward a common spatial goal. Critically, motor-vector direction was systematically related to the direction of the visual receptive field represented at the same GLv locus, while motor-vector amplitude covaried with receptive-field eccentricity. These defining features persisted after optic tectum ablation. Together, these findings reveal a retinotopically-organized map of fixed-vector head movements in the avian GLv and identify a tectum-independent route through which visual spatial representations can access descending orienting circuitry.

Increasing experimental evidence suggests that biological systems cancel predictable components of sensory signals while maintaining sensitivity to externally induced state changes. This strategy provides task-specific sensor responses for posture, locomotion, and gaze control. A prime example is found in interneurons that respond to visual image shifts resulting from the relative motion between an animal's eyes and its visual surroundings. Such optic flow-processing interneurons, found across phyla and are particularly well characterized in Dipteran and other flying insects. We studied optic flow-processing interneurons in the Monarch butterfly whose large and highly contrasted wings sweep through the visual field with every wing-beat cycle, potentially obscuring interneuron output signals. Our results show baseline spiking activity increases when animals flap their wings, and individual spikes are phase-locked to the wing-beat cycle, even in the dark, when no visual motion input is available. A qualitative estimate of the interneurons' response to directional wing motion through its receptive field is not sufficient to explain the recorded activity patterns. Our results suggest that an additional internal signal suppresses responses to wing-induced visual motion to support effective vision-based stabilization reflexes. These findings support the principle that self-generated signals are suppressed while sensitivity to external modulation is preserved.

Emerging research on desynchronization reveals strong relations to memory formation and recollection with much of the evidence originating from studies of the hippocampus, a brain region central to memory processing. However, growing evidence emphasizing the role of desynchronization is accompanied by challenges, most notably the synchronization/desynchronization conundrum. The conundrum arises from an apparent contradiction between learning and Shannon's information theory: spike-timing-dependent plasticity (STDP) acquires information via synchronized populational activity whereas information theory suggests that information channel is encoded through higher variability. Both frameworks are well-founded. Learning is widely accepted as the mathematical abstraction of STDP while Shannon's information theory showcases its power ubiquitously across fields from communication systems to neuroscience. Here, we propose that learning and Shannon's information theory are not necessarily opposing principles. Rather, learning plays a critical role in the process of synchronization and desynchronization. To justify our claim, we conduct computational simulations based on a Hodgkin-Huxley neuronal model coupled with NMDA, AMPA, and GABA synapses with inputs of biologically realistic spiking data. Our results show that enabling STDP significantly influences synchronization and desynchronization dynamics. Specifically, we find that STDP and desynchronization form a regulatory loop, in which STDP regulates the level of synchrony, and synchrony regulates subsequent learning strength. Further study reveals STDP is capable of switching neurons from synchronization to desynchronization. This framework mitigates the synchronization/desynchronization conundrum by clarifying the relationship between desynchronization and learning, and offers a new perspective on how synchrony contributes to memory formation and recollection.

Axonal projections and precise synapse formation are essential for the establishment of functional neural circuits, and their dysregulation contributes to various psychiatric and neurodegenerative disorders. Although numerous extracellular cues secreted from surrounding tissues regulate axon guidance and synapse formation, the mechanisms by which neurons locally regulate terminal patterning within their projection fields remain poorly understood. Bone morphogenetic protein 4 (BMP4) is a classical morphogen that is involved in early neural tube patterning during development. However, its postnatal function remains unclear. Previous in vitro studies using hippocampal glutamatergic neurons demonstrated that BMP4 can act locally on axons to suppress synapse formation, raising the possibility that BMP4 regulates terminal differentiation after target innervation. Here, we investigated the role of BMP4 in postnatal cholinergic circuit development using cholinergic neuron-specific Bmp4 conditional knockout (Bmp4 cKO) mice, with adult analyses performed in males. Basal forebrain cholinergic neurons project extensively throughout the neocortex and are essential for higher brain functions, including arousal and attention. Bmp4 cKO mice exhibited increased cholinergic axon terminals in the neocortex, hippocampus, and amygdala, as well as increased axonal ramification in the neocortex without affecting cytoarchitectonic organization or cholinergic neuron numbers in the basal forebrain. These findings demonstrate that BMP4 functions as a negative regulator of cholinergic terminal formation and axonal arborization, suggesting that BMP4 may act locally to restrict cholinergic axonal expansion during neural circuit maturation.

A moving object passes through locations in visual space in a particular order. To distinguish opposite directions of motion, visual circuits must convert this temporal order into different direction selective neuronal responses. This ability emerges and is refined as visual circuits develop. In Xenopus laevis tadpoles, direction selectivity in the optic tectum sharpens over development. Companion work by Zheng et al (2026) shows that direction selectivity sharpens between stage 45 (approximately 6 to 7 days postfertilization), when the retinotectal circuit is undergoing rapid refinement, and stage 48 (approximately 10 to 16 days postfertilization), when the projection has completed one phase of refinement and visual acuity has improved. The same study shows that, over this period, both the excitatory synaptic input received by tectal neurons and the intrinsic properties of those neurons change. How these synaptic and intrinsic changes work together to produce a sharpening of direction selectivity unclear. Here, we combined visually evoked excitatory postsynaptic current trains recorded at each stage with stage-specific single-compartment conductance-based models. These simulations reproduced the developmental increase in direction selectivity and reduction in spiking at stage 48. Changing intrinsic properties produced only modest changes in spike counts, while reassigning amplitudes among the original event times did not eliminate developmental sharpening. Together, these results suggest that the temporal organization of synaptic input carries much of the directional information, while intrinsic maturation lowers overall spike output, making the existing directional bias in the input more pronounced.

The mammalian neocortex is a complex structure with many interacting regions and cell types. Multiple efforts have recently generated large datasets from multiple cortical regions to determine generalizing principles of cortical organization and activity. One such generalizing principle is the concept of a cortical hierarchy - low-dimensional macroscopic gradients of biological properties across cortical areas and a hierarchy of timescales for information processing. Such gradients in properties along a cortical hierarchy may explain how different cortical regions serve different computational roles (i.e. sensory processing versus working memory). We set out to investigate such principles using biologically realistic simulations. Starting from our previously published model of the mouse primary visual cortex (VISp) with updated connectivity reflecting recent large-scale connectomics and synaptic physiology datasets, we generated multiple versions of the cortical circuit model with increased connectivity as measured along the cortical hierarchy. We then measure the resulting neural activity in response to a simulated single-cell photostimulation paradigm and thalamocortical inputs. We found that overall circuit stability increased across the cortical hierarchy, due to both increases in connection density and increases in the relative proportion of SST cells. The results of this study link cortical cell types to population-level activity, generating insight into the function of local circuits across cortex.

Background: Insufficient oxygen (hypoxia) or complete lack of oxygen (anoxia) causes cellular dysfunction and death in terrestrial animals. As a result, animals have developed homeostatic strategies, including changes in movement strategies to escape and survive stressful environments. Caenorhabditis elegans respond to changes in oxygen by increasing the frequency of reversals (backward movement) and increasing locomotor speed; these behaviors enable them to escape unfavorable environments and move to more suitable ones. The molecular and neural mechanisms underlying behavioral responses to low-oxygen environments are incomplete. Neuropeptides regulate C. elegans behaviors by modifying neural circuit function in response to hypoxia. Loss of function in C. elegans neuropeptide nlp-40 and its receptor aex-2 increased survival to anoxia [1]. However, the cells in which NLP-40 and AEX-2 function for anoxia, as well as the mechanisms underlying responses to anoxia, remain elusive. We hypothesized that NLP-40 and AEX-2 regulate anoxia by altering escape behaviors. Results: We found that neuropeptide NLP-40 functions in cholinergic neurons and AEX-2 functions in cholinergic or GLR-1 interneurons or motor neurons to regulate susceptibility to anoxia. We found that loss of either nlp-40 or aex-2 decreased locomotor activity and reversal frequency early during 48 hours of anoxia, suggesting that nlp-40 and aex-2 are required for the proper execution of these behaviors. We found that neuronal knockdown of nlp-40 recapitulated the behaviors observed in nlp-40 mutant animals and increased survival; however, restoring aex-2 function in glr-1 interneurons or motor neurons was sufficient to rescue behaviors to wild-type and restore vulnerability to anoxia. Conclusions: Overall, our results suggest that NLP-40 and AEX-2 likely function in cholinergic or glr-1 interneurons or motor neurons to regulate escape behaviors during anoxia. Escape behaviors are part of the homeostatic response and are typically protective in the wild; however, in our paradigm, we show that loss of either nlp-40 or aex-2 reduces escape responses and confers protection against 48 hours of anoxia. Collectively, these results highlight a new role for NLP-40 and AEX-2 in anoxia and shed light on mechanisms underlying the adaptive responses to anoxia.

Amacrine cells (ACs) are the most diverse neuron in the retina, with more than sixty different subtypes, each contributing to the detection of specific visual features. Despite their importance in visual feature detection, the genetic basis for this diversity is still not well understood. Recent single-cell transcriptomic datasets have identified several potential genes that may regulate cellular diversity, but the underlying mechanisms have not been investigated. For example, the transcription factor Meis2 is selectively expressed in the GABAergic subclass of ACs. In this study, we focused on how Meis2 regulates the development of GABAergic ACs. We hypothesized that Meis2 is required for specification and survival of GABAergic ACs. To test this, we used the Meis2 conditional knockout mouse (Meis2-CKO) where Meis2 was deleted from either the entire retina or specifically from AC precursor cells. The deletion of Meis2 led to a ~60% reduction in total GABAergic ACs in the retina. This loss of GABAergic ACs occurred only after postnatal day 5 (P5), suggesting Meis2 is not required for early specification but may be required for survival. To further investigate cell death and survival, we quantified cleaved caspase-3 positive cells in the retina at several developmental timepoints. In Meis2-CKO mice, we found an increase in cleaved caspase-3 immunolabeling at P5 and P6 timepoints coinciding with the reduction of GABAergic ACs. Further analysis of GABAergic AC subtypes demonstrated a subtype-specific cell death in Meis2-CKO retinas. For example, the total number of dopaminergic (TH) ACs were significantly reduced, whereas starburst (ChAT) ACs remained unchanged. These findings suggest that Meis2 is important for the survival of a subset of GABAergic AC subtypes in the mammalian retina. In addition, Meis2 may control the expression of specific survival factors that prevent apoptosis during developmental cell death in the retina.

Electrical synapses are prevalent throughout nervous systems, including the mammalian brain. Several lines of evidence implicate these gap junction connections in several important roles in neural networks. Yet, progress has been hampered by a shortage of experimental tools to investigate their function with sufficient precision. In an effort to address this deficit, we here take advantage of a curious species-difference in electrical coupling in tuberoinfundibular dopamine (TIDA) neurons of the rodent hypothalamus. In rats, these cells exhibit strong electrical coupling, generating stereotyped, slow oscillations that are synchronized across the population. In contrast, mouse TIDA neurons lack gap junctions and display diverse, faster, and asynchronous oscillations. Motivated by this natural discrepancy, we designed a gain-of-function strategy to induce localized and robust expression of the main pore-forming protein of neuronal gap junctions, connexin-36 (Cx36), in mouse TIDA neurons by viral vectors. This perturbation yielded electrical coupling that was weaker than the rat TIDA system, but on par with many other brain populations connected by gap junctions. Cx36 overexpression resulted in significantly increased auto- and cross-correlation, as well as augmented functional connectivity, in agreement with the induction of electrical synapses in the population. Yet, these measures were modest in comparison with rat TIDA neurons, and Cx36 overexpression failed to alter serum levels of the hormone prolactin, which is controlled by this neuroendocrine system. These findings highlight the potential and limitations of experimentally inducing electrical synapses in a natively uncoupled system, and suggest directions for future improvements.

Cephalopod skin exhibits a wide range of dynamic visual displays, including traveling waves, light/dark flashes, and flickering, all generated by muscle-regulated expansion and retraction of pigment-filled elastic sacs known as chromatophores. While central neural control is essential for high-level body-wide pattern coordination, experimental evidence from excised and denervated skin reveals that intricate spatiotemporal patterns can also emerge spontaneously in the skin. This raises questions about the respective roles of central versus peripheral control. To determine the simplest control necessary to generate such patterns, we developed ChromatoNet, a biophysical model of chromatophore arrays that includes mechanical interactions on 1- and 2-dimensional lattices with the excitability properties of radial muscles. With minimal external input, our modified Morris--Lecar model reproduces a rich repertoire of skin dynamics, including spontaneous flickering as well as traveling and spiral waves. Both spontaneous and stimulus-evoked waves emerge at an intrinsic resonant frequency, determined by model parameters. Propagation speeds remain stable across conditions and are consistent with the range observed in denervated skin preparations. The model generates diverse output states in response to local couplings and the time-dependence and shape of the input stimulation, with little top-down direction. The results provide a proof-of-principle that chromatophore/muscle dynamics with minimal central neural driving can produce rich dynamic patterns.

The basal ganglia (BG), thalamus and cortex form the BG-thalamo-cortical (BGTC) network, which is essential for voluntary movement and centrally involved in Parkinson's disease (PD). In both patients and animal models, BG neuronal activity exhibits exaggerated oscillatory synchronization in the beta frequencies (13-30 Hz). Theoretical studies have proposed multiple network mechanisms for the generation of these abnormal beta oscillations. However, key properties, such as frequency and power distribution across BG nuclei, vary substantially among patients and between animal models (rodents vs. non-human primates). This variability complicates direct comparisons between theoretical models and experimental data, and questions whether distinct neuronal mechanisms may underlie beta oscillations across species. In an experimentally constrained BGTC network model with species-specific parameters (synaptic, neuronal, and network properties), we evaluate the features of abnormal beta oscillatory activity generated by different mechanisms. The network's negative feedback loops serve as potential sources of spontaneous oscillations. Using rodent- or primate-constrained models, we compare the spectral properties of oscillatory activity across network populations for each loop and derive the expected phase relationships between populations to align predictions with existing rodent data and propose testable hypotheses for primates. We also demonstrate how oscillation frequency can be modulated when multiple generation mechanisms interact as coupled oscillators in the full network. Our results, combined with observed cross-species beta oscillations characteristics, suggest that abnormal beta oscillations likely arise from distinct mechanisms in rodents and primates.

The adult size of the vertebrate telencephalon typically impedes our interpreting its functions within the context of brain-wide circuit dynamics. Danionella, a genus of miniature and transparent teleost fishes closely related to zebrafish (Danio rerio), holds promise for whole-brain imaging and connectomics in an adult vertebrate. These advantages result from progenesis, a form of heterochrony characterized by early developmental onset of sexual maturation and cessation of growth leading to the retention of larval or juvenile characters in adults. Using molecular markers, tract tracing, and quantitative comparisons of cellular distribution patterns, we report a detailed neuroanatomical atlas of the adult Danionella dracula (Dracula fish) telencephalon. The results demonstrate that adults of Dracula fish and other Danionella species show extreme reduction in cellular migration from periventricular zones and topographic reorganization of major pallial divisions, including a compartment-like caudal pallium reminiscent of insect glomeruli (a dense neuropil surrounded by a thin layer of somata). We further document these characters in larval zebrafish, providing essential evidence corroborating a larval-like telencephalon in Danionella adults. Despite this phenotype, most canonical regions of the adult teleost telencephalon are identified. We also generate a transgenic GCaMP Dracula fish line, an annotated 3-dimensional atlas, and align functional imaging data to demonstrate the usefulness of this atlas as a resource for deciphering how the novel progenetic cytoarchitecture of the adult Danionella telencephalon can support its rich behavioral repertoire.

Most animals move intermittently. Of these, animals that fly and swim move in two stages: during active propulsion, when they beat their wings or swing their tails, and right after, when they glide or coast through the air or water. The kinematics of active movements are typically well studied, but the coasting period afterwards is less understood. We used larval zebrafish as a model of intermittent locomotion. Larval zebrafish swim in discrete bouts lasting ~200 ms, coast for short durations and distances, and then are largely stationary for ~800 ms. We find that larval zebrafish do not coast like a passive object. While they coast for distances that are correlated with the prior swim's strength, as expected from physics, they seem to be able to modulate the mechanics of their coasting: the time constant is not a constant, but varies from coast-to-coast. Furthermore, the time constant is correlated with the duration of the interval between swim bouts. This suggests that larval zebrafish can either shorten or extend their coasting duration, and that coasting inhibits the initiation of the next swim. Finally, the time constant changes quickly, while other swimming kinematics (e.g., distance swum) are autocorrelated over the course of at least several seconds. Altogether, this suggests that fish, and perhaps other animals that move intermittently, actively modulate their post-propulsion movement, possibly to gather sensory feedback in the absence of blurry visual feedback associated with fast locomotion.

We present a network model that enables a navigating agent to shape the spatial and temporal structure of its paths through its environment. The model is inspired by the insect fan-shaped body. In it, a recurrent neural network receives an input that encodes an agent's velocity vector. Meanwhile, network activity determines the setpoint of a control loop that influences this velocity vector through motor outputs. The network thus guides future movement using memory of past movement. We illustrate how the network's dynamics determine the trajectory features it extracts to produce the setpoint. We then relate the joint dynamics of network activity and the agent's velocity vector to the structure of the resulting paths. This network can produce paths suitable for different forms of exploration. It can also stabilize movements initiated by lower-level systems. Our analyses illustrate how recurrent neural dynamics and memory can shape behavior when embedded in closed loops.

Ambient illumination influences many aspects of brain function, including responses to threats. One brain region proposed to mediate these effects is the periaqueductal gray (PAG), an evolutionarily conserved midbrain structure that contains multiple subpopulations of peptidergic neurons. Here we ask which cell types in the larval zebrafish PAG respond to changes in ambient illumination. By registering post hoc gene expression to neurons recorded during exposure to sensory stimuli, we show that GABAergic PAG neurons expressing the neuropeptide Relaxin-3 (rln3a+) are persistently activated by darkness, while a neighboring subpopulation of GABAergic PAG neurons expressing penka is not. Zebrafish lacking rln3a show a reduction in locomotion during darkness. We propose that darkness recruits Relaxin-3-releasing PAG neurons to promote vigilance and potentiate defense circuits. These results identify a specific peptidergic population of PAG neurons that are potentially relevant to behavioral state dysregulation associated with excessive darkness.

The brain frequently updates or controls its internal representations of sensory or motor variables over time. An example is transsaccadic updating of stimuli's retinotopic positions: When the eye moves in one direction, the positions are updated continuously in the opposite direction, and the process is controlled by the corollary discharge (CD) of the saccade motor command. We previously trained neural networks to perform such updating using the desired time courses of stimuli's positions at every time step. However, this may not be biologically plausible because, before a system learns to perform the task, it may not have access to complete time courses and the actual visual inputs are delayed and thus incorrect. Here we show that by adding the continuity equation to the loss, we can train neural networks with only stimuli's pre- and post-saccadic retinotopic positions (without specifying the intermediate transitions), and with heavily down-sampled time courses. Moreover, both the connectivity patterns and the CD control signal can be learned simultaneously. Since the continuity equation can be applied to waves of neural population activities that are distributed representations of variables, our work also suggests an advantage of distributed representations which are ubiquitous in the brain.

Human working memory enables us to temporarily store and flexibly utilize information. It is thought that there are two distinct neural mechanisms by which information is retained in working memory: persistent firing of working memory-relevant neurons, or short-term synaptic plasticity in the absence of ongoing neuronal firing. However, both these mechanisms can lead to strong neural interference when working memory contents are updated with novel information. As an alternative, here we propose that information can be flexibly held in working memory in the form of traveling waves - spatiotemporal patterns of neural activity that propagate across brain tissue. In an artificial neural network, we simulated wave propagation by passing transient neural firing patterns representative of single-item information across different network layers. In comparison to sustained neural firing, we demonstrate that these transient traveling waves result in minimal synaptic plasticity, thereby facilitating working memory updating without significant neural interference. We then identified such traveling waves in intracranial recordings from the human temporal lobe. Traveling waves started precisely when information was being encoded and persisted uniformly throughout maintenance and recall, aligning with the activation pattern seen in the artificial neural network. In trials where participants committed memory errors, no such continuous traveling wave activity in the temporal lobe was observed. Our data from artificial neural networks and human intracranial brain recordings converge to indicate that neural traveling waves support information processing in working memory while minimizing interference during updating. This reported mechanism, together with the classical working memory models, serves as a mutually complementary, multi-mechanistic framework for working memory storage.