Individual Neurons Research Articles

Structural, Functional and Molecular Dynamics Examination of a de novo cloned Otopetrin-like Proton Channel in crayfish.

Proton channels play a crucial role in many biological functions, as they are responsible for the selective transport of protons across cell membranes. Recently, Otopetrins, a family of eukaryotic proton-selective ion channels, have attracted significant attention due to their diverse physiological roles. Despite the importance of Otopetrins, their structural and functional properties remain relatively unexplored. As a model organism, crayfish have been extensively studied to gain insights into the functioning of the nervous system. These studies cover a wide range of aspects, including the properties of individual neurons and behavioral science. However, studying the physiological systems of crayfish poses challenges for molecular research due to limited molecular sequence information available for these organisms. In the present work was identified an originally cloned mRNA, coding an Otopetrin like proton channel in the crayfish. The coded protein was modeled in silico and possible conduction mechanisms and pathways were revealed. A plasmid of the cloned mRNA was heterologously expressed in HEK293T cells. Functional experiments on transfected cells indicated that the expressed mRNA was coupled to proton conduction across the cell membrane.

Different state-dependence of population codes across cortex.

During perceptual decision-making, behavioral performance varies with changes in internal states such as arousal, motivation, and strategy. Yet it is unknown how these internal states affect information coding across cortical regions involved in differing aspects of sensory perception and decision-making. We recorded neural activity from the primary auditory cortex (AC) and posterior parietal cortex (PPC) in mice performing a navigation-based sound localization task. We then modeled transitions in the behavioral strategies mice used during task performance. Mice transitioned between three latent performance states with differing decision-making strategies: an 'optimal' state and two 'sub-optimal' states characterized by choice bias and frequent errors. Performance states strongly influenced population activity patterns in association but not sensory cortex. Surprisingly, activity of individual PPC neurons was better explained by external inputs and behavioral variables during suboptimal behavioral performance than in the optimal performance state. Furthermore, shared variability across neurons (coupling) in PPC was strongest in the optimal state. In AC, shared variability was similarly weak across all performance states. Together, these findings indicate that neural activity in association cortex is more strongly linked to internal state than in sensory cortex.

Some aspects of bidomain modeling with volume conductors

The concept of dynamic multiscaling has changed our approach to multi-neuronal cable theory. Previously, computational neuroscientists considered individual neurons as neural masses or compartmental models, but now, a distributed representation of single neurons as ionic cable structures is most likely to lead to a greater understanding of how the distribution of ionic channels and synaptic input along the dendrites of a few neurons can offset the collective behavior of a large ensemble of neurons and, therefore, provide a measure of the dynamical brain. This change in perspective forms the basis of volume conductor-bidomain modeling, a new method that captures multiscalar electrophysiology.

Activity-dependent dendrite patterning in the postnatal barrel cortex.

For neural circuit construction in the brain, coarse neuronal connections are assembled prenatally following genetic programs, being reorganized postnatally by activity-dependent mechanisms to implement area-specific computational functions. Activity-dependent dendrite patterning is a critical component of neural circuit reorganization, whereby individual neurons rearrange and optimize their presynaptic partners. In the rodent primary somatosensory cortex (barrel cortex), driven by thalamocortical inputs, layer 4 (L4) excitatory neurons extensively remodel their basal dendrites at neonatal stages to ensure specific responses of barrels to the corresponding individual whiskers. This feature of barrel cortex L4 neurons makes them an excellent model, significantly contributing to unveiling the activity-dependent nature of dendrite patterning and circuit reorganization. In this review, we summarize recent advances in our understanding of the activity-dependent mechanisms underlying dendrite patterning. Our focus lays on the mechanisms revealed by in vivo time-lapse imaging, and the role of activity-dependent Golgi apparatus polarity regulation in dendrite patterning. We also discuss the type of neuronal activity that could contribute to dendrite patterning and hence connectivity.

Cellular resolution contributions to ictal population signals.

The increased amplitude of ictal activity is a common feature of epileptic seizures, but the determinants of this amplitude have not been identified. Clinically, ictal amplitudes are measured electrographically (using, e.g., electroencephalography, electrocorticography, and depth electrodes), but these methods do not enable the assessment of the activity of individual neurons. Population signal may increase from three potential sources: (1) increased synchrony (i.e., more coactive neurons); (2) altered active state, from bursts of action potentials and/or paroxysmal depolarizing shifts in membrane potential; and (3) altered subthreshold state, which includes all lower levels of activity. Here, we quantify the fraction of ictal signal from each source. To identify the cellular determinants of the ictal signal, we measured single cell and population electrical activity and neuronal calcium levels via optical imaging of the genetically encoded calcium indicator (GECI) GCaMP. Spontaneous seizure activity was assessed with microendoscopy in an APP/PS1 mouse with focal cortical injury and via widefield imaging in the organotypic hippocampal slice cultures (OHSCs) model of posttraumatic epilepsy. Single cell calcium signals were linked to a range of electrical activities by performing simultaneous GECI-based calcium imaging and whole-cell patch-clamp recordings in spontaneously seizing OHSCs. Neuronal resolution calcium imaging of spontaneous seizures was then used to quantify the cellular contributions to population-level ictal signal. The seizure onset signal was primarily driven by increased subthreshold activity, consistent with either barrages of excitatory postsynaptic potentials or sustained membrane depolarization. Unsurprisingly, more neurons entered the active state as seizure activity progressed. However, the increasing fraction of active cells was primarily driven by synchronous reactivation and not from continued recruitment of new populations of neurons into the seizure. This work provides a critical link between single neuron activity and population measures of seizure activity.

Two distinct mechanisms of Plexin A function in Drosophila optic lobe lamination and morphogenesis.

Visual circuit development is characterized by subdivision of neuropils into layers that house distinct sets of synaptic connections. We find that, in the Drosophila medulla, this layered organization depends on the axon guidance regulator Plexin A. In Plexin A null mutants, synaptic layers of the medulla neuropil and arborizations of individual neurons are wider and less distinct than in controls. Analysis of semaphorin function indicates that Semaphorin 1a, acting in a subset of medulla neurons, is the primary partner for Plexin A in medulla lamination. Removal of the cytoplasmic domain of endogenous Plexin A has little effect on the formation of medulla layers; however, both null and cytoplasmic domain deletion mutations of Plexin A result in an altered overall shape of the medulla neuropil. These data suggest that Plexin A acts as a receptor to mediate morphogenesis of the medulla neuropil, and as a ligand for Semaphorin 1a to subdivide it into layers. Its two independent functions illustrate how a few guidance molecules can organize complex brain structures by each playing multiple roles.

ОДНОВИМІРНА ЗГОРТКОВА МОДЕЛЬ НЕЙРОННОЇ МЕРЕЖІ ДЛЯ ОБРОБЛЕННЯ СИГНАЛІВ З АМПЛІТУДНОЮ МОДУЛЯЦІЄЮ БАГАТЬОХ СКЛАДОВИХ

The processing of radio signals using artificial neural networks (ANNs) has great potential for research, which can be explained by the adaptability of ANNs to various transmission conditions and the ability to detect abstract patterns of changes in signal parameters. The article reviews the works of other authors devoted to different ways of using ANNs for processing radio signals. Taking into account the information in the reviewed works, the research task was formed, which consists in developing an optimized ANN model for radio signal processing. Signals with amplitude modulation of many components (AMMC) were chosen to form training samples for ANN. The choice of modulation type is justified by greater energy efficiency compared to other widely used digital modulation types, such as quadrature amplitude modulation. Mathematic basis of AMMC signal generation is described. The process of finding the coordinates of three component 8-AMMC signal constellation is explained, the formation of signals in the time plane based on the found coordinates is explained as well as their discretization and the addition of white noise. An iterative algorithm for generating initial data for ANN based on the described ratios is proposed. The general structure of one-dimensional convolutional neural network is considered. Functions of individual neurons, connections between them, the formation of layers and the convolution operation are described mathematically. On the basis of the previously given ratios, a final display of the network was formed. Specific dimensions and activation functions for layers are selected. The use of convolutional layers is justified by time invariance. Based on the reviewed mathematical models, selected activation functions and dimensions, a neural model was formed. The process of validating the effectiveness of the formed neural model is described, which is based on comparing the symbolic error probabilities of the proposed and reference models at different signal-to-noise ratios. The validation results are presented. The advantages of the obtained model over the previously proposed purely recurrent model and the AMMC reference receiver are explained.

The Determining Role of Covariances in Large Networks of Stochastic Neurons.

Biological neural networks are notoriously hard to model due to their stochastic behavior and high dimensionality. We tackle this problem by constructing a dynamical model of both the expectations and covariances of the fractions of active and refractory neurons in the network's populations. We do so by describing the evolution of the states of individual neurons with a continuous-time Markov chain, from which we formally derive a low-dimensional dynamical system. This is done by solving a moment closure problem in a way that is compatible with the nonlinearity and boundedness of the activation function. Our dynamical system captures the behavior of the high-dimensional stochastic model even in cases where the mean-field approximation fails to do so. Taking into account the second-order moments modifies the solutions that would be obtained with the mean-field approximation and can lead to the appearance or disappearance of fixed points and limit cycles. We moreover perform numerical experiments where the mean-field approximation leads to periodically oscillating solutions, while the solutions of the second-order model can be interpreted as an average taken over many realizations of the stochastic model. Altogether, our results highlight the importance of including higher moments when studying stochastic networks and deepen our understanding of correlated neuronal activity.

Multifunctional and Flexible Neural Probe with Thermally Drawn Fibers for Bidirectional Synaptic Probing in the Brain.

Synapses in the brain utilize two distinct communication mechanisms: chemical and electrical. For a comprehensive investigation of neural circuitry, neural interfaces should be capable of both monitoring and stimulating these types of physiological interactions. However, previously developed interfaces for neurotransmitter monitoring have been limited in interaction modality due to constraints in device size, fabrication techniques, and the usage of flexible materials. To address this obstacle, we propose a multifunctional and flexible fiber probe fabricated through the microwire codrawing thermal drawing process, which enables the high-density integration of functional components with various materials such as polymers, metals, and carbon fibers. The fiber enables real-time monitoring of transient dopamine release in vivo, real-time stimulation of cell-specific neuronal populations via optogenetic stimulation, single-unit electrophysiology of individual neurons localized to the tip of the neural probe, and chemical stimulation via drug delivery. This fiber will improve the accessibility and functionality of bidirectional interrogation of neurochemical mechanisms in implantable neural probes.

Speckle-enabled in vivo demixing of neural activity in the mouse brain.

Functional imaging of neuronal activity in awake animals, using a combination of fluorescent reporters of neuronal activity and various types of microscopy modalities, has become an indispensable tool in neuroscience. While various imaging modalities based on one-photon (1P) excitation and parallel (camera-based) acquisition have been successfully used for imaging more transparent samples, when imaging mammalian brain tissue, due to their scattering properties, two-photon (2P) microscopy systems are necessary. In 2P microscopy, the longer excitation wavelengths reduce the amount of scattering while the diffraction-limited 3D localization of excitation largely eliminates out-of-focus fluorescence. However, this comes at the cost of time-consuming serial scanning of the excitation spot and more complex and expensive instrumentation. Thus, functional 1P imaging modalities that can be used beyond the most transparent specimen are highly desirable. Here, we transform light scattering from an obstacle into a tool. We use speckles with their unique patterns and contrast, formed when fluorescence from individual neurons propagates through rodent cortical tissue, to encode neuronal activity. Spatiotemporal demixing of these patterns then enables functional recording of neuronal activity from a group of discriminable sources. For the first time, we provide an experimental, in vivo characterization of speckle generation, speckle imaging and speckle-assisted demixing of neuronal activity signals in the scattering mammalian brain tissue. We found that despite an initial fast speckle decorrelation, substantial correlation was maintained over minute-long timescales that contributed to our ability to demix temporal activity traces in the mouse brain in vivo. Informed by in vivo quantifications of speckle patterns from single and multiple neurons excited using 2P scanning excitation, we recorded and demixed activity from several sources excited using 1P oblique illumination. In our proof-of-principle experiments, we demonstrate in vivo speckle-assisted demixing of functional signals from groups of sources in a depth range of 220-320 µm in mouse cortex, limited by available speckle contrast. Our results serve as a basis for designing an in vivo functional speckle imaging modality and for maximizing the key resource in any such modality, the speckle contrast. We anticipate that our results will provide critical quantitative guidance to the community for designing techniques that overcome light scattering as a fundamental limitation in bioimaging.

Multimodal convergence in the pedunculopontine tegmental nucleus: Motor, sensory and theta-frequency inputs influence activity of single neurons.

The pedunculopontine tegmental nucleus of the brainstem (PPTg) has extensive interconnections and neuronal-behavioural correlates. It is implicated in movement control and sensorimotor integration. We investigated whether single neuron activity in freely moving rats is correlated with components of skilled forelimb movement, and whether individual neurons respond to both motor and sensory events. We found that individual PPTg neurons showed changes in firing rate at different times during the reach. This type of temporally specific modulation is like activity seen elsewhere in voluntary movement control circuits, such as the motor cortex, and suggests that PPTg neural activity is related to different specific events occurring during the reach. In particular, many neuronal modulations were time-locked to the end of the extension phase of the reach, when fine distal movements related to food grasping occur, indicating strong engagement of PPTg in this phase of skilled individual forelimb movements. In addition, some neurons showed brief periods of apparent oscillatory firing in the theta range at specific phases of the reach-to-grasp movement. When movement-related neurons were tested with tone stimuli, many also responded to this auditory input, allowing for sensorimotor integration at the cellular level. Together, these data extend the concept of the PPTg as an integrative structure in generation of complex movements, by showing that this function extends to the highly coordinated control of the forelimb during skilled reach to grasp movement, and that sensory and motor-related information converges on single neurons, allowing for direct integration at the cellular level.

Changes in preBötzinger Complex neuron discharge associated with changes in PCO2 in decerebrate rabbits

Background: Maskrey and Nicol reported a strong increase in minute ventilation with increase in PCO2 (J Physiol 1980, 301: 49-58). We investigated a) whether there was a ceiling to this effect at high CO2 levels and b) whether the change in ventilation was associated with specific changes in respiratory neurons in the preBötzinger complex (preBC). Methods: The study was approved by the local Animal Care Committee and conformed to NIH standards. Adult New Zealand White rabbits (3-4 kg) were anesthetized, tracheotomized, ventilated, decerebrated and vagotomized. Phrenic nerve activity was recorded from the C5 rootlet, time averaged and used to calculate inspiratory (TI) and expiratory durations (TE) and peak phrenic activity (PPA). PPA was normalized to the value at PCO2 50mmHg. Individual neurons were recorded in the functionally identified preBC using multichannel electrodes at increasing CO2 levels. Statistical analysis used the Wilcoxon signed-rank test to determine changes in respiratory parameters between CO2 levels and Friedman RM-ANOVA to determine changes in neuronal discharge frequency (Fn). A generalized linear mixed model was used to determine associations between CO2-dependent changes in TI, TE, PPA, and changes in Fn for different neuron types. p<0.05 indicated a significant difference. Results: In 34 animals, the increase in minute ventilation with increasing PCO2 was due mostly to the change in PPA. The increase in respiratory rate was due mostly to a decrease in TE. There was little increase in respiratory output at PCO2 > 50 mmHg. In 209 neurons, increasing PCO2 increased Fn in inspiratory augmenting (I aug, n= 70, p<0.0001 for CO2 30 vs 40 and 40 vs 50mmHg), I parabolic (I para, n=43, p<0.0001 for CO2 40 vs 50 mmHg), pre-inspiratory (pre-I, n=35, p<0.01 for CO2 30 vs 40 mmHg), and expiratory decrementing (E dec, n=44, p<0.01 for CO2 40 vs 50 mmHg) neurons, but not in I dec (n=8) and non-respiratory modulated (NRM, n=9) neurons. The strongest correlation was found between the changes in phase timing and PPA and Fn in I aug and pre-I neurons. Conclusion: We found a ceiling effect to the increase in respiratory output at PCO2 levels > 50 mmHg. Inspiratory preBC neuron subtypes were more affected by the changes in PCO2. NIH R01HL159546. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Identification of Spinal Afferent Innervation in the Rat Heart: Atria and Ventricles: Anterograde Tracing

The spinal afferent innervation of the heart regulates cardiac functions by sending sensory information from the dorsal root ganglia (DRG) to the brain. However, the distribution and morphology of spinal afferents in the whole heart are not well characterized. The challenges here are: 1) diffculty in surgically accessing the upper thoracic DRG to label only cardiac spinal afferents. 2) handling flat-mounts of whole atria and ventricles (thickness ~850 μm) without using sections or partial tissues that could disrupt the continuity of axonal structures. To overcome these challenges, we injected anterograde tracer dextran biotin (DB) into the left DRG (C8-T3) of male SD rats (3-5 months) and allowed them to recover for 14 days for tracer transportation. Flat-mounts of the left and right atria and ventricles were prepared, and DAB (3,3′-Diaminobenzidine) stained, followed by imaging, tracing, and digitization using the Neurolucida system. Our findings are: In the atria, the DB-labeled axons entered the atria potentially through the left precaval vein (LPCV), with predominant innervation of the left side of the atrial wall and extended their projection towards the auricles, middle region of the atrium, and pulmonary veins. Most of the spinal afferent axons were present in the myocardial layer. Varicose DB-labeled axons were also observed on cardiac targets at different regions, and distinct morphological structures were found. In the cardiac muscle, DB-labeled axons ran mainly in the direction of muscle fibers. Also, varicose axons ran along the small vasculature on the atria. Spinal afferents formed varicose contacts with individual principal neurons within some intrinsic cardiac ganglia (ICG). In the ventricles, DB-labeled axons were present in the left and right ventricles, which ramified and expressed spherical-like varicosities on the cardiac muscle. In both the atria and ventricles, spinal afferent axons formed simple, branching, and complex terminal structures. Thus, our work, for the first time, successfully labeled, traced, and digitized the spinal cardiac afferents in the flat-mounts of whole atria and ventricles, which will provide a foundation for specific labeling of cardiac spinal afferent fibers. In addition, it will lead to the future study of topographical cardiac spinal afferent innervation, functional studies, and their remodeling in pathological conditions. This study was supported by NIH HEAL/SPARC U01 NS113867-01, NIH R15 R15HL137143-01A1, and UCF dissertation completion Fellowships. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Drosophila learning and memory centers and the actions of drugs of abuse.

Drug addiction and the circuitry for learning and memory are intimately intertwined. Drugs of abuse create strong, inappropriate, and lasting memories that contribute to many of their destructive properties, such as continued use despite negative consequences and exceptionally high rates of relapse. Studies in Drosophila melanogaster are helping us understand how drugs of abuse, especially alcohol, create memories at the level of individual neurons and in the circuits where they function. Drosophila is a premier organism for identifying the mechanisms of learning and memory. Drosophila also respond to drugs of abuse in ways that remarkably parallel humans and rodent models. An emerging consensus is that, for alcohol, the mushroom bodies participate in the circuits that control acute drug sensitivity, not explicitly associative forms of plasticity such as tolerance, and classical associative memories of their rewarding and aversive properties. Moreover, it is becoming clear that drugs of abuse use the mushroom body circuitry differently from other behaviors, potentially providing a basis for their addictive properties.

Aberrant cortical activity, functional connectivity, and neural assembly architecture after photothrombotic stroke in mice.

Despite substantial progress in mapping the trajectory of network plasticity resulting from focal ischemic stroke, the extent and nature of changes in neuronal excitability and activity within the peri-infarct cortex of mice remains poorly defined. Most of the available data have been acquired from anesthetized animals, acute tissue slices, or infer changes in excitability from immunoassays on extracted tissue, and thus may not reflect cortical activity dynamics in the intact cortex of an awake animal. Here, in vivo two-photon calcium imaging in awake, behaving mice was used to longitudinally track cortical activity, network functional connectivity, and neural assembly architecture for 2 months following photothrombotic stroke targeting the forelimb somatosensory cortex. Sensorimotor recovery was tracked over the weeks following stroke, allowing us to relate network changes to behavior. Our data revealed spatially restricted but long-lasting alterations in somatosensory neural network function and connectivity. Specifically, we demonstrate significant and long-lasting disruptions in neural assembly architecture concurrent with a deficit in functional connectivity between individual neurons. Reductions in neuronal spiking in peri-infarct cortex were transient but predictive of impairment in skilled locomotion measured in the tapered beam task. Notably, altered neural networks were highly localized, with assembly architecture and neural connectivity relatively unaltered a short distance from the peri-infarct cortex, even in regions within 'remapped' forelimb functional representations identified using mesoscale imaging with anaesthetized preparations 8 weeks after stroke. Thus, using longitudinal two-photon microscopy in awake animals, these data show a complex spatiotemporal relationship between peri-infarct neuronal network function and behavioral recovery. Moreover, the data highlight an apparent disconnect between dramatic functional remapping identified using strong sensory stimulation in anaesthetized mice compared to more subtle and spatially restricted changes in individual neuron and local network function in awake mice during stroke recovery.

Aberrant cortical activity, functional connectivity, and neural assembly architecture after photothrombotic stroke in mice

Despite substantial progress in mapping the trajectory of network plasticity resulting from focal ischemic stroke, the extent and nature of changes in neuronal excitability and activity within the peri-infarct cortex of mice remains poorly defined. Most of the available data have been acquired from anesthetized animals, acute tissue slices, or infer changes in excitability from immunoassays on extracted tissue, and thus may not reflect cortical activity dynamics in the intact cortex of an awake animal. Here, in vivo two-photon calcium imaging in awake, behaving mice was used to longitudinally track cortical activity, network functional connectivity, and neural assembly architecture for 2 months following photothrombotic stroke targeting the forelimb somatosensory cortex. Sensorimotor recovery was tracked over the weeks following stroke, allowing us to relate network changes to behavior. Our data revealed spatially restricted but long-lasting alterations in somatosensory neural network function and connectivity. Specifically, we demonstrate significant and long-lasting disruptions in neural assembly architecture concurrent with a deficit in functional connectivity between individual neurons. Reductions in neuronal spiking in peri-infarct cortex were transient but predictive of impairment in skilled locomotion measured in the tapered beam task. Notably, altered neural networks were highly localized, with assembly architecture and neural connectivity relatively unaltered a short distance from the peri-infarct cortex, even in regions within ‘remapped’ forelimb functional representations identified using mesoscale imaging with anaesthetized preparations 8 weeks after stroke. Thus, using longitudinal two-photon microscopy in awake animals, these data show a complex spatiotemporal relationship between peri-infarct neuronal network function and behavioral recovery. Moreover, the data highlight an apparent disconnect between dramatic functional remapping identified using strong sensory stimulation in anaesthetized mice compared to more subtle and spatially restricted changes in individual neuron and local network function in awake mice during stroke recovery.

A novel method for culturing enteric neurons generates neurospheres containing functional myenteric neuronal subtypes

BackgroundThe enteric nervous system (ENS) is comprised of neurons, glia, and neural progenitor cells that regulate essential gastrointestinal functions. Advances in high-efficiency enteric neuron culture would facilitate discoveries surrounding ENS regulatory processes, pathophysiology, and therapeutics. New methodDevelopment of a simple, robust, one-step method to culture murine enteric neurospheres in a 3D matrix that supports neural growth and differentiation. ResultsMyenteric plexus cells isolated from the entire length of adult murine small intestine formed ≥3000 neurospheres within 7 days. Matrigel-embedded neurospheres exhibited abundant neural stem and progenitor cells expressing Sox2, Sox10 and Msi1 by day 4. By day 5, neural progenitor cell marker Nestin appeared in the periphery of neurospheres prior to differentiation. Neurospheres produced extensive neurons and neurites, confirmed by Tubulin beta III, PGP9.5, HuD/C, and NeuN immunofluorescence, including neural subtypes Calretinin, ChAT, and nNOS following 8 days of differentiation. Individual neurons within and external to neurospheres generated depolarization induced action potentials which were inhibited in the presence of sodium channel blocker, Tetrodotoxin. Differentiated neurospheres also contained a limited number of glia and endothelial cells. Comparison with existing methodsThis novel one-step neurosphere growth and differentiation culture system, in 3D format (in the presence of GDNF, EGF, and FGF2), allows for ∼2-fold increase in neurosphere count in the derivation of enteric neurons with measurable action potentials. ConclusionOur method describes a novel, robust 3D culture of electrophysiologically active enteric neurons from adult myenteric neural stem and progenitor cells.

Location analysis of presynaptically active and silent synapses in single-cultured hippocampal neurons.

A morphologically present but non-functioning synapse is termed a silent synapse. Silent synapses are categorized into "postsynaptically silent synapses," where AMPA receptors are either absent or non-functional, and "presynaptically silent synapses," where neurotransmitters cannot be released from nerve terminals. The presence of presynaptically silent synapses remains enigmatic, and their physiological significance is highly intriguing. In this study, we examined the distribution and developmental changes of presynaptically active and silent synapses in individual neurons. Our findings show a gradual increase in the number of excitatory synapses, along with a corresponding decrease in the percentage of presynaptically silent synapses during neuronal development. To pinpoint the distribution of presynaptically active and silent synapses, i.e., their positional information, we employed Sholl analysis. Our results indicate that the distribution of presynaptically silent synapses within a single neuron does not exhibit a distinct pattern during synapse development in different distance from the cell body. However, irrespective of neuronal development, the proportion of presynaptically silent synapses tends to rise as the projection site moves farther from the cell body, suggesting that synapses near the cell body may exhibit higher synaptic transmission efficiency. This study represents the first observation of changes in the distribution of presynaptically active and silent synapses within a single neuron.

Sparse Firing in a Hybrid Central Pattern Generator for Spinal Motor Circuits.

Central pattern generators are circuits generating rhythmic movements, such as walking. The majority of existing computational models of these circuits produce antagonistic output where all neurons within a population spike with a broad burst at about the same neuronal phase with respect to network output. However, experimental recordings reveal that many neurons within these circuits fire sparsely, sometimes as rarely as once within a cycle. Here we address the sparse neuronal firing and develop a model to replicate the behavior of individual neurons within rhythm-generating populations to increase biological plausibility and facilitate new insights into the underlying mechanisms of rhythm generation. The developed network architecture is able to produce sparse firing of individual neurons, creating a novel implementation for exploring the contribution of network architecture on rhythmic output. Furthermore, the introduction of sparse firing of individual neurons within the rhythm-generating circuits is one of the factors that allows for a broad neuronal phase representation of firing at the population level. This moves the model toward recent experimental findings of evenly distributed neuronal firing across phases among individual spinal neurons. The network is tested by methodically iterating select parameters to gain an understanding of how connectivity and the interplay of excitation and inhibition influence the output. This knowledge can be applied in future studies to implement a biologically plausible rhythm-generating circuit for testing biological hypotheses.

Exploring Present and Future Directions in Nano-Enhanced Optoelectronic Neuromodulation.

Electrical neuromodulation has achieved significant translational advancements, including the development of deep brain stimulators for managing neural disorders and vagus nerve stimulators for seizure treatment. Optoelectronics, in contrast to wired electrical systems, offers the leadless feature that guides multisite and high spatiotemporal neural system targeting, ensuring high specificity and precision in translational therapies known as "photoelectroceuticals". This Account provides a concise overview of developments in novel optoelectronic nanomaterials that are engineered through innovative molecular, chemical, and nanostructure designs to facilitate neural interfacing with high efficiency and minimally invasive implantation.This Account outlines the progress made both within our laboratory and across the broader scientific community, with particular attention to implications in materials innovation strategies, studying bioelectrical activation with spatiotemporal methods, and applications in regenerative medicine. In materials innovation, we highlight a nongenetic, biocompatible, and minimally invasive approach for neuromodulation that spans various length scales, from single neurons to nerve tissues using nanosized particles and monolithic membranes. Furthermore, our discussion exposes the critical unresolved questions in the field, including mechanisms of interaction at the nanobio interface, the precision of cellular or tissue targeting, and integration into existing neural networks with high spatiotemporal modulation. In addition, we present the challenges and pressing needs for long-term stability and biocompatibility, scalability for clinical applications, and the development of noninvasive monitoring and control systems.In addressing the existing challenges in the field of nanobio interfaces, particularly for neural applications, we envisage promising strategic directions that could significantly advance this burgeoning domain. This involves a deeper theoretical understanding of nanobiointerfaces, where simulations and experimental validations on how nanomaterials interact spatiotemporally with biological systems are crucial. The development of more durable materials is vital for prolonged applications in dynamic neural interfaces, and the ability to manipulate neural activity with high specificity and spatial resolution, paves the way for targeting individual neurons or specific neural circuits. Additionally, integrating these interfaces with advanced control systems, possibly leveraging artificial intelligence and machine learning algorithms and programming dynamically responsive materials designs, could significantly ease the implementation of stimulation and recording. These innovations hold the potential to introduce novel treatment modalities for a wide range of neurological and systemic disorders.