Imaging Calcium in Neurons

Sg-snn: a self-organizing spiking neural network based on temporal information

Neurodynamic observations indicate that the cerebral cortex evolved by self-organizing into functional networks, These networks, or distributed clusters of regions, display various degrees of attention maps based on input. Traditionally, the study of network self-organization relies predominantly on static data, overlooking temporal information in dynamic neuromorphic data. This paper proposes Temporal Self-Organizing (TSO) method for neuromorphic data processing using a spiking neural network. The TSO method incorporates information from multiple time steps into the selection strategy of the Best Matching Unit (BMU) neurons. It enables the coupled BMUs to radiate the weight across the same layer of neurons, ultimately forming a hierarchical self-organizing topographic map of concern. Additionally, we simulate real neuronal dynamics, introduce a glial cell-mediated Glial-LIF (Leaky Integrate-and-fire) model, and adjust multiple levels of BMUs to optimize the attention topological map.Experiments demonstrate that the proposed Self-organizing Glial Spiking Neural Network (SG-SNN) can generate attention topographies for dynamic event data from coarse to fine. A heuristic method based on cognitive science effectively guides the network's distribution of excitatory regions. Furthermore, the SG-SNN shows improved accuracy on three standard neuromorphic datasets: DVS128-Gesture, CIFAR10-DVS, and N-Caltech 101, with accuracy improvements of 0.3%, 2.4%, and 0.54% respectively. Notably, the recognition accuracy on the DVS128-Gesture dataset reaches 99.3%, achieving state-of-the-art (SOTA) performance.

Calcium Imaging in Vivo: How to Correctly Select and Apply Fiber Optic Photometric Indicators

Fiber-photometric is a novel optogenetic method for recording neural activity in vivo, which allows the use of calcium indicators to observe and study the relationship between neural activity and behavior in free-ranging animals. Calcium indicators also convert changes in calcium concentration in cells or tissues into recordable fluorescent signals, which can then be observed using the system of fiber-photometric. To date, there is a paucity of relevant literature on the proper selection and application of fiber-photometric indicators. Therefore, this paper will detail how to correctly select and apply fiber-photometer indicators in four sections: the basic principle of optical fiber photometry, the selection of calcium fluorescent probes and viral vector systems, and the measurement of specific expression of fluorescent proteins in specific tissues. Therefore, the correct use of suitable fiber optic recording indicators will greatly assist researchers in exploring the link between neuronal activity and neuropsychiatric disorders.

Activation of Epac2 improves Aβ-induced impairment of memory retrieval in an acute model of Alzheimer's disease

Impaired memory retrieval is one of the cognitive markers in the early stage of Alzheimer's Disease (AD). Previous studies report that exchange protein directly activated by cAMP 2 (Epac2) plays a specific and time-limited role in promoting memory retrieval. In this study, we investigated the effect of a novel Epac2 activator, S220, on neuronal and synaptic activities, and memory impairment in an acute AD mouse model. S220 treatment increased the firing rate of action potential and intracellular calcium in primary neuronal cultures. Moreover, S220 treatment increased synaptic currents in CA1 neurons. In the acute AD mouse model, intrahippocampal injection of amyloid-β (Aβ) oligomers impaired memory performance. Notably, administering S220 20 min before retention of contextual fear conditioning recovered the Aβ-induced memory impairment, suggesting an enhancing effect on memory retrieval. Collectively, our data demonstrate that the novel Epac2 activator S220 promotes synaptic communication and neuronal firing, and thereby improves Aβ-induced memory impairment via enhancing memory retrieval, indicating the role of Epac2 as a potential treatment target for AD.

Physiological noise: a comprehensive review on informative randomness in neural systems

Noise is often regarded as mere interference in the analysis of biomedical signals. Nonetheless, stochasticity plays a critical and informative role in the dynamics of complex systems, particularly in neurocardiovascular and neural systems. This review provides a comprehensive exploration on informative randomness in physiological contexts, tracing the evolution of noise research from its foundations on Brownian motion to its applications in neural systems, including the neuroautonomic regulation of cardiovascular dynamics. Key distinctions are made between output (measurement) noise and dynamic (intrinsic) noise, which directly influence the system behaviors at various levels. Several physiological noise identification techniques, such as stochastic differential equations, Bayesian methods, and Kalman filters, are evaluated in real-world scenarios. Special emphasis is placed on the role of physiological noise in multiscale neural systems, such as brain dynamics, neuronal communication, and heart-brain interactions, highlighting how it shapes complex functions. Furthermore, physiological noise is presented as a potential clinical biomarker, offering insights into the underlying structure and health of neural systems. Future research is encouraged to investigate multivariate noise estimation methods and their implications for understanding causality and systemic interactions in neurocardiovascular networks.

Integration of signal transduction pathways in sensory epithelial enteroendocrine cells

The gastrointestinal (GI) tract plays a crucial role in nutrient absorption, motility, and metabolism, while serving as a barrier against pathogens. The intestinal epithelial layer, particularly enteroendocrine cells (EEC), is pivotal in sensing luminal stimuli due to its strategic position. Although comprising only 1% of the GI epithelium, in total EEC comprises perhaps the largest endocrine organ that couples GI luminal stimuli with release of hormones and neurotransmitters such as serotonin, glucagon-like peptide-1 (GLP-1), and peptide-tyrosine-tyrosine (PYY), which regulate local and systemic physiology. In this review, we use EECs as a model to explore critical intracellular signaling pathways-centering around calcium (Ca²⁺) and cyclic adenosine monophosphate (cAMP). EECs utilize ionotropic and metabotropic receptors to detect luminal stimuli, leading to increased intracellular cytoplasmic Ca²⁺ and altered intracellular cAMP dynamics. Ca²⁺ influx is critical for the exocytosis of signaling molecules. The interplay between Ca²⁺ and cAMP signaling pathways enhances the release of these molecules, affecting both local and systemic responses. We make a point to discuss the conventional and emerging methodologies for measuring Ca²⁺ and cAMP dynamics in EECs, which is a rapidly expanding toolbox, containing genetically encoded indicators and resonance energy transfer techniques. Understanding these signaling cascades is essential for deciphering the complex roles of EECs in GI physiology and their impact on systemic health.

Probing neuronal activity with genetically encoded calcium and voltage fluorescent indicators

Monitoring neural activity in individual neurons is crucial for understanding neural circuits and brain functions. The emergence of optical imaging technologies has dramatically transformed the field of neuroscience, enabling detailed observation of large-scale neuronal populations with both cellular and subcellular resolution. This transformation will be further accelerated by the integration of these imaging technologies and advanced big data analysis. Genetically encoded fluorescent indicators to detect neural activity with high signal-to-noise ratios are pivotal in this advancement. In recent years, these indicators have undergone significant developments, greatly enhancing the understanding of neural dynamics and networks. This review highlights the recent progress in genetically encoded calcium and voltage indicators and discusses the future direction of imaging techniques with big data analysis that deepens our understanding of the complexities of the brain.

Inference of monosynaptic connections from parallel spike trains: A review

This article presents a mini-review about the progress in inferring monosynaptic connections from spike trains of multiple neurons over the past twenty years. First, we explain a variety of meanings of "neuronal connectivity" in different research areas of neuroscience, such as structural connectivity, monosynaptic connectivity, and functional connectivity. Among these, we focus on the methods used to infer the monosynaptic connectivity from spike data. We then summarize the inference methods based on two main approaches, i.e., correlation-based and model-based approaches. Finally, we describe available source codes for connectivity inference and future challenges. Although inference will never be perfect, the accuracy of identifying the monosynaptic connections has improved dramatically in recent years due to continuous efforts.

Reveal the mechanism of brain function with fluorescence microscopy at single-cell resolution: from neural decoding to encoding

As a key pathway for understanding behavior, cognition, and emotion, neural decoding and encoding provide effective tools to bridge the gap between neural mechanisms and imaging recordings, especially at single-cell resolution. While neural decoding aims to establish an interpretable theory of how complex biological behaviors are represented in neural activities, neural encoding focuses on manipulating behaviors through the stimulation of specific neurons. We thoroughly analyze the application of fluorescence imaging techniques, particularly two-photon fluorescence imaging, in decoding neural activities, showcasing the theoretical analysis and technological advancements from imaging recording to behavioral manipulation. For decoding models, we compared linear and nonlinear methods, including independent component analysis, random forests, and support vector machines, highlighting their capabilities to reveal the intricate mapping between neural activity and behavior. By employing synthetic stimuli via optogenetics, fundamental principles of neural encoding are further explored. We elucidate various encoding types based on different stimulus paradigms-quantity encoding, spatial encoding, temporal encoding, and frequency encoding-enhancing our understanding of how the brain represents and processes information. We believe that fluorescence imaging-based neural decoding and encoding techniques have deepened our understanding of the brain, and hold great potential in paving the way for future neuroscience research and clinical applications.

Three-photon in vivo imaging of neurons and glia in the medial prefrontal cortex with sub-cellular resolution

The medial prefrontal cortex (mPFC) is important for higher cognitive functions, including working memory, decision making, and emotional control. In vivo recordings of neuronal activity in the mPFC have been achieved via invasive electrical and optical approaches. Here we apply low invasive three-photon in vivo imaging in the mPFC of the mouse at unprecedented depth. Specifically, we measure neuronal and astrocytic Ca2+-transient parameters in awake head-fixed mice up to a depth of 1700 µm. Furthermore, we longitudinally record dendritic spine density (0.41 ± 0.07 µm-1) deeper than 1 mm for a week. Using 1650 nm wavelength to excite red fluorescent microglia, we quantify their processes' motility (58.9 ± 2% turnover rate) at previously unreachable depths (1100 µm). We establish three-photon imaging of the mPFC enabling neuronal and glial recordings with subcellular resolution that will pave the way for novel discoveries in this brain region.

Low Intensity Pulsed Ultrasound Activates Excitatory Synaptic Networks in Cultured Hippocampal Neurons

OBJECTIVE

Ultrasound can noninvasively penetrate deep into the brain for neuromodulation, demonstrating good potential for clinical application. However, the underlying mechanisms are unclear. So far most in vitro studies have focused on the activation of individual neurons by ultrasound with calcium imaging. As the focal region of ultrasound is typically millimeter or submillimeter size, it is important to investigate yet so far unclear how the mechanical effects of ultrasound would influence the synaptic circuit activity of neurons.

METHODS

Low-intensity pulse ultrasound was used to stimulate cultured hippocampal neurons. Postsynaptic currents were recorded in individual cells with the whole-cell patch-clamp technique. We also simultaneously imaged intracellular calcium, along with neuronal electrical signals, to resolve neuronal network dynamics during ultrasound stimulation.

RESULTS

Excitatory postsynaptic currents (EPSCs) were evoked by ultrasound in high-density neuronal cultures with increased frequency and amplitude, indicating enhanced glutamatergic synaptic transmission. The probability of evoking responses and the total charge of EPSCs increased with ultrasound intensity. Mechanistic analysis reveals that extracellular calcium influx, action potential firing and synaptic transmission are necessary for the responses to ultrasound in high-density culture. In contrast, EPSCs were not enhanced in low-density culture. Simultaneous calcium imaging of neuronal network activity indicates that recurrent excitatory network activity is recruited during ultrasound stimulation in high-density cultures, which lasts over tens to hundreds of seconds.

CONCLUSION

Our study provides insights into the mechanisms involved in the response of the brain to ultrasound and illuminates the potential to use ultrasound to regulate synaptic function in neurological disorders.

Selectively vulnerable deep cortical layer 5/6 fast-spiking interneurons in Alzheimer's disease models in vivo

Alzheimer's disease (AD) is initiated by amyloid-beta (Aβ) accumulation in the neocortex; however, the cortical layers and neuronal cell types first susceptible to Aβ remain unknown. Using in vivo two-photon Ca2+ imaging in the visual cortex of AD mouse models, we found that cortical layer 5 neurons displayed abnormally prolonged Ca2+ transients before substantial plaque formation. Neuropixels recordings revealed that these abnormal transients were associated with reduced spiking and impaired visual tuning of parvalbumin (PV)-positive fast-spiking interneurons (FSIs) in layers 5/6, whereas PV-FSIs in superficial layers remained unaffected. These dysfunctions occurred alongside a deep-layer-specific reduction in neuronal pentraxin 2 (NPTX2) within excitatory neurons, decreased GluA4 in PV-FSIs, and fewer excitatory synapses onto PV-FSIs. Notably, NPTX2 overexpression increased excitatory input onto layers 5/6 PV-FSIs and rectified their spiking activity. Thus, our findings reveal an early selective impairment of deep cortical layers 5/6 in AD models and identify deep-layer PV-FSIs as therapeutic targets.

The Medaka approach to evolutionary social neuroscience

Previously, the integration of comparative biological and neuroscientific approaches has led to significant advancements in social neuroscience. This review highlights the potential and future directions of evolutionary social neuroscience research utilizing medaka fishes (the family Adrianichthyidae) including Japanese medaka (Oryzias latipes). We focus on medaka social cognitive capabilities and mate choice behavior, particularly emphasizing mate preference using visual cues. Medaka fishes are also advantageous due to their abundant genetic resources, extensive genomic information, and the relative ease of laboratory breeding and genetic manipulation. Here we present some research examples of both the conventional neuroscience approach and evolutionary approach involving medaka fishes and other species. We also discuss the prospects of uncovering the molecular and cellular mechanisms underlying the diversity of visual mate preference among species. Especially, we introduce that the single-cell transcriptome technology, particularly in conjunction with 'Adaptive Circuitry Census', is an innovative tool that bridges comparative biological methods and neuroscientific approaches. Evolutionary social neuroscience research using medaka has the potential to unveil fundamental principles in neuroscience and elucidate the mechanisms responsible for generating diversity in mating strategies.

Evidence for a push-pull interaction between superior colliculi in monocular dynamic vision mode

Visual perception can operate in two distinct vision modes-static and dynamic-that have been associated with different neural activity regimes in the superior colliculus (SC). However, the associated pathway-wide mechanisms remain poorly understood, especially in terms of corticotectal and tectotectal feedback upon encoding the continuity illusion during the dynamic vision mode. Here, we harness functional MRI combined with rat brain lesions to investigate whole-pathway neural interactions in the dynamic vision mode. We find a push-pull mechanism embodying contralateral suppression of SC activity opposing positive ipsilateral neural activation upon monocular visual stimulation. Cortical amplification is confirmed through cortical lesions, while further lesioning the ipsilateral SC leads to a boost in the contralateral SC negative signals, suggesting a tectal origin for the push-pull interaction. These results highlight hitherto unreported frequency-dependent modulations in the tectotectal pathway and further challenge the notion that intertectal connections solely serve as reciprocal inhibitory mechanisms for avoiding visual blur during saccades.

Interpretable deep learning for deconvolutional analysis of neural signals

The widespread adoption of deep learning to model neural activity often relies on "black-box" approaches that lack an interpretable connection between neural activity and network parameters. Here, we propose using algorithm unrolling, a method for interpretable deep learning, to design the architecture of sparse deconvolutional neural networks and obtain a direct interpretation of network weights in relation to stimulus-driven single-neuron activity through a generative model. We introduce our method, deconvolutional unrolled neural learning (DUNL), and demonstrate its versatility by applying it to deconvolve single-trial local signals across multiple brain areas and recording modalities. We uncover multiplexed salience and reward prediction error signals from midbrain dopamine neurons, perform simultaneous event detection and characterization in somatosensory thalamus recordings, and characterize the heterogeneity of neural responses in the piriform cortex and across striatum during unstructured, naturalistic experiments. Our work leverages advances in interpretable deep learning to provide a mechanistic understanding of neural activity.

A time window for memory consolidation during NREM sleep revealed by cAMP oscillation

Memory formation requires specific neural activity in coordination with intracellular signaling mediated by second messengers such as cyclic adenosine monophosphate (cAMP). However, the real-time dynamics of cAMP remain largely unknown. Here, using a genetically encoded cAMP sensor with high temporal resolution, we found neural-activity-dependent rapid cAMP elevation during learning. Interestingly, in slow-wave sleep, during which memory consolidation occurs, the cAMP level in mice was anti-correlated with neural activity and exhibited norepinephrine β1 receptor-dependent infra-slow oscillations that were synchronized across the hippocampus and cortex. Furthermore, the hippocampal-cortical interactions increased during the narrow time-window of the peak cAMP level; suppressing hippocampal activity specifically during this window impaired spatial memory consolidation. Thus, hippocampal-dependent memory consolidation occurs within a specific time window of high cAMP activity during slow-wave sleep.

Far-red fluorescent genetically encoded calcium ion indicators

Genetically encoded calcium ion (Ca2+) indicators (GECIs) are widely-used molecular tools for functional imaging of Ca2+ dynamics and neuronal activities with single-cell resolution. Here we report the design and development of two far-red fluorescent GECIs, FR-GECO1a and FR-GECO1c, based on the monomeric far-red fluorescent proteins mKelly1 and mKelly2. FR-GECOs have excitation and emission maxima at ~596 nm and ~644 nm, respectively, display large responses to Ca2+ in vitro (ΔF/F0 = 6 for FR-GECO1a, 18 for FR-GECO1c), are bright under both one-photon and two-photon illumination, and have high affinities (apparent Kd = 29 nM for FR-GECO1a, 83 nM for FR-GECO1c) for Ca2+. FR-GECOs offer sensitive and fast detection of single action potentials in neurons, and enable in vivo all-optical manipulation and measurement of cellular activities in combination with optogenetic actuators.

Exploring neuropharmacokinetics: mechanisms, models, and clinical implications

Neuropharmacokinetics is an emerging field dedicated to understanding the pharmacokinetics of drugs within the central nervous system (CNS), with a particular emphasis on overcoming the challenges posed by the blood-brain barrier. This paper reviews the latest advancements in drug delivery strategies, including nanoparticle-based systems, receptor-mediated transcytosis, and efflux transporter inhibition, which have been designed to enhance drug penetration into the brain. Additionally, the use of advanced imaging techniques such as positron emission tomography, functional magnetic resonance imaging, and magnetic resonance imaging with contrast agents has provided critical insights into drug distribution, receptor occupancy, and the functional impact of therapeutic agents within the CNS. These innovations not only enhance our understanding of CNS drug action but also pave the way for more effective treatments for neurological and psychiatric disorders.

A sensitive soma-localized red fluorescent calcium indicator for in vivo imaging of neuronal populations at single-cell resolution

Recent advancements in genetically encoded calcium indicators, particularly those based on green fluorescent proteins, have optimized their performance for monitoring neuronal activities in a variety of model organisms. However, progress in developing red-shifted GECIs, despite their advantages over green indicators, has been slower, resulting in fewer options for end users. In this study, we explored topological inversion and soma-targeting strategies, which are complementary to conventional mutagenesis, to re-engineer a red genetically encoded calcium indicator, FRCaMP, for enhanced in vivo performance. The resulting sensors, FRCaMPi and soma-targeted FRCaMPi (SomaFRCaMPi), exhibit up to 2-fold higher dynamic range and peak ΔF/F0 per single AP compared to widely used jRGECO1a in neurons both in culture and in vivo. Compared to jRGECO1a and FRCaMPi, SomaFRCaMPi reduces erroneous correlation of neuronal activity in the brains of mice and zebrafish by two- to 4-fold due to diminished neuropil contamination without compromising the signal-to-noise ratio. Under wide-field imaging in primary somatosensory and visual cortices in mice with high labeling density (80-90%), SomaFRCaMPi exhibits up to 40% higher SNR and decreased artifactual correlation across neurons. Altogether, SomaFRCaMPi improves the accuracy and scale of neuronal activity imaging at single-neuron resolution in densely labeled brain tissues due to a 2-3-fold enhanced automated neuronal segmentation, 50% higher fraction of responsive cells, up to 2-fold higher SNR compared to jRGECO1a. Our findings highlight the potential of SomaFRCaMPi, comparable to the most sensitive soma-targeted GCaMP, for precise spatial recording of neuronal populations using popular imaging modalities in model organisms such as zebrafish and mice.

Spike rate inference from mouse spinal cord calcium imaging data

Calcium imaging is a key method to record the spiking activity of identified and genetically targeted neurons. However, the observed calcium signals are only an indirect readout of the underlying electrophysiological events (single spikes or bursts of spikes) and require dedicated algorithms to recover the spike rate. These algorithms for spike inference can be optimized using ground truth data from combined electrical and optical recordings, but it is not clear how such optimized algorithms perform on cell types and brain regions for which ground truth does not exist. Here, we use a state-of-the-art algorithm based on supervised deep learning (CASCADE) and a non-supervised algorithm based on non-negative deconvolution (OASIS) to test spike rate inference in spinal cord neurons. To enable these tests, we recorded specific ground truth from glutamatergic and GABAergic somatosensory neurons in the superficial dorsal horn of spinal cord in mice of both sexes. We find that CASCADE and OASIS algorithms that were designed for cortical excitatory neurons generalize well to both spinal cord cell types. However, CASCADE models re-trained on our ground truth further improved the performance, resulting in a more accurate inference of spiking activity from spinal cord neurons. We openly provide re-trained models that can be applied to spinal cord data with variable noise levels and frame rates. Together, our ground-truth recordings and analyses provide a solid foundation for the interpretation of calcium imaging data from spinal cord dorsal horn and showcase how spike rate inference can generalize between different regions of the nervous system.Significance Statement Calcium imaging is a powerful method for measuring the activity of genetically identified neurons. However, accurate interpretation of calcium transients depends on having a detailed understanding of how neuronal activity correlates with fluorescence. Such calibration recordings have been performed for cerebral cortex but not yet for most other CNS regions and neuron types. Here, we obtained ground truth data in spinal cord by conducting simultaneous calcium and electrophysiology recordings in excitatory and inhibitory neurons. We systematically investigated the transferability of cortical algorithms to spinal neuron subpopulations and generated inference algorithms optimized to excitatory and inhibitory neurons. Our study provides a foundation for the rigorous interpretation of calcium imaging data from spinal cord.

Integrative single-cell metabolomics and phenotypic profiling reveals metabolic heterogeneity of cellular oxidation and senescence

Emerging evidence has unveiled heterogeneity in phenotypic and transcriptional alterations at the single-cell level during oxidative stress and senescence. Despite the pivotal roles of cellular metabolism, a comprehensive elucidation of metabolomic heterogeneity in cells and its connection with cellular oxidative and senescent status remains elusive. By integrating single-cell live imaging with mass spectrometry (SCLIMS), we establish a cross-modality technique capturing both metabolome and oxidative level in individual cells. The SCLIMS demonstrates substantial metabolomic heterogeneity among cells with diverse oxidative levels. Furthermore, the single-cell metabolome predicted heterogeneous states of cells. Remarkably, the pre-existing metabolomic heterogeneity determines the divergent cellular fate upon oxidative insult. Supplementation of key metabolites screened by SCLIMS resulted in a reduction in cellular oxidative levels and an extension of C. elegans lifespan. Altogether, SCLIMS represents a potent tool for integrative metabolomics and phenotypic profiling at the single-cell level, offering innovative approaches to investigate metabolic heterogeneity in cellular processes.

Targeting Ion Channels: Blockers Suppress Calcium Signals and Induce Cytotoxicity Across Medulloblastoma Cell Models

Medulloblastoma (MB) groups 3 and 4 lack targeted therapies despite their dismal prognoses. Ion channels and pumps have been implicated in promoting MB metastasis and growth; however, their roles remain poorly understood. In this study, we repurposed FDA-approved channel blockers and modulators to investigate their potential anti-tumor effects in MB cell lines (DAOY and D283) and primary cell cultures derived from a patient with MB. For the first time, we report spontaneous calcium signaling in MB cells. Spontaneous calcium signals were significantly reduced by mibefradil (calcium channel blocker), paxilline (calcium-activated potassium channel blocker), and thioridazine (potassium channel blocker). These drugs induced dose-dependent cytotoxicity in both the DAOY and D283 cell lines, as well as in primary cell cultures of a patient with group 3 or 4 MB. In contrast, digoxin and ouabain, inhibitors of the Na/K pump, reduced the calcium signaling by over 90% in DAOY cells and induced approximately 90% cell death in DAOY cells and 80% cell death in D283 cells. However, these effects were significantly diminished in the cells derived from a patient with MB, highlighting the variability in drug sensitivity among MB models. These findings demonstrate that calcium signaling is critical for MB cell survival and that the targeted inhibition of calcium pathways suppresses tumor cell growth across multiple MB models.

Analyzing the brain's dynamic response to targeted stimulation using generative modeling

Generative models of brain activity have been instrumental in testing hypothesized mechanisms underlying brain dynamics against experimental datasets. Beyond capturing the key mechanisms underlying spontaneous brain dynamics, these models hold an exciting potential for understanding the mechanisms underlying the dynamics evoked by targeted brain stimulation techniques. This paper delves into this emerging application, using concepts from dynamical systems theory to argue that the stimulus-evoked dynamics in such experiments may be shaped by new types of mechanisms distinct from those that dominate spontaneous dynamics. We review and discuss (a) the targeted experimental techniques across spatial scales that can both perturb the brain to novel states and resolve its relaxation trajectory back to spontaneous dynamics and (b) how we can understand these dynamics in terms of mechanisms using physiological, phenomenological, and data-driven models. A tight integration of targeted stimulation experiments with generative quantitative modeling provides an important opportunity to uncover novel mechanisms of brain dynamics that are difficult to detect in spontaneous settings.

Seeing the Spikes: The Future of Targetable Synthetic Voltage Sensors

Measuring the transduction of electrical signals within neurons is a key capability in neuroscience. Fluorescent voltage sensitive dyes (VSDs) were early tools that complemented classical electrophysiology by enabling the optical recording of membrane potential changes from many cells simultaneously. Recent advances in the VSD field have led to bright and highly sensitive sensors that can be targeted to the desired cell populations in live brain tissue. Despite this progress, recently, protein-based genetically encoded voltage indicators (GEVIs) have become the go-to tools for targeted voltage imaging in complex environments. In this Perspective, we summarize progress in developing targetable VSDs, discuss areas where these synthetic sensors are or could become relevant, and outline hurdles that need to be overcome to promote the routine use of targetable VSDs in neuroscience research.

3D-printed fiber-bundle fluorescence microscope for quantifying single-cell responses to high-power radiofrequency sources

Modern telecommunications systems rely on the ubiquitous use of radiofrequency (RF) fields. To ensure the safety of living systems under RF exposure, standards have been developed which rely on observed thresholds that produce an adverse response. Unfortunately, real-time imaging of single-cell responses to high-peak power RF exposures is experimentally difficult, as high-power RF may damage sensitive electronics such as cameras or photodetectors, and any metal in the exposure zone (such as a microscope objective or translation stage) interacts with the RF by reflecting the RF field, acting as an antenna, or altering the dose delivered to the sample. In this work, we present a custom fluorescence microcopy system compatible with high-power RF environments. Our device uses a custom, 3D-printed objective consisting entirely of plastic and glass components as well as a coherent fiber bundle to relay light between the exposure zone and the fluorescence detection scheme. Our device was validated against a high-end commercial confocal microscope by comparing cellular responses to a well-characterized nanosecond pulsed electric field (nsPEF) stimulus delivered via an electrode pair. Our system performed well under extreme RF exposure, demonstrating continuous fluorescence imaging and maintenance of the focal plane despite >40°C temperature variation at the sample caused by high peak power free-field RF exposure at a frequency of 2.8 GHz. This system is intended to aid researchers in investigating real-time biological responses to radiofrequency and microwave sources.

Ratiometric Imaging for Quantification of Elevated Ca2+ in Neurons Using Synthetic Low-Affinity Fluorescent Probe

The availability of various calcium ion (Ca2+) fluorescent probes has contributed to revealing physiological events related to intracellular Ca2+. However, conventional probes face challenges for quantitatively and selectively visualizing high Ca2+ concentrations in cells induced by any stimuli, including biomolecules or electrical signal that disrupt Ca2+ homeostasis. In this report, we designed and synthesized a low-affinity ratiometric Ca2+ probe, KLCA-Fura, utilizing o-aminophenol-N,N-diacetate-O-methylene-methylphosphinate (APDAP) as a ligand, for which we recently demonstrated the suitability as a new low-affinity ligand for Ca2+. KLCA-Fura showed a blue shift in excitation wavelength with increasing Ca2+ concentration based on the intramolecular charge transfer (ICT). Its affinity for Ca2+ is lower than commercially available conventional Ca2+ probes. Furthermore, the selectivity for Ca2+ and the fluorescence intensity were considered sufficient to accurately detect Ca2+. The corresponding acetoxymethyl ester, KLCA-FuraAM, was synthesized for intracellular imaging and applied to Ca2+ quantification in neurons. KLCA-FuraAM enabled quantitative ratiometric monitoring of the two-step Ca2+ concentration increase induced by glutamate stimulation. While this two-step response was not clearly observed with a commercially available low-affinity ratiometric Ca2+ probe, Fura-FF, KLCA-FuraAM has demonstrated the potential to quantitatively visualize the behavior of high Ca2+ concentrations. The ratiometric low-affinity Ca2+ probe, KLCA-Fura, is expected to be a powerful tool for discovering new functions of Ca2+ in neurons.

A Sensitive Soma-localized Red Fluorescent Calcium Indicator for Multi-Modality Imaging of Neuronal Populations In Vivo

Recent advancements in genetically encoded calcium indicators, particularly those based on green fluorescent proteins, have optimized their performance for monitoring neuronal activities in a variety of model organisms. However, progress in developing red-shifted GECIs, despite their advantages over green indicators, has been slower, resulting in fewer options for end-users. In this study, we explored topological inversion and soma-targeting strategies, which are complementary to conventional mutagenesis, to re-engineer a red genetically encoded calcium indicator, FRCaMP, for enhanced in vivo performance. The resulting sensors, FRCaMPi and soma-targeted FRCaMPi (SomaFRCaMPi), exhibit up to 2-fold higher dynamic range and peak ΔF/F0 per single AP compared to widely used jRGECO1a in neurons in culture and in vivo. Compared to jRGECO1a and FRCaMPi, SomaFRCaMPi reduces erroneous correlation of neuronal activity in the brains of mice and zebrafish by two- to four-fold due to diminished neuropil contamination without compromising the signal-to-noise ratio. Under wide-field imaging in primary somatosensory and visual cortex in mice with high labeling density (80-90%), SomaFRCaMPi exhibits up to 40% higher SNR and decreased artifactual correlation across neurons. Altogether, SomaFRCaMPi improves the accuracy and scale of neuronal activity imaging at single-neuron resolution in densely labeled brain tissues due to a 2-3-fold enhanced automated neuronal segmentation, 50% higher fraction of responsive cells, up to 2-fold higher SNR compared to jRGECO1a. Our findings highlight the potential of SomaFRCaMPi, comparable to the most sensitive soma-targeted GCaMP, for precise spatial recording of neuronal populations using popular imaging modalities in model organisms such as zebrafish and mice.

Visualizing the modulation of neurokinin 1 receptor-positive neurons in the superficial dorsal horn by spinal cord stimulation in vivo

ABSTRACT

Spinal cord stimulation (SCS) is an effective modality for pain treatment, yet its underlying mechanisms remain elusive. Neurokinin 1 receptor-positive (NK1R + ) neurons in spinal lamina I play a pivotal role in pain transmission. To enhance our mechanistic understanding of SCS-induced analgesia, we investigated how different SCS paradigms modulate the activation of NK1R + neurons, by developing NK1R-Cre;GCaMP6s transgenic mice and using in vivo calcium imaging of superficial NK1R + neurons under anesthesia (1.5% isoflurane). Neurokinin 1 receptor-positive neurons in the lumbar spinal cord (L4-5) showed a greater activation by electrical test stimulation (TS, 3.0 mA, 1 Hz) at the hindpaw at 2 weeks after tibia-sparing nerve injury (SNI-t) than in naïve mice. Spinal cord stimulation was then delivered through a bipolar plate electrode placed epidurally at L1-2 level. The short-term 50-Hz high-intensity SCS (80% motor threshold [MoT], 10 minutes) induced robust and prolonged inhibition of NK1R + neuronal responses to TS in both naïve and SNI-t mice. The 30-minute 50-Hz and 900-Hz SCS applied at moderate intensity (50% MoT) also significantly inhibited neuronal responses in SNI-t mice. However, at low intensity (20% MoT), the 30-minute 900-Hz SCS only induced persistent neuronal inhibition in naïve mice, but not in SNI-t mice. In conclusion, both 10-minute high-intensity SCS and 30-minute SCS at moderate intensity inhibit the activation of superficial NK1R + neurons, potentially attenuating spinal nociceptive transmission. Furthermore, in vivo calcium imaging of NK1R + neurons provides a new approach for exploring the spinal neuronal mechanisms of pain inhibition by neuromodulation pain therapies.

Entropy and Complexity Tools Across Scales in Neuroscience: A Review

Understanding the brain's intricate dynamics across multiple scales-from cellular interactions to large-scale brain behavior-remains one of the most significant challenges in modern neuroscience. Two key concepts, entropy and complexity, have been increasingly employed by neuroscientists as powerful tools for characterizing the interplay between structure and function in the brain across scales. The flexibility of these two concepts enables researchers to explore quantitatively how the brain processes information, adapts to changing environments, and maintains a delicate balance between order and disorder. This review illustrates the main tools and ideas to study neural phenomena using these concepts. This review does not delve into the specific methods or analyses of each study. Instead, it aims to offer a broad overview of how these tools are applied within the neuroscientific community and how they are transforming our understanding of the brain. We focus on their applications across scales, discuss the strengths and limitations of different metrics, and examine their practical applications and theoretical significance.

The Impact of Optical Undersampling on the Ca2+ Signal Resolution in Ca2+ Imaging of Spontaneous Neuronal Activity

BACKGROUND

In neuroscience, Ca2+ imaging is a prevalent technique used to infer neuronal electrical activity, often relying on optical signals recorded at low sampling rates (3 to 30 Hz) across multiple neurons simultaneously. This study investigated whether increasing the sampling rate preserves critical information that may be missed at slower acquisition speeds.

METHODS

Primary neuronal cultures were prepared from the cortex of newborn pups. Neurons were loaded with Oregon Green BAPTA-1 AM (OGB1-AM) fluorescent indicator. Spontaneous neuronal activity was recorded at low (14 Hz) and high (500 Hz) sampling rates, and the same neurons (n = 269) were analyzed under both conditions. We compared optical signal amplitude, duration, and frequency.

RESULTS

Although recurring Ca2+ transients appeared visually similar at 14 Hz and 500 Hz, quantitative analysis revealed significantly faster rise times and shorter durations (half-widths) at the higher sampling rate. Small-amplitude Ca2+ transients, undetectable at 14 Hz, became evident at 500 Hz, particularly in the neuropil (putative dendrites and axons), but not in nearby cell bodies. Large Ca2+ transients exhibited greater amplitudes and faster temporal dynamics in dendrites compared with somas, potentially due to the higher surface-to-volume ratio of dendrites. In neurons bulk-loaded with OGB1-AM, cell nucleus-mediated signal distortions were observed in every neuron examined (n = 57). Specifically, two regions of interest (ROIs) on different segments of the same cell body displayed significantly different signal amplitudes and durations due to dye accumulation in the nucleus.

CONCLUSIONS

Our findings reveal that Ca2+ signal undersampling leads to three types of information loss: (1) distortion of rise times and durations for large-amplitude transients, (2) failure to detect small-amplitude transients in cell bodies, and (3) omission of small-amplitude transients in the neuropil.

Window into the Brain: In Vivo Multiphoton Imaging

Decoding the principles underlying neuronal information processing necessitates the emergence of techniques and methodologies to monitor multiscale brain networks in behaving animals over long periods of time. Novel advances in biophotonics, specifically progress in multiphoton microscopy, combined with the development of optical indicators for neuronal activity have provided the possibility to concurrently track brain functions at scales ranging from individual neurons to thousands of neurons across connected brain regions. This Review presents state-of-the-art multiphoton imaging modalities and optical indicators for in vivo brain imaging, highlighting recent advancements and current challenges in the field.

Spike rate inference from mouse spinal cord calcium imaging data

Calcium imaging is a key method to record the spiking activity of identified and genetically targeted neurons. However, the observed calcium signals are only an indirect readout of the underlying electrophysiological events (single spikes or bursts of spikes) and require dedicated algorithms to recover the spike rate. These algorithms for spike inference can be optimized using ground truth data from combined electrical and optical recordings, but it is not clear how such optimized algorithms perform on cell types and brain regions for which ground truth does not exist. Here, we use a state-of-the-art algorithm based on supervised deep learning (CASCADE) and a non-supervised algorithm based on non-negative deconvolution (OASIS) to test spike rate inference in spinal cord neurons. To enable these tests, we recorded specific ground truth from glutamatergic and GABAergic somatosensory neurons in the superficial dorsal horn of spinal cord in mice of both sexes. We find that CASCADE and OASIS algorithms that were designed for cortical excitatory neurons generalize well to both spinal cord cell types. However, CASCADE models re-trained on our ground truth further improved the performance, resulting in a more accurate inference of spiking activity from spinal cord neurons. We openly provide re-trained models that can be applied to spinal cord data of variable noise levels and frame rates. Together, our ground-truth recordings and analyses provide a solid foundation for the interpretation of calcium imaging data from spinal cord dorsal horn and showcase how spike rate inference can generalize between different regions of the nervous system.

Inferring structure of cortical neuronal networks from activity data: A statistical physics approach

Understanding the relation between cortical neuronal network structure and neuronal activity is a fundamental unresolved question in neuroscience, with implications to our understanding of the mechanism by which neuronal networks evolve over time, spontaneously or under stimulation. It requires a method for inferring the structure and composition of a network from neuronal activities. Tracking the evolution of networks and their changing functionality will provide invaluable insight into the occurrence of plasticity and the underlying learning process. We devise a probabilistic method for inferring the effective network structure by integrating techniques from Bayesian statistics, statistical physics, and principled machine learning. The method and resulting algorithm allow one to infer the effective network structure, identify the excitatory and inhibitory type of its constituents, and predict neuronal spiking activity by employing the inferred structure. We validate the method and algorithm's performance using synthetic data, spontaneous activity of an in silico emulator, and realistic in vitro neuronal networks of modular and homogeneous connectivity, demonstrating excellent structure inference and activity prediction. We also show that our method outperforms commonly used existing methods for inferring neuronal network structure. Inferring the evolving effective structure of neuronal networks will provide new insight into the learning process due to stimulation in general and will facilitate the development of neuron-based circuits with computing capabilities.

Multimodal Characterization of Cortical Neuron Response to Permanent Magnetic Field Induced Nanomagnetic Force Maps

Nanomagnetic forces deliver precise mechanical cues to biological systems through the remote pulling of magnetic nanoparticles under a permanent magnetic field. Cortical neurons respond to nanomagnetic forces with cytosolic calcium influx and event rate shifts. However, the underlying consequences of nanomagnetic force modulation on cortical neurons remain to be elucidated. Here, we integrate electrophysiological and optical recording modalities with nanomagnetic forces to characterize the in vitro functional response to mechanical cues. Neurons exposed to chitosan functionalized magnetic nanoparticles for 24 h and then exposed to magnetic fields capable of generating forces of 2-160 pN present elevated cytosolic calcium in neurons and a time-dynamic electrophysiological spike rate and magnitude response. Extracellular recordings with microelectrode arrays revealed a 2-8 pN force-specific increase in electrophysiological spiking with a trend in reduced activity following 2 min of continuous force exposure. Nanomagnetic forces in the 16-160 pN range produced increased electrophysiological activity and remained excited for up to 4 h under continuous stimulation before silencing. Furthermore, the neuronal response to nanomagnetic forces at 16-160 pN can be electrophysiologically mediated without calcium influx by altering the magnetic nanoparticle-neuron interactions. These results demonstrate that low pN nanomagnetic forces mediate neuronal function and suggest that magnetic nanoparticle interactions and force magnitudes can be harnessed to provoke different responses in cortical neurons.

Investigation of epilepsy-related genes in a Drosophila model

ABSTRACT

Complex genetic architecture is the major cause of heterogeneity in epilepsy, which poses challenges for accurate diagnosis and precise treatment. A large number of epilepsy candidate genes have been identified from clinical studies, particularly with the widespread use of next-generation sequencing. Validating these candidate genes is emerging as a valuable yet challenging task. Drosophila serves as an ideal animal model for validating candidate genes associated with neurogenetic disorders such as epilepsy, due to its rapid reproduction rate, powerful genetic tools, and efficient use of ethological and electrophysiological assays. Here, we systematically summarize the advantageous techniques of the Drosophila model used to investigate epilepsy genes, including genetic tools for manipulating target gene expression, ethological assays for seizure-like behaviors, electrophysiological techniques, and functional imaging for recording neural activity. We then introduce several typical strategies for identifying epilepsy genes and provide new insights into gene-gene interactions in epilepsy with polygenic causes. We summarize well- established precision medicine strategies for epilepsy and discuss prospective treatment options, including drug therapy and gene therapy for genetic epilepsy based on the Drosophila model. Finally, we also address genetic counseling and assisted reproductive technology as potential approaches for the prevention of genetic epilepsy.

Redefining Molecular Probes for Monitoring Subcellular Environment: A Perspective

The development of small-molecule fluorescent probes has revolutionized the monitoring of in vivo physicochemical parameters, offering unprecedented insights into biological processes. In this perspective, we critically examine recent advances and trends in the design and application of fluorescent probes for real-time in vivo monitoring of subcellular environments. Traditional concepts such as membrane potential, microviscosity, and micropolarity have been superseded by more biologically relevant parameters like membrane voltage, tension, and hydration, enhancing the accuracy of physiological assessments. This redefinition not only presents an evolved concept with broader applications in monitoring subcellular dynamics but also addresses the unmet needs of subcellular biology more effectively. We also highlight the limitations of commonly used probes in providing specific information about the redox environment, noting their nonspecificity to oxidants and the influence of various chemical interactions. These probes typically rely on free radical mechanisms and require metal catalysts to react with hydrogen peroxide. They include naphthalimide, fluorescein, BODIPY, rhodamine, cyanine cores to cover the UV-vis-near-infrared window. The motif of this perspective is to provide critical insights into trending fluorescent-based systems employed in real-time or in vivo physicochemical-responsive monitoring, thus aiming to inform and inspire further research in creating robust and efficient fluorescent probes for comprehensive in vivo monitoring applications.

Interpretable deep learning for deconvolutional analysis of neural signals

The widespread adoption of deep learning to build models that capture the dynamics of neural populations is typically based on "black-box" approaches that lack an interpretable link between neural activity and network parameters. Here, we propose to apply algorithm unrolling, a method for interpretable deep learning, to design the architecture of sparse deconvolutional neural networks and obtain a direct interpretation of network weights in relation to stimulus-driven single-neuron activity through a generative model. We characterize our method, referred to as deconvolutional unrolled neural learning (DUNL), and show its versatility by applying it to deconvolve single-trial local signals across multiple brain areas and recording modalities. To exemplify use cases of our decomposition method, we uncover multiplexed salience and reward prediction error signals from midbrain dopamine neurons in an unbiased manner, perform simultaneous event detection and characterization in somatosensory thalamus recordings, and characterize the heterogeneity of neural responses in the piriform cortex and in the striatum during unstructured, naturalistic experiments. Our work leverages the advances in interpretable deep learning to gain a mechanistic understanding of neural activity.

Elucidating sequence-function relationships in a template-independent polymerase to enable novel DNA recording applications

Harnessing DNA as a high-density storage medium for information storage and molecular recording of signals has been of increasing interest in the biotechnology field. Recently, progress in enzymatic DNA synthesis, DNA digital data storage, and DNA-based molecular recording has been made by leveraging the activity of the template-independent DNA polymerase, terminal deoxynucleotidyl transferase (TdT). TdT adds deoxyribonucleotides to the 3' end of single-stranded DNA, generating random sequences of single-stranded DNA. TdT can use several divalent cations for its enzymatic activity and exhibits shifts in deoxyribonucleotide incorporation frequencies in response to changes in its reaction environment. However, there is limited understanding of sequence-structure-function relationships regarding these properties, which in turn limits our ability to modulate TdT to further advance TdT-based tools. Most TdT literature to-date explores the activity of murine, bovine or human TdTs; studies probing TdT sequence and structure largely focus on strictly conserved residues that are functionally critical to TdT activity. Here, we explore non-conserved TdT sequence space by surveying the natural diversity of TdT. We characterize a diverse set of TdT homologs from different organisms and identify several TdT residues/regions that confer differences in TdT behavior between homologs. The observations in this study can design rules for targeted TdT libraries, in tandem with a screening assay, to modulate TdT properties. Moreover, the data can be useful in guiding further studies of potential residues of interest. Overall, we characterize TdTs that have not been previously studied in the literature, and we provide new insights into TdT sequence-function relationships.

Visualizing DNA/RNA, Proteins, and Small Molecule Metabolites within Live Cells

Live cell imaging is essential for obtaining spatial and temporal insights into dynamic molecular events within heterogeneous individual cells, in situ intracellular networks, and in vivo organisms. Molecular tracking in live cells is also a critical and general requirement for studying dynamic physiological processes in cell biology, cancer, developmental biology, and neuroscience. Alongside this context, this review provides a comprehensive overview of recent research progress in live-cell imaging of RNAs, DNAs, proteins, and small-molecule metabolites, as well as their applications in molecular diagnosis, immunodiagnosis, and biochemical diagnosis. A series of advanced live-cell imaging techniques have been introduced and summarized, including high-precision live-cell imaging, high-resolution imaging, low-abundance imaging, multidimensional imaging, multipath imaging, rapid imaging, and computationally driven live-cell imaging methods, all of which offer valuable insights for disease prevention, diagnosis, and treatment. This review article also addresses the current challenges, potential solutions, and future development prospects in this field.

In vitro neurotoxicity testing: lessons from chemotherapy-induced peripheral neurotoxicity

INTRODUCTION

Chemotherapy induced peripheral neurotoxicity (CIPN) is a long-lasting, or even permanent, late toxicity caused by largely used anticancer drugs. CIPN affects a growing population of cancer survivors and diminishes their quality of life since there is no curative/preventive treatment. Among several reasons for this unmet clinical need, there is an incomplete knowledge on mechanisms leading to CIPN. Therefore, bench side research is still greatly needed: in vitro studies are pivotal to both evaluate neurotoxicity mechanisms and potential neuroprotection strategies.

AREAS COVERED

Advantages and disadvantages of in vitro approaches are addressed with respect to their applicability to the CIPN field. Different cell cultures and techniques to assess neurotoxicity/neuroprotection are described. PubMed search-string: (chemotherapy-induced) AND (((neuropathy) OR neurotoxicity) OR neuropathic pain) AND (in vitro) AND (((((model) OR SH-SY5Y) OR PC12) OR iPSC) OR DRG neurons); (chemotherapy-induced) AND (((neuropathy) OR neurotoxicity) OR neuropathic pain) AND (model) AND (((neurite elongation) OR cell viability) OR morphology). No articles published before 1990 were selected.

EXPERT OPINION

CIPN is an ideal experimental setting to test axonal damage and, in general, peripheral nervous system mechanisms of disease and neuroprotection. Therefore, starting from robust preclinical data in this field, potentially, relevant biological rationale can be transferred to other human spontaneous diseases of the peripheral nervous system.

Identifying dysfunctional cell types and circuits in animal models for psychiatric disorders with calcium imaging

A central goal of neuroscience is to understand how the brain transforms external stimuli and internal bodily signals into patterns of activity that underlie cognition, emotional states, and behavior. Understanding how these patterns of activity may be disrupted in mental illness is crucial for developing novel therapeutics. It is well appreciated that psychiatric disorders are complex, circuit-based disorders that arise from dysfunctional activity patterns generated in discrete cell types and their connections. Recent advances in large-scale, cell-type specific calcium imaging approaches have shed new light on the cellular, circuit, and network-level dysfunction in animal models for psychiatric disorders. Here, we highlight a series of recent findings over the last ~10 years from in vivo calcium imaging studies that show how aberrant patterns of activity in discrete cell types and circuits may underlie behavioral deficits in animal models for several psychiatric disorders, including depression, anxiety, autism spectrum disorders, and schizophrenia. These advances in calcium imaging in pre-clinical models demonstrate the power of cell-type-specific imaging tools in understanding the underlying dysfunction in cell types, activity patterns, and neural circuits that may contribute to disease and provide new blueprints for developing more targeted therapeutics and treatment strategies.

Simultaneous detection of dynamic calcium signaling and ERK activity in living cells

Calcium (Ca2+) is a universal second messenger in eukaryotic cells, and extracellular regulated protein kinases (ERK) are the core component of the mitogen-activated protein kinase (MAPK) signaling cascade. Both are involved in numerous physiological and pathological processes, such as organogenesis, tumorigenesis, proliferation, migration and apoptosis. Over the past decade, it has been found that calcium signaling can regulate the ERK activity through multiple mechanisms, and conversely, ERK signaling transduction can also affect the triggering and intensity of calcium signaling. However, there are few reports on how to perform real-time synchronous detection of these two signals. Here we described a method for dynamically and synchronously recording calcium signals and ERK activity in living cells, utilizing stable expression of multiple genetically-encoded probes and multi-channel synchronous detection technology using confocal microscopy. The protocol can be useful to address the spatiotemporal encoding dynamic mechanism of calcium signaling and ERK activity in single or multiple cells, and to reveal the interaction and causal characteristics of these two signals.

NeuroTD: A Time-Frequency Based Multimodal Learning Approach to Analyze Time Delays in Neural Activities

Studying temporal features of neural activities is crucial for understanding the functions of neurons as well as underlying neural circuits. To this end, recent researches employ emerging techniques including calcium imaging, Neuropixels, depth electrodes, and Patch-seq to generate multimodal time-series data that depict the activities of single neurons, groups of neurons, and behaviors. However, challenges persist, including the analysis of noisy, high-sampling-rate neuronal data, and the modeling of temporal dynamics across various modalities. To address these challenges, we developed NeuroTD, a novel deep learning approach to align multimodal time-series datasets and infer cross-modality temporal relationships such as time delays or shifts. Particularly, NeuroTD integrates Siamese neural networks with frequency domain transformations and complex value optimization for inference. We applied NeuroTD to three multimodal datasets to (1) analyze electrophysiological (ephys) time series measured by depth electrodes, identifying time delays among neurons across various positions, (2) investigate neural activity and behavioral time series data derived from Neuropixels and 3D motion captures, establishing causal relationships between neural activities and corresponding behavioral activities, and (3) explore gene expression and ephys data of single neurons from Patch-seq, identifying gene expression signatures highly correlated with time shifts in ephys responses. Finally, NeuroTD is open-source at https://github.com/daifengwanglab/NeuroTD for general use.

Expanded ATXN1 alters transcription and calcium signaling in SCA1 human motor neurons differentiated from induced pluripotent stem cells

Spinocerebellar ataxia type 1 (SCA1) is a dominantly inherited and lethal neurodegenerative disease caused by the abnormal expansion of CAG repeats in the ATAXIN-1 (ATXN1) gene. Pathological studies identified dysfunction and loss of motor neurons (MNs) in the brain stem and spinal cord, which are thought to contribute to premature lethality by affecting the swallowing and breathing of SCA1 patients. However, the molecular and cellular mechanisms of MN pathogenesis remain unknown. To study SCA1 pathogenesis in human MNs, we differentiated induced pluripotent stem cells (iPSCs) derived from SCA1 patients and their unaffected siblings into MNs. We examined proliferation of progenitor cells, neurite outgrowth, spontaneous and glutamate-induced calcium activity of SCA1 MNs to investigate cellular mechanisms of pathogenesis. RNA sequencing was then used to identify transcriptional alterations in iPSC-derived MN progenitors (pMNs) and MNs which could underlie functional changes in SCA1 MNs. We found significantly decreased spontaneous and evoked calcium activity and identified dysregulation of genes regulating calcium signaling in SCA1 MNs. These results indicate that expanded ATXN1 causes dysfunctional calcium signaling in human MNs.

Shot-Noise Limited Nonlinear Optical Imaging Excited With GHz Femtosecond Pulses and Denoised by Deep-Learning

Multiphoton fluorescence microscopy excited with femtosecond pulses at high repetition rates, particularly in the range of 100's MHz to GHz, offers an alternative solution to suppress photoinduced damage to biological samples, for example, photobleaching. Here, we demonstrate the use of a U-Net-based deep-learning algorithm for suppressing the inherent shot noise of the two-photon fluorescence images excited with GHz femtosecond pulses. With the trained denoising neural network, the image quality of the representative two-photon fluorescence images of the biological samples is shown to be significantly improved. Moreover, for input raw images with even SNR reduced to -4.76 dB, the trained denoising network can recover the main image structure from noise floor with acceptable fidelity and spatial resolution. It is anticipated that the combination of GHz femtosecond pulses and deep-learning denoising algorithm can be a promising solution for eliminating the trade-off between photoinduced damage and image quality in nonlinear optical imaging platforms.

Effects of transcranial magneto-acoustic stimulation on cognitive function and neural signal transmission in the hippocampal CA1 region of mice

As a new means of brain neuroregulation and research, transcranial magneto-acoustic stimulation (TMAS) uses the coupling effect of ultrasound and a static magnetic field to regulate neural activity in the corresponding brain areas. Calcium ions can promote the secretion of neurotransmitters and play a key role in the transmission of neural signals in brain cognition. In this study, to explore the effects of TMAS on cognitive function and neural signaling in the CA1 region of the hippocampus, TMAS was applied to male 2-month-old C57 mice with a magnetic field strength of 0.3 T and ultrasound intensity of 2.6 W/cm2. First, the efficiency of neural signaling in the CA1 region of the mouse hippocampus was detected by fiber photometry. Second, the effects of TMAS on cognitive function in mice were investigated through multiple behavioral experiments, including spatial learning and memory ability, anxiety and desire for novelty. The experimental results showed that TMAS could improve cognitive function in mice, and the efficiency of neural signaling in the CA1 area of the hippocampus was significantly increased during stimulation and maintained for one week after stimulation. In addition, the neural signaling efficiency in the CA1 area of the hippocampus increased in the open field (OF) experiment and recovered after one week, the neural signaling efficiency in the new object exploration (NOE) experiment was significantly enhanced, and the intensity slowed after one week. In conclusion, TMAS enhances cognitive performance and promotes neural signaling in the CA1 region of the mouse hippocampus.

ARViS: a bleed-free multi-site automated injection robot for accurate, fast, and dense delivery of virus to mouse and marmoset cerebral cortex

Genetically encoded fluorescent sensors continue to be developed and improved. If they could be expressed across multiple cortical areas in non-human primates, it would be possible to measure a variety of spatiotemporal dynamics of primate-specific cortical activity. Here, we develop an Automated Robotic Virus injection System (ARViS) for broad expression of a biosensor. ARViS consists of two technologies: image recognition of vasculature structures on the cortical surface to determine multiple injection sites without hitting them, and robotic control of micropipette insertion perpendicular to the cortical surface with 50 μm precision. In mouse cortex, ARViS sequentially injected virus solution into 100 sites over a duration of 100 min with a bleeding probability of only 0.1% per site. Furthermore, ARViS successfully achieved 266-site injections over the frontoparietal cortex of a female common marmoset. We demonstrate one-photon and two-photon calcium imaging in the marmoset frontoparietal cortex, illustrating the effective expression of biosensors delivered by ARViS.

Destabilized near-infrared fluorescent nanobodies enable background-free targeting of GFP-based biosensors for imaging and manipulation

Near-infrared (NIR) probes are highly sought after as fluorescent tags for multicolor cellular and in vivo imaging. Here we develop small NIR fluorescent nanobodies, termed NIR-FbLAG16 and NIR-FbLAG30, enabling background-free visualization of various GFP-derived probes and biosensors. We also design a red-shifted variant, NIR-Fb(718), to simultaneously target several antigens within the NIR spectral range. Leveraging the antigen-stabilizing property of the developed NIR-Fbs, we then create two modular systems for precise control of gene expression in GFP-labeled cells. Applying the NIR-Fbs in vivo, we target cells expressing GFP and the calcium biosensor GCaMP6 in the somatosensory cortex of transgenic mice. Simultaneously tracking calcium activity and the reference signal from NIR-FbLAGs bound to GCaMP6 enables ratiometric deep-brain in vivo imaging. Altogether, NIR-FbLAGs present a promising approach for imaging and manipulating various processes in live cells and behaving animals expressing GFP-based probes.

Photothermal Excitation of Neurons Using MXene: Cellular Stress and Phototoxicity Evaluation

Understanding the communication of individual neurons necessitates precise control of neural activity. Photothermal modulation is a remote and non-genetic technique to control neural activity with high spatiotemporal resolution. The local heat release by photothermally active nanomaterial will change the membrane properties of the interfaced neurons during light illumination. Recently, it is demonstrated that the two-dimensional Ti3C2Tx MXene is an outstanding candidate to photothermally excite neurons with low incident energy. However, the safety of using Ti3C2Tx for neural modulation is unknown. Here, the biosafety of Ti3C2Tx-based photothermal modulation is thoroughly investigated, including assessments of plasma membrane integrity, mitochondrial stress, and oxidative stress. It is demonstrated that culturing neurons on 25 µg cm-2 Ti3C2Tx films and illuminating them with laser pulses (635 nm) with different incident energies (2-10 µJ per pulse) and different pulse frequencies (1 pulse, 1 Hz, and 10 Hz) neither damage the cell membrane, induce cellular stress, nor generate oxidative stress. The threshold energy to cause damage (i.e., 14 µJ per pulse) exceeded the incident energy for neural excitation (<10 µJ per pulse). This multi-assay safety evaluation provides crucial insights for guiding the establishment of light conditions and protocols in the clinical translation of photothermal modulation.

A comprehensive review of electrophysiological techniques in amyotrophic lateral sclerosis research

Amyotrophic lateral sclerosis (ALS), a devastating neurodegenerative disease, is characterized by progressive motor neuron degeneration, leading to widespread weakness and respiratory failure. While a variety of mechanisms have been proposed as causes of this disease, a full understanding remains elusive. Electrophysiological alterations, including increased motor axon excitability, likely play an important role in disease progression. There remains a critical need for non-animal disease models that can integrate electrophysiological tools to better understand underlying mechanisms, track disease progression, and evaluate potential therapeutic interventions. This review explores the integration of electrophysiological technologies with ALS disease models. It covers cellular and clinical electrophysiological tools and their applications in ALS research. Additionally, we examine conventional animal models and highlight advancements in humanized models and 3D organoid technologies. By bridging the gap between these models, we aim to enhance our understanding of ALS pathogenesis and facilitate the development of new therapeutic strategies.

Ex Tenebris Lux: Illuminating Reactive Oxygen and Nitrogen Species with Small Molecule Probes

Reactive oxygen and nitrogen species are small reactive molecules derived from elements in the air─oxygen and nitrogen. They are produced in biological systems to mediate fundamental aspects of cellular signaling but must be very tightly balanced to prevent indiscriminate damage to biological molecules. Small molecule probes can transmute the specific nature of each reactive oxygen and nitrogen species into an observable luminescent signal (or even an acoustic wave) to offer sensitive and selective imaging in living cells and whole animals. This review focuses specifically on small molecule probes for superoxide, hydrogen peroxide, hypochlorite, nitric oxide, and peroxynitrite that provide a luminescent or photoacoustic signal. Important background information on general photophysical phenomena, common probe designs, mechanisms, and imaging modalities will be provided, and then, probes for each analyte will be thoroughly evaluated. A discussion of the successes of the field will be presented, followed by recommendations for improvement and a future outlook of emerging trends. Our objectives are to provide an informative, useful, and thorough field guide to small molecule probes for reactive oxygen and nitrogen species as well as important context to compare the ecosystem of chemistries and molecular scaffolds that has manifested within the field.