RESUMEN
Existing stress evaluation methods based on the Lamb waves mainly use the time of flight (TOF) or velocity as the means of stress measurement. However, these two features used for stress measurement are sometimes insensitive to stress changes. Therefore, it is essential to explore other features that are potentially more sensitive to stress changes. The time-frequency spectrums of signals containing stress information have not yet been fully studied for stress evaluation. This paper proposes a uniaxial stress measurement method based on two time-frequency characteristics of Lamb waves, i.e., the slope of time-frequency spectrum distribution (TFSD) and pulse width impact factor. Theoretical expressions of the slope of TFSD are derived. The impacts of excitation signal parameters (i.e., bandwidth and center frequency) and noise on two time-frequency characteristics were discussed. Then, the fitting results of the finite element simulation are consistent with the results predicted by theory. To experimentally validate the proposed theory, aluminum plate specimens with two different types of adhesives were used for the experiment. According to the experimental stress measurement expression, three uniaxial tensile tests in the range of 35-95 MPa were conducted on the identical batch of specimens. The maximum standard deviation of multiple measured stress based on pulse width impact factor is 3.76433 MPa, demonstrating excellent measurement stability. The maximum standard deviation of multiple measured stress based on the slope of TFSD is 9.12492 MPa. It shows that the proposed methodology is a promising alternative for stress measurement.
RESUMEN
Two-photon Ca2+ imaging technology increasingly plays an essential role in neuroscience research. However, the requirement for extensive professional annotation poses a significant challenge to improving the performance of neuron segmentation models. Here, we present NeuroSeg-III, an innovative self-supervised learning approach specifically designed to achieve fast and precise segmentation of neurons in imaging data. This approach consists of two modules: a self-supervised pre-training network and a segmentation network. After pre-training the encoder of the segmentation network via a self-supervised learning method without any annotated data, we only need to fine-tune the segmentation network with a small amount of annotated data. The segmentation network is designed with YOLOv8s, FasterNet, efficient multi-scale attention mechanism (EMA), and bi-directional feature pyramid network (BiFPN), which enhanced the model's segmentation accuracy while reducing the computational cost and parameters. The generalization of our approach was validated across different Ca2+ indicators and scales of imaging data. Significantly, the proposed neuron segmentation approach exhibits exceptional speed and accuracy, surpassing the current state-of-the-art benchmarks when evaluated using a publicly available dataset. The results underscore the effectiveness of NeuroSeg-III, with employing an efficient training strategy tailored for two-photon Ca2+ imaging data and delivering remarkable precision in neuron segmentation.
RESUMEN
In recent years, the number of functional magnetic resonance imaging (fMRI) research in acupuncture grows increasingly. However, due to the differences in acupoint selection, acupuncture technique and sample size, the problems get more prominent in terms of the diverse results and the lack of common rules of acupuncture among researches. By taking the fMRI research for post-stroke motor dysfunction (PSMD) treated with acupuncture as the example, this paper introduces the fMRI Meta-analysis technology for integrating the relevant research results and extracting the common rules, namely image-based Meta-analysis (IBMA) and coordinate-based Meta-analysis (CBMA). Considering the higher feasibility of CBMA, three available CBMA methods are explained specially, including activation likelihood estimation (ALE), kernel density analysis (KDA), and seed-based d mapping (SDM). Focusing on the precautions and operation procedure of CBMA, the review is conducted systematically on the type of fMRI research, task design, analytical method, and the thinking integrity of fMRI Meta-analysis, and the review findings are collated in charts. It aims to assist readers to understand the abstract and complex theories and practical information of this technology efficiently, conveniently and systematically, and hopes to provide the references for the future learning and the application.
Asunto(s)
Terapia por Acupuntura , Puntos de Acupuntura , Aprendizaje , Imagen por Resonancia Magnética , Tamaño de la MuestraRESUMEN
The sensory neocortex has been suggested to be a substrate for long-term memory storage, yet which exact single cells could be specific candidates underlying such long-term memory storage remained neither known nor visible for over a century. Here, using a combination of day-by-day two-photon Ca2+ imaging and targeted single-cell loose-patch recording in an auditory associative learning paradigm with composite sounds in male mice, we reveal sparsely distributed neurons in layer 2/3 of auditory cortex emerged step-wise from quiescence into bursting mode, which then invariably expressed holistic information of the learned composite sounds, referred to as holistic bursting (HB) cells. Notably, it was not shuffled populations but the same sparse HB cells that embodied the behavioral relevance of the learned composite sounds, pinpointing HB cells as physiologically-defined single-cell candidates of an engram underlying long-term memory storage in auditory cortex.
Asunto(s)
Corteza Auditiva , Neocórtex , Masculino , Ratones , Animales , Corteza Auditiva/fisiología , Aprendizaje/fisiología , Memoria a Largo Plazo , Neocórtex/fisiología , Neuronas/fisiología , Percepción Auditiva/fisiologíaRESUMEN
The prevalence and disease burden of urolithiasis has increased substantially worldwide in the last decade, and intraluminal holmium laser lithotripsy has become the primary treatment method. However, inappropriate laser energy settings increase the risk of perioperative complications, largely due to the lack of intraoperative information on the stone composition, which determines the stone melting point. To address this issue, we developed a fiber-based fluorescence spectrometry method that detects and classifies the autofluorescence spectral fingerprints of urinary stones into three categories: calcium oxalate, uric acid, and struvite. By applying the support vector machine (SVM), the prediction accuracy achieved 90.28 % and 96.70% for classifying calcium stones versus non-calcium stones and uric acid versus struvite, respectively. High accuracy and specificity were achieved for a wide range of working distances and angles between the fiber tip and stone surface in an emulated intraoperative ambient. Our work establishes the methodological basis for engineering a clinical device that achieves real-time, in situ classification of urinary stones for optimizing the laser ablation parameters and reducing perioperative complications in lithotripsy.
Asunto(s)
Litotripsia por Láser , Cálculos Urinarios , Urolitiasis , Humanos , Ácido Úrico/análisis , Estruvita , Cálculos Urinarios/cirugía , Cálculos Urinarios/químicaRESUMEN
Significance: The studying of rapid neuronal signaling across large spatial scales in intact, living brains requires both high temporal resolution and versatility of the measurement device. Aim: We introduce a high-speed two-photon microscope based on a custom-built acousto-optic deflector (AOD). This microscope has a maximum line scan frequency of 400 kHz and a maximum frame rate of 10,000 frames per second (fps) at 250 × 40 pixels . For stepwise magnification from population view to subcellular view with high spatial and temporal resolution, we combined the AOD with resonance-galvo (RS) scanning. Approach: With this combinatorial device that supports both large-view navigation and small-view high-speed imaging, we measured dendritic calcium propagation velocity and the velocity of single red blood cells (RBCs). Results: We measured dendritic calcium propagation velocity ( 80 / 62.5 - 116.7 µ m / ms ) in OGB-1-labeled single cortical neurons in mice in vivo. To benchmark the spatial precision and detection sensitivity of measurement in vivo, we also visualized the trajectories of single RBCs and found that their movement speed follows Poiseuille's law of laminar flow. Conclusions: This proof-of-concept methodological development shows that the combination of AOD and RS scanning two-photon microscopy provides both versatility and precision for quantitative analysis of single neuronal activities and hemodynamics in vivo.
RESUMEN
Neocortical layer 6 (L6) is less understood than other more superficial layers, largely owing to limitations of performing high-resolution investigations in vivo. Here, we show that labeling with the Challenge Virus Standard (CVS) rabies virus strain enables high-quality imaging of L6 neurons by conventional two-photon microscopes. CVS virus injection into the medial geniculate body can selectively label L6 neurons in the auditory cortex. Only three days after injection, dendrites and cell bodies of L6 neurons could be imaged across all cortical layers. Ca2+ imaging in awake mice showed that sound stimulation evokes neuronal responses from cell bodies with minimal contamination from neuropil signals. In addition, dendritic Ca2+ imaging revealed significant responses from spines and trunks across all layers. These results demonstrate a reliable method capable of rapid, high-quality labeling of L6 neurons that can be readily extended to other brain regions.
RESUMEN
The development of two-photon microscopy and Ca2+ indicators has enabled the recording of multiscale neuronal activities in vivo and thus advanced the understanding of brain functions. However, it is challenging to perform automatic, accurate, and generalized neuron segmentation when processing a large amount of imaging data. Here, we propose a novel deep-learning-based neural network, termed as NeuroSeg-II, to conduct automatic neuron segmentation for in vivo two-photon Ca2+ imaging data. This network architecture is based on Mask region-based convolutional neural network (R-CNN) but has enhancements of an attention mechanism and modified feature hierarchy modules. We added an attention mechanism module to focus the computation on neuron regions in imaging data. We also enhanced the feature hierarchy to extract feature information at diverse levels. To incorporate both spatial and temporal information in our data processing, we fused the images from average projection and correlation map extracting the temporal information of active neurons, and the integrated information was expressed as two-dimensional (2D) images. To achieve a generalized neuron segmentation, we conducted a hybrid learning strategy by training our model with imaging data from different labs, including multiscale data with different Ca2+ indicators. The results showed that our approach achieved promising segmentation performance across different imaging scales and Ca2+ indicators, even including the challenging data of large field-of-view mesoscopic images. By comparing state-of-the-art neuron segmentation methods for two-photon Ca2+ imaging data, we showed that our approach achieved the highest accuracy with a publicly available dataset. Thus, NeuroSeg-II enables good segmentation accuracy and a convenient training and testing process.
RESUMEN
Quantitative and mechanistic understanding of learning and long-term memory at the level of single neurons in living brains require highly demanding techniques. A specific need is to precisely label one cell whose firing output property is pinpointed amidst a functionally characterized large population of neurons through the learning process and then investigate the distribution and properties of dendritic inputs. Here, we disseminate an integrated method of daily two-photon neuronal population Ca2+ imaging through an auditory associative learning course, followed by targeted single-cell loose-patch recording and electroporation of plasmid for enhanced chronic Ca2+ imaging of dendritic spines in the targeted cell. Our method provides a unique solution to the demand, opening a solid path toward the hard-cores of how learning and long-term memory are physiologically carried out at the level of single neurons and synapses.
RESUMEN
The ability to form predictions based on recent sensory experience is essential for behavioral adaptation to our ever-changing environment. Predictive encoding represented by neuronal activity has been observed in sensory cortex, but how this neuronal activity is transformed into anticipatory motor behavior remains unclear. Fiber photometry to investigate a corticostriatal projection from the auditory cortex to the posterior striatum during an auditory paradigm in mice, and pharmacological experiments in a task that induces a temporal expectation of upcoming sensory stimuli. We find that the auditory corticostriatal projection relays both sound-evoked stimulus information as well as predictive signals in relation to stimulus timing following rhythmic auditory stimulation. Pharmacological experiments suggest that this projection is required for the initiation of both sound-evoked and anticipatory licking behavior in an auditory associative-learning behavioral task, but not for the general recognition of presented auditory stimuli. This auditory corticostriatal projection carries predictive signals, and the posterior striatum is critical to the anticipatory stimulus-driven motor behavior.
Asunto(s)
Corteza Auditiva , Sonido , Animales , Ratones , Estimulación Acústica , Neostriado , CogniciónRESUMEN
Astrocytic Ca2+ transients are essential for astrocyte integration into neural circuits. These Ca2+ transients are primarily sequestered in subcellular domains, including primary branches, branchlets and leaflets, and endfeet. In previous studies, it suggests that aging causes functional defects in astrocytes. Until now, it was unclear whether and how aging affects astrocytic Ca2+ transients at subcellular domains. In this study, we combined a genetically encoded Ca2+ sensor (GCaMP6f) and in vivo two-photon Ca2+ imaging to determine changes in Ca2+ transients within astrocytic subcellular domains during brain aging. We showed that aging increased Ca2+ transients in astrocytic primary branches, higher-order branchlets, and terminal leaflets. However, Ca2+ transients decreased within astrocytic endfeet during brain aging, which could be caused by the decreased expressions of Aquaporin-4 (AQP4). In addition, aging-induced changes of Ca2+ transient types were heterogeneous within astrocytic subcellular domains. These results demonstrate that the astrocytic Ca2+ transients within subcellular domains are affected by aging differently. This finding contributes to a better understanding of the physiological role of astrocytes in aging-induced neural circuit degeneration.
RESUMEN
The hippocampal CA2 region plays a key role in social memory. The encoding of such memory involves afferent activity from the hypothalamic supramammillary nucleus (SuM) to CA2. However, the neuronal circuits required for consolidation of freshly encoded social memory remain unknown. Here, we used circuit-specific optical and single-cell electrophysiological recordings in mice to explore the role of sleep in social memory consolidation and its underlying circuit mechanism. We found that SuM neurons projecting to CA2 were highly active during rapid-eye-movement (REM) sleep but not during non-REM sleep or quiet wakefulness. REM-sleep-selective optogenetic silencing of these neurons impaired social memory. By contrast, the silencing of another group of REM sleep-active SuM neurons that projects to the dentate gyrus had no effect on social memory. Therefore, we provide causal evidence that the REM sleep-active hypothalamic neurons that project to CA2 are specifically required for the consolidation of social memory.
Asunto(s)
Consolidación de la Memoria , Animales , Ratones , SueñoRESUMEN
The olivocerebellar circuitry is important to convey both motor and non-motor information from the inferior olive (IO) to the cerebellar cortex. Several methods are currently established to observe the dynamics of the olivocerebellar circuitry, largely by recording the complex spike activity of cerebellar Purkinje cells; however, these techniques can be technically challenging to apply in vivo and are not always possible in freely behaving animals. Here, we developed a method for the direct, accessible, and robust recording of climbing fiber (CF) Ca2+ signals based on optical fiber photometry. We first verified the IO stereotactic coordinates and the organization of contralateral CF projections using tracing techniques and then injected Ca2+ indicators optimized for axonal labeling, followed by optical fiber-based recordings. We demonstrated this method by recording CF Ca2+ signals in lobule IV/V of the cerebellar vermis, comparing the resulting signals in freely moving mice. We found various movement-evoked CF Ca2+ signals, but the onset of exploratory-like behaviors, including rearing and tiptoe standing, was highly synchronous with recorded CF activity. Thus, we have successfully established a robust and accessible method to record the CF Ca2+ signals in freely behaving mice, which will extend the toolbox for studying cerebellar function and related disorders.
RESUMEN
Two-photon Ca2+ imaging is a widely used technique for investigating brain functions across multiple spatial scales. However, the recording of neuronal activities is affected by movement of the brain during tasks in which the animal is behaving normally. Although post-hoc image registration is the commonly used approach, the recent developments of online neuroscience experiments require real-time image processing with efficient motion correction performance, posing new challenges in neuroinformatics. We propose a fast and accurate image density feature-based motion correction method to address the problem of imaging animal during behaviors. This method is implemented by first robustly estimating and clustering the density features from two-photon images. Then, it takes advantage of the temporal correlation in imaging data to update features of consecutive imaging frames with efficient calculations. Thus, motion artifacts can be quickly and accurately corrected by matching the features and obtaining the transformation parameters for the raw images. Based on this efficient motion correction strategy, our algorithm yields promising computational efficiency on imaging datasets with scales ranging from dendritic spines to neuronal populations. Furthermore, we show that the proposed motion correction method outperforms other methods by evaluating not only computational speed but also the quality of the correction performance. Specifically, we provide a powerful tool to perform motion correction for two-photon Ca2+ imaging data, which may facilitate online imaging experiments in the future.
RESUMEN
Reconstructing axonal projections of single neurons at the whole-brain level is currently a converging goal of the neuroscience community that is fundamental for understanding the logic of information flow in the brain. Thousands of single neurons from different brain regions have recently been morphologically reconstructed, but the corresponding physiological functional features of these reconstructed neurons are unclear. By combining two-photon Ca2+ imaging with targeted single-cell plasmid electroporation, we reconstruct the brain-wide morphologies of single neurons that are defined by a sound-evoked response map in the auditory cortices (AUDs) of awake mice. Long-range interhemispheric projections can be reliably labelled via co-injection with an adeno-associated virus, which enables enhanced expression of indicator protein in the targeted neurons. Here we show that this method avoids the randomness and ambiguity of conventional methods of neuronal morphological reconstruction, offering an avenue for developing a precise one-to-one map of neuronal projection patterns and physiological functional features.
Asunto(s)
Encéfalo , Neuronas , Animales , Axones , Electroporación/métodos , Ratones , NeuritasRESUMEN
Currently, the most effective strategy for dealing with Alzheimer's disease (AD) is delaying the onset of dementia. Severe hypoglycemia is strongly associated with dementia; however, the effects of recurrent moderate hypoglycemia (RH) on the progression of cognitive deficits in patients with diabetes with genetic susceptibility to AD remain unclear. Here, we report that insulin-controlled hyperglycemia slightly aggravated AD-type pathologies and cognitive impairment; however, RH significantly increased neuronal hyperactivity and accelerated the progression of cognitive deficits in streptozotocin-induced (STZ-induced) diabetic APP/PS1 mice. Glucose transporter 3-mediated (GLUT3-mediated) neuronal glucose uptake was not significantly altered under hyperglycemia but was markedly reduced by RH, which induced excessive mitochondrial fission in the hippocampus. Overexpression of GLUT3, specifically in the dentate gyrus (DG) area of the hippocampus, enhanced mitochondrial function and improved cognitive deficits. Activation of the transient receptor potential channel 6 (TRPC6) increased GLUT3-mediated glucose uptake in the brain and alleviated RH-induced cognitive deficits, and inactivation of the Ca2+/AMPK pathway was responsible for TRPC6-induced GLUT3 inhibition. Taken together, RH impairs brain GLUT3-mediated glucose uptake and further provokes neuronal mitochondrial dysfunction by inhibiting TRPC6 expression, which then accelerates progression of cognitive deficits in diabetic APP/PS1 mice. Avoiding RH is essential for glycemic control in patients with diabetes, and TRPC6/GLUT3 represents potent targets for delaying the onset of dementia in patients with diabetes.
Asunto(s)
Enfermedad de Alzheimer , Hiperglucemia , Hipoglucemia , Canales de Potencial de Receptor Transitorio , Enfermedad de Alzheimer/patología , Animales , Glucosa/metabolismo , Transportador de Glucosa de Tipo 3 , Hipoglucemia/complicaciones , Insulina/metabolismo , Ratones , Ratones Transgénicos , Canal Catiónico TRPC6RESUMEN
Two-photon Ca2+ imaging is a leading technique for recording neuronal activities in vivo with cellular or subcellular resolution. However, during experiments, the images often suffer from corruption due to complex noises. Therefore, the analysis of Ca2+ imaging data requires preprocessing steps, such as denoising, to extract biologically relevant information. We present an approach that facilitates imaging data restoration through image denoising performed by a neural network combining spatiotemporal filtering and model blind learning. Tests with synthetic and real two-photon Ca2+ imaging datasets demonstrate that the proposed approach enables efficient restoration of imaging data. In addition, we demonstrate that the proposed approach outperforms the current state-of-the-art methods by evaluating the qualities of the denoising performance of the models quantitatively. Therefore, our method provides an invaluable tool for denoising two-photon Ca2+ imaging data by model blind spatiotemporal processing.
RESUMEN
Neurostimulant drugs or magnetic/electrical stimulation techniques can overcome attention deficits, but these drugs or techniques are weakly beneficial in boosting the learning capabilities of healthy subjects. Here, we report a stimulation technique, mid-infrared modulation (MIM), that delivers mid-infrared light energy through the opened skull or even non-invasively through a thinned intact skull and can activate brain neurons in vivo without introducing any exogeneous gene. Using c-Fos immunohistochemistry, in vivo single-cell electrophysiology and two-photon Ca2+ imaging in mice, we demonstrate that MIM significantly induces firing activities of neurons in the targeted cortical area. Moreover, mice that receive MIM targeting to the auditory cortex during an auditory associative learning task exhibit a faster learning speed (~50% faster) than control mice. Together, this non-invasive, opsin-free MIM technique is demonstrated with potential for modulating neuronal activity.
Asunto(s)
Corteza Auditiva/metabolismo , Neuronas/metabolismo , Opsinas/metabolismo , Animales , Electrofisiología , Inmunohistoquímica , Masculino , Ratones , Opsinas/genética , Proteínas Proto-Oncogénicas c-fos/genética , Proteínas Proto-Oncogénicas c-fos/metabolismoRESUMEN
BACKGROUND: Recurrent moderate hypoglycemia (RH), a major adverse effect of hypoglycemic therapy in diabetic patients, is one of the main risk factors for cognitive impairment and dementia. Transient receptor potential canonical channel 6 (TRPC6) is a potential therapeutic target for Alzheimer's disease (AD) and its expression is highly regulated by glucose concentration. OBJECTIVE: To investigate whether RH regulates the expression of TRPC6 in brain and whether TRPC6 dysfunction can drive hypoglycemia-associated cognitive impairment in diabetes, and reveal the underlying mechanism. METHODS: Histological staining, in vivo two-photon Ca2+ imaging, and behavioral tests were used to measure neuronal death, brain network activity, and cognitive function in mice, respectively. High-resolution respirometry and transmission electron microscope were used to assess mitochondrial structure and function. Intracellular calcium measurement and molecular biology techniques were conducted to uncover the underlying mechanism. RESULTS: Here, we report that the expression of TRPC6 in hippocampus was specifically repressed by RH in streptozocin-induced type 1 diabetic mice, but not in nondiabetic mice. TRPC6 knockout directly leads to neuron loss, neuronal activity, and cognitive function impairment under diabetic condition, the degree of which is similar to that of RH. Activation of TRPC6 with hyperforin substantially improved RH-induced cognitive impairment. Mechanistically, TRPC6 inhibited mitochondrial fission in the hippocampus of diabetic mice undergoing RH episodes by activating adenosine 5'-monophosphate-activated protein kinase, and TRPC6-mediated cytosolic calcium influx was required for this process. Clinically, dysfunction of TRPC6 was closely associated with cognitive impairment in type 2 diabetic patients with RH. CONCLUSIONS: Our results indicate that TRPC6 is a critical sensitive cation channel to hypoglycemia and is a promising target to prevent RH-induced cognitive impairment by properly orchestrating the mitochondrial dynamics in diabetic patients.