Recent advances in computational methods for measurement of dendritic spines imaged by light microscopy

Spot Spine, a freely available ImageJ plugin for 3D detection and morphological analysis of dendritic spines

Background

Dendritic spines are tiny protrusions found along the dendrites of neurons, and their number is a measure of the density of synaptic connections. Altered density and morphology is observed in several pathologies, and spine formation as well as morphological changes correlate with learning and memory. The detection of spines in microscopy images and the analysis of their morphology is therefore a prerequisite for many studies. We have developed a new open-source, freely available, plugin for ImageJ/FIJI, called Spot Spine, that allows detection and morphological measurements of spines in three dimensional images.

Method

Local maxima are detected in spine heads, and the intensity distribution around the local maximum is computed to perform the segmentation of each spine head. Spine necks are then traced from the spine head to the dendrite. Several parameters can be set to optimize detection and segmentation, and manual correction gives further control over the result of the process.

Results

The plugin allows the analysis of images of dendrites obtained with various labeling and imaging methods. Quantitative measurements are retrieved including spine head volume and surface, and neck length.

Conclusion

The plugin and instructions for use are available at https://imagej.net/plugins/spot-spine.

Between neurons and networks: investigating mesoscale brain connectivity in neurological and psychiatric disorders

The study of brain connectivity has been a cornerstone in understanding the complexities of neurological and psychiatric disorders. It has provided invaluable insights into the functional architecture of the brain and how it is perturbed in disorders. However, a persistent challenge has been achieving the proper spatial resolution, and developing computational algorithms to address biological questions at the multi-cellular level, a scale often referred to as the mesoscale. Historically, neuroimaging studies of brain connectivity have predominantly focused on the macroscale, providing insights into inter-regional brain connections but often falling short of resolving the intricacies of neural circuitry at the cellular or mesoscale level. This limitation has hindered our ability to fully comprehend the underlying mechanisms of neurological and psychiatric disorders and to develop targeted interventions. In light of this issue, our review manuscript seeks to bridge this critical gap by delving into the domain of mesoscale neuroimaging. We aim to provide a comprehensive overview of conditions affected by aberrant neural connections, image acquisition techniques, feature extraction, and data analysis methods that are specifically tailored to the mesoscale. We further delineate the potential of brain connectivity research to elucidate complex biological questions, with a particular focus on schizophrenia and epilepsy. This review encompasses topics such as dendritic spine quantification, single neuron morphology, and brain region connectivity. We aim to showcase the applicability and significance of mesoscale neuroimaging techniques in the field of neuroscience, highlighting their potential for gaining insights into the complexities of neurological and psychiatric disorders.

Current Best Practices for Analysis of Dendritic Spine Morphology and Number in Neurodevelopmental Disorder Research

Quantitative methods for assessing neural anatomy have rapidly evolved in neuroscience and provide important insights into brain health and function. However, as new techniques develop, it is not always clear when and how each may be used to answer specific scientific questions posed. Dendritic spines, which are often indicative of synapse formation and neural plasticity, have been implicated across many brain regions in neurodevelopmental disorders as a marker for neural changes reflecting neural dysfunction or alterations. In this Perspective we highlight several techniques for staining, imaging, and quantifying dendritic spines as well as provide a framework for avoiding potential issues related to pseudoreplication. This framework illustrates how others may apply the most rigorous approaches. We consider the cost-benefit analysis of the varied techniques, recognizing that the most sophisticated equipment may not always be necessary for answering some research questions. Together, we hope this piece will help researchers determine the best strategy toward using the ever-growing number of techniques available to determine neural changes underlying dendritic spine morphology in health and neurodevelopmental disorders.

3dSpAn: An interactive software for 3D segmentation and analysis of dendritic spines

Three-dimensional segmentation and analysis of dendritic spine morphology involve two major challenges: 1) how to segment individual spines from the dendrites and 2) how to quantitatively assess the morphology of individual spines. To address these two issues, we developed software called 3dSpAn (3-dimensional Spine Analysis), based on implementing a previously published method, 3D multi-scale opening algorithm in shared intensity space. 3dSpAn consists of four modules: a) Preprocessing and Region of Interest (ROI) selection, b) Intensity thresholding and seed selection, c) Multi-scale segmentation, and d) Quantitative morphological feature extraction. In this article, we present the results of segmentation and morphological analysis for different observation methods and conditions, including in vitro and ex vivo imaging with confocal microscopy, and in vivo observations using high-resolution two-photon microscopy. In particular, we focus on software usage, the influence of adjustable parameters on the obtained results, user reproducibility, accuracy analysis, and also include a qualitative comparison with a commercial benchmark. 3dSpAn software is freely available for non-commercial use at www.3dSpAn.org .

A Deep Learning-Based Workflow for Dendritic Spine Segmentation

The morphological analysis of dendritic spines is an important challenge for the neuroscientific community. Most state-of-the-art techniques rely on user-supervised algorithms to segment the spine surface, especially those designed for light microscopy images. Therefore, processing large dendritic branches is costly and time-consuming. Although deep learning (DL) models have become one of the most commonly used tools in image segmentation, they have not yet been successfully applied to this problem. In this article, we study the feasibility of using DL models to automatize spine segmentation from confocal microscopy images. Supervised learning is the most frequently used method for training DL models. This approach requires large data sets of high-quality segmented images (ground truth). As mentioned above, the segmentation of microscopy images is time-consuming and, therefore, in most cases, neuroanatomists only reconstruct relevant branches of the stack. Additionally, some parts of the dendritic shaft and spines are not segmented due to dyeing problems. In the context of this research, we tested the most successful architectures in the DL biomedical segmentation field. To build the ground truth, we used a large and high-quality data set, according to standards in the field. Nevertheless, this data set is not sufficient to train convolutional neural networks for accurate reconstructions. Therefore, we implemented an automatic preprocessing step and several training strategies to deal with the problems mentioned above. As shown by our results, our system produces a high-quality segmentation in most cases. Finally, we integrated several postprocessing user-supervised algorithms in a graphical user interface application to correct any possible artifacts.

Imaging neural circuit pathology of autism spectrum disorders: autism-associated genes, animal models and the application of in vivo two-photon imaging

Recent advances in human genetics identified genetic variants involved in causing autism spectrum disorders (ASDs). Mouse models that mimic mutations found in patients with ASD exhibit behavioral phenotypes consistent with ASD symptoms. These mouse models suggest critical biological factors of ASD etiology. Another important implication of ASD genetics is the enrichment of ASD risk genes in molecules involved in developing synapses and regulating neural circuit function. Sophisticated in vivo imaging technologies applied to ASD mouse models identify common synaptic impairments in the neocortex, with genetic-mutation-specific defects in local neural circuits. In this article, we review synapse- and circuit-level phenotypes identified by in vivo two-photon imaging in multiple mouse models of ASD and discuss the contributions of altered synapse properties and neural circuit activity to ASD pathogenesis.

Advanced Technologies for Local Neural Circuits in the Cerebral Cortex

The neural network in the brain can be viewed as an integrated system assembled from a large number of local neural circuits specialized for particular brain functions. Activities of neurons in local neural circuits are thought to be organized both spatially and temporally under the rules optimized for their roles in information processing. It is well perceived that different areas of the mammalian neocortex have specific cognitive functions and distinct computational properties. However, the organizational principles of the local neural circuits in different cortical regions have not yet been clarified. Therefore, new research principles and related neuro-technologies that enable efficient and precise recording of large-scale neuronal activities and synaptic connections are necessary. Innovative technologies for structural analysis, including tissue clearing and expansion microscopy, have enabled super resolution imaging of the neural circuits containing thousands of neurons at a single synapse resolution. The imaging resolution and volume achieved by new technologies are beyond the limits of conventional light or electron microscopic methods. Progress in genome editing and related technologies has made it possible to label and manipulate specific cell types and discriminate activities of multiple cell types. These technologies will provide a breakthrough for multiscale analysis of the structure and function of local neural circuits. This review summarizes the basic concepts and practical applications of the emerging technologies and new insight into local neural circuits obtained by these technologies.

Super-Resolution Microscopy: Shedding New Light on In Vivo Imaging

Over the past two decades, super-resolution microscopy (SRM), which offered a significant improvement in resolution over conventional light microscopy, has become a powerful tool to visualize biological activities in both fixed and living cells. However, completely understanding biological processes requires studying cells in a physiological context at high spatiotemporal resolution. Recently, SRM has showcased its ability to observe the detailed structures and dynamics in living species. Here we summarized recent technical advancements in SRM that have been successfully applied to in vivo imaging. Then, improvements in the labeling strategies are discussed together with the spectroscopic and chemical demands of the fluorophores. Finally, we broadly reviewed the current applications for super-resolution techniques in living species and highlighted some inherent challenges faced in this emerging field. We hope that this review could serve as an ideal reference for researchers as well as beginners in the relevant field of in vivo super resolution imaging.

Three-Dimensional Structure of Dendritic Spines Revealed by Volume Electron Microscopy Techniques

Electron microscopy (EM)-based synaptology is a fundamental discipline for achieving a complex wiring diagram of the brain. A quantitative understanding of synaptic ultrastructure also serves as a basis to estimate the relative magnitude of synaptic transmission across individual circuits in the brain. Although conventional light microscopic techniques have substantially contributed to our ever-increasing understanding of the morphological characteristics of the putative synaptic junctions, EM is the gold standard for systematic visualization of the synaptic morphology. Furthermore, a complete three-dimensional reconstruction of an individual synaptic profile is required for the precise quantitation of different parameters that shape synaptic transmission. While volumetric imaging of synapses can be routinely obtained from the transmission EM (TEM) imaging of ultrathin sections, it requires an unimaginable amount of effort and time to reconstruct very long segments of dendrites and their spines from the serial section TEM images. The challenges of low throughput EM imaging have been addressed to an appreciable degree by the development of automated EM imaging tools that allow imaging and reconstruction of dendritic segments in a realistic time frame. Here, we review studies that have been instrumental in determining the three-dimensional ultrastructure of synapses. With a particular focus on dendritic spine synapses in the rodent brain, we discuss various key studies that have highlighted the structural diversity of spines, the principles of their organization in the dendrites, their presynaptic wiring patterns, and their activity-dependent structural remodeling.

Quantification of Dendritic Spines Remodeling under Physiological Stimuli and in Pathological Conditions

Numerous brain diseases are associated with abnormalities in morphology and density of dendritic spines, small membranous protrusions whose structural geometry correlates with the strength of synaptic connections. Thus, the quantitative analysis of dendritic spines remodeling in microscopic images is one of the key elements towards understanding mechanisms of structural neuronal plasticity and bases of brain pathology. In the following article, we review experimental approaches designed to assess quantitative features of dendritic spines under physiological stimuli and in pathological conditions. We compare various methodological pipelines of biological models, sample preparation, data analysis, image acquisition, sample size, and statistical analysis. The methodology and results of relevant experiments are systematically summarized in a tabular form. In particular, we focus on quantitative data regarding the number of animals, cells, dendritic spines, types of studied parameters, size of observed changes, and their statistical significance.

The role of molecular diffusion within dendritic spines in synaptic function

Spines are tiny nanoscale protrusions from dendrites of neurons. In the cortex and hippocampus, most of the excitatory postsynaptic sites reside in spines. The bulbous spine head is connected to the dendritic shaft by a thin membranous neck. Because the neck is narrow, spine heads are thought to function as biochemically independent signaling compartments. Thus, dynamic changes in the composition, distribution, mobility, conformations, and signaling properties of molecules contained within spines can account for much of the molecular basis of postsynaptic function and regulation. A major factor in controlling these changes is the diffusional properties of proteins within this small compartment. Advances in measurement techniques using fluorescence microscopy now make it possible to measure molecular diffusion within single dendritic spines directly. Here, we review the regulatory mechanisms of diffusion in spines by local intra-spine architecture and discuss their implications for neuronal signaling and synaptic plasticity.

Imaging of spine synapses using super-resolution microscopy

Neuronal circuits in the neocortex and hippocampus are essential for higher brain functions such as motor learning and spatial memory. In the mammalian forebrain, most excitatory synapses of pyramidal neurons are formed on spines, which are tiny protrusions extending from the dendritic shaft. The spine contains specialized molecular machinery that regulates synaptic transmission and plasticity. Spine size correlates with the efficacy of synaptic transmission, and spine morphology affects signal transduction at the post-synaptic compartment. Plasticity-related changes in the structural and molecular organization of spine synapses are thought to underlie the cellular basis of learning and memory. Recent advances in super-resolution microscopy have revealed the molecular mechanisms of the nanoscale synaptic structures regulating synaptic transmission and plasticity in living neurons, which are difficult to investigate using electron microscopy alone. In this review, we summarize recent advances in super-resolution imaging of spine synapses and discuss the implications of nanoscale structures in the regulation of synaptic function, learning, and memory.

Geometry and the Organizational Principle of Spine Synapses along a Dendrite

Precise information on synapse organization in a dendrite is crucial to understanding the mechanisms underlying voltage integration and the variability in the strength of synaptic inputs across dendrites of different complex morphologies. Here, we used focused ion beam/scanning electron microscope (FIB/SEM) to image the dendritic spines of mice in the hippocampal CA1 region, CA3 region, somatosensory cortex, striatum, and cerebellum (CB). Our results show that the spine geometry and dimensions differ across neuronal cell types. Despite this difference, dendritic spines were organized in an orchestrated manner such that the postsynaptic density (PSD) area per unit length of dendrite scaled positively with the dendritic diameter in CA1 proximal stratum radiatum (PSR), cortex, and CB. The ratio of the PSD area to neck length was kept relatively uniform across dendrites of different diameters in CA1 PSR. Computer simulation suggests that a similar level of synaptic strength across different dendrites in CA1 PSR enables the effective transfer of synaptic inputs from the dendrites toward soma. Excitatory postsynaptic potentials (EPSPs), evoked at single spines by glutamate uncaging and recorded at the soma, show that the neck length is more influential than head width in regulating the EPSP magnitude at the soma. Our study describes thorough morphologic features and the organizational principles of dendritic spines in different brain regions.

Dendrimers as Modulators of Brain Cells

Nanostructured hyperbranched macromolecules have been extensively studied at the chemical, physical and morphological levels. The cellular structural and functional complexity of neural cells and their cross-talk have made it rather difficult to evaluate dendrimer effects in a mixed population of glial cells and neurons. Thus, we are at a relatively early stage of bench-to-bedside translation, and this is due mainly to the lack of data valuable for clinical investigations. It is only recently that techniques have become available that allow for analyses of biological processes inside the living cells, at the nanoscale, in real time. This review summarizes the essential properties of neural cells and dendrimers, and provides a cross-section of biological, pre-clinical and early clinical studies, where dendrimers were used as nanocarriers. It also highlights some examples of biological studies employing dendritic polyglycerol sulfates and their effects on glia and neurons. It is the aim of this review to encourage young scientists to advance mechanistic and technological approaches in dendrimer research so that these extremely versatile and attractive nanostructures gain even greater recognition in translational medicine.