@article {68709, title = {BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets.}, journal = {Nature Methods}, volume = {20}, year = {2023}, month = {2023 Jun 01}, abstract = {

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

}, issn = {1548-7105}, doi = {10.1038/s41592-023-01848-5}, author = {Manubens-Gil, Linus and Zhou, Zhi and Chen, Hanbo and Ramanathan, Arvind and Liu, Xiaoxiao and Liu, Yufeng and Bria, Alessandro and Gillette, Todd and Ruan, Zongcai and Yang, Jian and Radojevi{\'c}, Miroslav and Zhao, Ting and Cheng, Li and Qu, Lei and Liu, Siqi and Bouchard, Kristofer E and Gu, Lin and Cai, Weidong and Ji, Shuiwang and Roysam, Badrinath and Wang, Ching-Wei and Yu, Hongchuan and Sironi, Amos and Iascone, Daniel Maxim and Zhou, Jie and Bas, Erhan and Conde-Sousa, Eduardo and Aguiar, Paulo and Li, Xiang and Li, Yujie and Nanda, Sumit and Wang, Yuan and Muresan, Leila and Fua, Pascal and Ye, Bing and He, Hai-Yan and Staiger, Jochen F and Peter, Manuel and Cox, Daniel N and Simonneau, Michel and Oberlaender, Marcel and Jefferis, Gregory and Ito, Kei and Gonzalez-Bellido, Paloma and Kim, Jinhyun and Rubel, Edwin and Cline, Hollis T and Zeng, Hongkui and Nern, Aljoscha and Chiang, Ann-Shyn and Yao, Jianhua and Roskams, Jane and Livesey, Rick and Stevens, Janine and Liu, Tianming and Dang, Chinh and Guo, Yike and Zhong, Ning and Tourassi, Georgia and Hill, Sean and Hawrylycz, Michael and Koch, Christof and Meijering, Erik and Ascoli, Giorgio A and Peng, Hanchuan} } @article {49196, title = {Schaffer collateral inputs to CA1 excitatory and inhibitory neurons follow different connectivity rules.}, journal = {The Journal of Neuroscience : the official journal of the Society for Neuroscience}, volume = {38}, year = {2018}, month = {2018 May 04}, pages = {5140-52}, abstract = {

Neural circuits, governed by a complex interplay between excitatory and inhibitory neurons, are the substrate for information processing, and the organization of synaptic connectivity in neural network is an important determinant of circuit function. Here, we analyzed the fine structure of connectivity in hippocampal CA1 excitatory and inhibitory neurons innervated by Schaffer collaterals (SCs) using mGRASP in male mice. Our previous study revealed spatially structured synaptic connectivity between CA3-CA1 pyramidal cells (PCs). Surprisingly, parvalbumin-positive interneurons (PVs) showed a significantly more random pattern spatial structure. Notably, application of Peters{\textquoteright} Rule for synapse prediction by random overlap between axons and dendrites enhanced structured connectivity in PCs, but, by contrast, made the connectivity pattern in PVs more random. In addition, PCs in a deep sublayer of striatum pyramidale appeared more highly structured than PCs in superficial layers, and little or no sublayer specificity was found in PVs. Our results show that CA1 excitatory PCs and inhibitory PVs innervated by the same SC inputs follow different connectivity rules. The different organizations of fine scale structured connectivity in hippocampal excitatory and inhibitory neurons provide important insights into the development and functions of neural networks.Understanding how neural circuits generate behavior is one of the central goals of neuroscience. An important component of this endeavor is the mapping of fine-scale connection patterns that underlie, and help us infer, signal processing in the brain. Here, using our recently developed synapse detection technology (mGRASP and neuTube), we provide detailed profiles of synaptic connectivity in excitatory (CA1 pyramidal) and inhibitory (CA1 parvalbumin-positive) neurons innervated by the same presynaptic inputs (CA3 Schaffer collaterals). Our results reveal that these two types of CA1 neurons follow different connectivity patterns. Our new evidence for differently structured connectivity at a fine scale in hippocampal excitatory and inhibitory neurons provides a better understanding of hippocampal networks and will guide theoretical and experimental studies.

}, issn = {1529-2401}, doi = {10.1523/JNEUROSCI.0155-18.2018}, author = {Kwon, Osung and Feng, Linqing and Druckmann, Shaul and Kim, Jinhyun} } @article {46862, title = {From a meso- to micro-scale connectome: array tomography and mGRASP.}, journal = {Frontiers in Neuroanatomy}, volume = {9}, year = {2015}, month = {2015 Jun 04}, pages = {78}, abstract = {

Mapping mammalian synaptic connectivity has long been an important goal of neuroscience because knowing how neurons and brain areas are connected underpins an understanding of brain function. Meeting this goal requires advanced techniques with single synapse resolution and large-scale capacity, especially at multiple scales tethering the meso- and micro-scale connectome. Among several advanced LM-based connectome technologies, Array Tomography (AT) and mammalian GFP-Reconstitution Across Synaptic Partners (mGRASP) can provide relatively high-throughput mapping synaptic connectivity at multiple scales. AT- and mGRASP-assisted circuit mapping (ATing and mGRASPing), combined with techniques such as retrograde virus, brain clearing techniques, and activity indicators will help unlock the secrets of complex neural circuits. Here, we discuss these useful new tools to enable mapping of brain circuits at multiple scales, some functional implications of spatial synaptic distribution, and future challenges and directions of these endeavors.

}, issn = {1662-5129}, doi = {10.3389/fnana.2015.00078}, author = {Rah, Jong-Cheol and Feng, Linqing and Druckmann, Shaul and Lee, Hojin and Kim, Jinhyun} } @article {6713, title = {Structured synaptic connectivity between hippocampal regions.}, journal = {Neuron}, volume = {81}, year = {2014}, month = {2014 Feb 5}, pages = {629-40}, abstract = {

The organization of synaptic connectivity within a neuronal circuit is a prime determinant of circuit function. We performed a comprehensive fine-scale circuit mapping of hippocampal regions (CA3-CA1) using the newly developed synapse labeling method, mGRASP. This mapping revealed spatially nonuniform and clustered synaptic connectivity patterns. Furthermore, synaptic clustering was enhanced between groups of neurons that shared a similar developmental/migration time window, suggesting a mechanism for establishing the spatial structure of synaptic connectivity. Such connectivity patterns are thought to effectively engage active dendritic processing and storage mechanisms, thereby potentially enhancing neuronal feature selectivity.

}, issn = {1097-4199}, doi = {10.1016/j.neuron.2013.11.026}, author = {Shaul Druckmann and Feng, Linqing and Lee, Bokyoung and Yook, Chaehyun and Zhao, Ting and Magee, Jeffrey C and Kim, Jinhyun} } @article {6714, title = {Mapping mammalian synaptic connectivity.}, journal = {Cellular and Molecular Life Sciences: CMLS}, volume = {70}, year = {2013}, month = {2013 Dec}, pages = {4747-57}, abstract = {

Mapping mammalian synaptic connectivity has long been an important goal of neuroscientists since it is considered crucial for explaining human perception and behavior. Yet, despite enormous efforts, the overwhelming complexity of the neural circuitry and the lack of appropriate techniques to unravel it have limited the success of efforts to map connectivity. However, recent technological advances designed to overcome the limitations of conventional methods for connectivity mapping may bring about a turning point. Here, we address the promises and pitfalls of these new mapping technologies.

}, keywords = {Animals, Brain, Computational Biology, Connectome, Humans, Mammals, Nervous System Diseases, Synapses}, issn = {1420-9071}, doi = {10.1007/s00018-013-1417-y}, author = {Yook, Chaehyun and Druckmann, S and Kim, Jinhyun} } @article {5924, title = {Control of timing, rate and bursts of hippocampal place cells by dendritic and somatic inhibition.}, journal = {Nature neuroscience}, volume = {15}, year = {2012}, month = {2012 May}, pages = {769-75}, abstract = {A consortium of inhibitory neurons control the firing patterns of pyramidal cells, but their specific roles in the behaving animal are largely unknown. We performed simultaneous physiological recordings and optogenetic silencing of either perisomatic (parvalbumin (PV) expressing) or dendrite-targeting (somatostatin (SOM) expressing) interneurons in hippocampal area CA1 of head-fixed mice actively moving a treadmill belt rich with visual-tactile stimuli. Silencing of either PV or SOM interneurons increased the firing rates of pyramidal cells selectively in their place fields, with PV and SOM interneurons having their largest effect during the rising and decaying parts of the place field, respectively. SOM interneuron silencing powerfully increased burst firing without altering the theta phase of spikes. In contrast, PV interneuron silencing had no effect on burst firing, but instead shifted the spikes{\textquoteright} theta phase toward the trough of theta. These findings indicate that perisomatic and dendritic inhibition have distinct roles in controlling the rate, burst and timing of hippocampal pyramidal cells.}, keywords = {Action Potentials, Animal, Animals, Behavior, Biophysics, Dendrites, Electric Stimulation, Exercise Test, Green Fluorescent Proteins, Halorhodopsins, Hippocampus, Humans, Inbred C57BL, Light, Mice, Movement, Neural Inhibition, Neurons, Optics and Photonics, Parvalbumins, Patch-Clamp Techniques, Photic Stimulation, Probability, Somatostatin, Spectrum Analysis, Time Factors, Time Perception, Touch, Transgenic}, issn = {1546-1726}, doi = {10.1038/nn.3077}, author = {Royer, S{\'e}bastien and Zemelman, Boris V and Losonczy, Attila and Kim, Jinhyun and Chance, Frances and Magee, Jeffrey C and Buzs{\'a}ki, Gy{\"o}rgy} } @article {4487, title = {mGRASP enables mapping mammalian synaptic connectivity with light microscopy.}, journal = {Nature Methods}, volume = {9}, year = {2012}, month = {2012 Jan}, pages = {96-102}, abstract = {

The GFP reconstitution across synaptic partners (GRASP) technique, based on functional complementation between two nonfluorescent GFP fragments, can be used to detect the location of synapses quickly, accurately and with high spatial resolution. The method has been previously applied in the nematode and the fruit fly but requires substantial modification for use in the mammalian brain. We developed mammalian GRASP (mGRASP) by optimizing transmembrane split-GFP carriers for mammalian synapses. Using in silico protein design, we engineered chimeric synaptic mGRASP fragments that were efficiently delivered to synaptic locations and reconstituted GFP fluorescence in vivo. Furthermore, by integrating molecular and cellular approaches with a computational strategy for the three-dimensional reconstruction of neurons, we applied mGRASP to both long-range circuits and local microcircuits in the mouse hippocampus and thalamocortical regions, analyzing synaptic distribution in single neurons and in dendritic compartments.

}, issn = {1548-7105}, doi = {10.1038/nmeth.1784}, author = {Kim, Jinhyun and Zhao, Ting and Petralia, Ronald S and Yu, Yang and Peng, Hanchuan and Myers, Eugene and Magee, Jeffrey C} } @article {6388, title = {Scanning light-sheet microscopy in the whole mouse brain with HiLo background rejection.}, journal = {Journal of Biomedical Optics}, volume = {15}, year = {2010}, month = {2010 Jan-Feb}, pages = {016027}, abstract = {

It is well known that light-sheet illumination can enable optically sectioned wide-field imaging of macroscopic samples. However, the optical sectioning capacity of a light-sheet macroscope is undermined by sample-induced scattering or aberrations that broaden the thickness of the sheet illumination. We present a technique to enhance the optical sectioning capacity of a scanning light-sheet microscope by out-of-focus background rejection. The technique, called HiLo microscopy, makes use of two images sequentially acquired with uniform and structured sheet illumination. An optically sectioned image is then synthesized by fusing high and low spatial frequency information from both images. The benefits of combining light-sheet macroscopy and HiLo background rejection are demonstrated in optically cleared whole mouse brain samples, using both green fluorescent protein (GFP)-fluorescence and dark-field scattered light contrast.

}, keywords = {Animals, Background Radiation, Brain, Computer-Assisted, Fluorescence, Image Processing, Mice, Microscopy}, issn = {1560-2281}, doi = {10.1117/1.3324890}, author = {Mertz, Jerome and Kim, Jinhyun} } @article {6487, title = {Tetracycline-controlled transgene activation using the ROSA26-iM2-GFP knock-in mouse strain permits GFP monitoring of DOX-regulated transgene-expression.}, journal = {BMC Developmental Biology}, volume = {10}, year = {2010}, month = {2010}, pages = {95}, abstract = {

BACKGROUND: Conditional gene activation is an efficient strategy for studying gene function in genetically modified animals. Among the presently available gene switches, the tetracycline-regulated system has attracted considerable interest because of its unique potential for reversible and adjustable gene regulation. RESULTS: To investigate whether the ubiquitously expressed Gt(ROSA)26Sor locus enables uniform DOX-controlled gene expression, we inserted the improved tetracycline-regulated transcription activator iM2 together with an iM2 dependent GFP gene into the Gt(ROSA)26Sor locus, using gene targeting to generate ROSA26-iM2-GFP (R26t1Δ) mice. Despite the presence of ROSA26 promoter driven iM2, R26t1Δ mice showed very sparse DOX-activated expression of different iM2-responsive reporter genes in the brain, mosaic expression in peripheral tissues and more prominent expression in erythroid, myeloid and lymphoid lineages, in hematopoietic stem and progenitor cells and in olfactory neurons. CONCLUSIONS: The finding that gene regulation by the DOX-activated transcriptional factor iM2 in the Gt(ROSA)26Sor locus has its limitations is of importance for future experimental strategies involving transgene activation from the endogenous ROSA26 promoter. Furthermore, our ROSA26-iM2 knock-in mouse model (R26t1Δ) represents a useful tool for implementing gene function in vivo especially under circumstances requiring the side-by-side comparison of gene manipulated and wild type cells. Since the ROSA26-iM2 mouse allows mosaic gene activation in peripheral tissues and haematopoietic cells, this model will be very useful for uncovering previously unknown or unsuspected phenotypes.

}, keywords = {Animals, Doxycycline, Gene Knock-In Techniques, Genetic Techniques, Green Fluorescent Proteins, Mice, Tetracycline, Transgenes, Transgenic}, issn = {1471-213X}, doi = {10.1186/1471-213X-10-95}, author = {W{\"o}rtge, Simone and Eshkind, Leonid and Cabezas-Wallscheid, Nina and Lakaye, Bernard and Kim, Jinhyun and Heck, Rosario and Abassi, Yasmin and Diken, Mustafa and Sprengel, Rolf and Bockamp, Ernesto} }