Determining Burst Firing Time Distributions from Multiple Spike Trains

2009 ◽  
Vol 21 (4) ◽  
pp. 973-990 ◽  
Author(s):  
Luis F. Lago-Fernández ◽  
Attila Szücs ◽  
Pablo Varona
Keyword(s):  
Temporal Structure ◽  
Alignment Algorithm ◽  
Firing Time ◽  
Cell Type ◽  
Firing Patterns ◽  
Bursting Neurons ◽  
Cell Type Specific ◽  
Experimental Findings ◽  
General Tool

Recent experimental findings have shown the presence of robust and cell-type-specific intraburst firing patterns in bursting neurons. We address the problem of characterizing these patterns under the assumption that the bursts exhibit well-defined firing time distributions. We propose a method for estimating these distributions based on a burst alignment algorithm that minimizes the overlap among the firing time distributions of the different spikes within the burst. This method provides a good approximation to the burst's intrinsic temporal structure as a set of firing time distributions. In addition, the method allows labeling the spikes in any particular burst, establishing a correspondence between each spike and the distribution that best explains it, and identifying missing spikes. Our results on both simulated and experimental data from the lobster stomatogastric ganglion show that the proposed method provides a reliable characterization of the intraburst firing patterns and avoids the errors derived from missing spikes. This method can also be applied to nonbursting neurons as a general tool for the study and the interpretation of firing time distributions as part of a temporal neural code.

scholarly journals Connectivity characterization of the mouse basolateral amygdalar complex

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Houri Hintiryan ◽  
Ian Bowman ◽  
David L. Johnson ◽  
Laura Korobkova ◽  
Muye Zhu ◽  
...  
Keyword(s):  
Granular Cell ◽  
Cell Types ◽  
Projection Neurons ◽  
Cell Type ◽  
Connectivity Map ◽  
Analysis Techniques ◽  
Domain Specific ◽  
Cell Type Specific ◽  
Unique Domain

AbstractThe basolateral amygdalar complex (BLA) is implicated in behaviors ranging from fear acquisition to addiction. Optogenetic methods have enabled the association of circuit-specific functions to uniquely connected BLA cell types. Thus, a systematic and detailed connectivity profile of BLA projection neurons to inform granular, cell type-specific interrogations is warranted. Here, we apply machine-learning based computational and informatics analysis techniques to the results of circuit-tracing experiments to create a foundational, comprehensive BLA connectivity map. The analyses identify three distinct domains within the anterior BLA (BLAa) that house target-specific projection neurons with distinguishable morphological features. We identify brain-wide targets of projection neurons in the three BLAa domains, as well as in the posterior BLA, ventral BLA, posterior basomedial, and lateral amygdalar nuclei. Inputs to each nucleus also are identified via retrograde tracing. The data suggests that connectionally unique, domain-specific BLAa neurons are associated with distinct behavior networks.

Cytometric Profiling of CD133+ Cells in Human Colon Carcinoma Cell Lines Identifies a Common core Phenotype and Cell Type-specific Mosaics

2013 ◽  
Vol 28 (3) ◽  
pp. 267-273 ◽  
Author(s):  
Marica Gemei ◽  
Rosa Di Noto ◽  
Peppino Mirabelli ◽  
Luigi Del Vecchio
Keyword(s):  
Colorectal Cancer ◽  
Stem Cells ◽  
Cancer Stem Cells ◽  
Colon Carcinoma ◽  
Cell Lines ◽  
Carcinoma Cell ◽  
Cell Type ◽  
Carcinoma Cell Lines ◽  
Cell Type Specific

In colorectal cancer, CD133+ cells from fresh biopsies proved to be more tumorigenic than their CD133– counterparts. Nevertheless, the function of CD133 protein in tumorigenic cells seems only marginal. Moreover, CD133 expression alone is insufficient to isolate true cancer stem cells, since only 1 out of 262 CD133+ cells actually displays stem-cell capacity. Thus, new markers for colorectal cancer stem cells are needed. Here, we show the extensive characterization of CD133+ cells in 5 different colon carcinoma continuous cell lines (HT29, HCT116, Caco2, GEO and LS174T), each representing a different maturation level of colorectal cancer cells. Markers associated with stemness, tumorigenesis and metastatic potential were selected. We identified 6 molecules consistently present on CD133+ cells: CD9, CD29, CD49b, CD59, CD151, and CD326. By contrast, CD24, CD26, CD54, CD66c, CD81, CD90, CD99, CD112, CD164, CD166, and CD200 showed a discontinuous behavior, which led us to identify cell type-specific surface antigen mosaics. Finally, some antigens, e.g. CD227, indicated the possibility of classifying the CD133+ cells into 2 subsets likely exhibiting specific features. This study reports, for the first time, an extended characterization of the CD133+ cells in colon carcinoma cell lines and provides a “dictionary” of antigens to be used in colorectal cancer research.

Characterization of cell type-specific S100B expression in the mouse olfactory bulb

Cell Calcium ◽  
2021 ◽  
Vol 94 ◽  
pp. 102334
Author(s):  
Xin Su ◽  
Tamara Vasilkovska ◽  
Nicole Fröhlich ◽  
Olga Garaschuk
Keyword(s):  
Olfactory Bulb ◽  
Cell Type ◽  
Cell Type Specific

scholarly journals Identification and characterization of cell type-specific and ubiquitous chromatin regulatory structures in the human genome

PLoS Genetics ◽  
2005 ◽  
Vol preprint (2007) ◽  
pp. e136
Author(s):  
Hualin Xi ◽  
Hennady P Shulha ◽  
Jane M Lin ◽  
Teresa R Vales ◽  
Yutao Fu ◽  
...  
Keyword(s):  
Human Genome ◽  
Cell Type ◽  
Cell Type Specific ◽  
Identification And Characterization

scholarly journals Characterization of Cre recombinase  mouse lines enabling cell type‐specific targeting of postnatal intervertebral discs

2019 ◽  
Vol 234 (9) ◽  
pp. 14422-14431 ◽  
Author(s):  
Yixin Zheng ◽  
Xuejie Fu ◽  
Qingbai Liu ◽  
Shengqi Guan ◽  
Cunchang Liu ◽  
...  
Keyword(s):  
Cre Recombinase ◽  
Intervertebral Discs ◽  
Cell Type ◽  
Specific Targeting ◽  
Cell Type Specific ◽  
Mouse Lines

scholarly journals Multilayer OMICS characterization of APOE‐modulated isogenic hiPSCs elucidates cell‐type–specific mechanisms modified by APOE: A study of the IMI ADAPTED Consortium

2020 ◽  
Vol 16 (S2) ◽  
Author(s):  
Janina S. Ried ◽  
Marco Rocha Curado ◽  
María Eugenia Sáez ◽  
Lamiaa Bahnassawy ◽  
Heyne Lee ◽  
...  
Keyword(s):  
Cell Type ◽  
Cell Type Specific

scholarly journals Bulk Tissue Cell Type Deconvolution with Multi-Subject Single-Cell Expression Reference

2018 ◽  
Author(s):  
Xuran Wang ◽  
Jihwan Park ◽  
Katalin Susztak ◽  
Nancy R. Zhang ◽  
Mingyao Li
Keyword(s):  
Single Cell ◽  
Cell Types ◽  
Cellular Heterogeneity ◽  
Tissue Cell ◽  
Specific Gene ◽  
Rna Seq ◽  
Cell Type ◽  
Cell Type Specific ◽  
Cell Expression

AbstractWe present MuSiC, a method that utilizes cell-type specific gene expression from single-cell RNA sequencing (RNA-seq) data to characterize cell type compositions from bulk RNA-seq data in complex tissues. When applied to pancreatic islet and whole kidney expression data in human, mouse, and rats, MuSiC outperformed existing methods, especially for tissues with closely related cell types. MuSiC enables characterization of cellular heterogeneity of complex tissues for identification of disease mechanisms.

scholarly journals Subcellular sequencing of single neurons reveals the dendritic transcriptome of GABAergic interneurons

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Julio D Perez ◽  
Susanne tom Dieck ◽  
Beatriz Alvarez-Castelao ◽  
Georgi Tushev ◽  
Ivy CW Chan ◽  
...  
Keyword(s):  
Hippocampal Neurons ◽  
Large Population ◽  
Cell Types ◽  
Mrna Localization ◽  
Gabaergic Neurons ◽  
Local Translation ◽  
Single Neurons ◽  
Cell Type ◽  
Cell Type Specific

Although mRNAs are localized in the processes of excitatory neurons, it is still unclear whether interneurons also localize a large population of mRNAs. In addition, the variability in the localized mRNA population within and between cell-types is unknown. Here we describe the unbiased transcriptomic characterization of the subcellular compartments of hundreds of single neurons. We separately profiled the dendritic and somatic transcriptomes of individual rat hippocampal neurons and investigated mRNA abundances in the soma and dendrites of single glutamatergic and GABAergic neurons. We found that, like their excitatory counterparts, interneurons contain a rich repertoire of ~4000 mRNAs. We observed more cell type-specific features among somatic transcriptomes than their associated dendritic transcriptomes. Finally, using cell-type specific metabolic labelling of isolated neurites, we demonstrated that the processes of Glutamatergic and, notably, GABAergic neurons were capable of local translation, suggesting mRNA localization and local translation is a general property of neurons.

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