PhAT: A flexible open-source GUI-driven toolkit for photometry analysis (original) (raw)
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Journal of Neuroscience Methods, 2019
Background: The development and increasing adoption of advanced microscopy imaging technologies, including high resolution, multi-dimensional digital photography and multiple fluorescence channel acquisition, as well as the availability of inexpensive terabyte-capacity storage, have enabled research laboratories to pursue neurohistological imaging experiments involving multiple neurochemical probes and experimental conditions covering a variety of brain regions. Analyzing and processing the resulting datasets, composed of hundreds of micrographs, presents challenges in ensuring accuracy and reproducibility under demanding time and training constraints. New method: The 'Custom Macros' plugin suite for ImageJ automates and systematizes user interaction in neurohistological image analysis tasks, including region selection and thresholding, point/object counts, area measurement, batch filter processing, and data review. Written in the accessible ImageJ macro language, the plugin implements a user login-based data storage framework and facilitates inter-laboratory collaboration over cloud file server clients. Results: A macro-based interface approach integrates dozens of novel operations, software interactions, algorithm calls, and background tasks into individual shortcut commands. Every completed procedure generates image, region, and calibrated measurement records that are saved in a standardized folder structure. Comparisons with existing methods: Plugin installation adds startup access to a persistent interface layer of extensive and streamlined functionality that is generalizable to a variety of neurohistological contexts, thus providing an efficient and reliable alternative to the use of analysis software in an unstructured, provisional manner that necessitates repeated menu and plugin interaction. Conclusions: Our free/open-source software provides researchers a straightforward solution to addressing daunting usability and data oversight issues, ultimately making efficient, accessible, and reproducible image analysis methodology attainable for many laboratories.
OpenFluo: A free open-source software for optophysiological data analyses
Journal of Neuroscience Methods, 2009
Optophysiological imaging methods can be used to record the activity in vivo of groups of neurons from particular areas of the nervous system (e.g. the brain) or of cell cultures. Such methods are used, for example, in the spatio-temporal coding and processing of sensory information. However, the data generated by optophysiological methods must be processed carefully if relevant results are to be obtained. The raw fluorescence data must be digitally filtered and analyzed appropriately to obtain activity maps and fluorescence time course for single spots. We used a Matlab ® environment to implement the necessary procedures in a user-friendly manner. We developed OpenFluo, a program for people inexperienced in optophysiological methods and for advanced users wishing to perform simple, rapid data analyses without the need for complex, time-consuming programming procedures. This program will be made available as stand-alone software and as an open-source Matlab ® tool. It will therefore be possible for experienced users to integrate their own routines. We validated this software by assessing its ability to process both artificial recordings and real biological data corresponding to recordings of the honeybee brain.
A beginner’s guide to rigor and reproducibility in fluorescence imaging experiments
Molecular Biology of the Cell, 2018
Fluorescence light microscopy is an indispensable approach for the investigation of cell biological mechanisms. With the development of cutting-edge tools such as genetically encoded fluorescent proteins and superresolution methods, light microscopy is more powerful than ever at providing insight into a broad range of phenomena, from bacterial fission to cancer metastasis. However, as with all experimental approaches, care must be taken to ensure reliable and reproducible data collection, analysis, and reporting. Each step of every imaging experiment, from design to execution to communication to data management, should be critically assessed for bias, rigor, and reproducibility. This Perspective provides a basic “best practices” guide for designing and executing fluorescence imaging experiments, with the goal of introducing researchers to concepts that will help empower them to acquire images with rigor.
2020
Collaboration in neuroscience is impeded by the difficulty of sharing primary data, results, and software across labs. Here we introduce Neuroscience Data Interface (NDI), a platform-independent standard that allows an analyst to use and create software that functions independently from the format of the raw data or the manner in which the data is organized into files. The interface is rooted in a simple vocabulary that describes common apparatus and storage devices used in neuroscience experiments. Results of analyses – and analyses of analyses – are stored as documents in a scalable, queryable database that stores the relationships and history among the experiment elements and documents. The interface allows the development of an application ecosystem where applications can focus on calculation rather than data format or organization. This tool can be used by individual labs to exchange and analyze data, and it can serve to curate neuroscience data for searchable archives.
Journal of Neurochemistry, 2013
The direct visualization of subcellular dynamic processes is often hampered by limitations in the resolving power achievable with conventional microscopy techniques. Fluorescence recovery after photobleaching has emerged as a highly informative approach to address this challenge, permitting the quantitative measurement of the movement of small organelles and proteins in living functioning cells, and offering detailed insights into fundamental cellular phenomena of physiological importance. In recent years, its implementation has benefited from the increasing availability of confocal microscopy systems and of powerful labeling techniques based on genetically encoded fluorescent proteins or other chemical markers. In this review, we present fluorescence recovery after photobleaching and related techniques in the context of contemporary neurobiological research and discuss quantitative and semi-quantitative approaches to their interpretation.
Vobi One: a data processing software package for functional optical imaging
Frontiers in Neuroscience, 2014
Optical imaging is the only technique that allows to record the activity of a neuronal population at the mesoscopic scale. A large region of the cortex (10-20 mm diameter) is directly imaged with a CCD camera while the animal performs a behavioral task, producing spatio-temporal data with an unprecedented combination of spatial and temporal resolutions (respectively, tens of micrometers and milliseconds). However, researchers who have developed and used this technique have relied on heterogeneous software and methods to analyze their data. In this paper, we introduce Vobi One, a software package entirely dedicated to the processing of functional optical imaging data. It has been designed to facilitate the processing of data and the comparison of different analysis methods. Moreover, it should help bring good analysis practices to the community because it relies on a database and a standard format for data handling and it provides tools that allow producing reproducible research. Vobi One is an extension of the BrainVISA software platform, entirely written with the Python programming language, open source and freely available for download at https://trac.int.univ-amu.fr/vobi\_one.
Genetically Encoded Fluorescent Indicators for Imaging Brain Chemistry
2021
Genetically encoded fluorescent indicators, combined with optical imaging, enable the detection of physiologically or behaviorally relevant neural activity with high spatiotemporal resolution. Recent developments in protein engineering and screening strategies have improved the dynamic range, kinetics, and spectral properties of genetically encoded fluorescence indicators of brain chemistry. Such indicators have detected neurotransmitter and calcium dynamics with high signal-to-noise ratio at multiple temporal and spatial scales in vitro and in vivo. This review summarizes the current trends in these genetically encoded fluorescent indicators of neurotransmitters and calcium, focusing on their key metrics and in vivo applications.
EZcalcium: Open Source Toolbox for Analysis of Calcium Imaging Data
2020
Fluorescence calcium imaging using a range of microscopy approaches, such as 2-photon excitation or head-mounted ‘miniscopes’, is one of the preferred methods to record neuronal activity and glial signals in various experimental settings, including acute brain slices, brain organoids, and behaving animals. Because changes in the fluorescence intensity of genetically encoded or chemical calcium indicators correlate with action potential firing in neurons, data analysis is based on inferring such spiking from changes in pixel intensity values across time within different regions of interest. However, the algorithms necessary to extract biologically relevant information from these fluorescent signals are complex and require significant expertise in programming to develop robust analysis pipelines. For decades, the only way to perform these analyses was for individual laboratories to write their own custom code. These routines were typically not well annotated and lacked intuitive graph...
EasyFRAP-web: a web-based tool for the analysis of fluorescence recovery after photobleaching data
Nucleic Acids Research
Understanding protein dynamics is crucial in order to elucidate protein function and interactions. Advances in modern microscopy facilitate the exploration of the mobility of fluorescently tagged proteins within living cells. Fluorescence recovery after photobleaching (FRAP) is an increasingly popular functional live-cell imaging technique which enables the study of the dynamic properties of proteins at a single-cell level. As an increasing number of labs generate FRAP datasets, there is a need for fast, interactive and user-friendly applications that analyze the resulting data. Here we present easyFRAP-web, a web application that simplifies the qualitative and quantitative analysis of FRAP datasets. EasyFRAP-web permits quick analysis of FRAP datasets through an intuitive web interface with interconnected analysis steps (experimental data assessment, different types of normalization and estimation of curve-derived quantitative parameters). In addition, easyFRAP-web provides dynamic and interactive data visualization and data and figure export for further analysis after every step. We test easyFRAP-web by analyzing FRAP datasets capturing the mobility of the cell cycle regulator Cdt2 in the presence and absence of DNA damage in cultured cells. We show that easyFRAP-web yields results consistent with previous studies and highlights cellto-cell heterogeneity in the estimated kinetic parameters. EasyFRAP-web is platform-independent and is freely accessible at: https://easyfrap.vmnet.upatras. gr/.
PackIO and EphysViewer: software tools for acquisition and analysis of neuroscience data
2016
We present an open-source synchronization software package, PackIO, that can record and generate voltage signals to enable complex experimental paradigms across multiple devices. This general purpose package is built on National Instruments data acquisition and generation hardware and has temporal precision up to the limit of the hardware. PackIO acts as a flexibly programmable master clock that can record experimental data (e.g. voltage traces), timing data (e.g. event times such as imaging frame times) while generating stimuli (e.g. voltage waveforms, voltage triggers to drive other devices, etc.). PackIO is particularly useful to record from and synchronize multiple devices, for example when simultaneously acquiring electrophysiology while generating and recording imaging timing data. Experimental control is easily enabled by an intuitive graphical user interface. We also release an open-source data visualisation and analysis tool, EphysViewer, written in MATLAB, as well as a mod...