scholarly journals Blind sparse deconvolution for inferring spike trains from fluorescence recordings

2017 ◽  
Author(s):  
Jérôme Tubiana ◽  
Sébastien Wolf ◽  
Georges Debregeas
Keyword(s):  
Action Potentials ◽  
Imaging Techniques ◽  
Real Data ◽  
Computational Framework ◽  
Systems Neuroscience ◽  
Neuronal Populations ◽  
Calcium Indicators ◽  
Genetically Encoded Calcium Indicators

The parallel developments of genetically-encoded calcium indicators and fast fluorescence imaging techniques makes it possible to simultaneously record neural activity of extended neuronal populations in vivo, opening a new arena for systems neuroscience. To fully harness the potential of functional imaging, one needs to infer the sequence of action potentials from fluorescence time traces. Here we build on recently proposed computational approaches to develop a blind sparse deconvolution algorithm (BSD), which we motivate by a theoretical analysis. We demonstrate that this method outperforms existing sparse deconvolution algorithms in terms of robustness, speed and/or accuracy on both synthetic and real fluorescence data. Furthermore, we provide solutions for the practical problems of thresholding and determination of the rise and decay time constants. We provide theoretical bounds on the performance of the algorithm in terms of precision-recall and temporal accuracy. Finally, we extend the computational framework to support temporal superresolution whose performance is established on real data.

scholarly journals Optimizing Calcium Detection Methods in Animal Systems: A Sandbox for Synthetic Biology

Biomolecules ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 343
Author(s):  
Elizabeth S. Li ◽  
Margaret S. Saha
Keyword(s):  
Synthetic Biology ◽  
Imaging Techniques ◽  
Detection Methods ◽  
Calcium Indicators ◽  
Model Animal ◽  
Calcium Dyes ◽  
Genetically Encoded Calcium Indicators ◽  
Synthetic Biology Approach

Since the 1970s, the emergence and expansion of novel methods for calcium ion (Ca2+) detection have found diverse applications in vitro and in vivo across a series of model animal systems. Matched with advances in fluorescence imaging techniques, the improvements in the functional range and stability of various calcium indicators have significantly enhanced more accurate study of intracellular Ca2+ dynamics and its effects on cell signaling, growth, differentiation, and regulation. Nonetheless, the current limitations broadly presented by organic calcium dyes, genetically encoded calcium indicators, and calcium-responsive nanoparticles suggest a potential path toward more rapid optimization by taking advantage of a synthetic biology approach. This engineering-oriented discipline applies principles of modularity and standardization to redesign and interrogate endogenous biological systems. This review will elucidate how novel synthetic biology technologies constructed for eukaryotic systems can offer a promising toolkit for interfacing with calcium signaling and overcoming barriers in order to accelerate the process of Ca2+ detection optimization.

scholarly journals Simultaneous two-photon imaging of action potentials and subthreshold inputs in vivo

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yuki Bando ◽  
Michael Wenzel ◽  
Rafael Yuste
Keyword(s):  
Action Potentials ◽  
Epileptic Seizures ◽  
Cortical Circuits ◽  
Neuronal Populations ◽  
Two Photon ◽  
Cellular Resolution ◽  
Photon Imaging ◽  
Two Photon Imaging ◽  
Voltage Indicator

AbstractTo better understand the input-output computations of neuronal populations, we developed ArcLight-ST, a genetically-encoded voltage indicator, to specifically measure subthreshold membrane potentials. We combined two-photon imaging of voltage and calcium, and successfully discriminated subthreshold inputs and spikes with cellular resolution in vivo. We demonstrate the utility of the method by mapping epileptic seizures progression through cortical circuits, revealing divergent sub- and suprathreshold dynamics within compartmentalized epileptic micronetworks. Two-photon, two-color imaging of calcium and voltage enables mapping of inputs and outputs in neuronal populations in living animals.

scholarly journals Signal-to-Signal Neural Networks for Improved Spike Estimation from Calcium Imaging Data

2020 ◽  
Author(s):  
Jilt Sebastian ◽  
Mriganka Sur ◽  
Hema A. Murthy ◽  
Mathew Magimai.-Doss
Keyword(s):  
Neural Network ◽  
Correlation Coefficient ◽  
Calcium Imaging ◽  
Action Potentials ◽  
Calcium Concentration ◽  
State Of The Art ◽  
Imaging Techniques ◽  
Data Driven ◽  
Signal Conversion ◽  
Calcium Indicators

AbstractSpiking information of individual neurons is essential for functional and behavioral analysis in neuroscience research. Calcium imaging techniques are generally employed to obtain activities of neuronal populations. However, these techniques result in slowly-varying fluorescence signals with low temporal resolution. Estimating the temporal positions of the neuronal action potentials from these signals is a challenging problem. In the literature, several generative model-based and data-driven algorithms have been studied with varied levels of success. This article proposes a neural network-based signal-to-signal conversion approach, where it takes as input raw-fluorescence signal and learns to estimate the spike information in an end-to-end fashion. Theoretically, the proposed approach formulates the spike estimation as a single channel source separation problem with unknown mixing conditions. The source corresponding to the action potentials at a lower resolution is estimated at the output. Experimental studies on the spikefinder challenge dataset show that the proposed signal-to-signal conversion approach significantly outperforms state-of-the-art-methods in terms of Pearson’s correlation coefficient and Spearman’s rank correlation coefficient and yields comparable performance for the area under the receiver operating characteristics measure. We also show that the resulting system: (a) has low complexity with respect to existing supervised approaches and is reproducible; (b) is layer-wise interpretable; and (c) has the capability to generalize across different calcium indicators.Author summaryInformation processing by a population of neurons is studied using two-photon calcium imaging techniques. A neuronal spike results in an increased intracellular calcium concentration. Fluorescent calcium indicators change their brightness upon a change in the calcium concentration, and this change is captured in the imaging technique. The task of estimating the actual spike positions from the brightness variations is formally referred to as spike estimation. Several signal processing and machine learning-based algorithms have been proposed in the past to solve this problem. However, the task is still far from being solved. Here we present a novel neural network-based data-driven algorithm for spike estimation. Our method takes the fluorescence recording as the input and synthesizes the spike information signal, which is well-correlated with the actual spike positions. Our method outperforms state-of-the-art methods on standard evaluation framework. We further analyze different components of the model and discuss its benefits.

Biomarkers for Alzheimer’s Disease

2019 ◽  
Vol 16 (6) ◽  
pp. 518-528 ◽  
Author(s):  
Leonardo Guzman-Martinez ◽  
Ricardo B. Maccioni ◽  
Gonzalo A. Farías ◽  
Patricio Fuentes ◽  
Leonardo P. Navarrete
Keyword(s):  
Imaging Techniques ◽  
Clinical Settings ◽  
Invasive Procedures ◽  
Effective Interventions ◽  
The World ◽  
New Biomarkers ◽  
The Brain

Alzheimer´s disease (AD) and related forms of dementia are increasingly affecting the aging population throughout the world, at an alarming rate. The World Alzheimer´s Report indicates a prevalence of 46.8 million people affected by AD worldwide. As population ages, this number is projected to triple by 2050 unless effective interventions are developed and implemented. Urgent efforts are required for an early detection of this disease. The ultimate goal is the identification of viable targets for the development of molecular markers and validation of their use for early diagnosis of AD that may improve treatment and the disease outcome in patients. The diagnosis of AD has been difficult to resolve since approaches for early and accurate detection and follow-up of AD patients at the clinical level have been reported only recently. Some proposed AD biomarkers include the detection of pathophysiological processes in the brain in vivo with new imaging techniques and novel PET ligands, and the determination of pathogenic proteins in cerebrospinal fluid showing anomalous levels of hyperphosphorylated tau and low Aβ peptide. These biomarkers have been increasingly accepted by AD diagnostic criteria and are important tools for the design of clinical trials, but difficulties in accessibility to costly and invasive procedures have not been completely addressed in clinical settings. New biomarkers are currently being developed to allow determinations of multiple pathological processes including neuroinflammation, synaptic dysfunction, metabolic impairment, protein aggregation and neurodegeneration. Highly specific and sensitive blood biomarkers, using less-invasive procedures to detect AD, are derived from the discoveries of peripheric tau oligomers and amyloid variants in human plasma and platelets. We have also developed a blood tau biomarker that correlates with a cognitive decline and also with neuroimaging determinations of brain atrophy.

Determination of depth of in vivo bioluminescent signals using spectral imaging techniques

2003 ◽  
Author(s):  
Olivier Coquoz ◽  
Tamara L. Troy ◽  
Dragana Jekic-McMullen ◽  
Bradley W. Rice
Keyword(s):  
Imaging Techniques ◽  
Spectral Imaging

scholarly journals Sensitive red protein calcium indicators for imaging neural activity

2016 ◽  
Author(s):  
Hod Dana ◽  
Boaz Mohar ◽  
Yi Sun ◽  
Sujatha Narayan ◽  
Andrew Gordus ◽  
...  
Keyword(s):  
Neural Activity ◽  
Emission Spectra ◽  
Tissue Imaging ◽  
C Elegans ◽  
Calcium Indicators ◽  
Large Populations ◽  
Consequent Reduction ◽  
Deep Tissue Imaging ◽  
Genetically Encoded Calcium Indicators

Genetically encoded calcium indicators (GECIs) allow measurement of activity in large populations of neurons and in small neuronal compartments, over times of milliseconds to months. Although GFP-based GECIs are widely used for in vivo neurophysiology, GECIs with red-shifted excitation and emission spectra have advantages for in vivo imaging because of reduced scattering and absorption in tissue, and a consequent reduction in phototoxicity. However, current red GECIs are inferior to the state-of-the-art GFP-based GCaMP6 indicators for detecting and quantifying neural activity. Here we present improved red GECIs based on mRuby (jRCaMP1a, b) and mApple (jRGECO1a), with sensitivity comparable to GCaMP6. We characterized the performance of the new red GECIs in cultured neurons and in mouse, Drosophila, zebrafish and C. elegans in vivo. Red GECIs facilitate deep-tissue imaging, dual-color imaging together with GFP-based reporters, and the use of optogenetics in combination with calcium imaging.

scholarly journals Population imaging discrepancies between a genetically-encoded calcium indicator (GECI) versus a genetically-encoded voltage indicator (GEVI)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mei Hong Zhu ◽  
Jinyoung Jang ◽  
Milena M. Milosevic ◽  
Srdjan D. Antic
Keyword(s):  
Brain Slices ◽  
Imaging Modalities ◽  
Population Activity ◽  
Optical Signals ◽  
Voltage Imaging ◽  
Neuronal Populations ◽  
Calcium Indicator ◽  
Calcium Indicators ◽  
Genetically Encoded Calcium Indicators ◽  
Voltage Indicator

AbstractGenetically-encoded calcium indicators (GECIs) are essential for studying brain function, while voltage indicators (GEVIs) are slowly permeating neuroscience. Fundamentally, GECI and GEVI measure different things, but both are advertised as reporters of “neuronal activity”. We quantified the similarities and differences between calcium and voltage imaging modalities, in the context of population activity (without single-cell resolution) in brain slices. GECI optical signals showed 8–20 times better SNR than GEVI signals, but GECI signals attenuated more with distance from the stimulation site. We show the exact temporal discrepancy between calcium and voltage imaging modalities, and discuss the misleading aspects of GECI imaging. For example, population voltage signals already repolarized to the baseline (~ disappeared), while the GECI signals were still near maximum. The region-to-region propagation latencies, easily captured by GEVI imaging, are blurred in GECI imaging. Temporal summation of GECI signals is highly exaggerated, causing uniform voltage events produced by neuronal populations to appear with highly variable amplitudes in GECI population traces. Relative signal amplitudes in GECI recordings are thus misleading. In simultaneous recordings from multiple sites, the compound EPSP signals in cortical neuropil (population signals) are less distorted by GEVIs than by GECIs.

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