scholarly journals ICoRD: Iterative Correlation-Based ROI Detection Method for the Extraction of Neural Signals in Calcium Imaging

2021 ◽  
Author(s):  
Seongtak Kang ◽  
Jiho Park ◽  
Kyungsoo Kim ◽  
Sung-Ho Lim ◽  
Joon Ho Choi ◽  
...  
Keyword(s):  
Calcium Imaging ◽  
Neural Circuit ◽  
Detection Methods ◽  
Calcium Signal ◽  
Noise Power ◽  
Imaging Data ◽  
Calcium Signals ◽  
Low Snr ◽  
Target Neuron

In vivo calcium imaging is a standard neuroimaging technique that allows the simultaneous observation of neuronal population activity. In calcium imaging, the activation signals of neurons are key information for the investigation of neural circuits. For efficient extraction of the calcium signals of neurons, selective detection of the region of interest (ROI) pixels corresponding to the active subcellular region of the target neuron is essential. However, current ROI detection methods for calcium imaging data exhibit relatively low extraction performance from neurons with a low signal-to-noise power ratio (SNR). This is problematic because a low SNR is unavoidable in many biological experimental settings. Therefore, we propose an iterative correlation-based ROI detection (ICoRD) method that robustly extracts the calcium signal of the target neuron from a calcium imaging series with severe noise. ICoRD extracts calcium signals closer to the ground truth than the conventional method from simulated calcium imaging data in all low SNR ranges. Additionally, this study confirmed that ICoRD robustly extracts activation signals against noise, even within in vivo environments. ICoRD showed reliable detection from neurons with low SNR and sparse activation, which were not detected by the conventional methods. ICoRD will facilitate our understanding of neural circuit activity by providing significantly improved ROI detection from noisy images.

scholarly journals Effective and Efficient Neural Networks for Spike Inference from In Vivo Calcium Imaging

2021 ◽  
Author(s):  
Zhanhong Zhou ◽  
Chung Tin
Keyword(s):  
Calcium Imaging ◽  
Signal To Noise Ratio ◽  
Large Population ◽  
Brain Regions ◽  
Spike Rate ◽  
Calcium Signal ◽  
Calcium Signals ◽  
Inference System ◽  
Spike Event

AbstractCalcium imaging technique provides irreplaceable advantages in monitoring large population of neuronal activities simultaneously. However, due to the generally low signal to noise ratio (SNR) of the calcium signal and variability in dye properties, it is still challenging to faithfully infer neuronal spikes from these calcium signals, especially from in vivo experiments. In this study, we tackled the problem of both spike-rate and spike-event predictions using a data-driven approach, based on a public pool of dataset with simultaneously recorded calcium and electrophysiological signals using different dyes and recorded from different brain regions. We proposed the ENS2 (effective and efficient neural networks for spike inference from calcium signals) system using raw calcium inputs and it consistently outperforms state-of-the-arts algorithms in both spike-rate and spike-event predictions with reduced computational load. We have also demonstrated that factors such as sampling rates, smoothing window sizes and parametric evaluation metrics could readily bias the interpretation of inference performance. We concluded that optimizing our system for spike-event prediction could produce a more versatile inference system for real neuroscience studies.

Two-Photon Processor and SeNeCA: a freely available software package to process data from two-photon calcium imaging at speeds down to several milliseconds per frame

2013 ◽  
Vol 110 (1) ◽  
pp. 243-256 ◽  
Author(s):  
Jakub Tomek ◽  
Ondrej Novak ◽  
Josef Syka
Keyword(s):  
Calcium Imaging ◽  
Software Package ◽  
Motion Artifacts ◽  
Calcium Signal ◽  
Neural Cells ◽  
Neuronal System ◽  
Process Data ◽  
Entire Area ◽  
Two Photon

Two-Photon Processor (TPP) is a versatile, ready-to-use, and freely available software package in MATLAB to process data from in vivo two-photon calcium imaging. TPP includes routines to search for cell bodies in full-frame (Search for Neural Cells Accelerated; SeNeCA) and line-scan acquisition, routines for calcium signal calculations, filtering, spike-mining, and routines to construct parametric fields. Searching for somata in artificial in vivo data, our algorithm achieved better performance than human annotators. SeNeCA copes well with uneven background brightness and in-plane motion artifacts, the major problems in simple segmentation methods. In the fast mode, artificial in vivo images with a resolution of 256 × 256 pixels containing ∼100 neurons can be processed at a rate up to 175 frames per second (tested on Intel i7, 8 threads, magnetic hard disk drive). This speed of a segmentation algorithm could bring new possibilities into the field of in vivo optophysiology. With such a short latency (down to 5–6 ms on an ordinary personal computer) and using some contemporary optogenetic tools, it will allow experiments in which a control program can continuously evaluate the occurrence of a particular spatial pattern of activity (a possible correlate of memory or cognition) and subsequently inhibit/stimulate the entire area of the circuit or inhibit/stimulate a different part of the neuronal system. TPP will be freely available on our public web site. Similar all-in-one and freely available software has not yet been published.

scholarly journals Fiber photometry does not reflect spiking activity in the striatum

2021 ◽  
Author(s):  
Alex A. Legaria ◽  
Julia A. Licholai ◽  
Alexxai V. Kravitz
Keyword(s):  
Neuronal Activity ◽  
Calcium Imaging ◽  
Brain Activity ◽  
Neural Population ◽  
Fluorescence Signal ◽  
Calcium Signals ◽  
Cellular Events ◽  
Neural Populations ◽  
Spiking Activity

AbstractFiber photometry recordings are commonly used as a proxy for neuronal activity, based on the assumption that increases in bulk calcium fluorescence reflect increases in spiking of the underlying neural population. However, this assumption has not been adequately tested. Here, using endoscopic calcium imaging in the striatum we report that the bulk fluorescence signal correlates weakly with somatic calcium signals, suggesting that this signal does not reflect spiking activity, but may instead reflect subthreshold changes in neuropil calcium. Consistent with this suggestion, the bulk fluorescence photometry signal correlated strongly with neuropil calcium signals extracted from these same endoscopic recordings. We further confirmed that photometry did not reflect striatal spiking activity with simultaneous in vivo extracellular electrophysiology and fiber photometry recordings in awake behaving mice. We conclude that the fiber photometry signal should not be considered a proxy for spiking activity in neural populations in the striatum.Significance statementFiber photometry is a technique for recording brain activity that has gained popularity in recent years due to it being an efficient and robust way to record the activity of genetically defined populations of neurons. However, it remains unclear what cellular events are reflected in the photometry signal. While it is often assumed that the photometry signal reflects changes in spiking of the underlying cell population, this has not been adequately tested. Here, we processed calcium imaging recordings to extract both somatic and non-somatic components of the imaging field, as well as a photometry signal from the whole field. Surprisingly, we found that the photometry signal correlated much more strongly with the non-somatic than the somatic signals. This suggests that the photometry signal most strongly reflects subthreshold changes in calcium, and not spiking. We confirmed this point with simultaneous fiber photometry and extracellular spiking recordings, again finding that photometry signals relate poorly to spiking in the striatum. Our results may change interpretations of studies that use fiber photometry as an index of spiking output of neural populations.

scholarly journals Automated cellular structure extraction in biological images with applications to calcium imaging data

2018 ◽  
Author(s):  
Gal Mishne ◽  
Ronald R. Coifman ◽  
Maria Lavzin ◽  
Jackie Schiller
Keyword(s):  
Calcium Imaging ◽  
Image Plane ◽  
Cellular Level ◽  
Full Potential ◽  
Imaging Data ◽  
Image Domain ◽  
Biological Images ◽  
Large Populations ◽  
In Vivo Calcium Imaging

AbstractRecent advances in experimental methods in neuroscience enable measuring in-vivo activity of large populations of neurons at cellular level resolution. To leverage the full potential of these complex datasets and analyze the dynamics of individual neurons, it is essential to extract high-resolution regions of interest, while addressing demixing of overlapping spatial components and denoising of the temporal signal of each neuron. In this paper, we propose a data-driven solution to these challenges, by representing the spatiotemporal volume as a graph in the image plane. Based on the spectral embedding of this graph calculated across trials, we propose a new clustering method, Local Selective Spectral Clustering, capable of handling overlapping clusters and disregarding clutter. We also present a new nonlinear mapping which recovers the structural map of the neurons and dendrites, and global video denoising. We demonstrate our approach on in-vivo calcium imaging of neurons and apical dendrites, automatically extracting complex structures in the image domain, and denoising and demixing their time-traces.

scholarly journals Efficient implementation of convolutional neural networks in the data processing of two-photon in vivo imaging

2019 ◽  
Vol 35 (17) ◽  
pp. 3208-3210 ◽  
Author(s):  
Yangzhen Wang ◽  
Feng Su ◽  
Shanshan Wang ◽  
Chaojuan Yang ◽  
Yonglu Tian ◽  
...  
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Detection Methods ◽  
Supplementary Information ◽  
Imaging Data ◽  
Two Photon ◽  
Processing Power ◽  
Fluctuation Method ◽  
The Brain

Abstract Motivation Functional imaging at single-neuron resolution offers a highly efficient tool for studying the functional connectomics in the brain. However, mainstream neuron-detection methods focus on either the morphologies or activities of neurons, which may lead to the extraction of incomplete information and which may heavily rely on the experience of the experimenters. Results We developed a convolutional neural networks and fluctuation method-based toolbox (ImageCN) to increase the processing power of calcium imaging data. To evaluate the performance of ImageCN, nine different imaging datasets were recorded from awake mouse brains. ImageCN demonstrated superior neuron-detection performance when compared with other algorithms. Furthermore, ImageCN does not require sophisticated training for users. Availability and implementation ImageCN is implemented in MATLAB. The source code and documentation are available at https://github.com/ZhangChenLab/ImageCN. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals All-optical interrogation of neural circuits in behaving mice

2021 ◽  
Author(s):  
Lloyd E. Russell ◽  
Henry W.P. Dalgleish ◽  
Rebecca Nutbrown ◽  
Oliver Gauld ◽  
Dustin Herrmann ◽  
...  
Keyword(s):  
Neural Circuits ◽  
Neural Circuit ◽  
Barrel Cortex ◽  
Brain Area ◽  
Imaging Data ◽  
Temporal Precision ◽  
Two Photon ◽  
All Optical ◽  
The Impact

Recent advances combining two-photon calcium imaging and two-photon optogenetics with digital holography now allow us to read and write neural activity in vivo at cellular resolution with millisecond temporal precision. Such 'all-optical' techniques enable experimenters to probe the impact of functionally defined neurons on neural circuit function and behavioural output with new levels of precision. This protocol describes the experimental strategy and workflow for successful completion of typical all-optical interrogation experiments in awake, behaving head-fixed mice. We describe modular procedures for the setup and calibration of an all-optical system, the preparation of an indicator and opsin-expressing and task-performing animal, the characterization of functional and photostimulation responses and the design and implementation of an all-optical experiment. We discuss optimizations for efficiently selecting and targeting neuronal ensembles for photostimulation sequences, as well as generating photostimulation response maps from the imaging data that can be used to examine the impact of photostimulation on the local circuit. We demonstrate the utility of this strategy using all-optical experiments in three different brain areas - barrel cortex, visual cortex and hippocampus - using different experimental setups. This approach can in principle be adapted to any brain area for all-optical interrogation experiments to probe functional connectivity in neural circuits and for investigating the relationship between neural circuit activity and behaviour.

scholarly journals All-optical imaging and patterned stimulation with a one-photon endoscope

2021 ◽  
Author(s):  
Jinyong Zhang ◽  
Ryan N Hughes ◽  
Namsoo Kim ◽  
Isabella P Fallon ◽  
Konstantin I bakhurin ◽  
...  
Keyword(s):  
Neural Activity ◽  
Calcium Imaging ◽  
Neural Circuit ◽  
Integrated System ◽  
Striatal Neurons ◽  
Indirect Pathway ◽  
Cellular Resolution ◽  
All Optical ◽  
Freely Moving

While in vivo calcium imaging makes it possible to record activity in defined neuronal populations with cellular resolution, optogenetics allows selective manipulation of neural activity. Recently, these two tools have been combined to stimulate and record neural activity at the same time, but current approaches often rely on two-photon microscopes that are difficult to use in freely moving animals. To address these limitations, we have developed a new integrated system combining a one-photon endoscope and a digital micromirror device for simultaneous calcium imaging and precise optogenetic photo-stimulation with near cellular resolution (Miniscope with All-optical Patterned Stimulation and Imaging, MAPSI). Using this highly portable system in freely moving mice, we were able to image striatal neurons from either the direct pathway or the indirect pathway while simultaneously activating any neuron of choice in the field of view, or to synthesize arbitrary spatiotemporal patterns of photo-stimulation. We could also select neurons based on their relationship with behavior and recreate the behavior by mimicking the natural neural activity with photo-stimulation. MAPSI thus provides a powerful tool for interrogation of neural circuit function in freely moving animals.

scholarly journals Beyond excitation/inhibition imbalance in multidimensional models of neural circuit changes in brain disorders

2016 ◽  
Author(s):  
Cian O’Donnell ◽  
J. Tiago Gonçalves ◽  
Carlos Portera-Cailliau ◽  
Terrence J. Sejnowski
Keyword(s):  
Neural Circuit ◽  
Fragile X ◽  
Brain Disorders ◽  
Imaging Data ◽  
Neural Firing ◽  
Knock Out ◽  
Brain Circuitry ◽  
Circuit Function ◽  
Cellular Components

AbstractA leading theory holds that neurodevelopmental brain disorders arise from imbalances in excitatory and inhibitory (E/I) brain circuitry. However, it is unclear whether this onedimensional model is rich enough to capture the multiple neural circuit alterations underlying brain disorders. Here we combined computational simulations with analysis of in vivo 2-photon Ca2+ imaging data from somatosensory cortex of Fmr1 knock-out (KO) mice, a model of Fragile-X Syndrome, to test the E/I imbalance theory. We found that: 1) The E/I imbalance model cannot account for joint alterations in the observed neural firing rates and correlations; 2) Neural circuit function is vastly more sensitive to changes in some cellular components over others; 3) The direction of circuit alterations in Fmr1 KO mice changes across development. These findings suggest that the basic E/I imbalance model should be updated to higher-dimensional models that can better capture the multidimensional computational functions of neural circuits.

scholarly journals A deep learning toolbox for noise-optimized, generalized spike inference from calcium imaging data

2020 ◽  
Author(s):  
Peter Rupprecht ◽  
Stefano Carta ◽  
Adrian Hoffmann ◽  
Mayumi Echizen ◽  
Kazuo Kitamura ◽  
...  
Keyword(s):  
Calcium Imaging ◽  
Action Potentials ◽  
Sampling Rate ◽  
Ground Truth ◽  
Cell Types ◽  
Imaging Data ◽  
Calcium Signals ◽  
Ground Truth Data ◽  
Unseen Data ◽  
User Friendly

ABSTRACTCalcium imaging is a key method to record patterns of neuronal activity across populations of identified neurons. Inference of temporal patterns of action potentials (‘spikes’) from calcium signals is, however, challenging and often limited by the scarcity of ground truth data containing simultaneous measurements of action potentials and calcium signals. To overcome this problem, we compiled a large and diverse ground truth database from publicly available and newly performed recordings. This database covers various types of calcium indicators, cell types, and signal-to-noise ratios and comprises a total of >20 hours from 225 neurons. We then developed a novel algorithm for spike inference (CASCADE) that is based on supervised deep networks, takes advantage of the ground truth database, infers absolute spike rates, and outperforms existing model-based algorithms. To optimize performance for unseen imaging data, CASCADE retrains itself by resampling ground truth data to match the respective sampling rate and noise level. As a consequence, no parameters need to be adjusted by the user. To facilitate routine application of CASCADE we developed systematic performance assessments for unseen data, we openly release all resources, and we provide a user-friendly cloud-based implementation.

scholarly journals Beyond excitation/inhibition imbalance in multidimensional models of neural circuit changes in brain disorders

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Cian O'Donnell ◽  
J Tiago Gonçalves ◽  
Carlos Portera-Cailliau ◽  
Terrence J Sejnowski
Keyword(s):  
Neural Circuit ◽  
Fragile X ◽  
Brain Disorders ◽  
Imaging Data ◽  
Neural Firing ◽  
Knock Out ◽  
Brain Circuitry ◽  
Circuit Function ◽  
Cellular Components

A leading theory holds that neurodevelopmental brain disorders arise from imbalances in excitatory and inhibitory (E/I) brain circuitry. However, it is unclear whether this one-dimensional model is rich enough to capture the multiple neural circuit alterations underlying brain disorders. Here, we combined computational simulations with analysis of in vivo two-photon Ca2+ imaging data from somatosensory cortex of Fmr1 knock-out (KO) mice, a model of Fragile-X Syndrome, to test the E/I imbalance theory. We found that: (1) The E/I imbalance model cannot account for joint alterations in the observed neural firing rates and correlations; (2) Neural circuit function is vastly more sensitive to changes in some cellular components over others; (3) The direction of circuit alterations in Fmr1 KO mice changes across development. These findings suggest that the basic E/I imbalance model should be updated to higher dimensional models that can better capture the multidimensional computational functions of neural circuits.

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