scholarly journals NoRMCorre: An online algorithm for piecewise rigid motion correction of calcium imaging data

2017 ◽  
Author(s):  
Eftychios A. Pnevmatikakis ◽  
Andrea Giovannucci
Keyword(s):  
Calcium Imaging ◽  
Motion Correction ◽  
Rigid Motion ◽  
Motion Artifacts ◽  
Streaming Data ◽  
Field Of View ◽  
Large Field ◽  
Motion Field ◽  
Imaging Data ◽  
Two Photon

AbstractBackgroundMotion correction is a challenging pre-processing problem that arises early in the analysis pipeline of calcium imaging data sequences. The motion artifacts in two-photon microscopy recordings can be non-rigid, arising from the finite time of raster scanning and non-uniform deformations of the brain medium.New methodWe introduce an algorithm for fast Non-Rigid Motion Correction (NoRMCorre) based on template matching. NoRMCorre operates by splitting the field of view into overlapping spatial patches that are registered at a sub-pixel resolution for rigid translation against a continuously updated template. The estimated alignments are subsequently up-sampled to create a smooth motion field for each frame that can efficiently approximate non-rigid motion in a piecewise-rigid manner.Existing methodsExisting approaches either do not scale well in terms of computational performance or are targeted to motion artifacts arising from low speed scanning, whereas modern datasets with large field of view are more prone to non-rigid brain deformation issues.ResultsNoRMCorre can be run in an online mode resulting in comparable to or even faster than real time motion registration on streaming data. We evaluate the performance of the proposed method with simple yet intuitive metrics and compare against other non-rigid registration methods on two-photon calcium imaging datasets. Open source Matlab and Python code is also made available.ConclusionsThe proposed method and code provide valuable support to the community for solving large scale image registration problems in calcium imaging, especially when non-rigid deformations are present in the acquired data.

scholarly journals Diesel2p mesoscope with dual independent scan engines for flexible capture of dynamics in distributed neural circuitry

2020 ◽  
Author(s):  
Che-Hang Yu ◽  
Jeffrey N. Stirman ◽  
Yiyi Yu ◽  
Riichiro Hira ◽  
Spencer L. Smith
Keyword(s):  
Adaptive Optics ◽  
Calcium Imaging ◽  
High Speed ◽  
Optical Design ◽  
Neural Circuitry ◽  
Brain Regions ◽  
Field Of View ◽  
Large Field ◽  
Two Photon ◽  
Subcellular Resolution

AbstractImaging the activity of neurons that are widely distributed across brain regions deep in scattering tissue at high speed remains challenging. Here, we introduce an open-source system with Dual Independent Enhanced Scan Engines for Large Field-of-view Two-Photon imaging (Diesel2p). Combining novel optical design, adaptive optics, and temporal multiplexing, the system offers subcellular resolution over a large field-of-view (∼ 25 mm2) with independent scan engines. We demonstrate the flexibility and various use cases of this system for calcium imaging of neurons in the living brain.

scholarly journals CaImAn an open source tool for scalable calcium imaging data analysis

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Andrea Giovannucci ◽  
Johannes Friedrich ◽  
Pat Gunn ◽  
Jérémie Kalfon ◽  
Brandon L Brown ◽  
...  
Keyword(s):  
Data Analysis ◽  
Open Source ◽  
Calcium Imaging ◽  
High Performance ◽  
Human Performance ◽  
Streaming Data ◽  
Imaging Data ◽  
Two Photon ◽  
Real Time Analysis

Advances in fluorescence microscopy enable monitoring larger brain areas in-vivo with finer time resolution. The resulting data rates require reproducible analysis pipelines that are reliable, fully automated, and scalable to datasets generated over the course of months. We present CaImAn, an open-source library for calcium imaging data analysis. CaImAn provides automatic and scalable methods to address problems common to pre-processing, including motion correction, neural activity identification, and registration across different sessions of data collection. It does this while requiring minimal user intervention, with good scalability on computers ranging from laptops to high-performance computing clusters. CaImAn is suitable for two-photon and one-photon imaging, and also enables real-time analysis on streaming data. To benchmark the performance of CaImAn we collected and combined a corpus of manual annotations from multiple labelers on nine mouse two-photon datasets. We demonstrate that CaImAn achieves near-human performance in detecting locations of active neurons.

scholarly journals PatchWarp: Corrections of non-uniform image distortions in two-photon calcium imaging data by patchwork affine transformations

2021 ◽  
Author(s):  
Ryoma Hattori ◽  
Takaki Komiyama
Keyword(s):  
Neural Activity ◽  
Calcium Imaging ◽  
Motion Correction ◽  
Extended Period ◽  
Affine Transformations ◽  
Imaging Data ◽  
Full Field ◽  
Two Photon ◽  
Automated Method ◽  
Wide Range

Two-photon microscopy has been widely used to record the activity of populations of individual neurons at high spatial resolution in behaving animals. The ability to perform imaging for an extended period of time allows the investigation of activity changes associated with behavioral states and learning. However, imaging often accompanies shifts of the imaging field, including rapid (~100ms) translation and slow, spatially non-uniform distortion. To combat this issue and obtain a stable time series of the target structures, motion correction algorithms are commonly applied. However, typical motion correction algorithms are limited to full field translation of images and are unable to correct non-uniform distortions. Here, we developed a novel algorithm, PatchWarp, to robustly correct slow image distortion for calcium imaging data. PatchWarp is a two-step algorithm with rigid and non-rigid image registrations. To correct non-uniform image distortions, it splits the imaging field and estimates the best affine transformation matrix for each of the subfields. The distortion-corrected subfields are stitched together like a patchwork to reconstruct the distortion-corrected imaging field. We show that PatchWarp robustly corrects image distortions of calcium imaging data collected from various cortical areas through glass window or GRIN lens with a higher accuracy than existing non-rigid algorithms. Furthermore, it provides a fully automated method of registering images from different imaging sessions for longitudinal neural activity analyses. PatchWarp improves the quality of neural activity analyses and would be useful as a general approach to correct image distortions in a wide range of disciplines.

scholarly journals CalmAn: An open source tool for scalable Calcium Imaging data Analysis

2018 ◽  
Author(s):  
Andrea Giovannucci ◽  
Johannes Friedrich ◽  
Pat Gunn ◽  
Jérémie Kalfon ◽  
Sue Ann Koay ◽  
...  
Keyword(s):  
Data Analysis ◽  
Open Source ◽  
Calcium Imaging ◽  
High Performance ◽  
Human Performance ◽  
Ground Truth ◽  
Streaming Data ◽  
Imaging Data ◽  
Two Photon

AbstractAdvances in fluorescence microscopy enable monitoring larger brain areas in-vivo with finer time resolution. The resulting data rates require reproducible analysis pipelines that are reliable, fully automated, and scalable to datasets generated over the course of months. Here we present CaImAn, an open-source library for calcium imaging data analysis. CaImAn provides automatic and scalable methods to address problems common to pre-processing, including motion correction, neural activity identification, and registration across different sessions of data collection. It does this while requiring minimal user intervention, with good performance on computers ranging from laptops to high-performance computing clusters. CaImAn is suitable for two-photon and one-photon imaging, and also enables real-time analysis on streaming data. To benchmark the performance of CaImAn we collected a corpus of ground truth annotations from multiple labelers on nine mouse two-photon datasets. We demonstrate that CaImAn achieves near-human performance in detecting locations of active neurons.

scholarly journals Diesel2p mesoscope with dual independent scan engines for flexible capture of dynamics in distributed neural circuitry

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Che-Hang Yu ◽  
Jeffrey N. Stirman ◽  
Yiyi Yu ◽  
Riichiro Hira ◽  
Spencer L. Smith
Keyword(s):  
Adaptive Optics ◽  
Calcium Imaging ◽  
High Speed ◽  
Optical Design ◽  
Neural Circuitry ◽  
Brain Regions ◽  
Field Of View ◽  
Large Field ◽  
Two Photon ◽  
Subcellular Resolution

AbstractImaging the activity of neurons that are widely distributed across brain regions deep in scattering tissue at high speed remains challenging. Here, we introduce an open-source system with Dual Independent Enhanced Scan Engines for Large field-of-view Two-Photon imaging (Diesel2p). Combining optical design, adaptive optics, and temporal multiplexing, the system offers subcellular resolution over a large field-of-view of ~25 mm2, encompassing distances up to 7 mm, with independent scan engines. We demonstrate the flexibility and various use cases of this system for calcium imaging of neurons in the living brain.

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 Community-based benchmarking improves spike rate inference from two-photon calcium imaging data

2018 ◽  
Vol 14 (5) ◽  
pp. e1006157 ◽  
Author(s):  
Philipp Berens ◽  
Jeremy Freeman ◽  
Thomas Deneux ◽  
Nikolay Chenkov ◽  
Thomas McColgan ◽  
...  
Keyword(s):  
Calcium Imaging ◽  
Spike Rate ◽  
Imaging Data ◽  
Community Based ◽  
Two Photon

scholarly journals CosMIC: A Consistent Metric for Spike Inference from Calcium Imaging

2017 ◽  
Author(s):  
Stephanie Reynolds ◽  
Therese Abrahamsson ◽  
P. Jesper Sjöström ◽  
Simon R. Schultz ◽  
Pier Luigi Dragotti
Keyword(s):  
Spike Train ◽  
Success Rate ◽  
Calcium Imaging ◽  
Ground Truth ◽  
Spike Trains ◽  
Imaging Data ◽  
Temporal Precision ◽  
Pulse Trains ◽  
Two Photon ◽  
Average Size

AbstractIn recent years, the development of algorithms to detect neuronal spiking activity from two-photon calcium imaging data has received much attention. Meanwhile, few researchers have examined the metrics used to assess the similarity of detected spike trains with the ground truth. We highlight the limitations of the two most commonly used metrics, the spike train correlation and success rate, and propose an alternative, which we refer to as CosMIC. Rather than operating on the true and estimated spike trains directly, the proposed metric assesses the similarity of the pulse trains obtained from convolution of the spike trains with a smoothing pulse. The pulse width, which is derived from the statistics of the imaging data, reflects the temporal tolerance of the metric. The final metric score is the size of the commonalities of the pulse trains as a fraction of their average size. Viewed through the lens of set theory, CosMIC resembles a continuous Sørensen-Dice coefficient — an index commonly used to assess the similarity of discrete, presence/absence data. We demonstrate the ability of the proposed metric to discriminate the precision and recall of spike train estimates. Unlike the spike train correlation, which appears to reward overestimation, the proposed metric score is maximised when the correct number of spikes have been detected. Furthermore, we show that CosMIC is more sensitive to the temporal precision of estimates than the success rate.

scholarly journals Extended field-of-view ultrathin microendoscopes for high-resolution two-photon imaging with minimal invasiveness

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Andrea Antonini ◽  
Andrea Sattin ◽  
Monica Moroni ◽  
Serena Bovetti ◽  
Claudio Moretti ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Neuronal Activity ◽  
Signal To Noise Ratio ◽  
Brain Regions ◽  
Field Of View ◽  
Imaging Data ◽  
Minimal Invasiveness ◽  
Two Photon ◽  
State Dependent ◽  
Set Up

Imaging neuronal activity with high and homogeneous spatial resolution across the field-of-view (FOV) and limited invasiveness in deep brain regions is fundamental for the progress of neuroscience, yet is a major technical challenge. We achieved this goal by correcting optical aberrations in gradient index lens-based ultrathin (≤500 µm) microendoscopes using aspheric microlenses generated through 3D-microprinting. Corrected microendoscopes had extended FOV (eFOV) with homogeneous spatial resolution for two-photon fluorescence imaging and required no modification of the optical set-up. Synthetic calcium imaging data showed that, compared to uncorrected endoscopes, eFOV-microendoscopes led to improved signal-to-noise ratio and more precise evaluation of correlated neuronal activity. We experimentally validated these predictions in awake head-fixed mice. Moreover, using eFOV-microendoscopes we demonstrated cell-specific encoding of behavioral state-dependent information in distributed functional subnetworks in a primary somatosensory thalamic nucleus. eFOV-microendoscopes are, therefore, small-cross-section ready-to-use tools for deep two-photon functional imaging with unprecedentedly high and homogeneous spatial resolution.

Sign in / Sign up

Export Citation Format

Share Document