An extension of the FRI framework for calcium transient detection

Reynolds, Stephanie; Copeland, Caroline S.; Schultz, Simon R.; Dragotti, Pier Luigi

doi:10.1109/isbi.2016.7493357

Cited by 7 publications

(16 citation statements)

References 11 publications

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“…On synthetic data, we observe that increasing cell 15 density only marginally affects the convergence rate, see Table 2. As emphasised in Section 2.5, updating 16 an active contour is a local problem -consequently, we observe that algorithm runtime increases linearly 17 with the total number of cells, see Table 1. Due to the independence of spatially separate ROIs in our 18 framework, further performance speed-ups are achievable by parallelizing the computation.…”

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confidence: 61%

“…We select a default correlation threshold of 0.8, derived from a default 15 expected SNR of 5 (dB). The user has the option to input an empirically measured SNR, which updates the 16 correlation threshold using the formula in Eq. (10).…”

Section: Merging and Pruning Roismentioning

confidence: 99%

“…Our algorithm is therefore versatile, it 15 can be applied to a variety of data types with minimal adjustment. For convenience, we refer to our method 16 as ABLE (an Activity-Based LEvel set method). In the following, we describe the method and demonstrate 17 its versatility and robustness on a range of in vitro and in vivo datasets.…”

Section: Introductionmentioning

confidence: 99%

“…We note that since the contour evolves with τ , φ i itself depends 15 upon τ . In the following, we present a set of M partial differential equations (PDEs) -one for each active 16 contour -derived in part from Eq. (4), which dictate the evolution of the level set functions.…”

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confidence: 99%

“…Cells are 'donut' (annulus) shaped to mimic videos generated by genetically encoded 15 calcium indicators, which are excluded from the nucleus. To achieve this, the temporal activity of a pixel in 16 a cell is generated by multiplying the cellular temporal activity vector by a factor in [0, 1] that decreases as 17 pixels are further from the cell boundary. When two cells overlap in one pixel, we sum the contributions of 18 both cells at that pixel.…”

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confidence: 99%

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ABLE: an Activity-Based Level Set Segmentation Algorithm for Two-Photon Calcium Imaging Data

Reynolds

Abrahamsson

Schuck

et al. 2017

Preprint

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We present an algorithm for detecting the location of cells from two-photon calcium imaging data. In our 1 framework, multiple coupled active contours evolve, guided by a model-based cost function, to identify cell 2 boundaries. An active contour seeks to partition a local region into two subregions, a cell interior and ex-3 terior, in which all pixels have maximally 'similar' time courses. This simple, local model allows contours to 4 be evolved predominantly independently. When contours are sufficiently close, their evolution is coupled, 5 in a manner that permits overlap. We illustrate the ability of the proposed method to demix overlapping 6 cells on real data. The proposed framework is flexible, incorporating no prior information regarding a cell's 7 morphology or stereotypical temporal activity, which enables the detection of cells with diverse properties. 8 We demonstrate algorithm performance on a challenging mouse in vitro dataset, containing synchronously 9 spiking cells, and a manually labelled mouse in vivo dataset, on which ABLE achieves a 67.5% success 10 rate. We developed a versatile algorithm based on a popular image segmentation approach (the Level Set 18 Method) and demonstrated its capability to overcome these challenges. We include no assumptions on 19 cell shape or stereotypical temporal activity. This lends our framework the flexibility to be applied to new 20 datasets with minimal adjustment.

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mentioning

confidence: 61%

Section: Merging and Pruning Roismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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confidence: 99%

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ABLE: an Activity-Based Level Set Segmentation Algorithm for Two-Photon Calcium Imaging Data

Reynolds

Abrahamsson

Schuck

et al. 2017

Preprint

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Advances in two photon scanning and scanless microscopy technologies for functional neural circuit imaging

Schultz

Copeland

Foust

et al. 2016

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Recent years have seen substantial developments in technology for imaging neural circuits, raising the prospect of large scale imaging studies of neural populations involved in information processing, with the potential to lead to step changes in our understanding of brain function and dysfunction. In this article we will review some key recent advances: improved fluorophores for single cell resolution functional neuroimaging using a two photon microscope; improved approaches to the problem of scanning active circuits; and the prospect of scanless microscopes which overcome some of the bandwidth limitations of current imaging techniques. These advances in technology for experimental neuroscience have in themselves led to technical challenges, such as the need for the development of novel signal processing and data analysis tools in order to make the most of the new experimental tools. We review recent work in some active topics, such as region of interest segmentation algorithms capable of demixing overlapping signals, and new highly accurate algorithms for calcium transient detection. These advances motivate the development of new data analysis tools capable of dealing with spatial or spatiotemporal patterns of neural activity, that scale well with pattern size.

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CosMIC: A Consistent Metric for Spike Inference from Calcium Imaging

Reynolds

Schultz

Dragotti

2017

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In 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 Sorensen-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 overfitting, the proposed metric score is maximised when the correct number of spikes have been detected. Furthermore, we show that CosMIC discriminates the temporal precision of estimates more consistently than either the success rate or the spike train correlation.

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An extension of the FRI framework for calcium transient detection

Cited by 7 publications

References 11 publications

ABLE: an Activity-Based Level Set Segmentation Algorithm for Two-Photon Calcium Imaging Data

ABLE: an Activity-Based Level Set Segmentation Algorithm for Two-Photon Calcium Imaging Data

Advances in two photon scanning and scanless microscopy technologies for functional neural circuit imaging

CosMIC: A Consistent Metric for Spike Inference from Calcium Imaging

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