Automated Analysis of Cellular Signals from Large-Scale Calcium Imaging Data

Mukamel, Eran A.; Nimmerjahn, Axel; Schnitzer, Mark J.

doi:10.1016/j.neuron.2009.08.009

Cited by 657 publications

(777 citation statements)

References 58 publications

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“…It is known from in vivo imaging and multielectrode array measurements that temporally correlated complex spikes occur in parasagittally oriented modules of PNs within the cerebellar cortex (40)(41)(42)(43), and recent evidence is consistent with the idea that the CF-associated teaching signal is encoded by temporally correlated complex spike activity (44). The axons of PNs are inhibitory and converge on single DCN neurons, thus prolonged post-CxSp pauses occurring synchronously in a module of PNs could provide an extended window of disinhibition to the DCN cells receiving such input (45,46).…”

Section: Discussionmentioning

confidence: 99%

Prolonging the postcomplex spike pause speeds eyeblink conditioning

Maiz

Karakossian

Pakaprot

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

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Climbing fiber input to the cerebellum is believed to serve as a teaching signal during associative, cerebellum-dependent forms of motor learning. However, it is not understood how this neural pathway coordinates changes in cerebellar circuitry during learning. Here, we use pharmacological manipulations to prolong the postcomplex spike pause, a component of the climbing fiber signal in Purkinje neurons, and show that these manipulations enhance the rate of learning in classical eyelid conditioning. Our findings elucidate an unappreciated aspect of the climbing fiber teaching signal, and are consistent with a model in which convergent postcomplex spike pauses drive learning-related plasticity in the deep cerebellar nucleus. They also suggest a physiological mechanism that could modulate motor learning rates.associative learning | pavlovian | ZD 7288 | 1-EBIO | rebound

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Section: Discussionmentioning

confidence: 99%

Prolonging the postcomplex spike pause speeds eyeblink conditioning

Maiz

Karakossian

Pakaprot

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

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“…Indeed, in recent years, synthetic and genetically encoded fluorescent Ca 2+ indicators have become prominent tools for imaging neural Ca 2+ dynamics across large sets of individual neurons of known types. [3][4][5][6][7][8] Nevertheless, though a useful correlation often exists between Ca 2+ dynamics and neuronal spiking across a range of spike frequencies, the slowkinetics and saturation of [Ca 2+ ]-related fluorescent signals constrain the utility of Ca 2+ imaging as a means of probing spiking dynamics in many neuron types. 4,9 Numerous voltage-sensitive indicators 1,[10][11][12][13][14][15][16][17][18] permit direct imaging of cellular membrane potentials.…”

Section: Introductionmentioning

confidence: 99%

Optical Strategies for Sensing Neuronal Voltage Using Quantum Dots and Other Semiconductor Nanocrystals

Marshall

Schnitzer

2013

ACS Nano

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Biophysicists have long sought optical methods capable of reporting the electrophysiological dynamics of large-scale neural networks with millisecond-scale temporal resolution. Existing fluorescent sensors of cell membrane voltage can report action potentials in individual cultured neurons, but limitations in brightness and dynamic range of both synthetic organic and genetically encoded voltage sensors have prevented concurrent monitoring of spiking activity across large populations of individual neurons. Here we propose a novel, inorganic class of fluorescent voltage sensors: semiconductor nanoparticles, such as ultrabright quantum dots (qdots). Our calculations revealed that transmembrane electric fields characteristic of neuronal spiking (~10 mV/nm) modulate a qdot's electronic structure and can induce ~5% changes in its fluorescence intensity and ~1 nm shifts in its emission wavelength, depending on the qdot's size, composition, and dielectric environment. Moreover, tailored qdot sensors composed of two different materials can exhibit substantial (~30%) changes in fluorescence intensity during neuronal spiking. Using signal detection theory, we show that conventional qdots should be capable of reporting voltage dynamics with millisecond precision across several tens or more individual neurons over a range of optical and neurophysiological conditions. These results unveil promising avenues for imaging spiking dynamics in neural networks and merit in-depth experimental investigation. Toward addressing these challenges, we studied whether tools from nanotechnology, specifically, bright, multifunctional semiconductor quantum dots (qdots), 22,23 might be useful for imaging neuronal membrane potentials. Qdots are known to possess voltagesensitive optical properties, including a red-shifting of the qdot's fluorescence emission peak, spectral broadening, and a decrease in the intensity of fluorescence emission ( Figure 1C,D). [24][25][26][27] Qdots also are highly resistant to photobleaching and exhibit large quantum yields and absorption cross sections for one-(σ 1 ) and two-photon (σ 2 ) excitation. For example, CdSe qdots with radius R ~ 3 nm exhibit cross sections of σ 1 > 1 nm 2 and σ 2 > 3 × 10 4 GM, as compared to σ 1 ~ 10 −2 nm 2 and σ 2 ~ 3 × 10 2 GM for green fluorescent protein. 28,29 Marshall and Schnitzer Page 2 ACS Nano. Author manuscript; available in PMC 2017 December 15. Graphical Abstract HHMI Author Manuscript HHMI Author Manuscript HHMI Author ManuscriptTo evaluate the spike detection capabilities of qdot indicators quantitatively, we applied a theoretical approach that incorporates the physical, biophysical, and statistical components of the problem. We calculated the effect of applied electric fields on the qdot's electronic structure and examined how this modulates a qdot's fluorescence intensity and emission spectra. We also studied nonspherical, nonhomogenous qdots, which we refer to more generally as semiconductor nanocrystals, and found that these nanoparticles can demonstrate muc...

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“…Previously ICA has been made available to Matlab via the open source FastICA toolkit (http://research.ics.aalto.fi/ica/software.shtml) and has thus far been developed into a Matlab command line toolkit, CellSort (Mukamel et al, 2009). Here we utilise the FastICA toolkit to provide ICA as a user configurable option within our GUI providing it as one option alongside additional visualisation tools.…”

Section: Independent Component Analysis (Ica) With Scintillatementioning

confidence: 99%

Scintillate: An open-source graphical viewer for time-series calcium imaging evaluation and pre-processing

Dublon

Nilsson

Balkenius

et al. 2016

Journal of Neuroscience Methods

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ScintillateAn open-source graphical viewer for time-series calcium imaging evaluation and preprocessing Dublon, I. A N; Nilsson, Markus; Balkenius, A.; Anderson, P.; Larsson, M. C. Methods, 273, 120-127. DOI: 10.1016/j.jneumeth.2016 General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal Final version of authors manuscript for archival at institutional repository Abstract BackgroundCalcium imaging is based on the detection of minute signal changes in an image time-series encompassing pre-and post-stimuli. Depending on the function of the elicited response, change may be pronounced, as in the case of a genetically encoded calciumreporter protein, or subtle, as is the case in a bath-applied dye system. Large datasets are thus often acquired and appraised only during post-processing where specific Regions of Interest (ROIs) are examined. New methodThe scintillate software provides a platform allowing for near instantaneous viewing of time-sequenced tiffs within a discrete GUI environment. Whole sequences may be evaluated. In its simplest form scintillate provides change in florescence (ΔF) across the entire tiff image matrix. Evaluating image intensity level differences across the whole image allows the user to rapidly establish the value of the preparation, without a priori ROI-selection. Additionally, an implementation of Independent Component Analysis (ICA) provides additional rapid insights into areas of signal change. ResultsWe imaged transgenic flies expressing Calcium-sensitive reporter proteins within projection neurons and moth mushroom bodies stained with a Ca 2+ sensitive bath-applied dye. Instantaneous pre-stimulation background subtraction allowed us to appraise strong genetically encoded neuronal Ca 2+ responses in flies and weaker, less apparent, responses within moth mushroom bodies. Comparison with existing methodsAt the time of acquisition, whole matrix ΔF analysis alongside ICA is ordinarily not performed. We found it invaluable, minimising time spent with unresponsive samples, and assisting in optimisation of subsequent acquisitions. ConclusionsWe provide a multi-platform open-source system to evaluate time-series images.Abbreviations: ΔF, change of intensity between frames; ICA, independent component analysis

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Automated Analysis of Cellular Signals from Large-Scale Calcium Imaging Data

Cited by 657 publications

References 58 publications

Prolonging the postcomplex spike pause speeds eyeblink conditioning

Prolonging the postcomplex spike pause speeds eyeblink conditioning

Optical Strategies for Sensing Neuronal Voltage Using Quantum Dots and Other Semiconductor Nanocrystals

Scintillate: An open-source graphical viewer for time-series calcium imaging evaluation and pre-processing

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