Publications
44 results found
Foust A, 2023, Voltage-sensitive optical probes for measuring cell membrane potentials: An update and applications to ‘non-excitable’ cells, Bioelectricity, ISSN: 2576-3105
Verinaz-Jadan H, Howe CL, Song P, et al., 2023, Physics-based deep learning for imaging neuronal activity via two-photon and light field microscopy, IEEE Transactions on Computational Imaging, Vol: 9, Pages: 565-580, ISSN: 2333-9403
Light Field Microscopy (LFM) is an imaging technique that offers the opportunity to study fast dynamics in biological systems due to its 3D imaging speed and is particularly attractive for functional neuroimaging. Traditional model-based approaches employed in microscopy for reconstructing 3D images from light-field data are affected by reconstruction artifacts and are computationally demanding. This work introduces a deep neural network for LFM to image neuronal activity under adverse conditions: limited training data, background noise, and scattering mammalian brain tissue. The architecture of the network is obtained by unfolding the ISTA algorithm and is based on the observation that neurons in the tissue are sparse. Our approach is also based on a novel modelling of the imaging system that uses a linear convolutional neural network to fit the physics of the acquisition process. We train the network in a semi-supervised manner based on an adversarial training framework. The small labelled dataset required for training is acquired from a single sample via two-photon microscopy, a point-scanning 3D imaging technique that achieves high spatial resolution and deep tissue penetration but at a lower speed than LFM. We introduce physics knowledge of the system in the design of the network architecture and during training to complete our semi-supervised approach. We experimentally show that in the proposed scenario, our method performs better than typical deep learning and model-based reconstruction strategies for imaging neuronal activity in mammalian brain tissue via LFM, considering reconstruction quality, generalization to functional imaging, and reconstruction speed.
Quicke P, Sun Y, Beykou M, et al., 2022, Voltage imaging reveals the dynamic electrical signatures of human breast cancer cells, Communications Biology, Vol: 5, ISSN: 2399-3642
Cancer cells feature a resting membrane potential (Vm) that is depolarized compared to normal cells, and express active ionic conductances, which factor directly in their pathophysiological behavior. Despite similarities to ‘excitable’ tissues, relatively little is known about cancer cell Vm dynamics. Here high-throughput, cellular-resolution Vm imaging reveals that Vm fluctuates dynamically in several breast cancer cell lines compared to non-cancerous MCF-10A cells. We characterize Vm fluctuations of hundreds of human triple-negative breast cancer MDA-MB-231 cells. By quantifying their Dynamic Electrical Signatures (DESs) through an unsupervised machine-learning protocol, we identify four classes ranging from "noisy” to “blinking/waving“. The Vm of MDA-MB-231 cells exhibits spontaneous, transient hyperpolarizations inhibited by the voltage-gated sodium channel blocker tetrodotoxin, and by calcium-activated potassium channel inhibitors apamin and iberiotoxin. The Vm of MCF-10A cells is comparatively static, but fluctuations increase following treatment with transforming growth factor-β1, a canonical inducer of the epithelial-to-mesenchymal transition. These data suggest that the ability to generate Vm fluctuations may be a property of hybrid epithelial-mesenchymal cells or those originated from luminal progenitors.
Verinaz-Jadan H, Song P, Howe CL, et al., 2022, Shift-invariant-subspace discretization and volume reconstruction for light field microscopy, IEEE Transactions on Computational Imaging, Vol: 8, Pages: 286-301, ISSN: 2573-0436
Light Field Microscopy (LFM) is an imaging technique that captures 3D spatial information with a single 2D image. LFM is attractive because of its relatively simple implementation and fast volume acquisition rate. Capturing volume time series at a camera frame rate can enable the study of the behaviour of many biological systems. For instance, it could provide insights into the communication dynamics of living 3D neural networks. However, conventional 3D reconstruction algorithms for LFM typically suffer from high computational cost, low lateral resolution, and reconstruction artifacts. In this work, we study the origin of these issues and propose novel techniques to improve the performance of the reconstruction process. First, we propose a discretization approach that uses shift-invariant subspaces to generalize the typical discretization framework used in LFM. Then, we study the shift-invariant-subspace assumption as a prior for volume reconstruction under ideal conditions. Furthermore, we present a method to reduce the computational time of the forward model by using singular value decomposition (SVD). Finally, we propose to use iterative approaches that incorporate additional priors to perform artifact-free 3D reconstruction from real light field images. We experimentally show that our approach performs better than Richardson-Lucy-based strategies in computational time, image quality, and artifact reduction.
Howe C, Song P, Verinaz Jadan HI, et al., 2022, Comparing synthetic refocusing to deconvolution for the extraction of neuronal calcium transients from light fields, Neurophotonics, Vol: 9, Pages: 1-17, ISSN: 2329-4248
Significance: Light-field microscopy (LFM) enables fast, light-efficient, volumetric imaging of neuronal activity with calcium indicators. Calcium transients differ in temporal signal-to-noise ratio (tSNR) and spatial confinement when extracted from volumes reconstructed by different algorithms.Aim: We evaluated the capabilities and limitations of two light-field reconstruction algorithms for calcium fluorescence imaging.Approach: We acquired light-field image series from neurons either bulk-labeled or filled intracellularly with the red-emitting calcium dye CaSiR-1 in acute mouse brain slices. We compared the tSNR and spatial onfinement of calcium signals extracted from volumes reconstructed with synthetic refocusing and Richardson-Lucy 3D deconvolution with and without total variation regularization.Results: Both synthetic refocusing and Richardson-Lucy deconvolution resolved calcium signals from single cells and neuronal dendrites in three dimensions. Increasing deconvolution iteration number improved spatial confinement but reduced tSNR compared to synthetic refocusing. Volumetric light-field imaging did not decrease calcium signal tSNR compared to interleaved, widefield image series acquired in matched planes.Conclusions: LFM enables high-volume rate, volumetric imaging of calcium transients in single cells (bulk-labeled), somata and dendrites (intracellular loaded). The trade-offs identified for tSNR, spatial confinement, and computational cost indicate which of synthetic refocusing or deconvolution can better realize the scientific requirements of future LFM calcium imaging applications.
Foust A, Song P, Verinaz Jadan HI, et al., 2022, Light-field microscopy for optical imaging of neuronal activity: when model-based methods meet data-driven approaches, IEEE: Signal Processing Magazine, Vol: 39, ISSN: 1053-5888
Understanding how networks of neurons process information is one of the key challenges in modern neuroscience.A necessary step to achieve this goal is to be able to observe the dynamics of large populations of neurons overa large area of the brain. Light-field microscopy (LFM), a type of scanless microscope, is a particularly attractivecandidate for high-speed three-dimensional (3D) imaging. It captures volumetric information in a single snapshot,allowing volumetric imaging at video frame-rates. Specific features of imaging neuronal activity using LFM callfor the development of novel machine learning approaches that fully exploit priors embedded in physics and opticsmodels. Signal processing theory and wave-optics theory could play a key role in filling this gap, and contributeto novel computational methods with enhanced interpretability and generalization by integrating model-driven anddata-driven approaches. This paper is devoted to a comprehensive survey to state-of-the-art of computational methods for LFM, with a focus on model-based and data-driven approaches
Quicke P, Howe CL, Foust A, 2021, Balancing the fluorescence imaging budget for all-optical neurophysiology experiments, All-optical methods to study neuronal function, Editors: Papagiakoumou, Publisher: Humana Press
The goal of this chapter is to establish a framework to evaluate imaging methodologies for all-optical neurophysiology experiments. This is not an exhaustive review of fluorescent indicators and imaging modalities but rather aims to distill the functional imaging principles driving the choice of both. Scientific priorities determine whether the imaging strategy is based on an “optimal fluorescent indicator” or “optimal imaging modality.” The choice of the first constrains the choice of the second due to each’s contributions to the fluorescence budget and signal-to-noise ratio of time-varying fluorescence changes.
Song P, Jadan HV, Howe CL, et al., 2021, MODEL-INSPIRED DEEP LEARNING FOR LIGHT-FIELD MICROSCOPY WITH APPLICATION TO NEURON LOCALIZATION, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Publisher: IEEE, Pages: 8087-8091
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Verinaz-Jadan H, Song P, Howe CL, et al., 2021, DEEP LEARNING FOR LIGHT FIELD MICROSCOPY USING PHYSICS-BASED MODELS, 18th IEEE International Symposium on Biomedical Imaging (ISBI), Publisher: IEEE, Pages: 1091-1094, ISSN: 1945-7928
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- Citations: 4
Howe CL, Quicke P, Song P, et al., 2020, Comparing synthetic refocusing to deconvolution for the extraction of neuronal calcium transients from light-fields
<jats:title>Abstract</jats:title><jats:sec><jats:title>Significance</jats:title><jats:p>Light-field microscopy (LFM) enables fast, light-efficient, volumetric imaging of neuronal activity with calcium indicators. Calcium transients differ in temporal signal-to-noise ratio (tSNR) and spatial confinement when extracted from volumes reconstructed by different algorithms.</jats:p></jats:sec><jats:sec><jats:title>Aim</jats:title><jats:p>We evaluated the capabilities and limitations of two light-field reconstruction algorithms for calcium fluorescence imaging.</jats:p></jats:sec><jats:sec><jats:title>Approach</jats:title><jats:p>We acquired light-field image series from neurons either bulk-labeled or filled intracellularly with the red-emitting calcium dye CaSiR-1 in acute mouse brain slices. We compared the tSNR and spatial confinement of calcium signals extracted from volumes reconstructed with synthetic refocusing and Richardson-Lucy 3D deconvolution with and without total variation regularization.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Both synthetic refocusing and Richardson-Lucy deconvolution resolved calcium signals from single cells and neuronal dendrites in three dimensions. Increasing deconvolution iteration number improved spatial confinement but reduced tSNR compared to synthetic refocusing. Volumetric light-field imaging did not decrease calcium signal tSNR compared to interleaved, widefield image series acquired in matched planes.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>LFM enables high-volume rate, volumetric imaging of calcium transients in single cells (bulk-labeled), somata and dendrites (intracellular loaded). The trade-offs identified for tSNR, spatial confinement, and computational cost indicate which of syntheti
Quicke P, Howe CL, Song P, et al., 2020, Subcellular resolution three-dimensional light-field imaging with genetically encoded voltage indicators, Neurophotonics, Vol: 7, ISSN: 2329-4248
Significance: Light-field microscopy (LFM) enables high signal-to-noise ratio (SNR) and light efficient volume imaging at fast frame rates. Voltage imaging with genetically encoded voltage indicators (GEVIs) stands to particularly benefit from LFM's volumetric imaging capability due to high required sampling rates and limited probe brightness and functional sensitivity. Aim: We demonstrate subcellular resolution GEVI light-field imaging in acute mouse brain slices resolving dendritic voltage signals in three spatial dimensions. Approach: We imaged action potential-induced fluorescence transients in mouse brain slices sparsely expressing the GEVI VSFP-Butterfly 1.2 in wide-field microscopy (WFM) and LFM modes. We compared functional signal SNR and localization between different LFM reconstruction approaches and between LFM and WFM. Results: LFM enabled three-dimensional (3-D) localization of action potential-induced fluorescence transients in neuronal somata and dendrites. Nonregularized deconvolution decreased SNR with increased iteration number compared to synthetic refocusing but increased axial and lateral signal localization. SNR was unaffected for LFM compared to WFM. Conclusions: LFM enables 3-D localization of fluorescence transients, therefore eliminating the need for structures to lie in a single focal plane. These results demonstrate LFM's potential for studying dendritic integration and action potential propagation in three spatial dimensions.
Quicke P, Howe CL, Song P, et al., 2020, Subcellular resolution 3D light field imaging with genetically encoded voltage indicators, Neurophotonics, Vol: 7, ISSN: 2329-4248
Significance: Light-field microscopy (LFM) enables high signal-to-noise ratio (SNR) and light efficient volume imaging at fast frame rates. Voltage imaging with genetically encoded voltage indicators (GEVIs) stands to particularly benefit from LFM’s volumetric imaging capability due to high required sampling rates and limited probe brightness and functional sensitivity.Aim: We demonstrate subcellular resolution GEVI light-field imaging in acute mouse brain slices resolving dendritic voltage signals in three spatial dimensions.Approach: We imaged action potential-induced fluorescence transients in mouse brain slices sparsely expressing the GEVI VSFP-Butterfly 1.2 in wide-field microscopy (WFM) and LFM modes. We compared functional signal SNR and localization between different LFM reconstruction approaches and between LFM and WFM.Results: LFM enabled three-dimensional (3-D) localization of action potential-induced fluorescence transients in neuronal somata and dendrites. Nonregularized deconvolution decreased SNR with increased iteration number compared to synthetic refocusing but increased axial and lateral signal localization. SNR was unaffected for LFM compared to WFM.Conclusions: LFM enables 3-D localization of fluorescence transients, therefore eliminating the need for structures to lie in a single focal plane. These results demonstrate LFM’s potential for studying dendritic integration and action potential propagation in three spatial dimensions.
Song P, Verinaz Jadan H, Howe C, et al., 2020, 3D localization for light-field microscopy via convolutional sparse coding on epipolar images, IEEE transactions on computational imaging, Vol: 6, Pages: 1017-1032, ISSN: 2333-9403
Light-field microscopy (LFM) is a type of all-optical imaging system that is able to capture 4D geometric information of light rays and can reconstruct a 3D model from a single snapshot. In this paper, we propose a new 3D localization approach to effectively detect 3D positions of neuronal cells from a single light-field image with high accuracy and outstanding robustness to light scattering. This is achieved by constructing a depth-aware dictionary and by combining it with convolutional sparse coding. Specifically, our approach includes 3 key parts: light-field calibration, depth-aware dictionary construction, and localization based on convolutional sparse coding (CSC). In the first part, an observed raw light-field image is calibrated and then decoded into a two-plane parameterized 4D format which leads to the epi-polar plane image (EPI). The second part involves simulating a set of light-fields using a wave-optics forward model for a ball-shaped volume that is located at different depths. Then, a depth-aware dictionary is constructed where each element is a synthetic EPI associated to a specific depth. Finally, by taking full advantage of the sparsity prior and shift-invariance property of EPI, 3D localization is achieved via convolutional sparse coding on an observed EPI with respect to the depth-aware EPI dictionary. We evaluate our approach on both non-scattering specimen (fluorescent beads suspended in agarose gel) and scattering media (brain tissues of genetically encoded mice). Extensive experiments demonstrate that our approach can reliably detect the 3D positions of granular targets with small Root Mean Square Error (RMSE), high robustness to optical aberration and light scattering in mammalian brain tissues.
Verinaz-Jadan H, Song P, Howe CL, et al., 2020, Volume reconstruction for light field microscopy, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Publisher: IEEE, Pages: 1459-1463
Light Field Microscopy (LFM) is a 3D imaging technique that captures volumetric information in a single snapshot. It is appealing in microscopy because of its simple implementation and the peculiarity that it is much faster than methods involving scanning. However, volume reconstruction for LFM suffers from low lateral resolution, high computational cost, and reconstruction artifacts near the native object plane. In this work, we make two contributions. First, we propose a simplification of the forward model based on a novel discretization approach that allows us to accelerate the computation without drastically increasing memory consumption. Second, we experimentally show that by including regularization priors and an appropriate initialization strategy, it is possible to remove the artifacts near the native object plane. The algorithm we use for this is ADMM. Finally, the combination of the two techniques leads to a method that outperforms classic volume reconstruction approaches (variants of Richardson-Lucy) in terms of average computational time and image quality (PSNR).
Howe CL, Quicke P, Song P, et al., 2020, Comparing wide field to 3d light field for imaging red calcium transients in mammalian brain
We apply light field (LF) microscopy to single-cell and bulk-loaded imaging of the red calcium dye, CaSiR-1 in mouse brain slices. We characterize the signal-to-noise ratio of images reconstructed from LF to wide-field time series.
Quicke P, Song C, McKimm EJ, et al., 2019, Corrigendum: Single-neuron level one-photon voltage imaging with sparsely targeted genetically encoded voltage indicators, Frontiers in Cellular Neuroscience, Vol: 13, ISSN: 1662-5102
Voltage imaging of many neurons simultaneously at single-cell resolution is hampered bythe difficulty of detecting small voltage signals from overlapping neuronal processes inneural tissue. Recent advances in genetically encoded voltage indicator (GEVI) imaginghave shown single-cell resolution optical voltage recordings in intact tissue throughimaging naturally sparse cell classes, sparse viral expression, soma restricted expression,advanced optical systems, or a combination of these. Widespread sparse and strongtransgenic GEVI expression would enable straightforward optical access to a denselyoccurring cell type, such as cortical pyramidal cells. Here we demonstrate that a recentlydescribed sparse transgenic expression strategy can enable single-cell resolution voltageimaging of cortical pyramidal cells in intact brain tissue without restricting expression tothe soma. We also quantify the functional crosstalk in brain tissue and discuss optimalimaging rates to inform future GEVI experimental design.
Soor N, Quicke P, Howe C, et al., 2019, All-optical crosstalk-free manipulation and readout of Chronos-expressing neurons, Journal of Physics D: Applied Physics, Vol: 52, Pages: 1-10, ISSN: 0022-3727
All optical neurophysiology allows manipulation and readout of neural network activity with single-cell spatial resolution and millisecond temporal resolution. Neurons can be made to express proteins that actuate transmembrane currents upon light absorption, enabling optical control of membrane potential and action potential signalling. In addition, neurons can be genetically or synthetically labelled with fluorescent reporters of changes in intracellular calcium concentration or membrane potential. Thus, to optically manipulate and readout neural activity in parallel, two spectra are involved: the action spectrum of the actuator, and the absorption spectrum of the fluorescent reporter. Due to overlap in these spectra, previous all-optical neurophysiology paradigms have been hindered by spurious activation of neuronal activity caused by the readout light. Here, we pair the blue-green absorbing optogenetic actuator, Chronos, with a deep red-emitting fluorescent calcium reporter CaSiR-1. We show that cultured Chinese hamster ovary cells transfected with Chronos do not exhibit transmembrane currents when illuminated with wavelengths and intensities suitable for exciting one-photon CaSiR-1 fluorescence. We then demonstrate crosstalk-free, high signal-to-noise ratio CaSiR-1 red fluorescence imaging at 100 frames s−1 of Chronos-mediated calcium transients evoked in neurons with blue light pulses at rates up to 20 Hz. These results indicate that the spectral separation between red light excited fluorophores, excited efficiently at or above 640 nm, with blue-green absorbing opsins such as Chronos, is sufficient to avoid spurious opsin actuation by the imaging wavelengths and therefore enable crosstalk-free all-optical neuronal manipulation and readout.
Quicke P, Song C, McKimm EJ, et al., 2019, Single-neuron level one-photon voltage imaging with sparsely targeted genetically encoded voltage indicators, Frontiers in Cellular Neuroscience, Vol: 13, ISSN: 1662-5102
Voltage imaging of many neurons simultaneously at single-cell resolution is hampered by the difficulty of detecting small voltage signals from overlapping neuronal processes in neural tissue. Recent advances in genetically encoded voltage indicator (GEVI) imaging have shown single-cell resolution optical voltage recordings in intact tissue through imaging naturally sparse cell classes, sparse viral expression, soma restricted expression, advanced optical systems, or a combination of these. Widespread sparse and strong transgenic GEVI expression would enable straightforward optical access to a densely occurring cell type, such as cortical pyramidal cells. Here we demonstrate that a recently described sparse transgenic expression strategy can enable single-cell resolution voltage imaging of cortical pyramidal cells in intact brain tissue without restricting expression to the soma. We also quantify the functional crosstalk in brain tissue and discuss optimal imaging rates to inform future GEVI experimental design.
Quicke P, Howe CL, Song P, et al., 2019, Calculation of high numerical aperture lightfield microscope point spread functions
3D deconvolution of lightfield images enables high resolution reconstruction of sample volumes. Previous point spread function calculations assume low to moderate NA objectives. Here we present a simple vectorial calculation valid for high NA objectives.
Song P, Jadan HV, Quicke P, et al., 2019, Location estimation for light field microscopy based on convolutional sparse coding
In this work, we propose an algorithm to estimate the depth location of objects from lightfield microscopy data by leveraging the sparsity of Epipolar Plane Images (EPIs) and convolutional sparse coding.
Quicke P, Reynolds S, Neil M, et al., 2018, High speed functional imaging with source localized multifocal two-photon microscopy, Biomedical Optics Express, Vol: 9, Pages: 3678-3693, ISSN: 2156-7085
Multifocal two-photon microscopy (MTPM) increases imaging speed over single-focus scanning by parallelizing fluorescence excitation. The imaged fluorescence’s susceptibility to crosstalk, however, severely degrades contrast in scattering tissue. Here we present a source-localized MTPM scheme optimized for high speed functional fluorescence imaging in scattering mammalian brain tissue. A rastered line array of beamlets excites fluorescence imaged with a complementary metal-oxide-semiconductor (CMOS) camera. We mitigate scattering-induced crosstalk by temporally oversampling the rastered image, generating grouped images with structured illumination, and applying Richardson-Lucy deconvolution to reassign scattered photons. Single images are then retrieved with a maximum intensity projection through the deconvolved image groups. This method increased image contrast at depths up to 112 μm in scattering brain tissue and reduced functional crosstalk between pixels during neuronal calcium imaging. Source-localization did not affect signal-to-noise ratio (SNR) in densely labeled tissue under our experimental conditions. SNR decreased at low frame rates in sparsely labeled tissue, with no effect at frame rates above 50 Hz. Our non-descanned source-localized MTPM system enables high SNR, 100 Hz capture of fluorescence transients in scattering brain, increasing the scope of MTPM to faster and smaller functional signals.
Ronzitti E, Conti R, Zampini V, et al., 2017, Submillisecond optogenetic control of neuronal firing with two-photon holographic photoactivation of chronos, The Journal of Neuroscience, Vol: 37, Pages: 10679-10689, ISSN: 0270-6474
Optogenetic neuronal network manipulation promises to unravel a long-standing mystery in neuroscience: how does microcircuit activity relate causally to behavioral and pathological states? The challenge to evoke spikes with high spatial and temporal complexity necessitates further joint development of light-delivery approaches and custom opsins. Two-photon (2P) light-targeting strategies demonstrated in-depth generation of action potentials in photosensitive neurons both in vitro and in vivo, but thus far lack the temporal precision necessary to induce precisely timed spiking events. Here, we show that efficient current integration enabled by 2P holographic amplified laser illumination of Chronos, a highly light-sensitive and fast opsin, can evoke spikes with submillisecond precision and repeated firing up to 100 Hz in brain slices from Swiss male mice. These results pave the way for optogenetic manipulation with the spatial and temporal sophistication necessary to mimic natural microcircuit activity.
Quicke P, Neil M, Knopfel T, et al., 2017, Source-Localized Multifocal Two-Photon Microscopy for High-Speed Functional Imaging, 71st Annual Meeting of the Society-of-General-Physiologists (SGP) on Optical Revolution in Physiology - From Membrane to Brain, Publisher: ROCKEFELLER UNIV PRESS, Pages: 13A-14A, ISSN: 0022-1295
Cazé RD, Jarvis S, Foust AJ, et al., 2017, Dendrites enable a robust mechanism for neuronal stimulus selectivity, Neural Computation, Vol: 29, Pages: 2511-2527, ISSN: 0899-7667
Hearing, vision, touch: underlying all of these senses is stimulus selectivity, a robust information processing operation in which cortical neurons respond more to some stimuli than to others. Previous models assume that these neurons receive the highest weighted input from an ensemble encoding the preferred stimulus, but dendrites enable other possibilities. Nonlinear dendritic processing can produce stimulus selectivity based on the spatial distribution of synapses, even if the total preferred stimulus weight does not exceed that of nonpreferred stimuli. Using a multi-subunit nonlinear model, we demonstrate that stimulus selectivity can arise from the spatial distribution of synapses. We propose this as a general mechanism for information processing by neurons possessing dendritic trees. Moreover, we show that this implementation of stimulus selectivity increases the neuron's robustness to synaptic and dendritic failure. Importantly, our model can maintain stimulus selectivity for a larger range of loss of synapses or dendrites than an equivalent linear model. We then use a layer 2/3 biophysical neuron model to show that our implementation is consistent with two recent experimental observations: (1) one can observe a mixture of selectivities in dendrites that can differ from the somatic selectivity, and (2) hyperpolarization can broaden somatic tuning without affecting dendritic tuning. Our model predicts that an initially nonselective neuron can become selective when depolarized. In addition to motivating new experiments, the model's increased robustness to synapses and dendrites loss provides a starting point for fault-resistant neuromorphic chip development.
Guillon M, Forget BC, Foust AJ, et al., 2017, Vortex-free phase profiles for uniform patterning with computer-generated holography, OPTICS EXPRESS, Vol: 25, Pages: 12640-12652, ISSN: 1094-4087
Schultz SR, Copeland CS, Foust AJ, et al., 2016, Advances in two-photon scanning and scanless microscopy technologies for functional neural circuit imaging, Proceedings of the IEEE, Vol: 105, Pages: 139-157, ISSN: 0018-9219
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 paper, 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.
Casale AE, Foust AJ, Bal T, et al., 2015, Cortical Interneuron Subtypes Vary in Their Axonal Action Potential Properties, JOURNAL OF NEUROSCIENCE, Vol: 35, Pages: 15555-15567, ISSN: 0270-6474
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Foust AJ, Zampini V, Tanese D, et al., 2015, Computer-generated holography enhances voltage dye fluorescence discrimination in adjacent neuronal structures, Neurophotonics, Vol: 2, Pages: 021007-1-021007-8, ISSN: 2329-4248
Voltage-sensitive fluorescence indicators enable tracking neuronal electrical signals simultaneously in multiple neurons or neuronal subcompartments difficult to access with patch electrodes. However, efficient widefield epifluorescence detection of rapid voltage fluorescence transients necessitates that imaged cells and structures lie sufficiently far from other labeled structures to avoid contamination from out of focal plane and scattered light. We overcame this limitation by exciting dye fluorescence with one-photon computer-generated holography shapes contoured to axons or dendrites of interest, enabling widefield detection of voltage fluorescence with high spatial specificity. By shaping light onto neighboring axons and dendrites, we observed that dendritic back-propagating action potentials were broader and slowly rising compared with axonal action potentials, differences not measured in the same structures illuminated with a large “pseudowidefield” (pWF) spot of the same excitation density. Shaped illumination trials showed reduced baseline fluorescence, higher baseline noise, and fractional fluorescence transient amplitudes two times greater than trials acquired with pWF illumination of the same regions.
Foust AJ, Casale AE, Zecevic D, et al., 2012, High signal-to-noise ratio voltage imaging: A powerful tool for determining electrophysiological properties of CNS axons
Although axons play a key role in neuronal computation, the small size of CNS axons precludes direct characterization with electrical recordings. We implement high signal-to-noise atio VSD imaging to determine cortical axon functional properties. © OSA 2012.
Foust AJ, Yu Y, Popovic M, et al., 2011, Somatic Membrane Potential and Kv1 Channels Control Spike Repolarization in Cortical Axon Collaterals and Presynaptic Boutons, JOURNAL OF NEUROSCIENCE, Vol: 31, Pages: 15490-15498, ISSN: 0270-6474
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- Citations: 68
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