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.

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

2020 ◽  
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

AbstractImaging 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.

scholarly journals Divergent excitation two photon microscopy for 3D random access mesoscale imaging at single cell resolution

2019 ◽  
Author(s):  
FK Janiak ◽  
P Bartel ◽  
MR Bale ◽  
T Yoshimatsu ◽  
E Komulainen ◽  
...  
Keyword(s):  
Single Cell ◽  
Neuronal Activity ◽  
Low Cost ◽  
Three Dimensional ◽  
Random Access ◽  
Field Of View ◽  
Three Dimensions ◽  
Two Photon ◽  
Wide Range ◽  
Effective Excitation

ABSTACTIn neuroscience, diffraction limited two-photon (2P) microscopy is a cornerstone technique that permits minimally invasive optical monitoring of neuronal activity. However, most conventional 2P microscopes impose significant constraints on the size of the imaging field-of-view and the specific shape of the effective excitation volume, thus limiting the scope of biological questions that can be addressed and the information obtainable. Here, employing ‘divergent beam optics’ (DBO), we present an ultra-low-cost, easily implemented and flexible solution to address these limitations, offering a several-fold expanded three-dimensional field of view that also maintains single-cell resolution. We show that this implementation increases both the space-bandwidth product and effective excitation power, and allows for straight-forward tailoring of the point-spread-function. Moreover, rapid laser-focus control via an electrically tunable lens now allows near-simultaneous imaging of remote regions separated in three dimensions and permits the bending of imaging planes to follow natural curvatures in biological structures. Crucially, our core design is readily implemented (and reversed) within a matter of hours, and fully compatible with a wide range of existing 2P customizations, making it highly suitable as a base platform for further development. We demonstrate the application of our system for imaging neuronal activity in a variety of examples in mice, zebrafish and fruit flies.

scholarly journals Perception and propagation of activity through the cortical hierarchy is determined by neural variability

2021 ◽  
Author(s):  
James M Rowland ◽  
Thijs L van der Plas ◽  
Matthias Loidolt ◽  
Robert Michael Lees ◽  
Joshua Keeling ◽  
...  
Keyword(s):  
Neural Activity ◽  
Signal To Noise Ratio ◽  
Brain Regions ◽  
Cortical Function ◽  
Population Activity ◽  
Two Photon ◽  
Secondary Somatosensory Cortex ◽  
Cortical Hierarchy ◽  
Robust Transmission ◽  
Neural Variability

The brains of higher organisms are composed of anatomically and functionally distinct regions performing specialised tasks; but regions do not operate in isolation. Orchestration of complex behaviours requires communication between brain regions, but how neural activity dynamics are organised to facilitate reliable transmission is not well understood. We studied this process directly by generating neural activity that propagates between brain regions and drives behaviour, allowing us to assess how populations of neurons in sensory cortex cooperate to transmit information. We achieved this by imaging two hierarchically organised and densely interconnected regions, the primary and secondary somatosensory cortex (S1 and S2) in mice while performing two-photon photostimulation of S1 neurons and assigning behavioural salience to the photostimulation. We found that the probability of perception is determined not only by the strength of the photostimulation signal, but also by the variability of S1 neural activity. Therefore, maximising the signal-to-noise ratio of the stimulus representation in cortex is critical to its continued propagation downstream. Further, we show that propagated, behaviourally salient activity elicits balanced, persistent, and generalised activation of the downstream region. Hence, our work adds to existing understanding of cortical function by identifying how population activity is formatted to ensure robust transmission of information, allowing specialised brain regions to communicate and coordinate behaviour.

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 LAB–QA2GO: A free, easy-to-use toolbox for the quality assessment of magnetic resonance imaging data

2019 ◽  
Author(s):  
Christoph Vogelbacher ◽  
Miriam H. A. Bopp ◽  
Verena Schuster ◽  
Peer Herholz ◽  
Andreas Jansen ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Virtual Machine ◽  
Signal To Noise Ratio ◽  
Imaging Data ◽  
Resonance Imaging ◽  
Data Set ◽  
Magnetic Resonance Imaging Mri ◽  
Movement Parameters ◽  
Set Up

AbstractImage characteristics of magnetic resonance imaging (MRI) data (e.g. signal-to-noise ratio, SNR) may change over the course of a study. To monitor these changes a quality assurance (QA) protocol is necessary. QA can be realized both by performing regular phantom measurements and by controlling the human MRI datasets (e.g. noise detection in structural or movement parameters in functional datasets). Several QA tools for the assessment of MRI data quality have been developed. Many of them are freely available. This allows in principle the flexible set-up of a QA protocol specifically adapted to the aims of one’s own study.However, setup and maintenance of these tools bind time, in particular since the installation and operation often require a fair amount of technical knowledge. In this article we present a light-weighted virtual machine, named LAB-QA2GO, which provides scripts for fully automated QA analyses of phantom and human datasets. This virtual machine is ready for analysis by starting it the first time. With minimal configuration in the guided web-interface the first analysis can start within 10 minutes, while adapting to local phantoms and needs is easily possible. The usability and scope of LAB–QA2GO is illustrated using a data set from the QA protocol of our lab. With LAB–QA2GO we hope to provide an easy-to-use toolbox that is able to calculate QA statistics without high effort.

scholarly journals Wide field-of-view, multi-region, two-photon imaging of neuronal activity in the mammalian brain

2016 ◽  
Vol 34 (8) ◽  
pp. 857-862 ◽  
Author(s):  
Jeffrey N Stirman ◽  
Ikuko T Smith ◽  
Michael W Kudenov ◽  
Spencer L Smith
Keyword(s):  
Neuronal Activity ◽  
Field Of View ◽  
Mammalian Brain ◽  
Wide Field ◽  
Two Photon ◽  
Wide Field Of View ◽  
Photon Imaging ◽  
Two Photon Imaging

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 Visual epidural field potentials possess high functional specificity in single trials

2019 ◽  
Author(s):  
Benjamin Fischer ◽  
Andreas Schander ◽  
Andreas K. Kreiter ◽  
Walter Lang ◽  
Detlef Wegener
Keyword(s):  
Neuronal Activity ◽  
Large Scale ◽  
Spatial Information ◽  
Signal To Noise Ratio ◽  
Electrode Array ◽  
Science Research ◽  
Machine Learning Algorithms ◽  
Field Potentials ◽  
Operating Characteristics ◽  
Minimal Invasiveness

AbstractRecordings of epidural field potentials (EFPs) allow to acquire neuronal activity over a large region of cortical tissue with minimal invasiveness. Because electrodes are placed on top of the dura and do not enter the neuronal tissue, EFPs offer intriguing options for both clinical and basic science research. On the other hand, EFPs represent the integrated activity of larger neuronal populations, possess a higher trial-by-trial variability, and a reduced signal-to-noise ratio due the additional barrier of the dura. It is thus unclear whether and to what extent EFPs have sufficient spatial selectivity to allow for conclusions about the underlying functional cortical architecture, and whether single EFP trials provide enough information on the short time scales relevant for many clinical and basic neuroscience purposes. We here use the high spatial resolution of primary visual cortex to address these issues and investigate the extent to which very short EFP traces allow reliable decoding of spatial information. We briefly presented different visual objects at one out of nine closely adjacent locations and recorded neuronal activity with a high-density, epidural multi-electrode array in three macaque monkeys. Using receiver-operating characteristics to identify most-informative data, machine-learning algorithms provided close-to-perfect classification rates for all 27 stimulus conditions. A binary classifier applying a simple max function on ROC-selected data further showed that single trials might be classified with 100% performance even without advanced offline classifiers. Thus, although highly variable, EFPs constitute an extremely valuable source of information and offer new perspectives for minimally invasive recording of large-scale networks.

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