Particle Tracking Facilitates Real Time Capable Motion Correction in 2D or 3D Two-Photon Imaging of Neuronal Activity

Review of data processing of functional optical microscopy for neuroscience

Functional optical imaging in neuroscience is rapidly growing with the development of optical systems and fluorescence indicators. To realize the potential of these massive spatiotemporal datasets for relating neuronal activity to behavior and stimuli and uncovering local circuits in the brain, accurate automated processing is increasingly essential. We cover recent computational developments in the full data processing pipeline of functional optical microscopy for neuroscience data and discuss ongoing and emerging challenges.

Axial motion estimation and correction for simultaneous multi-plane two-photon calcium imaging

Two-photon imaging in behaving animals is typically accompanied by brain motion. For functional imaging experiments, for example with genetically encoded calcium indicators, such brain motion induces changes in fluorescence intensity. These motion-related intensity changes or motion artifacts can typically not be separated from neural activity-induced signals. While lateral motion, within the focal plane, can be corrected by computationally aligning images, axial motion, out of the focal plane, cannot easily be corrected. Here, we developed an algorithm for axial motion correction for non-ratiometric calcium indicators taking advantage of simultaneous multi-plane imaging. Using temporally multiplexed beams, recording simultaneously from at least two focal planes at different z positions, and recording a z-stack for each beam as a calibration step, the algorithm separates motion-related and neural activity-induced changes in fluorescence intensity. The algorithm is based on a maximum likelihood optimisation approach; it assumes (as a first order approximation) that no distortions of the sample occurs during axial motion and that neural activity increases uniformly along the optical axis in each region of interest. The developed motion correction approach allows axial motion estimation and correction at high frame rates for isolated structures in the imaging volume in vivo, such as sparse expression patterns in the fruit fly brain.

Non-rigid Registration for Two-photon Imaging Using Triangulation and Piecewise Affine Transformation

Accurate and efficient non-rigid registration is important to investigate neural mechanisms in multi-session two-photon (2p) imaging across a few days. The 2p imaging recordings from different sessions usually possess certain complex misalignment or huge data variance due to relocation errors during experimental operations or brain recovery. Most of the reported neural image registration tools were able to solve the registration problem in the same session with small deformation. However, the registration of neural images across multi-sessions remains a challenge. In this study, we report the development of a non-rigid registration method for 2p imaging in mice based on image triangulation and piecewise affine transformation (TPAT) technologies. The TPAT method supported both automatic and semi-automatic operation types, and both showed great performance in the benchmark test of non-rigid neural image registration. The proposed method constitutes a step forward in promoting and accelerating discoveries from multi-session 2p imaging research.

Global motion detection and censoring in high-density diffuse optical tomography

Motion‐induced artifacts can significantly corrupt optical neuroimaging, as in most neuroimaging modalities. For high‐density diffuse optical tomography (HD‐DOT) with hundreds to thousands of source‐detector pair measurements, motion detection methods are underdeveloped relative to both functional magnetic resonance imaging (fMRI) and standard functional near‐infrared spectroscopy (fNIRS). This limitation restricts the application of HD‐DOT in many challenging imaging situations and subject populations (e.g., bedside monitoring and children). Here, we evaluated a new motion detection method for multi‐channel optical imaging systems that leverages spatial patterns across measurement channels. Specifically, we introduced a global variance of temporal derivatives (GVTD) metric as a motion detection index. We showed that GVTD strongly correlates with external measures of motion and has high sensitivity and specificity to instructed motion—with an area under the receiver operator characteristic curve of 0.88, calculated based on five different types of instructed motion. Additionally, we showed that applying GVTD‐based motion censoring on both hearing words task and resting state HD‐DOT data with natural head motion results in an improved spatial similarity to fMRI mapping. We then compared the GVTD similarity scores with several commonly used motion correction methods described in the fNIRS literature, including correlation‐based signal improvement (CBSI), temporal derivative distribution repair (TDDR), wavelet filtering, and targeted principal component analysis (tPCA). We find that GVTD motion censoring on HD‐DOT data outperforms other methods and results in spatial maps more similar to those of matched fMRI data.

Multiphoton intravital microscopy in small animals: motion artefact challenges and technical solutions

Since its invention 29 years ago, two‐photon laser‐scanning microscopy has evolved from a promising imaging technique, to an established widely available imaging modality used throughout the biomedical research community. The establishment of two‐photon microscopy as the preferred method for imaging fluorescently labelled cells and structures in living animals can be attributed to the biophysical mechanism by which the generation of fluorescence is accomplished. The use of powerful lasers capable of delivering infrared light pulses within femtosecond intervals, facilitates the nonlinear excitation of fluorescent molecules only at the focal plane and determines by objective lens position. This offers numerous benefits for studies of biological samples at high spatial and temporal resolutions with limited photo‐damage and superior tissue penetration. Indeed, these attributes have established two‐photon microscopy as the ideal method for live‐animal imaging in several areas of biology and have led to a whole new field of study dedicated to imaging biological phenomena in intact tissues and living organisms. However, despite its appealing features, two‐photon intravital microscopy is inherently limited by tissue motion from heartbeat, respiratory cycles, peristalsis, muscle/vascular tone and physiological functions that change tissue geometry. Because these movements impede temporal and spatial resolution, they must be properly addressed to harness the full potential of two‐photon intravital microscopy and enable accurate data analysis and interpretation. In addition, the sources and features of these motion artefacts are varied, sometimes unpredictable and unique to specific organs and multiple complex strategies have previously been devised to address them. This review will discuss these motion artefacts requirement and technical solutions for their correction and after intravital two‐photon microscopy.

Analysis pipelines for calcium imaging data

Calcium imaging is a popular tool among neuroscientists because of its capability to monitor in vivo large neural populations across weeks with single neuron and single spike resolution. Before any downstream analysis, the data needs to be pre-processed to extract the location and activity of the neurons and processes in the observed field of view. The ever increasing size of calcium imaging datasets necessitates scalable analysis pipelines that are reproducible and fully automated. This review focuses on recent methods for addressing the pre-processing problems that arise in calcium imaging data analysis, and available software tools for high throughput analysis pipelines.

Real-Time Processing of Two-Photon Calcium Imaging Data Including Lateral Motion Artifact Correction

Two-photon calcium imaging has been extensively used to record neural activity in the brain. It has been long used solely with post-hoc analysis, but the recent efforts began to include closed-loop experiments. Closed-loop experiments pose new challenges because they require fast, real-time image processing without iterative parameter tuning. When imaging awake animals, one of the crucial steps of post hoc image analysis is correction of lateral motion artifacts. In most of the closed-loop experiments, this step has not been implemented and ignored due to technical difficulties. We recently reported the first experiments with real-time processing of calcium imaging that included lateral motion correction. Here, we report the details of the implementation of fast motion correction and present performance analysis across several algorithms with different parameters. Additionally, we introduce a novel method to estimate baseline calcium signal using kernel density estimate, which reduces the number of parameters to be tuned. Combined, we propose a novel software pipeline of real-time image processing suited for closed-loop experiments. The pipeline is also useful for rapid post hoc image processing.