For example, Mehring et al showed that LFPs can be regarded as an additional source for decoding brain activity [25]; LFP activity, along with spikes, can be leveraged in a multi-scale model to decode a 3D reach task [35]. In addition, some material-based strategies are being developed to mitigate the problem of signal degradation over time [75]. In summary, the next generation of spike-based neural decoding will likely be fueled by the synergy of high-channel count recording, advanced electrode materials, and multi-scale methods. Combining multiple modalities in a single experimental inquiry has allowed researchers to achieve better performance in brain–machine interfaces (BMIs) and to gain new mechanistic insights. For example, mathematical models combining spiking activity with LFPs improved neural prosthetic prediction accuracy [25, 33–36].
The performance of the models is assessed with the F1 score and the macro F1 score. More detailed descriptions of the experimental setup and the metrics adopted are presented in the Supplementary Material. Table 5 and Table 6 summarize the results obtained respectively on the breast dataset and on lung dataset.
A multi-scale analysis framework of different methods used in establishing ecological networks
Other metrics used to characterize interactions include spike-field Granger causality [183], Volterra models of LFP-spike timing relationships [179], and multiscale causality estimation [184]. Large scale tissue imaging is becoming an everyday tool in developmental biology, but high throughput analysis methods are restricted to few laboratories. Etournay and co-workers present a software platform for segmentation and tracking of 2D epithelial monolayers.
Synergistic signals from multiple neural scales also minimized electrical and computational power requirements and increased the longevity of a BMI devices [34]. Furthermore, more recent studies demonstrated that measuring multi-scale activity enhanced decoding performance and provided information about connectivity or causality between different neural modalities in brain networks [35–38]. As highlighted by these select examples, multi-scale analyses have already significantly improved neuroscientific understanding and neural engineering applications, and merit more in-depth studies. We developed generic ‘multi-query functions’ (mqf) to collect specific information for individual movies.
Implementing the TissueMiner relational database
Cell elongation is characterized by a nematic tensor describing the axis and magnitude of the elongation (Aigouy et al., 2010). As with cell area, we map the magnitude of cell elongation to a color scale (Figure 2B–B’, Video 5). This fine-grained quantification of cell elongation highlights striking differences between inter-vein and vein cells. Inter-vein cells are more elongated than vein cells at 22 hr after puparium formation (hAPF), but this pattern is reversed by 31 hAPF. Some of these techniques aim to homogenize the properties of the local scale; others attempt to capture nonlinear behavior via curve fitting and progressive damage approaches. Many of the most famous techniques, such as those evaluated in the World Wide Failure Exercises, are related to the analysis of unidirectional composites.
The measured uncertainty is the 95% confidence interval of the standard error of the mean. The pure shear rate and its cellular contributions nearly vanish in this movie (Figure 5—figure supplement 1C,D). In the TissueMiner workflow, these properties are calculated from the original segmentation masks and stored in the database (Materials and methods). To visualize the evolution of the cell area pattern at the scale of the whole tissue, we map the area values of each individual cell to a gradient color scale (see Figure 2A–A’, Video 4). Figure 2A’ shows the pattern of cell areas in the wing at the end pupal wing blade elongation.
Mesoscopic and multiscale modelling in materials
We exclude changes in neighbor relationships resulting from cell division, extrusion or a cell moving in and out of the field of view. The remaining neighbor relationship changes are used to define cell contacts that have appeared or disappeared. To measure the orientation of cell divisions, we define a unit nematic tensor (see Materials and methods). For each cell division, the orientation of this unit nematic is defined by the line connecting the centers of mass of the two daughter cells when they first appear (see Figure 3C–C’, and TM R-User Manual section 2.8).
By using snakemake we enable the user to easily run and monitor TissueMiner, while maintaining a proper decoupling of tools as independent executables. To temporally align movies, TissueMiner provides a configuration file in which to manually define a time correction for each movie relative to one reference movie whose time correction is set to zero. The time correction can be estimated based on the appearance of morphological landmarks, or by aligning curves of a defined state quantity in time, such as cell area or cell elongation, on the assumption that this quantity has a similar qualitative time evolution.
4. EEG
These mqf tools are organized into fine-grained and coarse-grained categories according to the type of analysis to be carried out. The fine-grained tools aggregate data at cellular level, namely individual cell properties inside regions of interest. The coarse-grained mqf tools are further separated into ‘roi’ and ‘grid’ categories to distinguish between regions moving with the tissue and static square regions tiled into a grid. They allow one to visualize and quantify average cell properties at different tissue locations and various spatial scales, and are prefixed with ‘mqf_cg_roi_’ and ‘mqf_cg_grid_’ respectively. Relatively recently developed multivariate methods provide insights not only on patterns of local activation but also on patterns of connectivity between regions and networks [140].
Moreover, we find for these movies that expected deviations due to pixelation are two orders of magnitude smaller than the deformations that we aim to measure. To help the user to perform complex tissue morphogenesis analysis, we developed an automated pipeline that uses the tracked data from TissueAnalyzer as an input to build the database and perform all downstream analyses described above. To do so, we use the snakemake workflow engine developed by Koster and Rahmann (Koster and Rahmann, 2012). This engine channels the different processing steps into a well-formed workflow graph. Snakemake automatically determines the execution order, provides means for error recovery and job control, and supports High Performance Computing (HPC) environments.
These divisions are followed by a second peak of division in the inter-vein regions distInterL3-L4, interL2-L3 and postL5 (see cartoon in Figure 3A). Wing veins are specified during larval stages, but only become morphologically distinct during prepupal and pupal morphogenesis. During pupal morphogenesis, the dorsal and ventral surfaces of the wing epithelium become apposed to each other on their basal sides, except in the regions that will give rise to veins – here the basal surfaces of dorsal and ventral cells form a lumen. Vein cells have a narrower apical cross-section and form corrugations that protrude from the dorsal and ventral surfaces of the wing blade. The cell dynamics underlying vein morphogenesis have never been quantitatively examined.
- This includes the movie frames in which it first appears and disappears and why, along with its lineage relationship to other cells (see appendix 1).
- This allows an analyst to identify which details and relationships in the fine scale representation of a system have large scale implications, and which details disappear at coarser scales.
- We then selected the cluster corresponding to tracks that change latitudinal direction during the observation period for visualization.
- The scripts are developed to be multi-thread, in order to exploit hardware architectures with multiple cores.
- Our results show that the consistency of the three methods in identifying spatially priorities of protection ranged from 81.03% to 93.70%.
- For each track the change in radius and latitude was computed by first computing the difference between the last and the first position (in spherical coordinates) for non-overlapping pieces of 10 min duration and then averaging the results for each track.
Omicron SOLE-6 laser engine consisting of six different visible laser lines was mounted on the system and the laser beam through fiber was split into two for the two illumination arms. An optical chopper wheel (Thorlabs MC2000B, MC2F57Ba) was https://wizardsdev.com/en/news/multiscale-analysis/ used to generate alternate illumination of the sample from two sides. The chopper wheel provided the start trigger for cameras and stages for image acquisition and its rotation speed was synchronized with the acquisition of the camera.