(The limits of) eye-tracking with iPads Taore, Aryaman; Tiang, Michelle; Dakin, Steven C.
Journal of vision (Charlottesville, Va.),
07/2024, Letnik:
24, Številka:
7
Journal Article
Recenzirano
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Applications for eye-tracking-particularly in the clinic-are limited by a reliance on dedicated hardware. Here we compare eye-tracking implemented on an Apple iPad Pro 11" (third generation)-using ...the device's infrared head-tracking and front-facing camera-with a Tobii 4c infrared eye-tracker. We estimated gaze location using both systems while 28 observers performed a variety of tasks. For estimating fixation, gaze position estimates from the iPad were less accurate and precise than the Tobii (mean absolute error of 3.2° ± 2.0° compared with 0.75° ± 0.43°), but fixation stability estimates were correlated across devices (r = 0.44, p < 0.05). For tasks eliciting saccades >1.5°, estimated saccade counts (r = 0.4-0.73, all p < 0.05) were moderately correlated across devices. For tasks eliciting saccades >8° we observed moderate correlations in estimated saccade speed and amplitude (r = 0.4-0.53, all p < 0.05). We did, however, note considerable variation in the vertical component of estimated smooth pursuit speed from the iPad and a catastrophic failure of tracking on the iPad in 5% to 20% of observers (depending on the test). Our findings sound a note of caution to researchers seeking to use iPads for eye-tracking and emphasize the need to properly examine their eye-tracking data to remove artifacts and outliers.Applications for eye-tracking-particularly in the clinic-are limited by a reliance on dedicated hardware. Here we compare eye-tracking implemented on an Apple iPad Pro 11" (third generation)-using the device's infrared head-tracking and front-facing camera-with a Tobii 4c infrared eye-tracker. We estimated gaze location using both systems while 28 observers performed a variety of tasks. For estimating fixation, gaze position estimates from the iPad were less accurate and precise than the Tobii (mean absolute error of 3.2° ± 2.0° compared with 0.75° ± 0.43°), but fixation stability estimates were correlated across devices (r = 0.44, p < 0.05). For tasks eliciting saccades >1.5°, estimated saccade counts (r = 0.4-0.73, all p < 0.05) were moderately correlated across devices. For tasks eliciting saccades >8° we observed moderate correlations in estimated saccade speed and amplitude (r = 0.4-0.53, all p < 0.05). We did, however, note considerable variation in the vertical component of estimated smooth pursuit speed from the iPad and a catastrophic failure of tracking on the iPad in 5% to 20% of observers (depending on the test). Our findings sound a note of caution to researchers seeking to use iPads for eye-tracking and emphasize the need to properly examine their eye-tracking data to remove artifacts and outliers.
A plethora of problems from diverse disciplines such as Mathematics, Mathematical: Biology, Chemistry, Economics, Physics, Scientific Computing and also Engineering can be formulated as an equation ...defined in abstract spaces using Mathematical Modelling. The solutions of these equations can be found in closed form only in special case. That is why researchers and practitioners utilize iterative procedures from which a sequence is being generated approximating the solution under some conditions on the initial data.
This type of research is considered most interesting and challenging. This is our motivation for the introduction of this special issue on Iterative Procedures.
Sample preparation Chen, Yi; Guo, Zhenpeng; Wang, Xiaoyu ...
Journal of Chromatography A,
03/2008, Letnik:
1184, Številka:
1
Journal Article
Recenzirano
A panorama of sample preparation methods has been composed from 481 references, with a highlight of some promising methods fast developed during recent years and a somewhat brief introduction on most ...of the well-developed methods. All the samples were commonly referred to molecular composition, being extendable to particles including cells but not to organs, tissues and larger bodies. Some criteria to evaluate or validate a sample preparation method were proposed for reference. Strategy for integration of several methods to prepare complicated protein samples for proteomic studies was illustrated and discussed.
Stable isotope labeling of microbial taxa of interest and their sorting provide an efficient and direct way to answer the question "who does what?" in complex microbial communities when coupled with ...fluorescence in situ hybridization or downstream 'omics' analyses. We have developed a platform for automated Raman-based sorting in which optical tweezers and microfluidics are used to sort individual cells of interest from microbial communities on the basis of their Raman spectra. This sorting of cells and their downstream DNA analysis, such as by mini-metagenomics or single-cell genomics, or cultivation permits a direct link to be made between the metabolic roles and the genomes of microbial cells within complex microbial communities, as well as targeted isolation of novel microbes with a specific physiology of interest. We describe a protocol from sample preparation through Raman-activated live cell sorting. Subsequent cultivation of sorted cells is described, whereas downstream DNA analysis involves well-established approaches with abundant methods available in the literature. Compared with manual sorting, this technique provides a substantially higher throughput (up to 500 cells per h). Furthermore, the platform has very high sorting accuracy (98.3 ± 1.7%) and is fully automated, thus avoiding user biases that might accompany manual sorting. We anticipate that this protocol will empower in particular environmental and host-associated microbiome research with a versatile tool to elucidate the metabolic contributions of microbial taxa within their complex communities. After a 1-d preparation of cells, sorting takes on the order of 4 h, depending on the number of cells required.
Methods and advances for monitoring neurotransmitters
in vivo or for tissue analysis of neurotransmitters over the last five years are reviewed. The review is organized primarily by neurotransmitter ...type. Transmitter and related compounds may be monitored by either
in vivo sampling coupled to analytical methods or implanted sensors. Sampling is primarily performed using microdialysis, but low-flow push–pull perfusion may offer advantages of spatial resolution while minimizing the tissue disruption associated with higher flow rates. Analytical techniques coupled to these sampling methods include liquid chromatography, capillary electrophoresis, enzyme assays, sensors, and mass spectrometry. Methods for the detection of amino acid, monoamine, neuropeptide, acetylcholine, nucleoside, and soluble gas neurotransmitters have been developed and improved upon. Advances in the speed and sensitivity of these methods have enabled improvements in temporal resolution and increased the number of compounds detectable. Similar advances have enabled improved detection at tissue samples, with a substantial emphasis on single cell and other small samples. Sensors provide excellent temporal and spatial resolution for
in vivo monitoring. Advances in application to catecholamines, indoleamines, and amino acids have been prominent. Improvements in stability, sensitivity, and selectivity of the sensors have been of paramount interest.
Single-cell profiling methods have had a profound impact on the understanding of cellular heterogeneity. While genomes and transcriptomes can be explored at the single-cell level, single-cell ...profiling of proteomes is not yet established. Here we describe new single-molecule protein sequencing and identification technologies alongside innovations in mass spectrometry that will eventually enable broad sequence coverage in single-cell profiling. These technologies will in turn facilitate biological discovery and open new avenues for ultrasensitive disease diagnostics.
Cell identity is determined by the selective activation or silencing of specific genes via transcription factor binding and epigenetic modifications on the genome. Chromatin immunoprecipitation ...(ChIP) has been the standard technique for mapping the sites of transcription factor binding and histone modification. Recently, alternative methods to ChIP have been developed for addressing the increasing demands for low-input epigenomic profiling. Chromatin integration labeling (ChIL) followed by sequencing (ChIL-seq) has been demonstrated to be particularly useful for epigenomic profiling of low-input samples or even single cells because the technique amplifies the target genomic sequence before cell lysis. After labeling the target protein or modification in situ with an oligonucleotide-conjugated antibody (ChIL probe), the nearby genome sequence is amplified by Tn5 transposase-mediated transposition followed by T7 RNA polymerase-mediated transcription. ChIL-seq enables the detection of the antibody target localization under a fluorescence microscope and at the genomic level. Here we describe the detailed protocol of ChIL-seq with assessment methods for the key steps, including ChIL probe reaction, transposition, in situ transcription and sequencing library preparation. The protocol usually takes 3 d to prepare the sequencing library, including overnight incubations for the ChIL probe reaction and in situ transcription. The ChIL probe can be separately prepared and stored for several months, and its preparation and evaluation protocols are also documented in detail. An optional analysis for multiple targets (multitarget ChIL-seq) is also described. We anticipate that the protocol presented here will make the ChIL technique more widely accessible for analyzing precious samples and facilitate further applications.
Image-based cell profiling is a high-throughput strategy for the quantification of phenotypic differences among a variety of cell populations. It paves the way to studying biological systems on a ...large scale by using chemical and genetic perturbations. The general workflow for this technology involves image acquisition with high-throughput microscopy systems and subsequent image processing and analysis. Here, we introduce the steps required to create high-quality image-based (i.e., morphological) profiles from a collection of microscopy images. We recommend techniques that have proven useful in each stage of the data analysis process, on the basis of the experience of 20 laboratories worldwide that are refining their image-based cell-profiling methodologies in pursuit of biological discovery. The recommended techniques cover alternatives that may suit various biological goals, experimental designs, and laboratories' preferences.
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