Determining Which Sine Wave Frequencies Correspond to Signal and Which Correspond to Noise in Eye-Tracking Time-Series

The Fourier theorem states that any time-series can be decomposed into a set of sinusoidal frequencies, each with its own phase and amplitude. The literature suggests that some frequencies are important to reproduce key qualities of eye-movements ("signal") and some of frequencies are not important ("noise"). To investigate what is signal and what is noise, we analyzed our dataset in three ways: (1) visual inspection of plots of saccade, microsaccade and smooth pursuit exemplars; (2) analysis of the percentage of variance accounted for (PVAF) in 1,033 unfiltered saccade trajectories by each frequency band; (3) analyzing the main sequence relationship between saccade peak velocity and amplitude, based on a power law fit. Visual inspection suggested that frequencies up to 75 Hz are required to represent microsaccades. Our PVAF analysis indicated that signals in the 0-25 Hz band account for nearly 100% of the variance in saccade trajectories. Power law coefficients (a, b) return to unfiltered levels for signals low-pass filtered at 75 Hz or higher. We conclude that to maintain eye movement signal and reduce noise, a cutoff frequency of 75 Hz is appropriate. We explain why, given this finding, a minimum sampling rate of 750 Hz is suggested.Comment: Pages-16, Figures-11, Tables-4. arXiv admin note: text overlap with arXiv:2209.0765

Analysis of Heuristic and Digital Filters as Applied to Video-oculography Signals

In 1993, Stampe [1993] suggested two "heurisitic" filters that were designed for video-oculography data. Several manufacturers (e.g., SR-Research, Tobii T60 XL and SMI) have employed these filters as an option for recording eye-movements. For the EyeLink family of eye-trackers, these two filters are referred to as standard (STD) or EXTRA. We have implemented these filters as software functions. For those who use their eye-trackers for data-collection only, this will allow users to collect unfiltered data and simultaneously have access to unfiltered, STD filtered and EXTRA filtered data for the exact same recording. Based on the literature, which has employed various eye-tracking technologies, and our analysis of our EyeLink-1000 data, we conclude that the highest signal frequency content needed for most eye-tracking studies (i.e., saccades, microsaccades and smooth pursuit) is around 100 Hz, excluding fixation microtremor. For those who collect their data at 1000 Hz or higher, we test two zero-phase low-pass digital filters, one with a cutoff of 50 Hz and one with a cutoff of 100 Hz. We perform a Fourier (FFT) analysis to examine the frequency content for unfiltered data, STD data, EXTRA filtered data, and data filtered by low-pass digital filters. We also examine the frequency response of these filters. The digital filter with the 100 Hz cutoff dramatically outperforms both heuristic filters because the heuristic filters leave noise above 100 Hz. In the paper we provide additional conclusions and suggest the use of digital filters in scenarios where offline data processing is an option.Comment: 19 pages, 12 figures, 5 table

Volcanic ash supply to the surface ocean – remote sensing of biological responses and their wider biogeochemical significance

Transient micronutrient enrichment of the surface ocean can enhance phytoplankton growth rates and alter microbial community structure with an ensuing spectrum of biogeochemical feedbacks. Strong phytoplankton responses to micronutrients supplied by volcanic ash have been reported recently. Here we: (i) synthesize findings from these recent studies; (ii) report the results of a new remote sensing study of ash fertilization; and (iii) calculate theoretical bounds of ash-fertilized carbon export. Our synthesis highlights that phytoplankton responses to ash do not always simply mimic that of iron amendment; the exact mechanisms for this are likely biogeochemically important but are not yet well understood. Inherent optical properties of ash-loaded seawater suggest rhyolitic ash biases routine satellite chlorophyll-a estimation upwards by more than an order of magnitude for waters with 0.5 mg chlorophyll-a m-3. For this reason post-ash-deposition chlorophyll-a changes in oligotrophic waters detected via standard Case 1 (open ocean) algorithms should be interpreted with caution. Remote sensing analysis of historic events with a bias less than a factor of 2 provided limited stand-alone evidence for ash-fertilization. Confounding factors were poor coverage, incoherent ash dispersal, and ambiguity ascribing biomass changes to ash supply over other potential drivers. Using current estimates of iron release and carbon export efficiencies, uncertainty bounds of ash-fertilized carbon export for 3 events are presented. Patagonian iron supply to the Southern Ocean from volcanic eruptions is less than that of windblown dust on thousand year timescales but can dominate supply at shorter timescales. Reducing uncertainties in remote sensing of phytoplankton response and nutrient release from ash are avenues for enabling assessment of the oceanic response to large-scale transient nutrient enrichment

Op weg naar Park Essenburg : advies aan Bewonersgroep ProGroen Rotterdam

Bewonersgroep ProGroen in Rotterdam is voor het behoud van een miskende groenstrook van circa twaalf hectare tussen de spoordijk en Essenburgsingel. Ze wil dat het gebied in de deelgemeente Delfshaven het groene en duurzame karakter behoudt en dat het in de toekomst goed bruikbaar is en blijft voor alle mensen uit de buurt en de stad. De Wetenschapswinkel ziet voor ProGroen de opgave weggelegd om aan te tonen dat de strook een waardevol groenelement is in de stad. Het park draagt bij aan de sociale cohesie: het vergroot het aantal ontmoetingsplekken in de wijk, biedt laagdrempelige aanleidingen om contact te leggen en motiveert bewoners te investeren in relaties in de buurt. Daarnaast biedt het park de wijkbewoners nieuwe mogelijkheden om in contact te komen met groen, met natuur. De eerste concrete invulling van het park is PlukTuin Essenburg RFC. Deze PlukTuin, een buurttuin, wordt aangelegd op een voormalige parkeerplaats. Opzet is dat bewoners de PlukTuin zelf aanleggen en onderhoude

Medical Image Imputation from Image Collections

We present an algorithm for creating high resolution anatomically plausible images consistent with acquired clinical brain MRI scans with large inter-slice spacing. Although large data sets of clinical images contain a wealth of information, time constraints during acquisition result in sparse scans that fail to capture much of the anatomy. These characteristics often render computational analysis impractical as many image analysis algorithms tend to fail when applied to such images. Highly specialized algorithms that explicitly handle sparse slice spacing do not generalize well across problem domains. In contrast, we aim to enable application of existing algorithms that were originally developed for high resolution research scans to significantly undersampled scans. We introduce a generative model that captures fine-scale anatomical structure across subjects in clinical image collections and derive an algorithm for filling in the missing data in scans with large inter-slice spacing. Our experimental results demonstrate that the resulting method outperforms state-of-the-art upsampling super-resolution techniques, and promises to facilitate subsequent analysis not previously possible with scans of this quality. Our implementation is freely available at https://github.com/adalca/papago .Comment: Accepted at IEEE Transactions on Medical Imaging (\c{opyright} 2018 IEEE

Plug-and-play priors for model based reconstruction

Abstract-Model-based reconstruction is a powerful framework for solving a variety of inverse problems in imaging. In recent years, enormous progress has been made in the problem of denoising, a special case of an inverse problem where the forward model is an identity operator. Similarly, great progress has been made in improving model-based inversion when the forward model corresponds to complex physical measurements in applications such as X-ray CT, electron-microscopy, MRI, and ultrasound, to name just a few. However, combining state-of-theart denoising algorithms (i.e., prior models) with state-of-the-art inversion methods (i.e., forward models) has been a challenge for many reasons. In this paper, we propose a flexible framework that allows state-of-the-art forward models of imaging systems to be matched with state-of-the-art priors or denoising models. This framework, which we term as Plug-and-Play priors, has the advantage that it dramatically simplifies software integration, and moreover, it allows state-of-the-art denoising methods that have no known formulation as an optimization problem to be used. We demonstrate with some simple examples how Plug-and-Play priors can be used to mix and match a wide variety of existing denoising models with a tomographic forward model, thus greatly expanding the range of possible problem solutions