Dataset Information

Parametric Covariability in the Standard Model of the Saccadic Main Sequence.

ABSTRACT: SIGNIFICANCE:Saccades present a direct relationship between the size of the movement (SACSIZE) and its peak velocity (SACPEAK), the main sequence, which is traditionally quantified using the model SACPEAK = Vmax × (1 - e). This study shows that Vmax and SAT are not veridical indicators of saccadic dynamics. PURPOSE:Alterations in saccadic dynamics are used as a diagnostic tool. Are the 95% reference ranges (RRs) of Vmax and SAT correctly quantifying the variability in saccadic dynamics of a population? METHODS:Visually driven horizontal and vertical saccades were acquired from 116 normal subjects using the Neuro Kinetics Inc. Concussion Protocol with a 100-Hz I-Portal NOTC Vestibular System, and the main sequence models were computed. RESULTS:The 95% RRs of Vmax, the asymptotic peak velocity, and SAT, the speed of the exponential rise toward Vmax, were quite large. The finding of a strong correlation between Vmax and SAT suggests that their variability might be, in part, a computational interaction. In fact, the interplay between the two parameters greatly reduced the actual peak velocity variability for saccades less than 15°. This correlation was not strong enough to support the adoption of a one-parameter model, where Vmax is estimated from SAT using the regression parameters. We also evaluated the effects of interpolating the position data to a simulated acquisition rate of 1 kHz. Interpolation had no effect on the population average of Vmax and brought a decrease of the average SAT by roughly 8%. CONCLUSIONS:The 95% RRs of Vmax and SAT, treated as independent entities, are not a veridical representation of the variability in saccadic dynamics inside a population, especially for small saccades. We introduce a novel three-step method to determine if a data set is inside or outside a reference population that takes into account the correlation between Vmax and SAT.

SUBMITTER: Busettini C

PROVIDER: S-EPMC6212342 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Publications

Parametric Covariability in the Standard Model of the Saccadic Main Sequence.

Busettini Claudio C Christy Jennifer Braswell JB

Optometry and vision science : official publication of the American Academy of Optometry 20181101 11

<h4>Significance</h4>Saccades present a direct relationship between the size of the movement (SACSIZE) and its peak velocity (SACPEAK), the main sequence, which is traditionally quantified using the model SACPEAK = Vmax × (1 - e). This study shows that Vmax and SAT are not veridical indicators of saccadic dynamics.<h4>Purpose</h4>Alterations in saccadic dynamics are used as a diagnostic tool. Are the 95% reference ranges (RRs) of Vmax and SAT correctly quantifying the variability in saccadic dyn ...[more]

PMID: 30339645

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Project description:Trans-saccadic memory consists of keeping track of objects' locations and features across saccades; pre-saccadic information is remembered and compared with post-saccadic information. It has been shown to have limited resources and involve attention with respect to the selection of objects and features. In support, a previous study showed that recognition of distinct post-saccadic objects in the visual scene is impaired when pre-saccadic objects are relevant and thus already encoded in memory (Poth, Herwig, Schneider, 2015). Here, we investigated the inverse (i.e. how the memory of pre-saccadic objects is affected by abrupt but irrelevant changes in the post-saccadic visual scene). We also modulated the amount of attention to the relevant pre-saccadic object by having participants either make a saccade to it or elsewhere and observed that pre-saccadic attentional facilitation affected how much post-saccadic changes disrupted trans-saccadic memory of pre-saccadic objects. Participants identified a flashed symbol (d, b, p, or q, among distracters), at one of six placeholders (figures "8") arranged in circle around fixation while planning a saccade to one of them. They reported the identity of the symbol after the saccade. We changed the post-saccadic scene in Experiment one by removing the entire scene, only the placeholder where the pre-saccadic symbol was presented, or all other placeholders except this one. We observed reduced identification performance when only the saccade-target placeholder disappeared after the saccade. In Experiment two, we changed one placeholder location (inward/outward shift or rotation re. saccade vector) after the saccade and observed that identification performance decreased with increased shift/rotation of the saccade-target placeholder. We conclude that pre-saccadic memory is disrupted by abrupt attention-capturing post-saccadic changes of visual scene, particularly when these changes involve the object prioritized by being the goal of a saccade. These findings support the notion that limited trans-saccadic memory resources are disrupted when object correspondence at saccadic goal is broken through removal or location change.

Project description:BackgroundMethods of alignment masking, which refers to the technique of excluding alignment blocks prior to tree reconstructions, have been successful in improving the signal-to-noise ratio in sequence alignments. However, the lack of formally well defined methods to identify randomness in sequence alignments has prevented a routine application of alignment masking. In this study, we compared the effects on tree reconstructions of the most commonly used profiling method (GBLOCKS) which uses a predefined set of rules in combination with alignment masking, with a new profiling approach (ALISCORE) based on Monte Carlo resampling within a sliding window, using different data sets and alignment methods. While the GBLOCKS approach excludes variable sections above a certain threshold which choice is left arbitrary, the ALISCORE algorithm is free of a priori rating of parameter space and therefore more objective.ResultsALISCORE was successfully extended to amino acids using a proportional model and empirical substitution matrices to score randomness in multiple sequence alignments. A complex bootstrap resampling leads to an even distribution of scores of randomly similar sequences to assess randomness of the observed sequence similarity. Testing performance on real data, both masking methods, GBLOCKS and ALISCORE, helped to improve tree resolution. The sliding window approach was less sensitive to different alignments of identical data sets and performed equally well on all data sets. Concurrently, ALISCORE is capable of dealing with different substitution patterns and heterogeneous base composition. ALISCORE and the most relaxed GBLOCKS gap parameter setting performed best on all data sets. Correspondingly, Neighbor-Net analyses showed the most decrease in conflict.ConclusionsAlignment masking improves signal-to-noise ratio in multiple sequence alignments prior to phylogenetic reconstruction. Given the robust performance of alignment profiling, alignment masking should routinely be used to improve tree reconstructions. Parametric methods of alignment profiling can be easily extended to more complex likelihood based models of sequence evolution which opens the possibility of further improvements.

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Dataset Information

Parametric Covariability in the Standard Model of the Saccadic Main Sequence.

Publications

Parametric Covariability in the Standard Model of the Saccadic Main Sequence.

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