29 research outputs found

    A population study of binocular function.

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    As part of a genome-wide association study (GWAS) of perceptual traits in healthy adults, we measured stereo acuity, the duration of alternative percepts in binocular rivalry and the extent of dichoptic masking in 1060 participants. We present the distributions of the measures, the correlations between measures, and their relationships to other psychophysical traits. We report sex differences, and correlations with age, interpupillary distance, eye dominance, phorias, visual acuity and personality. The GWAS, using data from 988 participants, yielded one genetic association that passed a permutation test for significance: The variant rs1022907 in the gene VTI1A was associated with self-reported ability to see autostereograms. We list a number of other suggestive genetic associations (p<10(-5)).This work was supported by the Gatsby Charitable Foundation (GAT2903). J.B. was supported by a fellowship from Gonville and Caius College.This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.visres.2015.02.01

    Individual differences in human eye movements: An oculomotor signature?

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    Human eye movements are stereotyped and repeatable, but how specific to a normal individual are the quantitative properties of his or her eye movements? We recorded saccades, anti-saccades and smooth-pursuit eye movements in a sample of over 1000 healthy young adults. A randomly selected subsample (10%) of participants were re-tested on a second occasion after a median interval of 18.8 days, allowing us to estimate reliabilities. Each of several derived measures, including latencies, accuracies, velocities, and left-right asymmetries, proved to be very reliable. We give normative means and distributions for each measure and describe the pattern of correlations amongst them. We identify several measures that exhibit significant sex differences. The profile of our oculomotor measures for an individual constitutes a personal oculomotor signature that distinguishes that individual from most other members of the sample of 1000.This research was funded by the Gatsby Charitable Foundation (GAT2903). PTG was supported by the Cambridge Commonwealth and Overseas Trusts and the Overseas Research Students Awards Scheme, and JMB by a Research Fellowship at Gonville and Caius College, Cambridge

    An exploratory factor analysis of visual performance in a large population

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    A factor analysis was performed on 25 visual and auditory performance measures from 1060 participants. The results revealed evidence both for a factor relating to general perceptual performance, and for eight independent factors that relate to particular perceptual skills. In an unrotated PCA, the general factor for perceptual performance accounted for 19.9% of the total variance in the 25 performance measures. Following varimax rotation, 8 consistent factors were identified, which appear to relate to (1) sensitivity to medium and high spatial frequencies, (2) auditory perceptual ability (3) oculomotor speed, (4) oculomotor control, (5) contrast sensitivity at low spatial frequencies, (6) stereo acuity, (7) letter recognition, and (8) flicker sensitivity. The results of a hierarchical cluster analysis were consistent with our rotated factor solution. We also report correlations between the eight performance factors and other (non-performance) measures of perception, demographic and anatomical measures, and questionnaire items probing other psychological variables.This work was supported by the Gatsby Charitable Foundation (GAT2903). J.B. was supported by a fellowship from Gonville and Caius College

    PCA of waveforms and functional PCA: A primer for biomechanics.

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    Principal components analysis (PCA) of waveforms and functional PCA (fPCA) are statistical approaches used to explore patterns of variability in biomechanical curve data, with fPCA being an accepted statistical method grounded within the functional data analysis (FDA) statistical framework. This technical note demonstrates that PCA of waveforms is the most rudimentary form of FDA, and consequently can be rationalised within the FDA framework of statistical processes. Mathematical proofing applied demonstrations of both techniques, and an example of when fPCA may be of greater benefit to control over smoothing of functional principal components is provided using an open access motion sickness dataset. Finally, open access software is provided with this paper as means of priming the biomechanics community for using these methods as a part of future functional data explorations

    Predicting Patterns of Customer Usage, with Niftecash

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    Report is the result of the working during 93rd European Study Group with Industry in Limerick

    Predicting Patterns of Customer Usage, with Niftecash

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    Report is the result of the working during 93rd European Study Group with Industry in Limerick

    Deep Eyedentification: Biometric Identification using Micro-Movements of the Eye

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    We study involuntary micro-movements of the eye for biometric identification. While prior studies extract lower-frequency macro-movements from the output of video-based eye-tracking systems and engineer explicit features of these macro-movements, we develop a deep convolutional architecture that processes the raw eye-tracking signal. Compared to prior work, the network attains a lower error rate by one order of magnitude and is faster by two orders of magnitude: it identifies users accurately within seconds

    The emergence of synaesthesia in a Neuronal Network Model via changes in perceptual sensitivity and plasticity

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    Synaesthesia is an unusual perceptual experience in which an inducer stimulus triggers a percept in a different domain in addition to its own. To explore the conditions under which synaesthesia evolves, we studied a neuronal network model that represents two recurrently connected neural systems. The interactions in the network evolve according to learning rules that optimize sensory sensitivity. We demonstrate several scenarios, such as sensory deprivation or heightened plasticity, under which synaesthesia can evolve even though the inputs to the two systems are statistically independent and the initial cross-talk interactions are zero. Sensory deprivation is the known causal mechanism for acquired synaesthesia and increased plasticity is implicated in developmental synaesthesia. The model unifies different causes of synaesthesia within a single theoretical framework and repositions synaesthesia not as some quirk of aberrant connectivity, but rather as a functional brain state that can emerge as a consequence of optimising sensory information processing
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