Evidence for scanpaths in hemianopic patients shown through string editing methods

Zangemeister, Wolfgang H.; Oechsner, Ulrich

doi:10.1016/s0166-4115(96)80078-1

Cited by 7 publications

(10 citation statements)

References 36 publications

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“…Weakest correlations were found for the new vector string editing methods (VSE, wVSE) combining the sequence of saccades and their spatial vectorial orientation with the advantage of making a priori regionalisation unnecessary. While previous numeric simulations ( Zangemeister & Oechsner, 1996) showed a superiority of the weighted vector string editing (wVSE) for comparison of gaze sequences against the unweighted vector string editing (VSE), we found this method, in comparison to the normal string editing and Markov analysis methods, unable to support our finding of similar imagery scanpaths in both groups. Further studies should clarify in which cases this method is suitable to describe and compare eye movements in human subjects.…”

Section: String Comparison Methodscontrasting

confidence: 94%

“…Most frequently used methods for the comparison of scanpaths (Choi, Mosley, & Stark, 1995;Zangemeister, Oechsner, et al, 1995;Zangemeister & Oechsner, 1996;Hacisalihzade, Stark, & Allen, 1992;Stark & Ellis, 1981;Stark & Choi, 1996) first divide the presented picture into regions (ROIs) and attach unique labels to each region (e.g., letters). We also chose a priori principal interesting features of our visual stimuli to regionalize them into different ROIs.…”

Section: Methods With a Priori Regionalization: Markov Analysis And Smentioning

confidence: 99%

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Visual Imagery in Hemianopic Patients

Gbadamosi¹,

Zangemeister

2001

Journal of Cognitive Neuroscience

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In this article we report some findings about visual imagery in patients with stable homonymous hemianopia compared to healthy control subjects. These findings were obtained by analyzing the gaze control through recording of eye movements in different phases of viewing and imagery. We used six different visual stimuli for the consecutive viewing and imagery phases. With infrared oculography, we recorded eye movements during this presentation phase and in three subsequent imagery phases in absence of the stimulus. Analyzing the basic parameters of the gaze sequences (known as "scanpaths"), we discovered distinct characteristics of the "viewing scanpaths" and the "imagery scanpaths" in both groups, which suggests a reduced extent of the image within the cognitive representation. We applied different similarity measures (string/vector string editing, Markov analysis). We found a "progressive consistency of imagery," shown through raising similarity values for the comparison of the late imagery scanpaths. This result suggests a strong top-down component in picture exploration: In both groups, healthy subjects and hemianopic patients, a mental model of the viewed picture must evolve very soon and substantially determine the eye movements. As our hemianopic patients showed analogous results to the normal subjects, we conclude that these patients are well adjusted to their deficit and, despite their perceptual defect, have a preserved cognitive representation, which follows the same top-down vision strategies in the process of visual imagery.

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Section: String Comparison Methodscontrasting

confidence: 94%

Section: Methods With a Priori Regionalization: Markov Analysis And Smentioning

confidence: 99%

Visual Imagery in Hemianopic Patients

Gbadamosi¹,

Zangemeister

2001

Journal of Cognitive Neuroscience

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“…We found that for short scanning sequences marking the first fixation n-gram uniquely can improve the results. This underlines the importance of the first few fixations in a static context (Zangemeister & Oechsner, 1996). This effect should also be observable in a global alignment of the sequences as a higher degree of conservation.…”

Section: Limitations and Considerationsmentioning

confidence: 59%

“…This method was applied to find differences in visual scanning behavior of hemianopic patients (Zangemeister & Oechsner, 1996). The authors utilized different weights between ROIs and a special weighting of the first fixation.…”

Section: String-based Comparison Of Scanpathsmentioning

confidence: 99%

SubsMatch 2.0: Scanpath comparison and classification based on subsequence frequencies

et al. 2016

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Our eye movements are driven by a continuous trade-off between the need for detailed examination of objects of interest and the necessity to keep an overview of our surrounding. In consequence, behavioral patterns that are characteristic for our actions and their planning are typically manifested in the way we move our eyes to interact with our environment. Identifying such patterns from individual eye movement measurements is however highly challenging. In this work, we tackle the challenge of quantifying the influence of experimental factors on eye movement sequences. We introduce an algorithm for extracting sequence-sensitive features from eye movements and for the classification of eye movements based on the frequencies of small subsequences. Our approach is evaluated against the state-of-the art on a novel and a very rich collection of eye movements data derived from four experimental settings, from static viewing tasks to highly dynamic outdoor settings. Our results show that the proposed method is able to classify eye movement sequences over a variety of experimental designs. The choice of parameters is discussed in detail with special focus on highlighting different aspects of general scanpath shape. Algorithms and evaluation data are available at: www.ti.uni-tuebingen.de/scanpathcomparison.html.

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“…Oculomotor compensation, this is adaptive visual scanning behaviour, can be assessed by recording eye movements (e.g. Zangemeister, Meienberg, Stark, & Hoyt, 1982;Zangemeister & Oechsner, 1996;Zihl, 1995Zihl, , 1999Zihl, , 2000.…”

Section: Introductionmentioning

confidence: 99%

Hemianopic visual field defects elicit hemianopic scanning

et al. 2002

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Previous explanations for the variability in success of compensating for homonymous hemianopia (HH) has been in terms of extent of the brain injury. In using on-line eye movement registrations, we simulated HH in 16 healthy subjects and compared their scanning performance on a dot counting task to their own "normal" condition and to real HH patients' performance. We evidenced clear parallels between simulated and real HH, suggesting that hemianopic scanning behaviour is primarily visually elicited, namely by the visual field defect, and not by the additional brain damage. We further observed age-related processes in compensating for the HH.

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Evidence for scanpaths in hemianopic patients shown through string editing methods

Cited by 7 publications

References 36 publications

Visual Imagery in Hemianopic Patients

Visual Imagery in Hemianopic Patients

SubsMatch 2.0: Scanpath comparison and classification based on subsequence frequencies

Hemianopic visual field defects elicit hemianopic scanning

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