Visual orienting in dynamic broadband (1/f) noise sequences

Rasche, Christoph; Gegenfurtner, Karl R.

doi:10.3758/app.72.1.100

Cited by 7 publications

(13 citation statements)

References 38 publications

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“…In addition to this vector average effect, the eye direction was biased towards the black RDK, which could be caused by a salience advantage of dark over bright regions (Komban, Alonso, & Zaidi, 2011;Lu & Sperling, 2012), presumably due to an excess of OFF cells (Ratliff et al, 2010). Consistent with this finding, saccades are also more strongly attracted by dark spots compared to bright spots (Rasche & Gegenfurtner, 2010). In a control condition with only one coherent signal, the eye direction was close to the target motion direction from about 200 ms.…”

Section: Experiments 1: Motion Coherencesupporting

confidence: 68%

Dynamic integration of information about salience and value for smooth pursuit eye movements

2015

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Eye movement behavior can be determined by bottom-up factors like visual salience and by top-down factors like expected value. These different types of signals have to be combined for the control of eye movements. In this study we investigated how smooth pursuit eye movements integrate salience and value information. Observers were asked to track a random-dot kinematogram containing two coherent motion directions. To manipulate salience, the coherence or the density of one of the motion signals was varied. To manipulate value, observers won or lost money in a separate experiment if they were tracking one or the other motion direction. Our results show that pursuit direction was initially determined only by salience. 300-400 ms after target motion onset, pursuit steered towards the rewarded direction and the salience effects disappeared. The time course of this effect depended crucially on the difficulty to segment the two signal directions. These results indicate that salience determines early pursuit responses in the same way as saccades with short latencies. Value information is processed slower and dominates pursuit after several 100 ms.

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Section: Experiments 1: Motion Coherencesupporting

confidence: 68%

Dynamic integration of information about salience and value for smooth pursuit eye movements

2015

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“…Finally, given that our experiment involved conditions of artificially high uncertainty that are uncommon in everyday life, one important issue in their interpretation is to what extent they generalize to more ecological conditions. While our experimental conditions were specifically designed to allow precise measurements of saccadic bias and variability under conditions of varying uncertainty, previous studies have demonstrated that a systematic undershoot bias is present also under more ecological conditions, involving for example free viewing (24), visual search (25, 26), and free scanning of continuously present targets (27). High rates of error-correcting secondary saccades were found also under conditions designed to increase the difficulty of saccadic targeting during the scanning of stationary targets (28).…”

Section: Discussionmentioning

confidence: 99%

Gain control of saccadic eye movements is probabilistic

Lisi

Solomon

Morgan

2019

Proc. Natl. Acad. Sci. U.S.A.

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Saccades are rapid eye movements that orient the visual axis toward objects of interest to allow their processing by the central, high-acuity retina. Our ability to collect visual information efficiently relies on saccadic accuracy, which is limited by a combination of uncertainty in the location of the target and motor noise. It has been observed that saccades have a systematic tendency to fall short of their intended targets, and it has been suggested that this bias originates from a cost function that overly penalizes hypermetric errors. Here, we tested this hypothesis by systematically manipulating the positional uncertainty of saccadic targets. We found that increasing uncertainty produced not only a larger spread of the saccadic endpoints but also more hypometric errors and a systematic bias toward the average of target locations in a given block, revealing that prior knowledge was integrated into saccadic planning. Moreover, by examining how variability and bias covaried across conditions, we estimated the asymmetry of the cost function and found that it was related to individual differences in the additional time needed to program secondary saccades for correcting hypermetric errors, relative to hypometric ones. Taken together, these findings reveal that the saccadic system uses a probabilistic-Bayesian control strategy to compensate for uncertainty in a statistically principled way and to minimize the expected cost of saccadic errors.

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“…Overall, the trend shows a dampening with regard to rare, high-magnitude distracter events that occur at a similar distracter parameter value. This suggests an inherent response mechanism that emerges from the dynamic, complex nature of the brain ( Rasche and Gegenfurter, 2010 ).…”

Section: Discussionmentioning

confidence: 99%

Network Dynamics of Attention During a Naturalistic Behavioral Paradigm

Weber

Alicea

Huskey

et al. 2018

Front. Hum. Neurosci.

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This study investigates the dynamics of attention during continuous, naturalistic interactions in a video game. Specifically, the effect of repeated distraction on a continuous primary task is related to a functional model of network connectivity. We introduce the Non-linear Attentional Saturation Hypothesis (NASH), which predicts that effective connectivity within attentional networks increases non-linearly with decreasing distraction over time, and exhibits dampening at critical parameter values. Functional magnetic resonance imaging (fMRI) data collected using a naturalistic behavioral paradigm coupled with an interactive video game is used to test the hypothesis. As predicted, connectivity in pre-defined regions corresponding to attentional networks increases as distraction decreases. Moreover, the functional relationship between connectivity and distraction is convex, that is, network connectivity somewhat increases as distraction decreases during the continuous primary task, however, connectivity increases considerably as distraction falls below critical levels. This result characterizes the non-linear pattern of connectivity within attentional networks, particularly with respect to their dynamics during behavior. These results are also summarized in the form of a network structure analysis, which underscores the role of various nodes in regulating the global network state. In conclusion, we situate the implications of this research in the context of cognitive complexity and an emerging theory of flow during media exposure.

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Visual orienting in dynamic broadband (1/f) noise sequences

Cited by 7 publications

References 38 publications

Dynamic integration of information about salience and value for smooth pursuit eye movements

Dynamic integration of information about salience and value for smooth pursuit eye movements

Gain control of saccadic eye movements is probabilistic

Network Dynamics of Attention During a Naturalistic Behavioral Paradigm

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