Publications by authors named "Gregory Francis"

Several studies suggest that breathing entrains neural oscillations and thereby improves visual detection and memory performance during nasal inhalation. However, the evidence for this association is mixed, with some studies finding no, minor, or opposite effects. Here, we tested whether nasal breathing phase influences memory of repeated images presented in a rapid serial visual presentation (RSVP) task.

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Nitric oxide (NO) is involved in a variety of biological functions including blood vessel dilation and neurotransmitter release. In animals, NO has been demonstrated to affect multiple behavioral outcomes, such as memory performance and arousal, whereas this link is less explored in humans. NO is created in the paranasal sinuses and studies show that humming releases paranasal NO to the nasal tract and that NO can then cross the blood brain barrier.

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A classic finding reported in Beck (1966a) is that observers tend to indicate a more natural texture break between a set of T's and tilted T's than between a set of T's and backward L's. This finding has played a prominent role in discussions about the properties of texture segmentation and in the development of computational theories of texture segmentation. Due to the small sample size of the original study, we replicated the original experiment with a larger sample.

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The black hole illusion (BHI) is a subtype of spatial disorientation that can result in fatal consequences in aviation. Research on the BHI has generally focused on altitude deviation, and few studies have examined the effect across different flight phases. In a simulation-based experiment, 18 participants performed 12 simulated approach and landing tasks in normal and BHI environments.

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In a series of articles, Jacob Beck proposed that a variety of texture segmentation phenomena occurs due to emergent features that arise from "links" between elements with appropriate local properties, such as alignment, orientation, and proximity. His findings and ideas guided theoretical and computational models, and some of his demonstrations became textbook knowledge about visual perception. We build on this work in two ways.

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Emerging evidence indicates that COVID-19 damages the central nervous system and thereby might engender long-term cognitive impairment. Self-reports and some measures of cognitive ability suggest that long COVID can lead to substantial and frightening detriments in cognition. To further explore this issue, we used data from university courses on cognitive psychology where students participated in classic experiments that measure various aspects of cognition.

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Although perceptual grouping has been widely studied, its mechanisms remain poorly understood. We propose a neural model of grouping that, through top-down control of its circuits, implements a grouping strategy involving both a connection strategy (which elements to connect) and a selection strategy (that defines spatiotemporal properties of a selection signal to segment target elements and facilitate identification). We apply the model to a letter discrimination task that investigated relationships among uniform connectedness and the grouping principles of proximity and shape similarity.

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A fundamental characteristic of human visual perception is the ability to group together disparate elements in a scene and treat them as a single unit. The mechanisms by which humans create such groupings remain unknown, but grouping seems to play an important role in a wide variety of visual phenomena, and a good understanding of these mechanisms might provide guidance for how to improve machine vision algorithms. Here, we build on a proposal that some groupings are the result of connections in cortical area V2 that join disparate elements, thereby allowing them to be selected and segmented together.

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Recent insights into problems with common statistical practice in psychology have motivated scientists to consider alternatives to the traditional frequentist approach that compares p-values to a significance criterion. While these alternatives have worthwhile attributes, Francis (Behavior Research Methods, 40, 1524-1538, 2017) showed that many proposed test statistics for the situation of a two-sample t-test are based on precisely the same information in a given data set; and for a given sample size, one can convert from any statistic to the others. Here, we show that the same relationship holds for the equivalent of a one-sample t-test.

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Twenty-five years of research has explored the object-based attention effect using the two-rectangles paradigm and closely related paradigms. While reading this literature, we noticed statistical attributes that are sometimes related to questionable research practices, which can undermine the reported conclusions. To quantify these attributes, we applied the Test for Excess Success (TES) individually to 37 articles that investigate various properties of object-based attention and comprise four or more experiments.

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In crowding, perception of a target deteriorates in the presence of nearby flankers. Traditionally, it is thought that visual crowding obeys Bouma's law, i.e.

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It is common for conclusions of empirical studies to depend on multiple significant outcomes. This practice may seem reasonable, but it has some unintended effects. In particular, the compound Type I error rate for multiple studies (the likelihood of concluding that an effect exists when it does not) can be much lower than that of the individual studies.

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We recently found only weak correlations between the susceptibility to various visual illusions. However, we observed strong correlations among different variants of an illusion, suggesting that the visual space of illusions includes several illusion-specific factors. Here, we specifically examined how factors for the vertical-horizontal, Müller-Lyer, and Ponzo illusions relate to each other.

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Common factors are ubiquitous. For example, there is a common factor, g, for intelligence. In vision, there is much weaker evidence for such common factors.

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Traditionally, human vision research has focused on specific paradigms and proposed models to explain very specific properties of visual perception. However, the complexity and scope of modern psychophysical paradigms undermine the success of this approach. For example, perception of an element strongly deteriorates when neighboring elements are presented in addition (visual crowding).

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Recent studies suggest that the accuracy of perceptual judgments can be influenced by the perceived illusory size of a stimulus, with judgments being more accurate for increased illusory size. This phenomenon seems consistent with recent neuroscientific findings that representations in early visual areas reflect the perceived (illusory) size of stimuli rather than the physical size. We further explored this idea with the moon illusion, in which the moon appears larger when it is close to the horizon and smaller when it is higher in the sky.

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In crowding, perception of an object deteriorates in the presence of nearby elements. Although crowding is a ubiquitous phenomenon, since elements are rarely seen in isolation, to date there exists no consensus on how to model it. Previous experiments showed that the global configuration of the entire stimulus must be taken into account.

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Visual persistence (stimulus perception that prolongs for a few milliseconds after the physical disappearance of the stimulus) and afterimages (an illusory percept that lingers after the physical disappearance of the stimulus at the retinotopic location of the preceding stimulus) are classic perceptual phenomena reflecting temporal characteristics of the visual system. These phenomena are modulated by some common stimulus aspects: A longer stimulus generates shorter persistence and a longer afterimage and a lower spatial-frequency stimulus generates shorter persistence and a stronger afterimage. The current study proposes that these spatiotemporal characteristics of visual persistence and afterimages can be explained by a generic retinal processing architecture.

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Deep learning algorithms achieve human-level (or better) performance on many tasks, but there still remain situations where humans learn better or faster. With regard to classification of images, we argue that some of those situations are because the human visual system represents information in a format that promotes good training and classification. To demonstrate this idea, we show how occluding objects can impair performance of a deep learning system that is trained to classify digits in the MNIST database.

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Investigations of visual crowding, where a target is difficult to identify because of flanking elements, has largely used a theoretical perspective based on local interactions where flanking elements pool with or substitute for properties of the target. This successful theoretical approach has motivated a wide variety of empirical investigations to identify mechanisms that cause crowding, and it has suggested practical applications to mitigate crowding effects. However, this theoretical approach has been unable to account for a parallel set of findings that crowding is influenced by long-range perceptual grouping effects.

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In some circumstances, people interact with a virtual keyboard by triggering a binary switch to guide a moving cursor to target characters or items. Such switch keyboards are commonly used by patients with severely restricted motor capabilities. Typing with such systems enables patients to interact with colleagues, but it is slow and error prone.

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In cognition, audition, and somatosensation, performance strongly correlates between different paradigms, which suggests the existence of common factors. In contrast, visual performance in seemingly very similar tasks, such as visual and bisection acuity, are hardly related, i.e.

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