The neural instantiation of a priority map

Bisley, James W.; Mirpour, Koorosh

doi:10.1016/j.copsyc.2019.01.002

Cited by 110 publications

(110 citation statements)

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“…The neural instantiation of a priority map—composed of the representations that guide where and when the eyes move—is focused on a network of regions that include the lateral intraparietal area (area LIP), frontal eye fields (FEFs), and superior colliculus (SC), all of which exhibit prioritized representations of visual space and activity that is crucial for the guidance and control of eye movements . A complementary network of regions that includes the dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC), and supplementary eye field (SEF) is thought to be involved in the cognitive control of saccades, providing additional goal‐directed inputs to the FEF and SC.…”

Section: Models Of Oculomotor Controlmentioning

confidence: 99%

“…Specifically, the authors note that if the purpose of eye movements is to acquire information, then where and when the eyes move can be modeled by understanding the expected benefit in moving the eyes versus remaining in the current location for ongoing and sufficient information extraction. 41 The neural instantiation of a priority mapcomposed of the representations that guide where and when the eyes move-is focused on a network of regions that include the lateral intraparietal area (area LIP), 42,43 frontal eye fields (FEFs), 44 and superior colliculus (SC), 45,46 all of which exhibit prioritized representations of visual space and activity that is crucial for the guidance and control of eye movements. [47][48][49][50] A complementary network of regions that includes the dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC), and supplementary eye field (SEF) is thought to be involved in the cognitive control of saccades, [51][52][53][54] providing additional goal-directed inputs to the FEF and SC.…”

Section: Models Of Oculomotor Controlmentioning

confidence: 99%

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The intersection between the oculomotor and hippocampal memory systems: empirical developments and clinical implications

Ryan

Shen

Liu

2019

Annals of the New York Academy of Sciences

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Decades of cognitive neuroscience research has shown that where we look is intimately connected to what we remember. In this article, we review findings from human and nonhuman animals, using behavioral, neuropsychological, neuroimaging, and computational modeling methods, to show that the oculomotor and hippocampal memory systems interact in a reciprocal manner, on a moment‐to‐moment basis, mediated by a vast structural and functional network. Visual exploration serves to efficiently gather information from the environment for the purpose of creating new memories, updating existing memories, and reconstructing the rich, vivid details from memory. Conversely, memory increases the efficiency of visual exploration. We call for models of oculomotor control to consider the influence of the hippocampal memory system on the cognitive control of eye movements, and for models of hippocampal and broader medial temporal lobe function to consider the influence of the oculomotor system on the development and expression of memory. We describe eye movement–based applications for the detection of neurodegeneration and delivery of therapeutic interventions for mental health disorders for which the hippocampus is implicated and memory dysfunctions are at the forefront.

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Section: Models Of Oculomotor Controlmentioning

confidence: 99%

Section: Models Of Oculomotor Controlmentioning

confidence: 99%

The intersection between the oculomotor and hippocampal memory systems: empirical developments and clinical implications

Ryan

Shen

Liu

2019

Annals of the New York Academy of Sciences

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“…We define a salience map as a 2D accumulation of visuo-spatial information that includes, but is not limited to, bottom-up information from input image features. Since this definition includes the possibility of top-down influence, it could also be accurately referred to as a priority map [17], but we keep the term salience for consistancy with the original model. Like the many salience models suggest, this map provides a source for effective shifts of attention over time.…”

Section: What Is the Salience Problem?mentioning

confidence: 99%

“…A salience map is represented as a two-dimensional array in the SC, where the field size increases with depth [19]. Another proposal for a neural map (for non-human primates) is LIP [20,21] (also reference [17], though they define their priority map as more strongly influenced by top-down attentional factors). This simple priority map may then work with FEF to tag previous locations [22] and SC as the result of the WTA [17].…”

Section: What Is the Salience Problem?mentioning

confidence: 99%

Salience Models: A Computational Cognitive Neuroscience Review

Krasovskaya

MacInnes

2019

Vision

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The seminal model by Laurent Itti and Cristoph Koch demonstrated that we can compute the entire flow of visual processing from input to resulting fixations. Despite many replications and follow-ups, few have matched the impact of the original model-so what made this model so groundbreaking? We have selected five key contributions that distinguish the original salience model by Itti and Koch; namely, its contribution to our theoretical, neural, and computational understanding of visual processing, as well as the spatial and temporal predictions for fixation distributions. During the last 20 years, advances in the field have brought up various techniques and approaches to salience modelling, many of which tried to improve or add to the initial Itti and Koch model. One of the most recent trends has been to adopt the computational power of deep learning neural networks; however, this has also shifted their primary focus to spatial classification. We present a review of recent approaches to modelling salience, starting from direct variations of the Itti and Koch salience model to sophisticated deep-learning architectures, and discuss the models from the point of view of their contribution to computational cognitive neuroscience.Vision 2019, 3, 56 2 of 24 a true sign of its importance in defining this field. We provide a review of the different approaches in modelling visual attention based on their contribution to computational cognitive neuroscience. We limit our review to models that were directly influenced by the Itti and Koch algorithm, and cover examples that model object attention, top-down influence, information theory, dual stream models, and conclude with recent advances in deep learning salience classifiers. We also include other methods of achieving the main goal: modelling image salience and the way it results in shifts of attention. The main questions this review tries to address are what contribution did these models make in our goal to explain human visual attention using computer simulations, and what directions are available for the next generation of models?In this review, we approach the salience problem from a computational cognitive neuroscience perspective, which implies a combination of theoretical and methodological concepts from several domains. Such a perspective suggests that the perfect salience model should be based on a strong theoretical foundation, model the neurobiological processes underlying visual saliency, use explicit computational tools as a means of modelling these processes, and be generative by taking both spatial and temporal predictions of visual salience into account.Studies of human visual salience have led to the creation of hundreds of computationally valid models, however, most of these models do not focus on all of the abovementioned components of salience simultaneously. We understand that with so many parameters to account for, like combining a broad cognitive theoretical scope and a focused precise neural approach, it is almost impossible to avoid trade-offs. Never...

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“…The Exploration-Exploitation Model for scan path generation 81 Our theoretical investigation of exploration and exploitation in saccadic behavior is 82 based on the implementation of a probabilistic generative model. The static viewer 83 independent priority map for saccadic selection [6] is thought to be the combined result 84 of early visual processing or saliency [7] and top-down cognitive control. While various 85 models for the computation of static priority maps exist, we extend the modeling approach to the generation of scan paths for a given static saliency map.…”

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confidence: 99%

A Mathematical Model of Exploration and Exploitation in Natural Scene Viewing

Malem-Shinitski

Opper

Reich

et al. 2020

Preprint

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Understanding the decision process underlying gaze control is an important question in cognitive neuroscience with applications in diverse fields ranging from psychology to computer vision. The decision for choosing an upcoming saccade target can be framed as a dilemma: Should the observer further exploit the information near the current gaze position or continue with exploration of other patches within the given scene? While several models attempt to describe the dynamics of saccade target selection, none of them explicitly addresses the underlying Exploration-Exploitation dilemma. Here we propose and investigate a mathematical model motivated by the Exploration-Exploitation dilemma in scene viewing. The model is derived from a minimal set of assumptions that generates realistic eye movement behavior. We implemented a Bayesian approach for model parameter inference based on the model's likelihood function. In order to simplify the inference, we applied data augmentation methods that allowed the use of conjugate priors and the construction of an efficient Gibbs sampler. This approach turned out to be numerically efficient and permitted fitting interindividual differences in saccade statistics. Thus, the main contribution of our modeling approach is two-fold; first, we propose a new model for saccade generation in scene viewing. Second, we demonstrate the use of novel methods from Bayesian inference in the field of scan path modeling. Author summaryThe Exploration-Exploitation dilemma is general concept that has been investigated in human information processing. We investigate whether the Exploration-Exploitation trade-off is a viable approach to model sequences of fixations generated by a human observer in a free viewing task with natural scenes. Variants of the basic model are used to predict to the experimental data based on Bayesian inference. Results indicate a high predictive power for both aggregated data and individual differences across observers. The combination of a novel model with state-of-the-art Bayesian methods lends support to the Exploration-Exploitation framework in the field of eye-movement research. Introduction 1 The human visual system acquires high-acuity information from a rather small region 2 (the fovea) surrounding the center of gaze [1]. The foveal organization of the visual 3 April 3, 2020 1/17 system has two immediate consequences. First, visual perception of natural scenes 4 depends critically on the control of precise and fast eye movements (saccades) that move 5 regions of interest into the fovea for high-acuity processing. During a typical visual task 6 (e.g., scene viewing or reading), saccades occur at a rate of 3 to 4 per second [2]. Second, 7 the decision process for an upcoming saccade target poses a dilemma: should the 8 observer further exploit the information near the fovea or continue with exploration of 9 other patches within the given scene? The latter problem is critical for scene 10 viewing [3, 4] and relevant to the broader field of cognitive processes in knowledge ...

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The neural instantiation of a priority map

Cited by 110 publications

References 62 publications

The intersection between the oculomotor and hippocampal memory systems: empirical developments and clinical implications

The intersection between the oculomotor and hippocampal memory systems: empirical developments and clinical implications

Salience Models: A Computational Cognitive Neuroscience Review

A Mathematical Model of Exploration and Exploitation in Natural Scene Viewing

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