Modeling visual attention-particularly stimulus-driven, saliency-based attention-has been a very active research area over the past 25 years. Many different models of attention are now available which, aside from lending theoretical contributions to other fields, have demonstrated successful applications in computer vision, mobile robotics, and cognitive systems. Here we review, from a computational perspective, the basic concepts of attention implemented in these models. We present a taxonomy of nearly 65 models, which provides a critical comparison of approaches, their capabilities, and shortcomings. In particular, 13 criteria derived from behavioral and computational studies are formulated for qualitative comparison of attention models. Furthermore, we address several challenging issues with models, including biological plausibility of the computations, correlation with eye movement datasets, bottom-up and top-down dissociation, and constructing meaningful performance measures. Finally, we highlight current research trends in attention modeling and provide insights for future.

State-of-the-Art in Visual Attention Modeling

Simple cells in the striate cortex have been depicted as half-wave-rectified linear operators. Complex cells have been depicted as energy mechanisms, constructed from the squared sum of the outputs of quadrature pairs of linear operators. However, the linear/energy model falls short of a complete explanation of striate cell responses. In this paper, a modified version of the linear/energy model is presented in which striate cells mutually inhibit one another, effectively normalizing their responses with respect to stimulus contrast. This paper reviews experimental measurements of striate cell responses, and shows that the new model explains a significantly larger body of physiological data.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0952523800009640

Normalization of cell responses in cat striate cortex

The human brain has some capabilities that the brains of other animals lack. It is to these distinctive capabilities that our species owes its dominant position. Other animals have stronger muscles or sharper claws, but we have cleverer brains. If machine brains one day come to surpass human brains in general intelligence, then this new superintelligence could become very powerful. As the fate of the gorillas now depends more on us humans than on the gorillas themselves, so the fate of our species then would come to depend on the actions of the machine superintelligence. But we have one advantage: we get to make the first move. Will it be possible to construct a seed AI or otherwise to engineer initial conditions so as to make an intelligence explosion survivable? How could one achieve a controlled detonation? To get closer to an answer to this question, we must make our way through a fascinating landscape of topics and considerations. Read the book and learn about oracles, genies, singletons; about boxing methods, tripwires, and mind crime; about humanity's cosmic endowment and differential technological development; indirect normativity, instrumental convergence, whole brain emulation and technology couplings; Malthusian economics and dystopian evolution; artificial intelligence, and biological cognitive enhancement, and collective intelligence. This profoundly ambitious and original book picks its way carefully through a vast tract of forbiddingly difficult intellectual terrain. Yet the writing is so lucid that it somehow makes it all seem easy. After an utterly engrossing journey that takes us to the frontiers of thinking about the human condition and the future of intelligent life, we find in Nick Bostrom's work nothing less than a reconceptualization of the essential task of our time.

Superintelligence: Paths, Dangers, Strategies

The primate visual system contains dozens of distinct areas in the cerebral cortex and several major subcortical structures. These subdivisions are extensively interconnected in a distributed hierarchical network that contains several intertwined processing streams. A number of strategies are used for efficient information processing within this hierarchy. These include linear and nonlinear filtering, passage through information bottlenecks, and coordinated use of multiple types of information. In addition, dynamic regulation of information flow within and between visual areas may provide the computational flexibility needed for the visual system to perform a broad spectrum of tasks accurately and at high resolution.

https://science.sciencemag.org/content/sci/255/5043/419.full.pdf

Information Processing in the Primate Visual System: An Integrated Systems Perspective

The small visual area known as MT or V5 has played a major role in our understanding of the primate cerebral cortex. This area has been historically important in the concept of cortical processing streams and the idea that different visual areas constitute highly specialized representations of visual information. MT has also proven to be a fertile culture dish--full of direction- and disparity-selective neurons--exploited by many labs to study the neural circuits underlying computations of motion and depth and to examine the relationship between neural activity and perception. Here we attempt a synthetic overview of the rich literature on MT with the goal of answering the question, What does MT do?

/pdf/structure-and-function-of-visual-area-mt-5cgljbd95o.pdf

Structure and Function of Visual Area MT

How Much the Eye Tells the Brain

Contribution of linear spatiotemporal receptive field structure to velocity selectivity of simple cells in area 17 of cat.

http://retina.anatomy.upenn.edu/pdfiles/6566.pdf

Efficiency of Information Transmission by Retinal Ganglion Cells

The production of vocalizations is intimately linked to the respiratory system. Despite our understanding of neural circuits that generate normal respiratory patterns, very little is understood regarding how these pontomedullary circuits become engaged during vocal production. Songbirds offer a potentially powerful model system for addressing this relationship. Songs dramatically alter the respiratory pattern in ways that are often highly predictable, and songbirds have a specialized telencephalic vocal motor circuit that provides massive innervation to a brainstem respiratory network that shares many similarities with its mammalian counterpart. In this review, we highlight interactions between the song motor circuit and the respiratory system, describing how both systems are likely to interact to produce the complex respiratory patterns that are observed during vocalization. We also discuss how the respiratory system, through its bilateral bottom-up projections to thalamus, might play a key role in sending precisely timed signals that synchronize premotor activity in both hemispheres.

https://physoc.onlinelibrary.wiley.com/doi/pdf/10.1113/expphysiol.2011.058669

Breathing and vocal control: the respiratory system as both a driver and a target of telencephalic vocal motor circuits in songbirds.

/pdf/report-how-much-the-eye-tells-the-brain-4hl73y3lmm.pdf

Report How Much the Eye Tells the Brain

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