24 papers · ranked by Valyu relevance
Ilona M. Bloem, Leah Bakst, Joseph T. McGuire, Sam Ling
Navigating around the world, we must adaptively allocate attention to our surroundings based on anticipated future stimuli and events. This allocation of spatial attention boosts visuocortical representations at attended locations and locally enhances perception. Indeed, spatial attention has often been analogized to a…
Basil Wahn, Peter König
In daily life, humans are bombarded with visual input. Yet, their attentional capacities for processing this input are severely limited. Several studies have investigated factors that influence these attentional limitations and have identified methods to circumvent them. Here, we provide a review of these findings. We…
Michele Burigo, Pia Knoeferle, Leonardo Chelazzi
Spatial terms such as “above”, “in front of”, and “on the left of” are all essential for describing the location of one object relative to another object in everyday communication. Apprehending such spatial relations involves relating linguistic to object representations by means of attention. This requires at least…
Monika Graumann, Lara A. Wallenwein, Radoslaw M. Cichy
Spatial attention helps us to efficiently localize objects in cluttered environments. However, the processing stage at which spatial attention modulates object location representations remains unclear. Here we investigated this question identifying processing stages in time and space in an EEG and fMRI experiment…
Jonathan Morgan, Badr Albanna, James P. Herman
We present a neural network model of visual attention (NNMVA) that integrates biased competition and reinforcement learning to capture key aspects of attentional behavior. The model combines selfattention mechanisms from Vision Transformers (ViTs), Long Short-Term Memory (LSTM) networks for working memory, and an…
Henry J. Alitto, Jeffrey S. Johnson, W. Martin Usrey
Visual responses in the cortex are strongly influenced by shifts in spatial attention. This modulation of visual processing includes changes in firing rate, decreased response variability, and decreased interneuronal correlations; all of which are thought to underlie enhanced perception near the center of attention at…
Kevin K. Rooney, Robert J. Condia, Lester C. Loschky
Neuroscience has well established that human vision divides into the central and peripheral fields of view. Central vision extends from the point of gaze (where we are looking) out to about 5° of visual angle (the width of one’s fist at arm’s length), while peripheral vision is the vast remainder of the visual field.…
Mariagrazia Capizzi, Ana B. Chica, Juan Lupiáñez, Pom Charras
While there is ample evidence for the ability to selectively attend to where in space and when in time a relevant event might occur, it remains poorly understood whether spatial and temporal attention operate independently or interactively to optimize behavior. To elucidate this important issue, we provide a narrative…
Kirsten A. Dalrymple, Jason J. S. Barton, Alan Kingstone
Simultanagnosia is a disorder of visual attention that leaves a patient's world unglued: scenes and objects are perceived in a piecemeal manner. It is generally agreed that simultanagnosia is related to an impairment of attention, but it is unclear whether this impairment is object- or space-based in nature. We first…
Alessandro Grillini, Remco J. Renken, Frans W. Cornelissen
Two prominent strategies that the human visual system uses to reduce incoming information are spatial integration and selective attention. While spatial integration summarizes and combines information over the visual field, selective attention can single it out for scrutiny. The way in which these well-known mechanisms…
Henry J. Alitto, Jeffrey S. Johnson, W. Martin Usrey
Visual responses in the cerebral cortex are strongly influenced by shifts in spatial attention. This modulation of visual processing includes changes in firing rate, decreased response variability, and decreased interneuronal correlations; all of which are thought to underlie enhanced visual perception near the center…
Jie Zhang, Xiaocang Zhu, Shanshan Wang, Hossein Esteky + 3 more
Visual search depends on both the foveal and peripheral visual system, yet the foveal attention mechanisms is still lack of insights. We simultaneously recorded the foveal and peripheral activities in V4, IT and LPFC, while monkeys performed a category-based visual search task. Feature attention enhanced responses of…
Matthew V. Chafee, David A. Crowe
Perhaps the simplest and most complete description of the cerebral cortex is that it is a sensorimotor controller whose primary purpose is to represent stimuli and movements, and adaptively control the mapping between them. However, in order to think, the cerebral cortex has to generate patterns of neuronal activity…
John K. Tsotsos, Iuliia Kotseruba, Amir Rasouli, Markus D. Solbach
It is almost universal to regard attention as the facility that permits an agent, human or machine, to give priority processing resources to relevant stimuli while ignoring the irrelevant. The reality of how this might manifest itself throughout all the forms of perceptual and cognitive processes possessed by humans…
Ralf Engbert, Hans A. Trukenbrod, Simon Barthelmé, Felix A. Wichmann
In humans and in foveated animals visual acuity is highly concentrated at the center of gaze, so that choosing where to look next is an important example of online, rapid decision making. Computational neuroscientists have developed biologically-inspired models of visual attention, termed saliency maps, which…
Dario Zanca, Marco Gori, Stefano Melacci, Alessandra Rufa
Visual attention refers to the human brain's ability to select relevant sensory information for preferential processing, improving performance in visual and cognitive tasks. It proceeds in two phases. One in which visual feature maps are acquired and processed in parallel. Another where the information from these maps…
Amélie Gruel, Jean Martinet
—Visual attention can be defined as the behavioral and cognitive process of selectively focusing on a discrete aspect of sensory cues while disregarding other perceivable information. This biological mechanism, more specifically saliency detection, has long been used in multimedia indexing to drive the analysis only on…
Lapo Faggi, Alessandro Betti, Dario Zanca, Stefano Melacci + 1 more
'Marco Gori'] Fast reactions to changes in the surrounding visual environment require efficient attention mechanisms to reallocate computational resources to most relevant locations in the visual field. While current computational models keep improving their predictive ability thanks to the increasing availability of…
David Berga, Xosé R. Fdez-Vidal, Xavier Otazu, Víctor Leborán + 1 more
'Xosé M. Pardo'] In this study we provide the analysis of eye movement behavior elicited by low-level feature distinctiveness with a dataset of synthetically-generated image patterns. Design of visual stimuli was inspired by the ones used in previous psychophysical experiments, namely in free-viewing and visual…
Authors not listed
Predicting protein-ligand binding affinity from three-dimensional (3D) structural data is a central task in structure-based drug discovery, yet it remains challenging due to limited data availability, structural complexity, and the sparse nature of 3D molecular representations. In this study, we investigate the…
Baiwei Liu, Zampeta-Sofia Alexopoulou, Siyang Kong, Anne Zonneveld + 1 more
A central challenge for working memory is to retain information in a format in which representations remain separated and can be selectively prioritised for behaviour. While it is established that space serves as a foundational “scaffold” for mnemonic individuation, the format and flexibility of spatial scaffolding for…
Kai-Fu Yang, Yong-Jie Li
Visual attention plays a critical role when our visual system executes active visual tasks by interacting with the physical scene. However, how to encode the visual object relationship in the psychological world of our brain deserves to be explored. In the field of computer vision, predicting visual fixations or…
Authors not listed
This research presents a novel approach to obstacle detection during navigation using a combination of Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. The primary objective is to generate accurate image captions that describe the content of images, which is crucial for applications such…
David Buterez, Jon Paul Janet, Steven J. Kiddle, Dino Oglic + 1 more
Atom-centred neural networks represent the state-of-the-art for approximating the quantum chemical properties of molecules, such as internal energies. While the design of machine learning architectures that respect chemical principles has continued to advance, the final atom pooling operation that is necessary to…