46,915 research outputs found
The evolution and development of visual perspective taking
I outline three conceptions of seeing that a creature might possess: ‘the headlamp conception,’ which involves an understanding of the causal connections between gazing at an object, certain mental states, and behavior; ‘the stage lights conception,’ which involves an understanding of the selective nature of visual attention; and seeing-as. I argue that infants and various nonhumans possess the headlamp conception. There is also evidence that chimpanzees and 3-year-old children have some grasp of seeing-as. However, due to a dearth of studies, there is no evidence that infants or nonhumans possess the stage lights conception of seeing. I outline the kinds of experiments that are needed, and what we stand to learn about the evolution and development of perspective taking
Self-Selective Correlation Ship Tracking Method for Smart Ocean System
In recent years, with the development of the marine industry, navigation
environment becomes more complicated. Some artificial intelligence
technologies, such as computer vision, can recognize, track and count the
sailing ships to ensure the maritime security and facilitates the management
for Smart Ocean System. Aiming at the scaling problem and boundary effect
problem of traditional correlation filtering methods, we propose a
self-selective correlation filtering method based on box regression (BRCF). The
proposed method mainly include: 1) A self-selective model with negative samples
mining method which effectively reduces the boundary effect in strengthening
the classification ability of classifier at the same time; 2) A bounding box
regression method combined with a key points matching method for the scale
prediction, leading to a fast and efficient calculation. The experimental
results show that the proposed method can effectively deal with the problem of
ship size changes and background interference. The success rates and precisions
were higher than Discriminative Scale Space Tracking (DSST) by over 8
percentage points on the marine traffic dataset of our laboratory. In terms of
processing speed, the proposed method is higher than DSST by nearly 22 Frames
Per Second (FPS)
The role of attention in motion extrapolation: Are moving objects 'corrected' or flashed objects attentionally delayed?
No description supplie
Visual attention deficits in schizophrenia can arise from inhibitory dysfunction in thalamus or cortex
Schizophrenia is associated with diverse cognitive deficits, including disorders of attention-related oculomotor behavior. At the structural level, schizophrenia is associated with abnormal inhibitory control in the circuit linking cortex and thalamus. We developed a spiking neural network model that demonstrates how dysfunctional inhibition can degrade attentive gaze control. Our model revealed that perturbations of two functionally distinct classes of cortical inhibitory neurons, or of the inhibitory thalamic reticular nucleus, disrupted processing vital for sustained attention to a stimulus, leading to distractibility. Because perturbation at each circuit node led to comparable but qualitatively distinct disruptions in attentive tracking or fixation, our findings support the search for new eye movement metrics that may index distinct underlying neural defects. Moreover, because the cortico-thalamic circuit is a common motif across sensory, association, and motor systems, the model and extensions can be broadly applied to study normal function and the neural bases of other cognitive deficits in schizophrenia.R01 MH057414 - NIMH NIH HHS; R01 MH101209 - NIMH NIH HHS; R01 NS024760 - NINDS NIH HHSPublished versio
Building on a Solid Baseline: Anticipatory Biases in Attention.
A brain-imaging paper by Kastner and colleagues in 1999 was the first to demonstrate that merely focusing attention at a spatial location changed the baseline activity level in various regions of human visual cortex even before any stimuli appeared. The study provided a touchstone for investigating cognitive-sensory interactions and understanding the proactive endogenous signals that shape perception
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