AIMC Topic: Attention
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Patch Based Multiple Instance Learning Algorithm for Object Tracking.
Computational intelligence and neuroscience
Feb 22, 2017
To deal with the problems of illumination changes or pose variations and serious partial occlusion, patch based multiple instance learning (P-MIL) algorithm is proposed. The algorithm divides an object into many blocks. Then, the online MIL algorithm...
Effects of the Red Bull energy drink on cognitive function and mood in healthy young volunteers.
Journal of psychopharmacology (Oxford, England)
Dec 14, 2016
The present study compared the cognitive and mood effects of two commercially available products, Red Bull energy drink 250 mL and Red Bull Sugarfree energy drink 250 mL, together with a matching placebo 250 mL. Twenty-four healthy young volunteers t...
Reaction times in visual search can be explained by a simple model of neural synchronization.
Neural networks : the official journal of the International Neural Network Society
Dec 10, 2016
We present an oscillatory neural network model that can account for reaction times in visual search experiments. The model consists of a central oscillator that represents the central executive of the attention system and a number of peripheral oscil...
A neural network model for visual selection and shifting.
Journal of integrative neuroscience
Oct 24, 2016
In this paper, a two-layer network is built to simulate the mechanism of visual selection and shifting based on the mapping dynamic model for instantaneous frequency. Unlike the differential equation model using limit cycle to simulate neuron oscilla...
Do children and adolescent ice hockey players with and without a history of concussion differ in robotic testing of sensory, motor and cognitive function?
Journal of neuroengineering and rehabilitation
Oct 12, 2016
BACKGROUND: KINARM end point robotic testing on a range of tasks evaluating sensory, motor and cognitive function in children/adolescents with no neurologic impairment has been shown to be reliable. The objective of this study was to determine whethe...
Objects Classification by Learning-Based Visual Saliency Model and Convolutional Neural Network.
Computational intelligence and neuroscience
Oct 10, 2016
Humans can easily classify different kinds of objects whereas it is quite difficult for computers. As a hot and difficult problem, objects classification has been receiving extensive interests with broad prospects. Inspired by neuroscience, deep lear...
Artificial consciousness and the consciousness-attention dissociation.
Consciousness and cognition
Sep 19, 2016
Artificial Intelligence is at a turning point, with a substantial increase in projects aiming to implement sophisticated forms of human intelligence in machines. This research attempts to model specific forms of intelligence through brute-force searc...
Believing androids - fMRI activation in the right temporo-parietal junction is modulated by ascribing intentions to non-human agents.
Social neuroscience
Sep 2, 2016
Attributing mind to interaction partners has been shown to increase the social relevance we ascribe to others' actions and to modulate the amount of attention dedicated to them. However, it remains unclear how the relationship between higher-order mi...
Global oscillation regime change by gated inhibition.
Neural networks : the official journal of the International Neural Network Society
Jul 18, 2016
The role of sensory inputs in the modelling of synchrony regimes is exhibited by means of networks of spiking cells where the relative strength of the inhibitory interaction is controlled by the activation of a linear unit working as a gating variabl...
Evaluation of Strategies for Integrated Classification of Visual-Manual and Cognitive Distractions in Driving.
Human factors
May 10, 2016
BACKGROUND: Prior studies have demonstrated unique driver behavior outcomes when visual and cognitive distraction occurs simultaneously as compared to the occurrence of one form of distraction alone. This situation implies additional complexity for t...
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