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Emotional learning involves two stages. The first is to acquire reinforcers from stimuli and the second is to associate such reinforcers with emotional responses. Both stages can be found occurring in the amygdala. LeDoux's fear circuit model suggests two routes, a subcortical route and a cortical route, for emotional information entering the amygdala for associative learning. It can be used to explain...
This paper introduces a mathematical model of the spatio-temporal patterns of visually evoked activity observed using Voltage-Sensitive Dye Imaging (VSDI) of the visual cortex. The cortical activity is described using a linear superposition of waves traveling with different speeds. This model improves the quality of the wave detection and still respects the previous approaches, as it integrates several...
Sound is one of the media that brings information to human. However this information also distracted by noises that surround us. How human brain recognizes to the required sound is very much impressive. Vice versa, the human brain can learn to the new sound. Thus, we can just concentrate to the sound that we want to listen only. For instance, when two human communicate each other, to be precise in...
A neural architecture is introduced for how visual cortical areas V1 and V2 implement context-sensitive binding processes as attention modulation and cross-stream interaction. The present architecture based on LAMINART and FACADE theory shows how layered circuits in cortex areas enable feedforward, horizontal, feedback interactions and intractions to complete attention-modulated perceptual grouping...
The cerebral cortex is a brain region that is implicated in complex behaviors. Understanding the dynamics of neurons in areas of the cerebral cortex is, thus, an important goal in neuroscience. Methods for recording the activity of populations of neurons in cortical areas are now becoming available, but there are few analytic methods available to analyze such data. This paper introduces a simple dynamical...
The brain has the powerful capability of remembering key features of images. Based on the principle of spike timing dependent plasticity of spiking neurons and the ON/OFF pathways in the visual system, a spiking neural network is proposed to remember key features of visual images. The simulation results show that the network is capable of remembering key features according to a learning rule based...
This paper proposes a saliency-based attention model based on pulsed cosine transform that simulates the lateral surround inhibition of neurons with similar visual features. The model can be extended to Hebbian-based neural networks. The visual saliency can be represented in binary codes, which agrees with the firing pulse of neurons in human brain. In addition, motion saliency can be directly generated...
Jain et al. showed that a strong motion signal in one modality (visual/auditory) influences the perception of a simultaneously present weak motion signal in the other modality (auditory/visual) for motion along the three cardinal axes. Furthermore, they also observed auditory crossmodal motion aftereffects (MAE) for all directions and visual crossmodal MAE for vertical direction of motion. We developed...
The cellular neural/nonlinear network (CNN) has become a useful tool for image and signal processing, robotic and biological visions, and higher brain functions. visual illusion is defined as any fallacious perception of reality. In 1997, Chua proposed a CNN template named face-vase illusion (FVI) CNN. It can simulate some visual illusions. In this paper, we figure out the local rules of the FVI CNN...
Using functional magnetic resonance imaging, we examined whether distinct activity patterns are elicited by natural and unnatural visual stimuli. Stimuli were black and white pictures portraying various scenes (e.g., cities, country fields); natural pictures were unaltered, while unnatural pictures were produced by reversing their contrast curves (negative images). Low-contrast pictures were used...
In this paper, a first prototype of a multifunctional tactile sensor using ionic polymer metal composites (IPMCs) is proposed, designed, and tested. Two IPMC strips are used, one as an actuator and one as a sensor, both positioned in a cantilever configuration; working together they enable the system to detect the presence of a material in contact with it and to measure its stiffness. These sensing...
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