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Photic Stimulation

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Convolutional neural network models applied to neuronal responses in macaque V1 reveal limited nonlinear processing.

Journal of vision
Computational models of the primary visual cortex (V1) have suggested that V1 neurons behave like Gabor filters followed by simple nonlinearities. However, recent work employing convolutional neural network (CNN) models has suggested that V1 relies o...

Single-pixel imaging for edge images using deep neural networks.

Applied optics
Edge images are often used in computer vision, cellular morphology, and surveillance cameras, and are sufficient to identify the type of object. Single-pixel imaging (SPI) is a promising technique for wide-wavelength, low-light-level measurements. Co...

How multisensory neurons solve causal inference.

Proceedings of the National Academy of Sciences of the United States of America
Sitting in a static railway carriage can produce illusory self-motion if the train on an adjoining track moves off. While our visual system registers motion, vestibular signals indicate that we are stationary. The brain is faced with a difficult chal...

Exploring and explaining properties of motion processing in biological brains using a neural network.

Journal of vision
Visual motion perception underpins behaviors ranging from navigation to depth perception and grasping. Our limited access to biological systems constrains our understanding of how motion is processed within the brain. Here we explore properties of mo...

Person Reidentification via Structural Deep Metric Learning.

IEEE transactions on neural networks and learning systems
Despite the promising progress made in recent years, person reidentification (re-ID) remains a challenging task due to the complex variations in human appearances from different camera views. This paper proposes to tackle this task by jointly learnin...

A Convolutional Neural Network for Enhancing the Detection of SSVEP in the Presence of Competing Stimuli.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Stimulus proximity has been shown to have an influence on the classification performance of a steady-state visual evoked potential based brain-computer interface (SSVEP-BCI). Multiple visual stimuli placed close to each other compete for neural repre...

Extremely Reduced Data Sets Indicate Optimal Stimulation Parameters for Classification in Brain-Computer Interfaces.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The time between the onset of subsequent auditory or visual stimuli - also known as stimulus onset asynchrony (SOA) - determines many of the event-related potential characteristics of the resulting evoked brain signals. Specifically, the SOA value in...

Characterization of SSMVEP-based EEG signals using multiplex limited penetrable horizontal visibility graph.

Chaos (Woodbury, N.Y.)
The steady state motion visual evoked potential (SSMVEP)-based brain computer interface (BCI), which incorporates the motion perception capabilities of the human visual system to alleviate the negative effects caused by strong visual stimulation from...