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Modeling mesoscopic cortical dynamics using a mean-field model of conductance-based networks of adaptive exponential integrate-and-fire neurons.

Journal of computational neuroscience
Voltage-sensitive dye imaging (VSDi) has revealed fundamental properties of neocortical processing at macroscopic scales. Since for each pixel VSDi signals report the average membrane potential over hundreds of neurons, it seems natural to use a mean...

Code-modulated visual evoked potentials using fast stimulus presentation and spatiotemporal beamformer decoding.

Scientific reports
When encoding visual targets using various lagged versions of a pseudorandom binary sequence of luminance changes, the EEG signal recorded over the viewer's occipital pole exhibits so-called code-modulated visual evoked potentials (cVEPs), the phase ...

Deep Manifold Learning Combined With Convolutional Neural Networks for Action Recognition.

IEEE transactions on neural networks and learning systems
Learning deep representations have been applied in action recognition widely. However, there have been a few investigations on how to utilize the structural manifold information among different action videos to enhance the recognition accuracy and ef...

A machine learning approach for automated wide-range frequency tagging analysis in embedded neuromonitoring systems.

Methods (San Diego, Calif.)
EEG is a standard non-invasive technique used in neural disease diagnostics and neurosciences. Frequency-tagging is an increasingly popular experimental paradigm that efficiently tests brain function by measuring EEG responses to periodic stimulation...

Extending the Stabilized Supralinear Network model for binocular image processing.

Neural networks : the official journal of the International Neural Network Society
The visual cortex is both extensive and intricate. Computational models are needed to clarify the relationships between its local mechanisms and high-level functions. The Stabilized Supralinear Network (SSN) model was recently shown to account for ma...

Dynamic neural architecture for social knowledge retrieval.

Proceedings of the National Academy of Sciences of the United States of America
Social behavior is often shaped by the rich storehouse of biographical information that we hold for other people. In our daily life, we rapidly and flexibly retrieve a host of biographical details about individuals in our social network, which often ...

Patch Based Multiple Instance Learning Algorithm for Object Tracking.

Computational intelligence and neuroscience
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...

Face Alignment With Deep Regression.

IEEE transactions on neural networks and learning systems
In this paper, we present a deep regression approach for face alignment. The deep regressor is a neural network that consists of a global layer and multistage local layers. The global layer estimates the initial face shape from the whole image, while...

A robot-based behavioural task to quantify impairments in rapid motor decisions and actions after stroke.

Journal of neuroengineering and rehabilitation
BACKGROUND: Stroke can affect our ability to perform daily activities, although it can be difficult to identify the underlying functional impairment(s). Recent theories highlight the importance of sensory feedback in selecting future motor actions. T...