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Multineuron spike train analysis with R-convolution linear combination kernel.

Neural networks : the official journal of the International Neural Network Society
A spike train kernel provides an effective way of decoding information represented by a spike train. Some spike train kernels have been extended to multineuron spike trains, which are simultaneously recorded spike trains obtained from multiple neuron...

Classifying dynamic transitions in high dimensional neural mass models: A random forest approach.

PLoS computational biology
Neural mass models (NMMs) are increasingly used to uncover the large-scale mechanisms of brain rhythms in health and disease. The dynamics of these models is dependent upon the choice of parameters, and therefore it is crucial to be able to understan...

A robotic multidimensional directed evolution approach applied to fluorescent voltage reporters.

Nature chemical biology
We developed a new way to engineer complex proteins toward multidimensional specifications using a simple, yet scalable, directed evolution strategy. By robotically picking mammalian cells that were identified, under a microscope, as expressing prote...

Biologically Inspired Intensity and Depth Image Edge Extraction.

IEEE transactions on neural networks and learning systems
In recent years, artificial vision research has moved from focusing on the use of only intensity images to include using depth images, or RGB-D combinations due to the recent development of low-cost depth cameras. However, depth images require a lot ...

Neural electrical activity and neural network growth.

Neural networks : the official journal of the International Neural Network Society
The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary...

GXNOR-Net: Training deep neural networks with ternary weights and activations without full-precision memory under a unified discretization framework.

Neural networks : the official journal of the International Neural Network Society
Although deep neural networks (DNNs) are being a revolutionary power to open up the AI era, the notoriously huge hardware overhead has challenged their applications. Recently, several binary and ternary networks, in which the costly multiply-accumula...

O(t)-synchronization and Mittag-Leffler synchronization for the fractional-order memristive neural networks with delays and discontinuous neuron activations.

Neural networks : the official journal of the International Neural Network Society
This paper investigates O(t)-synchronization and adaptive Mittag-Leffler synchronization for the fractional-order memristive neural networks with delays and discontinuous neuron activations. Firstly, based on the framework of Filippov solution and di...

A novel type of activation function in artificial neural networks: Trained activation function.

Neural networks : the official journal of the International Neural Network Society
Determining optimal activation function in artificial neural networks is an important issue because it is directly linked with obtained success rates. But, unfortunately, there is not any way to determine them analytically, optimal activation functio...

The modulation of neural gain facilitates a transition between functional segregation and integration in the brain.

eLife
Cognitive function relies on a dynamic, context-sensitive balance between functional integration and segregation in the brain. Previous work has proposed that this balance is mediated by global fluctuations in neural gain by projections from ascendin...

Unsupervised heart-rate estimation in wearables with Liquid states and a probabilistic readout.

Neural networks : the official journal of the International Neural Network Society
Heart-rate estimation is a fundamental feature of modern wearable devices. In this paper we propose a machine learning technique to estimate heart-rate from electrocardiogram (ECG) data collected using wearable devices. The novelty of our approach li...