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Correlations between synapses in pairs of neurons slow down dynamics in randomly connected neural networks.

Physical review. E
Networks of randomly connected neurons are among the most popular models in theoretical neuroscience. The connectivity between neurons in the cortex is however not fully random, the simplest and most prominent deviation from randomness found in exper...

An Adaptive Neural Spike Processor With Embedded Active Learning for Improved Unsupervised Sorting Accuracy.

IEEE transactions on biomedical circuits and systems
There is a need for integrated spike sorting processors in implantable devices with low power consumption that have improved accuracy. Learning the characteristics of the variable input neural signals and adapting the functionality of the sorting pro...

An Extreme Learning Machine-Based Neuromorphic Tactile Sensing System for Texture Recognition.

IEEE transactions on biomedical circuits and systems
Despite significant advances in computational algorithms and development of tactile sensors, artificial tactile sensing is strikingly less efficient and capable than the human tactile perception. Inspired by efficiency of biological systems, we aim t...

Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning.

Journal of neural engineering
OBJECTIVE: Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit h...

SPICODYN: A Toolbox for the Analysis of Neuronal Network Dynamics and Connectivity from Multi-Site Spike Signal Recordings.

Neuroinformatics
We implemented an automated and efficient open-source software for the analysis of multi-site neuronal spike signals. The software package, named SPICODYN, has been developed as a standalone windows GUI application, using C# programming language with...

Competitive Spiking Neural P Systems With Rules on Synapses.

IEEE transactions on nanobioscience
This paper proposes an extension of spiking neural P systems with rules on synapses (SNP-RS systems) working in competitive strategy, called competitive SNP-RS (CSNP-RS systems). In CSNP-RS systems, the spikes are viewed as a kind of competitive reso...

Augmenting intracortical brain-machine interface with neurally driven error detectors.

Journal of neural engineering
OBJECTIVE: Making mistakes is inevitable, but identifying them allows us to correct or adapt our behavior to improve future performance. Current brain-machine interfaces (BMIs) make errors that need to be explicitly corrected by the user, thereby con...

Biological modelling of a computational spiking neural network with neuronal avalanches.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
In recent years, an increasing number of studies have demonstrated that networks in the brain can self-organize into a critical state where dynamics exhibit a mixture of ordered and disordered patterns. This critical branching phenomenon is termed ne...

Improving odorant chemical class prediction with multi-layer perceptrons using temporal odorant spike responses from drosophila melanogaster olfactory receptor neurons.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In this work, we examine the possibility of improving the prediction performance of an olfactory biosensor through the use of temporal spiking data. We present an Artificial Neural Network (ANN), in the form of an optimal hybrid Multi-Layer Perceptro...

A supervised learning rule for classification of spatiotemporal spike patterns.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This study introduces a novel supervised algorithm for spiking neurons that take into consideration synapse delays and axonal delays associated with weights. It can be utilized for both classification and association and uses several biologically inf...