Because different parts of the brain have rich interconnections, it is not possible to model small parts realistically in isolation. However, it is also impractical to simulate large neural systems in detail. This article outlines a new approach to m...
Journal of computational neuroscience
Mar 13, 2015
Granger causality (GC) analysis has emerged as a powerful analytical method for estimating the causal relationship among various types of neural activity data. However, two problems remain not very clear and further researches are needed: (1) The GC ...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mar 11, 2015
Noninvasive electroencephalography (EEG)-based brain-computer interfaces (BCIs) popularly utilize event-related potential (ERP) for intent detection. Specifically, for EEG-based BCI typing systems, different symbol presentation paradigms have been ut...
This letter presents a spike-based model that employs neurons with functionally distinct dendritic compartments for classifying high-dimensional binary patterns. The synaptic inputs arriving on each dendritic subunit are nonlinearly processed before ...
A striking feature of biological pattern generators is their ability to respond immediately to multisensory perturbations by modulating the dwell time at a particular phase of oscillation, which can vary force output, range of motion, or other charac...
Spike sorting, i.e., the separation of the firing activity of different neurons from extracellular measurements, is a crucial but often error-prone step in the analysis of neuronal responses. Usually, three different problems have to be solved: the d...
Understanding the patterns of interconnections between neurons in complex networks is an enormous challenge using traditional physiological approaches. Here we combine the use of an information theoretic approach with intracellular recording to estab...
Neural networks : the official journal of the International Neural Network Society
Feb 2, 2015
Top-down cognitive processes affect the way bottom-up cross-sensory stimuli are integrated. In this paper, we therefore extend a successful previous neural network model of learning multisensory integration in the superior colliculus (SC) by top-down...
Early brain connectivity development consists of multiple stages: birth of neurons, their migration and the subsequent growth of axons and dendrites. Each stage occurs within a certain period of time depending on types of neurons and cortical layers....
IEEE transactions on neural networks and learning systems
Jan 27, 2015
This paper presents a bioinspired digital liquid-state machine (LSM) for low-power very-large-scale-integration (VLSI)-based machine learning applications. To the best of the authors' knowledge, this is the first work that employs a bioinspired spike...