AI Medical Compendium Topic:
Models, Neurological

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Surrogate population models for large-scale neural simulations.

Neural computation
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...

Granger causality-based synaptic weights estimation for analyzing neuronal networks.

Journal of computational neuroscience
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 ...

Language-Model Assisted Brain Computer Interface for Typing: A Comparison of Matrix and Rapid Serial Visual Presentation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
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...

Hardware-amenable structural learning for spike-based pattern classification using a simple model of active dendrites.

Neural computation
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 ...

Designing responsive pattern generators: stable heteroclinic channel cycles for modeling and control.

Bioinspiration & biomimetics
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...

Bayes optimal template matching for spike sorting - combining fisher discriminant analysis with optimal filtering.

Journal of computational neuroscience
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...

Delayed mutual information infers patterns of synaptic connectivity in a proprioceptive neural network.

Journal of computational neuroscience
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...

Attention modeled as information in learning multisensory integration.

Neural networks : the official journal of the International Neural Network Society
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...

Developmental time windows for axon growth influence neuronal network topology.

Biological cybernetics
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....

A Digital Liquid State Machine With Biologically Inspired Learning and Its Application to Speech Recognition.

IEEE transactions on neural networks and learning systems
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...