The nematode Caenorhabditis elegans, with information on neural connectivity, three-dimensional position and cell linage provides a unique system for understanding the development of neural networks. Although C. elegans has been widely studied in the...
neuroConstruct: biophysically detailed neuronal modelling in 3D (⭐ 52)
Cortical neurons include many sub-cellular processes, operating at multiple timescales, which may affect their response to stimulation through non-linear and stochastic interaction with ion channels and ionic concentrations. Since new processes are c...
Repositorio del curso de Redes neuronales, en la Facultad de Ciencias, UNAM. (⭐ 31)
progressive loss of neurons, in the process known as neurodegeneration. Neuronal damage may also ultimately result in their death. Neurodegenerative diseases
1900s, the pioneering neuroscientist Santiago Ramón y Cajal used the term neuronal plasticity to describe nonpathological changes in the structure of adult
Many systems are modulated by unknown slow processes. This hinders analysis in highly non-linear systems, such as excitable systems. We show that for such systems, if the input matches the sparse `spiky' nature of the output, the spiking input-output...
Material de clase y ejercicios acerca de redes neuronales (⭐ 12)
Neuronal sprouting is any process where neurite growth occurs, typically through modifications to synapses where a neuron outgrowths to establish connections
A Python package for simulator-independent specification of neuronal network models. (⭐ 301)
Neuronal Morphology Analysis Tool (⭐ 108)
Points: 140 | Comments: 11 | Author: Tschayba
Python exercises accompanying the book "Neuronal Dynamics" (⭐ 277)
Networks with stochastic variables described by heavy tailed lognormal distribution are ubiquitous in nature, and hence they deserve an exact information-theoretic characterization. We derive analytical formulas for mutual information between element...
Spike sorting algorithms are used to separate extracellular recordings of neuronal populations into single-unit spike activities. The development of customized hardware implementing spike sorting algorithms is burgeoning. However, there is a lack of...
The specific connectivity of a neuronal network is reflected in the dynamics of the signals recorded on its nodes. The analysis of how the activity in one node predicts the behaviour of another gives the directionality in their relationship. However,...
Purpose: The primary aim of this study is to enhance fault diagnosis in induction machines by leveraging the Padé Approximant Neuron (PAON) model. While accelerometers and microphones are standard in motor condition monitoring, deep learning models...
On July 10, 2024, NATO unveiled its revised artificial intelligence (AI) strategy, designed to accelerate the adoption of AI technologies within the Alliance while ensuring their safe and responsible use.
Large Transformer-based Pretrained Language Models (PLMs) dominate almost all Natural Language Processing (NLP) tasks. Nevertheless, they still make mistakes from time to time. For a model deployed in an industrial environment, fixing these mistakes...
By way of explaining how a brain works logically, human associative memory is modeled with logical and memory neurons, corresponding to standard digital circuits. The resulting cognitive architecture incorporates basic psychological elements such a...