Bump competition and lattice solutions in two-dimensional neural fields.

Neural Netw

Department of Cognition, Development and Educational Psychology, Faculty of Psychology, University of Barcelona, Spain; Institut de Neurociències, University of Barcelona, Spain; Catalan Institution for Research and Advanced Studies (ICREA), Spain. Electronic address:

Published: October 2017

Some forms of competition among activity bumps in a two-dimensional neural field are studied. First, threshold dynamics is included and rivalry evolutions are considered. The relations between parameters and dominance durations can match experimental observations about ageing. Next, the threshold dynamics is omitted from the model and we focus on the properties of the steady-state. From noisy inputs, hexagonal grids are formed by a symmetry-breaking process. Particular issues about solution existence and stability conditions are considered. We speculate that they affect the possibility of producing basis grids which may be combined to form feature maps.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.neunet.2017.07.003DOI Listing

Publication Analysis

Top Keywords

two-dimensional neural
8
threshold dynamics
8
bump competition
4
competition lattice
4
lattice solutions
4
solutions two-dimensional
4
neural fields
4
fields forms
4
forms competition
4
competition activity
4

Similar Publications

Editorial: Biointerfacing 2D nanomaterials and engineered heterostructures, volume II.

Front Bioeng Biotechnol

December 2024

Biophotonic Nanosensors Laboratory, Centro de Física Aplicada y TecnologíaAvanzada (CFATA), Universidad Nacional Autónoma de México (UNAM), Querétaro, Mexico.

View Article and Find Full Text PDF

Two-dimensional identification of lower limb gait features based on the variational modal decomposition of sEMG signal and convolutional neural network.

Gait Posture

December 2024

Engineering Research Center of the Ministry of Education for Intelligent Rehabilitation Equipment and Detection Technologies, Hebei University of Technology, Tianjin 300401, PR China; Hebei Key Laboratory of Robot Sensing and Human-robot Interaction, Hebei University of Technology, Tianjin 300401, PR China; School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, PR China. Electronic address:

Background: Gait feature recognition is crucial to improve the efficiency and coordination of exoskeleton assistance. The recognition methods based on surface electromyographic (sEMG) signals are popular. However, the recognition accuracy of these methods is poor due to ignoring the correlation of the time series of sEMG signals.

View Article and Find Full Text PDF

Boron nitride (BN), renowned for its exceptional optoelectrical properties, mechanical robustness, and thermal stability, has emerged as a promising two-dimensional (2D) material. Reinforcing AZ80 magnesium alloy with BN can significantly enhance its mechanical properties. To investigate and predict this enhancement during hot deformation, we introduce two independent modeling approaches a modified Johnson-Cook (J-C) constitutive model and an Artificial Neural Network (ANN).

View Article and Find Full Text PDF

Two-dimensional (2D) materials hold significant potential for the development of neuromorphic computing architectures owing to their exceptional electrical tunability, mechanical flexibility, and compatibility with heterointegration. However, the practical implementation of 2D memristors in neuromorphic computing is often hindered by the challenges of simultaneously achieving low latency and low energy consumption. Here, we demonstrate memristors based on 2D cobalt phosphorus trisulfide (CoPS), which achieve impressive performance metrics including high switching speed (20 ns), low switching energy (1.

View Article and Find Full Text PDF

The two-dimensional (2D) irregular packing problem is a combinatorial optimization problem with NP-complete characteristics, which is common in the production process of clothing, ships, and plate metals. The classic packing solution is a hybrid algorithm based on heuristic positioning and meta-heuristic sequencing, which has the problems of complex solving rules and high time cost. In this study, the similarity measurement method based on the twin neural network model is used to evaluate the similarity of pieces in the source task and the target task.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!