International Journal of Neural Systems This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Announcement: The 2023 Hojjat Adeli Award for Outstanding Contributions in Neural Systems
Int J Neural Syst. 2023 Oct 13:2382001. doi: 10.1142/S0129065723820014. Online ahead of print.NO ABSTRACTPMID:37830299 | DOI:10.1142/S0129065723820014 (Source: International Journal of Neural Systems)
Source: International Journal of Neural Systems - October 13, 2023 Category: Neurology Source Type: research

Deep Learning-Based Classification of Epileptic Electroencephalography Signals Using a Concentrated Time-Frequency Approach
Int J Neural Syst. 2023 Oct 13:2350064. doi: 10.1142/S0129065723500648. Online ahead of print.ABSTRACTConceFT (concentration of frequency and time) is a new time-frequency (TF) analysis method which combines multitaper technique and synchrosqueezing transform (SST). This combination produces highly concentrated TF representations with approximately perfect time and frequency resolutions. In this paper, it is aimed to show the TF representation performance and robustness of ConceFT by using it for the classification of the epileptic electroencephalography (EEG) signals. Therefore, a signal classification algorithm which use...
Source: International Journal of Neural Systems - October 13, 2023 Category: Neurology Authors: Mosab A A Yousif Mahmut Ozturk Source Type: research

Eye State Detection Using Frequency Features from 1 or 2-Channel EEG
We present both hardware and algorithms for the detection of open and closed eyes. Firstly, we utilize a low-cost hardware device to capture EEG activity from one or two channels. Next, we apply the discrete Fourier transform to analyze the signals in the frequency domain, extracting features from each channel. For classification, we test various well-known techniques, including Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Decision Tree (DT), or Logistic Regression (LR). To evaluate the system, we conduct experiments, acquiring signals associated with open and closed eyes, and compare the performance b...
Source: International Journal of Neural Systems - October 12, 2023 Category: Neurology Authors: Francisco Laport Adriana Dapena Paula M Castro Daniel I Iglesias Francisco J Vazquez-Araujo Source Type: research

Improving the Effectiveness of Eigentrust in Computing the Reputation of Social Agents in Presence of Collusion
Int J Neural Syst. 2023 Oct 7:2350063. doi: 10.1142/S0129065723500636. Online ahead of print.ABSTRACTThe introduction of trust-based approaches in social scenarios modeled as multi-agent systems (MAS) has been recognized as a valid solution to improve the effectiveness of these communities. In fact, they make interactions taking place in social scenarios much fruitful as possible, limiting or even avoiding malicious or fraudulent behaviors, including collusion. This is also the case of multi-layered neural networks (NN), which can face limited, incomplete, misleading, controversial or noisy datasets, produced by untrustwor...
Source: International Journal of Neural Systems - October 8, 2023 Category: Neurology Authors: Mariantonia Cotronei Sofia Giuffr è Attilio Marcian ò Domenico Rosaci Giuseppe M L Sarn è Source Type: research

An Integrated Neurorobotics Model of the Cerebellar-Basal Ganglia Circuitry
Int J Neural Syst. 2023 Oct 4:2350059. doi: 10.1142/S0129065723500594. Online ahead of print.ABSTRACTThis work presents a neurorobotics model of the brain that integrates the cerebellum and the basal ganglia regions to coordinate movements in a humanoid robot. This cerebellar-basal ganglia circuitry is well known for its relevance to the motor control used by most mammals. Other computational models have been designed for similar applications in the robotics field. However, most of them completely ignore the interplay between neurons from the basal ganglia and cerebellum. Recently, neuroscientists indicated that neurons fr...
Source: International Journal of Neural Systems - October 4, 2023 Category: Neurology Authors: Jhielson M Pimentel Renan C Moioli Mariana F P De Araujo Patricia A Vargas Source Type: research

Human Gait Activity Recognition Using Multimodal Sensors
Int J Neural Syst. 2023 Sep 30:2350058. doi: 10.1142/S0129065723500582. Online ahead of print.ABSTRACTHuman activity recognition is an application of machine learning with the aim of identifying activities from the gathered activity raw data acquired by different sensors. In medicine, human gait is commonly analyzed by doctors to detect abnormalities and determine possible treatments for the patient. Monitoring the patient's activity is paramount in evaluating the treatment's evolution. This type of classification is still not enough precise, which may lead to unfavorable reactions and responses. A novel methodology that r...
Source: International Journal of Neural Systems - October 2, 2023 Category: Neurology Authors: Diego Teran-Pineda Karl Thurnhofer-Hemsi Enrique Dom ínguez Source Type: research