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.

Hierarchical Bayesian Causality Network to Extract High-Level Semantic Information in Visual Cortex
Int J Neural Syst. 2023 Nov 20:2450002. doi: 10.1142/S0129065724500023. Online ahead of print.ABSTRACTFunctional MRI (fMRI) is a brain signal with high spatial resolution, and visual cognitive processes and semantic information in the brain can be represented and obtained through fMRI. In this paper, we design single-graphic and matched/unmatched double-graphic visual stimulus experiments and collect 12 subjects' fMRI data to explore the brain's visual perception processes. In the double-graphic stimulus experiment, we focus on the high-level semantic information as "matching", and remove tail-to-tail conjunction by design...
Source: International Journal of Neural Systems - December 12, 2023 Category: Neurology Authors: Yongqiang Ma Wen Zhang Ming Du Haodong Jing Nanning Zheng Source Type: research

A Few-Shot Transfer Learning Approach for Motion Intention Decoding from Electroencephalographic Signals
This study suggests the effectiveness of EEG in capturing information related to the motor preparation of complex movements, potentially paving the way for BCI systems based on motion planning decoding. The proposed methodology could be straightforwardly extended to advanced EEG signal processing in other scenarios, such as motor imagery or neural disorder classification.PMID:38073546 | DOI:10.1142/S0129065723500685 (Source: International Journal of Neural Systems)
Source: International Journal of Neural Systems - December 11, 2023 Category: Neurology Authors: Nadia Mammone Cosimo Ieracitano Rossella Spataro Christoph Guger Woosang Cho Francesco Carlo Morabito Source Type: research

Variable Projection Support Vector Machines and Some Applications Using Adaptive Hermite Expansions
Int J Neural Syst. 2023 Dec 11:2450004. doi: 10.1142/S0129065724500047. Online ahead of print.ABSTRACTIn this paper, we develop the so-called variable projection support vector machine (VP-SVM) algorithm that is a generalization of the classical SVM. In fact, the VP block serves as an automatic feature extractor to the SVM, which are trained simultaneously. We consider the primal form of the arising optimization task and investigate the use of nonlinear kernels. We show that by choosing the so-called adaptive Hermite function system as the basis of the orthogonal projections in our classification scheme, several real-world...
Source: International Journal of Neural Systems - December 11, 2023 Category: Neurology Authors: Tam ás Dózsa Federico Deuschle Bram Cornelis P éter Kovács Source Type: research

Unsupervised Neural Manifold Alignment for Stable Decoding of Movement from Cortical Signals
Int J Neural Syst. 2023 Dec 6:2450006. doi: 10.1142/S0129065724500060. Online ahead of print.ABSTRACTThe stable decoding of movement parameters using neural activity is crucial for the success of brain-machine interfaces (BMIs). However, neural activity can be unstable over time, leading to changes in the parameters used for decoding movement, which can hinder accurate movement decoding. To tackle this issue, one approach is to transfer neural activity to a stable, low-dimensional manifold using dimensionality reduction techniques and align manifolds across sessions by maximizing correlations of the manifolds. However, the...
Source: International Journal of Neural Systems - December 8, 2023 Category: Neurology Authors: Mohammadali Ganjali Alireza Mehridehnavi Sajed Rakhshani Abed Khorasani Source Type: research

Bimodal Feature Analysis with Deep Learning for Autism Spectrum Disorder Detection
This study introduces a new Deep Neural Network for identifying ASD in children through gait analysis, using features extracted from frames composing video recordings of their walking patterns. The innovative method presented herein is based on imagery and combines gait analysis and deep learning, offering a noninvasive and objective assessment of neurodevelopmental disorders while delivering high accuracy in ASD detection. Our model proposes a bimodal approach based on the concatenation of two distinct Convolutional Neural Networks processing two feature sets extracted from the same videos. The features obtained from the ...
Source: International Journal of Neural Systems - December 8, 2023 Category: Neurology Authors: Federica Colonnese Francesco Di Luzio Antonello Rosato Massimo Panella Source Type: research

Discriminative Power of Handwriting and Drawing Features in Depression
This study contributes knowledge on the detection of depression through handwriting/drawing features, to identify quantitative and noninvasive indicators of the disorder for implementing algorithms for its automatic detection. For this purpose, an original online approach was adopted to provide a dynamic evaluation of handwriting/drawing performance of healthy participants with no history of any psychiatric disorders ([Formula: see text]), and patients with a clinical diagnosis of depression ([Formula: see text]). Both groups were asked to complete seven tasks requiring either the writing or drawing on a paper while five h...
Source: International Journal of Neural Systems - November 27, 2023 Category: Neurology Authors: Claudia Greco Gennaro Raimo Terry Amorese Marialucia Cuciniello Gavin Mcconvey Gennaro Cordasco Marcos Faundez-Zanuy Alessandro Vinciarelli Zoraida Callejas-Carrion Anna Esposito Source Type: research