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.

Enhancing Prediction of Forelimb Movement Trajectory through a Calibrating-Feedback Paradigm Incorporating RAT Primary Motor and Agranular Cortical Ensemble Activity in the Goal-Directed Reaching Task
Int J Neural Syst. 2023 Aug 24:2350051. doi: 10.1142/S012906572350051X. Online ahead of print.ABSTRACTComplete reaching movements involve target sensing, motor planning, and arm movement execution, and this process requires the integration and communication of various brain regions. Previously, reaching movements have been decoded successfully from the motor cortex (M1) and applied to prosthetic control. However, most studies attempted to decode neural activities from a single brain region, resulting in reduced decoding accuracy during visually guided reaching motions. To enhance the decoding accuracy of visually guided fo...
Source: International Journal of Neural Systems - August 26, 2023 Category: Neurology Authors: Han-Lin Wang Yun-Ting Kuo Yu-Chun Lo Chao-Hung Kuo Bo-Wei Chen Ching-Fu Wang Zu-Yu Wu Chi-En Lee Shih-Hung Yang Sheng-Huang Lin Po-Chuan Chen You-Yin Chen Source Type: research

A Deep Regression Approach for Human Activity Recognition Under Partial Occlusion
Int J Neural Syst. 2023 Aug 19:2350047. doi: 10.1142/S0129065723500478. Online ahead of print.ABSTRACTIn real-life scenarios, Human Activity Recognition (HAR) from video data is prone to occlusion of one or more body parts of the human subjects involved. Although it is common sense that the recognition of the majority of activities strongly depends on the motion of some body parts, which when occluded compromise the performance of recognition approaches, this problem is often underestimated in contemporary research works. Currently, training and evaluation is based on datasets that have been shot under laboratory (ideal) c...
Source: International Journal of Neural Systems - August 21, 2023 Category: Neurology Authors: Ioannis Vernikos Evaggelos Spyrou Ioannis-Aris Kostis Eirini Mathe Phivos Mylonas Source Type: research

Evaluation of Spiking Neural Nets-Based Image Classification Using the Runtime Simulator RAVSim
Int J Neural Syst. 2023 Aug 17:2350044. doi: 10.1142/S0129065723500442. Online ahead of print.ABSTRACTSpiking Neural Networks (SNNs) help achieve brain-like efficiency and functionality by building neurons and synapses that mimic the human brain's transmission of electrical signals. However, optimal SNN implementation requires a precise balance of parametric values. To design such ubiquitous neural networks, a graphical tool for visualizing, analyzing, and explaining the internal behavior of spikes is crucial. Although some popular SNN simulators are available, these tools do not allow users to interact with the neural net...
Source: International Journal of Neural Systems - August 21, 2023 Category: Neurology Authors: None Sanaullah Shamini Koravuna Ulrich R ückert Thorsten Jungeblut Source Type: research

Few-Shot Pixel-Precise Document Layout Segmentation via Dynamic Instance Generation and Local Thresholding
Int J Neural Syst. 2023 Aug 10:2350052. doi: 10.1142/S0129065723500521. Online ahead of print.ABSTRACTOver the years, the humanities community has increasingly requested the creation of artificial intelligence frameworks to help the study of cultural heritage. Document Layout segmentation, which aims at identifying the different structural components of a document page, is a particularly interesting task connected to this trend, specifically when it comes to handwritten texts. While there are many effective approaches to this problem, they all rely on large amounts of data for the training of the underlying models, which i...
Source: International Journal of Neural Systems - August 11, 2023 Category: Neurology Authors: Axel De Nardin Silvia Zottin Claudio Piciarelli Emanuela Colombi Gian Luca Foresti Source Type: research

Decoupled Edge Guidance Network for Automatic Checkout
Int J Neural Syst. 2023 Aug 10:2350049. doi: 10.1142/S0129065723500491. Online ahead of print.ABSTRACTAutomatic checkout (ACO) aims at correctly generating complete shopping lists from checkout images. However, the domain gap between the single product in training data and multiple products in checkout images endows ACO tasks with a major difficulty. Despite remarkable advancements in recent years, resolving the significant domain gap remains challenging. It is possibly because networks trained solely on synthesized images may struggle to generalize well to realistic checkout scenarios. To this end, we propose a decoupled ...
Source: International Journal of Neural Systems - August 11, 2023 Category: Neurology Authors: Rongbiao You Fuxiong He Weiming Lin Source Type: research

Localization of Epileptic Brain Responses to Single-Pulse Electrical Stimulation by Developing an Adaptive Iterative Linearly Constrained Minimum Variance Beamformer
Int J Neural Syst. 2023 Aug 9:2350050. doi: 10.1142/S0129065723500508. Online ahead of print.ABSTRACTDelayed responses (DRs) to single pulse electrical stimulation (SPES) in patients with severe refractory epilepsy, from their intracranial recordings, can help to identify regions associated with epileptogenicity. Automatic DR localization is a large step in speeding up the identification of epileptogenic focus. Here, for the first time, an adaptive iterative linearly constrained minimum variance beamformer (AI-LCMV) is developed and employed to localize the DR sources from intracranial electroencephalogram (EEG) recorded u...
Source: International Journal of Neural Systems - August 11, 2023 Category: Neurology Authors: Sepehr Shirani Antonio Valentin Bahman Abdi-Sargezeh Gonzalo Alarcon Saeid Sanei Source Type: research