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๐Ÿ” program development ๐Ÿ“‚ Neuroscience
Showing 809 results for "program development" in Neuroscience
Neuroscience Preprint PDF DOI

Personalized Transcranial Electrical Stimulation: A Review of Computational Modeling and Optimization

Mo Wang, Kexin Zheng, Yingyue Xin, Xiang Chen, Yiling Liu, Huichun Luo, Jingsheng Tang, Tifei Yuan, Hongkai Wen, Pengfei Wei, Quanying Liu ยท 2025

Objective. Personalized transcranial electrical stimulation (tES) has gained growing attention due to the substantial inter-individual variability in brain anatomy and physiology. While previous revieโ€ฆ

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Neuroscience Preprint PDF DOI

Sleep Disorder Diagnosis Using EEG Signals and LSTM Deep Learning Method

Mohammad Reza Yousefi, Reza Rahimi ยท 2025

Diagnosing sleep disorders is an important focus in neuroscience and engineering, as these conditions involve issues such as insufficient sleep, frequent awakenings, and difficulty reaching deep sleepโ€ฆ

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Neuroscience Preprint PDF DOI

Technical Development of Two-Photon Optogenetic Stimulation and Its Potential Application to Brain-Machine Interfaces

Riichiro Hira, Yoshikazu Isomura ยท 2025

Over the past decade, techniques enabling bidirectional modulation of neuronal activity with single cell precision have rapidly advanced in the form of two-photon optogenetic stimulation. Unlike conveโ€ฆ

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Neuroscience Preprint PDF DOI

Alljoined-1.6M: A Million-Trial EEG-Image Dataset for Evaluating Affordable Brain-Computer Interfaces

Jonathan Xu, Ugo Bruzadin Nunes, Wangshu Jiang, Samuel Ryther, Jordan Pringle, Paul S. Scotti, Arnaud Delorme, Reese Kneeland ยท 2025

We present a new large-scale electroencephalography (EEG) dataset as part of the THINGS initiative, comprising over 1.6 million visual stimulus trials collected from 20 participants, and totaling moreโ€ฆ

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Neuroscience Preprint PDF DOI

DLGE: Dual Local-Global Encoding for Generalizable Cross-BCI-Paradigm

Jingyuan Wang, Junhua Li ยท 2025

Deep learning models have been frequently used to decode a single brain-computer interface (BCI) paradigm based on electroencephalography (EEG). It is challenging to decode multiple BCI paradigms usinโ€ฆ

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Neuroscience Preprint PDF DOI

Predicting Brain Morphogenesis via Physics-Transfer Learning

Yingjie Zhao, Yicheng Song, Fan Xu, Zhiping Xu ยท 2025

Brain morphology is shaped by genetic and mechanical factors and is linked to biological development and diseases. Its fractal-like features, regional anisotropy, and complex curvature distributions hโ€ฆ

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Neuroscience Preprint PDF DOI

The Prompting Brain: Neurocognitive Markers of Expertise in Guiding Large Language Models

Hend Al-Khalifa, Raneem Almansour, Layan Abdulrahman Alhuasini, Alanood Alsaleh, Mohamad-Hani Temsah, Mohamad-Hani_Temsah, Ashwag Rafea S Alruwaili ยท 2025

Prompt engineering has rapidly emerged as a critical skill for effective interaction with large language models (LLMs). However, the cognitive and neural underpinnings of this expertise remain largelyโ€ฆ

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Neuroscience Preprint PDF DOI

Benchmarking spike source localization algorithms in high density probes

Hao Zhao, Xinhe Zhang, Arnau Marin-Llobet, Xinyi Lin, Jia Liu ยท 2025

Estimating neuron location from extracellular recordings is essential for developing advanced brain-machine interfaces. Accurate neuron localization improves spike sorting, which involves detecting acโ€ฆ

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Synchronization and semantization in deep spiking networks

Jonas Oberste-Frielinghaus, Anno C. Kurth, Julian Goltz, Laura Kriener, Junji Ito, Mihai A. Petrovici, Sonja Grun ยท 2025

Recent studies have shown how spiking networks can learn complex functionality through error-correcting plasticity, but the resulting structures and dynamics remain poorly studied. To elucidate how thโ€ฆ

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Neuroscience Preprint PDF DOI

Perceptual Reality Transformer: Neural Architectures for Simulating Neurological Perception Conditions

Baihan Lin ยท 2025

Neurological conditions affecting visual perception create profound experiential divides between affected individuals and their caregivers, families, and medical professionals. We present the Perceptuโ€ฆ

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Neuroscience Preprint PDF DOI

Activity Coefficient-based Channel Selection for Electroencephalogram: A Task-Independent Approach

Kartik Pandey, Arun Balasubramanian, Debasis Samanta ยท 2025

Electroencephalogram (EEG) signals have gained widespread adoption in brain-computer interface (BCI) applications due to their non-invasive, low-cost, and relatively simple acquisition process. The deโ€ฆ

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Neuroscience Preprint PDF DOI

A large-scale complexity-graded dataset of neuronal images and annotations

Wu Chen, Mingwei Liao, Xueyan Jia, Xiaowei Chen, Chi Xiao, Qingming Luo, Hui Gong, Anan Li ยท 2025

Accurate reconstruction of neuronal morphology is essential for classifying cell types and understanding brain connectivity. Recent advances in imaging and reconstruction techniques have greatly expanโ€ฆ

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Neuroscience Preprint PDF DOI

Patterns of imbalance states between sub-brain regimes during development in the resting state

Fahimeh Ahmadi, Zahra Moradimanesh, Reza Khosrowabadi, G.Reza Jafari ยท 2025

The functional brain network emerges from the complex, coordinated activity of distinct yet connected regions, which underlie the diverse repertoire of human cognitive functions. Structural Balance Thโ€ฆ

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On the utility of toy models for theories of consciousness

Larissa Albantakis ยท 2025

Toy models are highly idealized and deliberately simplified models that retain only the essential features of a system in order to explore specific theoretical questions. Long used in physics and otheโ€ฆ

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Neuroscience Preprint PDF DOI

Alpha-Z divergence unveils further distinct phenotypic traits of human brain connectivity fingerprint

Md Kaosar Uddin, Nghi Nguyen, Huajun Huang, Duy Duong-Tran, Jingyi Zheng ยท 2025

The accurate identification of individuals from functional connectomes (FCs) is critical for advancing individualized assessments in neuropsychiatric research. Traditional methods, such as Pearson's cโ€ฆ

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Neuroscience Preprint PDF DOI

Comparing and Scaling fMRI Features for Brain-Behavior Prediction

Mikkel Schottner Sieler, Thomas A.W. Bolton, Jagruti Patel, Patric Hagmann ยท 2025

Predicting behavioral variables from neuroimaging modalities such as magnetic resonance imaging (MRI) has the potential to allow the development of neuroimaging biomarkers of mental and neurological dโ€ฆ

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Mixed genetic background better recapitulates developmental and psychiatric phenotypes and heterogeneity than inbred C57BL/6J mice

Ana Dudas (PRC), Ana Novak (CBM), Caroline Gora (PRC), Emmanuel Pecnard (PRC), Nicolas Azzopardi (PRC), Severine Morisset-Lopez (CBM), Lucie P. Pellissier (PRC) ยท 2025

Preclinical models of neurodevelopmental and psychiatric conditions often rely on inbred mouse strains like C57BL/6J (B6), which exhibit limited genetic and behavioral variability. This limitation hamโ€ฆ

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Neuroscience Preprint PDF DOI

Gender Similarities Dominate Mathematical Cognition at the Neural Level: A Japanese fMRI Study Using Advanced Wavelet Analysis and Generative AI

Tatsuru Kikuchi ยท 2025

Recent large scale behavioral studies suggest early emergence of gender differences in mathematical performance within months of school entry. However, these findings lack direct neural evidence and aโ€ฆ

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Emergence of Functionally Differentiated Structures via Mutual Information Minimization in Recurrent Neural Networks

Yuki Tomoda, Ichiro Tsuda, Yutaka Yamaguti ยท 2025

Functional differentiation in the brain emerges as distinct regions specialize and is key to understanding brain function as a complex system. Previous research has modeled this process using artificiโ€ฆ

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Neuroscience Preprint PDF DOI

EEG-fused Digital Twin Brain for Autonomous Driving in Virtual Scenarios

Yubo Hou, Zhengxin Zhang, Ziyi Wang, Wenlian Lu, Jianfeng Feng, Taiping Zeng ยท 2025

Current methodologies typically integrate biophysical brain models with functional magnetic resonance imaging(fMRI) data - while offering millimeter-scale spatial resolution (0.5-2 mm^3 voxels), theseโ€ฆ

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