Computational predictive processing models of consciousness: a systematic review of non-invasive brain signal analysis in disorders of consciousness [0.03%]
意识的计算预测处理模型：昏迷障碍中非侵入式脑信号分析系统的回顾
Sophie Adama,Martin Bogdan
Sophie Adama
Introduction: The clinical assessment of patients with Disorders of Consciousness (DoC), ranging from the Vegetative State (VS/UWS) to the Minimally Conscious State (MCS), remains a significant challenge in neurology. Gol...
Feature fusion and WOA-GWO optimization for Alzheimer's disease detection with sparse EEG channels [0.03%]
基于稀疏EEG通道的阿尔茨海默病检测中的特征融合与WOA-GWO优化方法研究
Ruofan Wang,Jitong Wang,Jiaxuan Cai et al.
Ruofan Wang et al.
Alzheimer's Disease (AD) is a neurodegenerative disorder with insidious onset, making early diagnosis challenging. Electroencephalogram (EEG) is a promising noninvasive tool for AD diagnosis, but high-density EEG configurations cause comput...
Contralateral dominance emerges from geometric transformation in bilateral control systems [0.03%]
双边控制系统的几何变换产生对侧优势现象
Nobuchika Yamaki,Tenna Churiki
Nobuchika Yamaki
Introduction: Contralateral organization is a defining feature of vertebrate nervous systems, yet its functional origin remains incompletely understood. We examined whether contralateral routing can arise as an advantageo...
A novel image-based neuronal network model framework for understanding visual multistability and neurological disorders [0.03%]
一种新的基于图像的神经网络模型框架，用于理解视觉多稳定性及神经系统疾病
Kaito N Hikino,Marina Nakayama,Yihui Wu et al.
Kaito N Hikino et al.
While perceptual multistability arises from many types of stimuli across different sensory systems, there are common dynamical features that may be rooted in universal organizing principles underlying perception. We probe the fundamental me...
Bridging modalities: a deep learning framework for brain tumor classification via CT-MRI integration and model fusion [0.03%]
基于CT和MRI融合的深度学习脑肿瘤分类框架
Ahmad Almadhor,Shtwai Alsubai,Najib Ben Aoun et al.
Ahmad Almadhor et al.
Artificial intelligence (AI) and machine learning (ML) have shown remarkable promise in advancing medical image analysis, yet their potential in neurology and psychiatry remains underexplored. This work explores the use of deep learning app...
A critical analysis of MBTI-based personality profiling with large language models [0.03%]
基于MBTI的人格测评与大型语言模型的批判分析
Jean Marie Tshimula,René Manassé Galekwa,Belkacem Chikhaoui
Jean Marie Tshimula
This paper critically analyzes MBTI-based personality profiling using Large Language Models (LLMs), examining both their use as tools for inferring human personality and as subjects evaluated through psychometric frameworks. We review recen...
Coşkun Çetin,Jose Roberto Castilho Piqueira,Burhaneddin İzgi et al.
Coşkun Çetin et al.
Large neuronal networks demonstrate complex dynamics across multiple scales, ranging from single-neuron excitability and spike-train variability to mesoscopic rhythms and whole-brain activity. Different types of differential equation models...
Commentary: Editorial: The convergence of AI, LLMs, and industry 4.0: enhancing BCI, HMI, and neuroscience research [0.03%]
评论：编辑室观点：AI、LLM与工业4.0的融合：增强BCI、HMI和神经科学研究
Alessandro Rossi
Alessandro Rossi
Thomas J Richner,Martynas Dervinis,Brian Nils Lundstrom
Thomas J Richner
The brain is a highly recurrent, nonlinear network hypothesized to remain near the edge of chaos for optimal performance. Excitation and inhibition must be balanced precisely within every neuron to ensure a consistent level of dynamical sta...
Simulated target search by bats using biomimetic SCAT biosonar model [0.03%]
基于蝙蝠仿生学模型SCAT的声呐目标搜索仿真研究
James A Simmons,Prithvi Thakur,Ashok Ragavendran et al.
James A Simmons et al.
Echolocating big brown bats broadcast short, wideband ultrasonic FM pulses for foraging and navigation. These broadcasts contain frequencies from 100 to 20 kHz (wavelengths 0.34-1.7 cm). Bats perceive target distance by measuring the time d...