Retooling Computational Techniques for EEG-Based Neurocognitive Modeling of Children's Data, Validity and Prospects for Learning and Education [0.03%]
基于EEG的神经认知模型在儿童数据有效性及学习教育中的应用：重新构建计算技术及前景展望
Amedeo D&#x;Angiulli,Peter Devenyi
Amedeo D&#x;Angiulli
This paper describes continuing research on the building of neurocognitive models of the internal mental and brain processes of children using a novel adapted combination of existing computational approaches and tools, and using electro-enc...
Enhancing Diagnosis of Autism With Optimized Machine Learning Models and Personal Characteristic Data [0.03%]
利用优化的机器学习模型和个体特征数据改进自闭症诊断
Milan N Parikh,Hailong Li,Lili He
Milan N Parikh
Autism spectrum disorder (ASD) is a developmental disorder, affecting about 1% of the global population. Currently, the only clinical method for diagnosing ASD are standardized ASD tests which require prolonged diagnostic time and increased...
Automated Detection of High-Frequency Oscillations in Epilepsy Based on a Convolutional Neural Network [0.03%]
基于卷积神经网络的癫痫高频振荡自动化检测方法
Rui Zuo,Jing Wei,Xiaonan Li et al.
Rui Zuo et al.
Epilepsy is one of the most common chronic neurological diseases. High-frequency oscillations (HFOs) have emerged as promising biomarkers for the epileptogenic zone. However, visual marking of HFOs is a time-consuming and laborious process....
Symbolic Modeling of Asynchronous Neural Dynamics Reveals Potential Synchronous Roots for the Emergence of Awareness [0.03%]
异步神经动力学的符号建模揭示了意识出现的潜在同步根源
Pierre Bonzon
Pierre Bonzon
A new computational framework implementing asynchronous neural dynamics is used to address the duality between synchronous vs. asynchronous processes, and their possible relation to conscious vs. unconscious behaviors. Extending previous re...
Patrick Krauss,Alexandra Zankl,Achim Schilling et al.
Patrick Krauss et al.
Recurrent neural networks can produce ongoing state-to-state transitions without any driving inputs, and the dynamical properties of these transitions are determined by the neuronal connection strengths. Due to non-linearity, it is not clea...
A Simplified Model of Communication Between Time Cells: Accounting for the Linearly Increasing Timing Imprecision [0.03%]
一个简化的时序单元间通信模型：线性增加的时间定位误差计入方法
Mustafa Zeki,Fuat Balcı
Mustafa Zeki
Many organisms can time intervals flexibly on average with high accuracy but substantial variability between the trials. One of the core psychophysical features of interval timing functions relates to the signatures of this timing variabili...
Qing-Long L Gu,Songting Li,Wei P Dai et al.
Qing-Long L Gu et al.
It is hypothesized that cortical neuronal circuits operate in a global balanced state, i.e., the majority of neurons fire irregularly by receiving balanced inputs of excitation and inhibition. Meanwhile, it has been observed in experiments ...
Modeling Emotions Associated With Novelty at Variable Uncertainty Levels: A Bayesian Approach [0.03%]
基于贝叶斯方法的不确定性水平变化下的新颖性情感模型研究
Hideyoshi Yanagisawa,Oto Kawamata,Kazutaka Ueda
Hideyoshi Yanagisawa
Acceptance of novelty depends on the receiver's emotional state. This paper proposes a novel mathematical model for predicting emotions elicited by the novelty of an event under different conditions. It models two emotion dimensions, arousa...
A General Model of Ion Passive Transmembrane Transport Based on Ionic Concentration [0.03%]
基于离子浓度的离子被动跨膜转运通用模型
Vincent Qiqian Wang,Shenquan Liu
Vincent Qiqian Wang
Current mainstream neural computing is based on the electricity model proposed by Hodgkin and Huxley in 1952, the core of which is ion passive transmembrane transport controlled by ion channels. However, studies on the evolutionary history ...
Albert Yankelovich,Hedva Spitzer
Albert Yankelovich
Boundary completion is one of the desired properties of a robust object boundary detection model, since in real-word images the object boundaries are commonly not fully and clearly seen. An extreme example of boundary completion occurs in i...