A functional contextual, observer-centric, quantum mechanical, and neuro-symbolic approach to solving the alignment problem of artificial general intelligence: safe AI through intersecting computational psychological neuroscience and LLM architecture for emergent theory of mind [0.03%]
一种功能情境化、观察者中心化的量子力学和神经符号方法，用于解决通用人工智能的对齐问题：通过计算心理神经科学与大型语言模型架构的交叉来实现安全AI并形成新兴的心智理论
Darren J Edwards
Darren J Edwards
There have been impressive advancements in the field of natural language processing (NLP) in recent years, largely driven by innovations in the development of transformer-based large language models (LLM) that utilize "attention." This appr...
Federico Tesler,Roberta Maria Lorenzi,Adam Ponzi et al.
Federico Tesler et al.
The development of biologically realistic models of brain microcircuits and regions constitutes currently a very relevant topic in computational neuroscience. One of the main challenges of such models is the passage between different scales...
Duho Sihn,Sung-Phil Kim
Duho Sihn
Introduction: Behaviors often involve a sequence of events, and learning and reproducing it is essential for sequential memory. Brain loop structures refer to loop-shaped inter-regional connection structures in the brain ...
Haiping Huang
Haiping Huang
A good theory of mathematical beauty is more practical than any current observation, as new predictions about physical reality can be self-consistently verified. This belief applies to the current status of understanding deep neural network...
EEG-based emotion recognition using graph convolutional neural network with dual attention mechanism [0.03%]
基于图卷积神经网络双注意力机制的脑电情绪识别
Wei Chen,Yuan Liao,Rui Dai et al.
Wei Chen et al.
EEG-based emotion recognition is becoming crucial in brain-computer interfaces (BCI). Currently, most researches focus on improving accuracy, while neglecting further research on the interpretability of models, we are committed to analyzing...
Hippocampal formation-inspired global self-localization: quick recovery from the kidnapped robot problem from an egocentric perspective [0.03%]
受海马体启发的全局自定位：从内禀视角快速恢复机器人被劫持问题
Takeshi Nakashima,Shunsuke Otake,Akira Taniguchi et al.
Takeshi Nakashima et al.
It remains difficult for mobile robots to continue accurate self-localization when they are suddenly teleported to a location that is different from their beliefs during navigation. Incorporating insights from neuroscience into developing a...
Rényi entropy-complexity causality space: a novel neurocomputational tool for detecting scale-free features in EEG/iEEG data [0.03%]
Rényi熵-复杂性因果空间：一种新颖的神经计算工具，用于检测EEG/iEEG数据中的尺度自由特征
Natalí Guisande,Fernando Montani
Natalí Guisande
Scale-free brain activity, linked with learning, the integration of different time scales, and the formation of mental models, is correlated with a metastable cognitive basis. The spectral slope, a key aspect of scale-free dynamics, was pro...
The synaptic correlates of serial position effects in sequential working memory [0.03%]
序列工作记忆中序位效应的突触相关因素研究
Jiaqi Zhou,Liping Gong,Xiaodong Huang et al.
Jiaqi Zhou et al.
Sequential working memory (SWM), referring to the temporary storage and manipulation of information in order, plays a fundamental role in brain cognitive functions. The serial position effect refers to the phenomena that recall accuracy of ...
SaE-GBLS: an effective self-adaptive evolutionary optimized graph-broad model for EEG-based automatic epileptic seizure detection [0.03%]
基于EEG的自动癫痫发作检测的有效自适应图谱广义模型SA-EGBLS的研究
Liming Cheng,Jiaqi Xiong,Junwei Duan et al.
Liming Cheng et al.
Introduction: Epilepsy is a common neurological condition that affects a large number of individuals worldwide. One of the primary challenges in epilepsy is the accurate and timely detection of seizure. Recently, the grap...