Tootfinder

Hippocampal plasticity and navigational skills in blindness https://www.intechopen.com/online-first/1228782 "We discuss how cross-modal plasticity repurposes the visual cortex for navigation, the role of sensory substitution devices in facilitating spatial learning, and behavioral …

Hippocampal Plasticity and Navigational Skills in Blindness

Navigation is a fundamental cognitive ability that relies on the hippocampus, a brain region that is known for its role in spatial representation and memory. In individuals with congenital blindness, the absence of visual input leads to significant neuroplastic adaptations that support alternative navigation strategies. This review examines the structural and functional modifications of the hippocampus in individuals who are blind and explores the broader neural mechanisms underlying…

Neuro-Informed Joint Learning Enhances Cognitive Workload Decoding in Portable BCIs
Xiaoxiao Yang, Chan Feng, Jiancheng Chen
https://arxiv.org/abs/2506.23458

Neuro-Informed Joint Learning Enhances Cognitive Workload Decoding in Portable BCIs
Portable and wearable consumer-grade electroencephalography (EEG) devices, like Muse headbands, offer unprecedented mobility for daily brain-computer interface (BCI) applications, including cognitive load detection. However, the exacerbated non-stationarity in portable EEG signals constrains data fidelity and decoding accuracy, creating a fundamental trade-off between portability and performance. To mitigate such limitation, we propose MuseCogNet (Muse-based Cognitive Network), a unified joint …

Composable OS Kernel Architectures for Autonomous Intelligence
Rajpreet Singh, Vidhi Kothari
https://arxiv.org/abs/2508.00604 https://arxiv.org/pdf/2508.00…

Composable OS Kernel Architectures for Autonomous Intelligence
As intelligent systems permeate edge devices, cloud infrastructure, and embedded real-time environments, this research proposes a new OS kernel architecture for intelligent systems, transforming kernels from static resource managers to adaptive, AI-integrated platforms. Key contributions include: (1) treating Loadable Kernel Modules (LKMs) as AI-oriented computation units for fast sensory and cognitive processing in kernel space; (2) expanding the Linux kernel into an AI-native environment with…

SCENIC: A Location-based System to Foster Cognitive Development in Children During Car Rides
Liuqing Chen, Yaxuan Song, Ke Lyu, Shuhong Xiao, Yilang Shen, Lingyun Sun
https://arxiv.org/abs/2508.17058

SCENIC: A Location-based System to Foster Cognitive Development in Children During Car Rides
Car-riding is common for children in modern life. Given the repetitive nature of daily commutes, they often feel bored and turn to electronic devices for entertainment. Meanwhile, the rich and dynamic scenery outside the car naturally attracts children's curiosity and offers valuable resources for cognitive development. Our formative study reveals that parents' support during car rides is often fleeting, as accompanying adults may struggle to consistently guide children's exploration. To addres…

Secure Multi-LLM Agentic AI and Agentification for Edge General Intelligence by Zero-Trust: A Survey
Yinqiu Liu, Ruichen Zhang, Haoxiang Luo, Yijing Lin, Geng Sun, Dusit Niyato, Hongyang Du, Zehui Xiong, Yonggang Wen, Abbas Jamalipour, Dong In Kim, Ping Zhang
https://arxiv.org/abs/2508.19870

Secure Multi-LLM Agentic AI and Agentification for Edge General Intelligence by Zero-Trust: A Survey
Agentification serves as a critical enabler of Edge General Intelligence (EGI), transforming massive edge devices into cognitive agents through integrating Large Language Models (LLMs) and perception, reasoning, and acting modules. These agents collaborate across heterogeneous edge infrastructures, forming multi-LLM agentic AI systems that leverage collective intelligence and specialized capabilities to tackle complex, multi-step tasks. However, the collaborative nature of multi-LLM systems int…

ProMemAssist: Exploring Timely Proactive Assistance Through Working Memory Modeling in Multi-Modal Wearable Devices
Kevin Pu, Ting Zhang, Naveen Sendhilnathan, Sebastian Freitag, Raj Sodhi, Tanya Jonker
https://arxiv.org/abs/2507.21378

ProMemAssist: Exploring Timely Proactive Assistance Through Working Memory Modeling in Multi-Modal Wearable Devices
Wearable AI systems aim to provide timely assistance in daily life, but existing approaches often rely on user initiation or predefined task knowledge, neglecting users' current mental states. We introduce ProMemAssist, a smart glasses system that models a user's working memory (WM) in real-time using multi-modal sensor signals. Grounded in cognitive theories of WM, our system represents perceived information as memory items and episodes with encoding mechanisms, such as displacement and interf…