Editorial: AI and neuroscience: integrating knowledge, reasoning, and theory of mind [0.03%]
评论：人工智能与神经科学：融合知识、推理和心智理论
Darren J Edwards,Bochao Zou,Rob Lowe et al.
Darren J Edwards et al.
NEURONpyxl: fast, flexible, Python-integrated simulation of biophysical neural networks with complex plastic synapses [0.03%]
NEURONpyxl：具备复杂塑性突触的快速、灵活且与Python集成的生物物理神经网络模拟工具
Uri Dickman,Peter J Thomas,Hillel J Chiel et al.
Uri Dickman et al.
Introduction: NEURON has been widely used as an empirically-based simulation tool, especially for multi-compartment conductance-based neuronal modeling. The network mediating feeding in Aplysia californica has been extens...
Rehab-DRLX: explainable neurorehabilitation prognosis using deep reinforcement learning and transformer-based models [0.03%]
基于深度强化学习和Transformer模型的可解释神经康复预后：REHAB-DRLX
Hadeel Alsolai,Shakir Khan,Rakesh Kumar Mahendran et al.
Hadeel Alsolai et al.
Neurorehabilitation poses a crucial problem in clinical recovery tasks, particularly for individuals with poor motor functions and neurological impairments, and problems in activities of daily living (ADL). To resolve this, we design a nove...
Deep learning guided propofol ketamine dosing and inflammation trajectories in elderly burns [0.03%]
深度学习指导的丙泊酚和氯胺酮给药以及老年烧伤患者的炎症轨迹研究
Xiaohui Yuan,Gang Wang,Xiaoyang Jiang et al.
Xiaohui Yuan et al.
Background and objectives: Elderly patients (≥65 years) who sustain burn injuries encounter a clinically significant perioperative challenge: a dysregulated hyperinflammatory response, characterized by elevated levels of...
Francisco Miqueles,Adrián G Palacios,John Atkinson et al.
Francisco Miqueles et al.
Introduction: Understanding how deep learning models map neural population activity to stimuli requires both high predictive accuracy and interpretable internal mechanisms. ...
Peter Cariani,Janet M Baker
Peter Cariani
This paper focuses on possible time-domain neurocomputational mechanisms for short-term anticipatory processes. Here we present a simple, signal processing functional model of how short-term rhythmic pattern expectancies could be computed o...
Coherent-resonant netting: disorder-enhanced selectivity from transient wave-like dynamics on biological connectomes [0.03%]
一致共振过滤：生物连接组上瞬时波动态选择性增强 disorder-enhanced selectivity来自生物连接组上的瞬时波动态 filtration via coherent-resonant netting：consistent resonance selection：disorder-enhanced selectivity from transient wave-like dynamics on biological connectomes
Oleg Dolgikh
Oleg Dolgikh
Biological agents face an energy-information bottleneck: inference requires rapid exploration of large hypothesis spaces, yet high-gain spiking is metabolically expensive. We propose Coherent-Resonant Netting (CRN) as a two-regime decision ...
Explainable hybrid CNN-transformer with self-supervised learning for structural analysis of paranasal sinus CT [0.03%]
具有自监督学习的可解释性混合CNN-Transformer鼻窦CT结构分析方法
Najeeb Ullah,Shabbab Ali Algamdi,Tariq Sadad
Najeeb Ullah
Introduction: The process of precise structural evaluation for paranasal sinuses based on CT scan data establishes a foundation for medical professionals to assess human anatomical variations, supporting the diagnosis and...
A predictive map learned from diverse entorhinal inputs explains the role of context-dependent reorganization of hippocampal place cells [0.03%]
来自多种内侧额内皮层输入的预测图可以解释海马区位置细胞的上下文相关改组现象的原因
Yusuke Kuniyoshi,Tadashi Yamazaki
Yusuke Kuniyoshi
The hippocampus is thought to support spatial memory and navigation by constructing predictive representations of the environment. Predictive map theory formalizes this function as a successor representation (SR). However, existing models a...
Biru B Dudhabhate,Kauê M Costa
Biru B Dudhabhate
Dopamine signaling has become closely associated with reward prediction errors (RPEs)-the difference between expected and experienced value. Although not without controversy, the dopamine RPE hypothesis is one of the most influential ideas ...