Théophile Champion,Howard Bowman,Dimitrije Marković et al.
Théophile Champion et al.
Active inference is a process theory of perception, learning, and decision making that is applied to a range of research fields, including neuroscience, robotics, psychology, and machine learning. Active inference rests on an objective func...
Exploring the Interplay between BOLD Signal Variability, Complexity, Static and Dynamic Functional Brain Network Features During Movie Viewing [0.03%]
利用功能性连接体和复杂网络理论探索电影观看过程中的血氧信号变异性和复杂性特征及其交互作用
Amir Hossein Ghaderi,Hongye Wang,Andrea B Protzner
Amir Hossein Ghaderi
Exploring the dynamics and complexity of brain signal is critical to advancing our understanding of brain function. Recent fMRI studies have revealed links between BOLD signal variability or complexity with static/dynamics features of funct...
Local Glutamate-Glutamine Cycling Underlies Presynaptic ATP Homeostasis [0.03%]
局部谷氨酸-谷氨酰胺循环是突触前ATP稳态的基础
Reinoud Maex
Reinoud Maex
Presynaptic axon terminals maintain in their cytosol an almost constant level of adenosine triphosphate (ATP) to safeguard neurotransmission during varying workloads. In the study reported in this letter, it is argued that the vesicular rel...
Neuromodulators Generate Multiple Context-Relevant Behaviors in Recurrent Neural Networks [0.03%]
神经调质在反馈神经网络中生成多种情境相关的行为模式
Ben Tsuda,Stefan C Pate,Kay M Tye et al.
Ben Tsuda et al.
Neuromodulators are critical controllers of neural states, with dysfunctions linked to various neuropsychiatric disorders. Although many biological aspects of neuromodulation have been studied, the computational principles underlying how ne...
Object Detection, Recognition, Deep Learning, and the Universal Law of Generalization [0.03%]
目标检测、识别、深度学习与普适泛化规律
Faris B Rustom,Rohan Sharma,Haluk Öğmen et al.
Faris B Rustom et al.
Object detection and recognition are fundamental functions that play a significant role in the success of species. Because the appearance of an object exhibits large variability, the brain has to group these different stimuli under the same...
Simulated Complex Cells Contribute to Object Recognition Through Representational Untangling [0.03%]
表征分离使得仿真复杂细胞有助于物体识别
Mitchell B Slapik,Harel Z Shouval
Mitchell B Slapik
The visual system performs a remarkable feat: it takes complex retinal activation patterns and decodes them for object recognition. This operation, termed "representational untangling," organizes neural representations by clustering similar...
Andersen Ang,Waqas Bin Hamed,Hans De Sterck
Andersen Ang
When applying nonnegative matrix factorization (NMF), the rank parameter is generally unknown. This rank, called the nonnegative rank, is usually estimated heuristically since computing its exact value is NP-hard. In this work, we propose a...
Approximation Rates in Fréchet Metrics: Barron Spaces, Paley-Wiener Spaces, and Fourier Multipliers [0.03%]
Frechet度量下的逼近率：Barron空间、Paley-Wiener空间和傅立叶乘子
Ahmed Abdeljawad,Thomas Dittrich
Ahmed Abdeljawad
Operator learning is a recent development in the simulation of partial differential equations by means of neural networks. The idea behind this approach is to learn the behavior of an operator, such that the resulting neural network is an a...
Neural Associative Skill Memories for Safer Robotics and Modeling Human Sensorimotor Repertoires [0.03%]
安全机器人技术及人体感觉-运动技能的记忆模型
Pranav Mahajan,Mufeng Tang,T Ed Li et al.
Pranav Mahajan et al.
Modern robots face a challenge shared by biological systems: how to learn and adaptively express multiple sensorimotor skills. A key aspect of this is developing an internal model of expected sensorimotor experiences to detect and react to ...
Lucas Shoji,Kenta Suzuki,Leo Kozachkov
Lucas Shoji
We establish that a broad class of effective learning rules-those that improve a scalar performance measure over a given time window-can be expressed as natural gradient descent with respect to an appropriately defined metric. Specifically,...