Unverified50% confidenceFactExact time
Closed-loop neural modulation refers to a system that acquires neural signals in real time, decodes state instantaneously and adjusts stimulation parameters accordingly, forming a "sensing-computing-stimulation" feedback loop.
1
Sources
50%
Confidence
Long-term
Relevance
10/24/2026
First Seen
Sources
Related Entities
Related Claims
Unverified闭环优化是神经科学中的实验范式，系统能实时根据大脑反馈信号动态调整刺激参数，形成刺激→神经响应→参数调整→新刺激的迭代回路79% similarUnverifiedAn artificial neuron receives multiple input signals, multiplies each input by a weight, adds a bias, and then passes the result through an activation function to determine whether to fire an output.75% similarUnverifiedEnd-to-end learning refers to having a neural network directly map from raw sensor inputs to motor control commands, bypassing independent modules such as perception, planning, and control.74% similarVerifiedFeedback loops give agent systems closed-loop control capability: observing the current state, comparing it with the target state, calculating the deviation, and driving corrective actions.74% similarUnverifiedThis mechanism can be described using a mathematical framework similar to neural networks or coupled oscillators, where the system achieves a dynamic balance between positive and negative feedback.73% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1094061API
curl https://kongchang.com/api/v1/knowledge/claims/1094061MCP
get_claim(id=1094061)