BRAID:神经行为数据的输入驱动的非线性动态建模
Parsa Vahidi1, Omid G Sani1, Maryam M Shanechi1,2,3
1Electrical and Computer Engineering, University of Southern California (USC), Los Angeles, CA.
ArXiv
|October 3, 2025
概括
我们开发了BRAID,这是一个深度学习框架,通过结合外部输入来模拟神经动态. 这种方法准确地捕捉神经行为关系,并通过将内在动态与输入效应分开来改善预测.
科学领域:
- 计算神经科学是一种神经科学.
- 机器学习 机器学习
- 系统神经科学 系统神经科学
背景情况:
- 神经群体表现出由外部输入影响的复杂动态.
- 传统模型往往忽视了这些输入对神经活动和行为的影响.
- 了解内在的神经动态对于解释行为至关重要.
研究的目的:
- 介绍BRAID,这是一个深度学习框架,用于建模非线性神经动态.
- 明确地将外部输入纳入神经人口模型.
- 从输入效应中分离内在的神经动力学,以改善行为预测.
主要方法:
- 开发了BRAID,这是一个使用输入驱动的循环神经网络的深度学习框架.
- 纳入了一个预测目标,将动态与输入分开.
- 使用多阶段优化方案来优先考虑与行为相关的内在动态.
- 通过非线性模拟验证并应用于运动皮质活动数据.
主要成果:
- 在模拟中,BRAID准确地学习神经和行为数据之间共享的内在动态.
- 将BRAID应用于运动皮质活动,通过结合感官刺激,改善了数据的拟合.
- 与基线方法相比,该框架增强了神经行为数据的预测.
结论:
- BRAID提供了一种通过整合外部输入来建模神经动态的新方法.
- 该方法有效地将内在动态与输入影响脱而出.
- BRAID提高了对神经活动和行为的理解和预测.
相关概念视频
Neural Circuits
Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
Multi-input and Multi-variable systems
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
In the absence of...
Modeling with Differential Equations
Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...


