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Updated: Sep 14, 2025

The DREAM Implant: A Lightweight, Modular, and Cost-Effective Implant System for Chronic Electrophysiology in Head-Fixed and Freely Behaving Mice

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基于内核的LFP估计在小鼠视觉皮层的详细大规模尖端网络模型中.

Nicolò Meneghetti¹, Atle E Rimehaug², Gaute T Einevoll³

¹The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa 56025, Italy; Department of Excellence for Robotics and AI, Scuola Superiore Sant'Anna, Pisa 56025, Italy.

Neural networks : the official journal of the International Neural Network Society

|July 22, 2025

概括

一种新的内核方法准确地估计大脑信号,如来自大型神经网络模拟的局部场势 (LFP). 这种高效的方法揭示了外部投入主导V1LFP,而不是本地活动.

关键词:

细胞外潜力细胞外潜力基于内核的LFP估计.大规模的神经模拟.地方现场潜力地方现场潜力鼠标视觉皮层的视觉皮层尖端网络模型的网络模型.

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科学领域:

计算神经科学是一种计算神经科学.
神经建模的神经建模
大脑信号分析分析

背景情况:

大规模神经活动的模拟对于理解大脑功能至关重要.
从这些模拟中估计可测量的大脑信号,例如局部场势 (LFP),对于桥梁模型和实验至关重要.
目前用于准确的LFP模拟的方法通常需要计算密集,高度详细的模型,限制实际应用.

研究的目的:

从大规模神经网络模型中演示基于内核的方法来准确和高效地估计LFP.
在小鼠初级视觉皮层 (V1) 模型中分析不同神经元群体对LFP的贡献.
调查外部突触输入与本地活动在塑造V1LFPs中的作用.

主要方法:

使用基于内核的方法,从鼠标V1的详细多分部网络模型中估计LFP.
模拟对视觉刺激的反应,包括漂移的格子和全场闪光.
应用该方法来解开神经元群体和突触输入对LFP的贡献.

主要成果:

核心方法在V1网络模型中准确有效地估计了LFP.
发现外部突触输入,特别是来自横介视觉区域和胸膜 afferents的反,主导了V1 LFP.
来自V1神经元家族的局部突触活动对LFP的贡献很小,相关性可能会掩盖实验数据中的这一发现.

结论:

内核方法是复杂神经网络模型中LFP估计的强大而准确的工具.
这种方法可以提供对可测量的大脑信号背后的神经机制的新见解.
外部突触输入在鼠标V1中塑造LFP中发挥着主导作用,挑战了以前关于局部电路贡献的假设.