很少有分类,总是高维度:神经代码如何在皮层层次上沿着皮层层次变化
Lorenzo Posani1,2, Shuqi Wang2,3, Samuel P Muscinelli1
1Zuckerman Institute, Columbia University, New York, NY, USA.
bioRxiv : the preprint server for biology
|November 28, 2024
概括
神经表现主要是非分类和高维的在皮质,挑战了长期存在的"分类"编码假设. 这种灵活的编码在大脑区域之间是一致的,使复杂的信息处理成为可能.
科学领域:
- 神经科学是一个神经科学.
- 计算神经科学是一种神经科学.
- 系统神经科学 系统神经科学
背景情况:
- 为信息编码而将神经群体组织成功能上不同的群体仍然是神经科学中的一个核心辩论.
- 了解神经表示是"分类"还是连续的,对于破译神经计算至关重要.
研究的目的:
- 系统地分析皮层神经元如何在多个大脑区域编码认知,感觉和运动变量.
- 研究神经编码的依赖规模的性质及其在皮层层次结构中的变化.
- 探索神经选择性,表示维度和计算灵活性之间的关系.
主要方法:
- 来自国际大脑实验室公共大脑全方位地图数据集的14000多个神经元单元的分析.
- 在复杂的任务中对43个皮质区域的神经编码的系统检查.
- 数学建模以解释单个神经元选择性和人口代码属性之间的联系.
主要成果:
- 神经编码结构是尺度依赖的:在整个皮层尺度上是分类的,但在大多数个体区域内是非分类的.
- 分类表现主要观察到主要的感官区域.
- 在分类聚类和神经表示的维度之间发现了强烈的反向相关性.
- 在所有皮层区域中,线性可分离条件的比例接近最大,这表明了强大的编码灵活性.
结论:
- 皮层神经代码主要是非分类和高维的,除了下层感官区域.
- 这种高维,非分类编码支持在整个皮层灵活处理信息.
- 这些发现挑战了对"分类"神经表征的传统观点,并提供了对大脑中神经计算的见解.
关键词:
国际大脑实验室 国际大脑实验室分类选择性的选择性.皮层 皮层 皮层决策是做出决策的过程.这就是维度的维度性.层次结构的层次结构.神经代码的神经代码神经几何学的神经几何学代表性 代表性的表现专业化 专业化 专业化结构 结构 结构 结构更多相关视频
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