(variable) Frequency-based Layer Identification Procedure (FLIP and vFLIP) for spectrolaminar analysis

The mammalian cerebral cortex is anatomically organized into a six-layer motif. In this dataset and associated paper (Mendoza-Halliday et al., 2023) we show that a corresponding laminar motif of neuronal activity patterns exists across the cortex in the power of local field potentials (LFP). Using laminar probes, we recorded LFPs in five macaque monkeys in 14 cortical areas across the cortical hierarchy. The laminar locations of recordings were histologically identified via electrolytic lesions. Across all areas, we found a ubiquitous spectrolaminar pattern characterized by an increasing deep-to-superficial layer gradient of high-frequency power peaking in layers 2/3 and an increasing superficial-to-deep gradient of alpha-beta power peaking in layers 5/6. Our results suggest the existence of a canonical layer- and frequency-based mechanism for cortical computation. To facilitate the detection of these spectrolaminar patterns, we are releasing data associated with "Study 1" and "Study 2" as reported in Mendoza-Halliday et al., 2023. This comprises relative power of LFPs recorded in 4 macaque monkeys from areas V4, 7A, MT, MST, LIP, and LPFC. The FLIP and vFLIP algorithms were created to facilitate electrophysiological characterization of cortical layers based on power analysis of the local field potential recordings (LFP) that are provided in these datasets. The algorithms can also be used to perform the same analysis on any other multi-channel LFP dataset. We have verified that the spectrolaminar pattern is highly preserved in macaque monkeys, marmosets, and humans, but is more dissimilar in mouse.哺乳动物大脑皮层（mammalian cerebral cortex）在解剖结构上呈现六层结构基序。本数据集及配套论文（Mendoza-Halliday等人，2023）证实，在局部场电位（local field potential, LFP）的功率谱中，全皮层范围内存在与之对应的神经元活动模式层状基序。本研究采用层状电极探针，对5只猕猴的14个覆盖皮层层级的皮层脑区开展了局部场电位记录，记录位点的皮层分层位置通过电解损伤进行了组织学鉴定。在所有脑区中，我们均观测到普遍存在的谱层状模式：高频功率呈深层至表层的逐层递增趋势，峰值位于2/3层；而α-β频段功率则呈表层至深层的逐层递增趋势，峰值位于5/6层。本研究结果提示，皮层计算存在基于皮层分层与频率特征的经典机制。为便于此类谱层状模式的识别，我们发布了Mendoza-Halliday等人2023年论文中所述"研究1"与"研究2"的相关数据。该数据集包含4只猕猴在V4、7A、MT、MST、LIP及LPFC脑区中记录得到的局部场电位相对功率数据。本数据集配套提供的FLIP与vFLIP算法，旨在基于数据集所提供的局部场电位记录的功率分析，实现皮层分层的电生理表征；该算法亦可用于对其他多通道局部场电位数据集开展同类分析。我们已证实，该谱层状模式在猕猴、狨猴及人类中高度保守，但在小鼠中保守性显著更低。