Mohr Kieran S, Geuzebroek Anna C, Kelly Simon P
School of Electrical and Electronic Engineering and UCD Centre for Biomedical Engineering, University College Dublin, Dublin, Ireland.
Imaging Neurosci (Camb). 2024 Apr 26;2. doi: 10.1162/imag_a_00152. eCollection 2024.
Central to our understanding of how visual-evoked potentials (VEPs) contribute to visual processing is the question of where their anatomical sources are. Three well-established measures of low-level visual cortical activity are widely used: the first component ("C1") of the transient and multifocal VEP, and the steady-state VEP (SSVEP). Although primary visual cortex (V1) activity has often been implicated in the generation of all three signals, their dominant sources remain uncertain due to the limited resolution and methodological heterogeneity of source modelling. Here, we provide the first characterisation of all three signals in one analytic framework centred on the "cruciform model", which describes how scalp topographies of V1 activity vary with stimulus location due to the retinotopy and unique folding pattern of V1. We measured the transient C1, multifocal C1, and SSVEPs driven by an 18.75 Hz and 7.5 Hz flicker, and regressed them against forward models of areas V1, V2, and V3 generated from the Benson-2014 retinotopy atlas. The topographic variations of all four VEP signals across the visual field were better captured by V1 models, explaining between 2 and 6 times more variance than V2/V3. Models with all three visual areas improved fit further, but complementary analyses of temporal dynamics across all three signals indicated that the bulk of extrastriate contributions occur considerably later than V1. Overall, our data support the use of peak C1 amplitude and SSVEPs to probe V1 activity, although the SSVEP contains stronger extrastriate contributions. Moreover, we provide elaborated heuristics to distinguish visual areas in VEP data based on signal lateralisation as well as polarity inversion.
我们对视觉诱发电位(VEP)如何促进视觉处理的理解的核心问题是其解剖学来源在哪里。三种公认的低水平视觉皮层活动测量方法被广泛使用:瞬态多焦点VEP的第一个成分(“C1”)和稳态VEP(SSVEP)。尽管初级视觉皮层(V1)活动常常被认为与所有这三种信号的产生有关,但由于源模型的分辨率有限和方法的异质性,它们的主要来源仍然不确定。在这里,我们在一个以“十字形模型”为中心的分析框架中首次对所有这三种信号进行了表征,该模型描述了由于V1的视网膜拓扑结构和独特的折叠模式,V1活动的头皮地形图如何随刺激位置而变化。我们测量了由18.75 Hz和7.5 Hz闪烁驱动的瞬态C1、多焦点C1和SSVEP,并将它们与从Benson - 2014视网膜拓扑图谱生成的V1、V2和V3区域的正向模型进行回归分析。V1模型能更好地捕捉所有四种VEP信号在视野中的地形变化,解释的方差比V2/V3多2至6倍。包含所有三个视觉区域的模型进一步提高了拟合度,但对所有三种信号的时间动态进行的补充分析表明,纹外区域的大部分贡献发生的时间比V1晚得多。总体而言,我们的数据支持使用C1峰值幅度和SSVEP来探测V1活动,尽管SSVEP包含更强的纹外区域贡献。此外,我们提供了详细的启发式方法,用于根据信号的侧向化以及极性反转在VEP数据中区分视觉区域。