Palenciano Ana F, Senoussi Mehdi, Formica Silvia, González-García Carlos
Mind, Brain, and Behavior Research Center, University of Granada, Granada, Spain.
CLLE Lab, CNRS UMR 5263, University of Toulouse, Toulouse, France.
Front Neuroimaging. 2023 Jan 9;1:974927. doi: 10.3389/fnimg.2022.974927. eCollection 2022.
Multivariate analyses of neural data have become increasingly influential in cognitive neuroscience since they allow to address questions about the representational signatures of neurocognitive phenomena. Here, we describe Canonical Template Tracking: a multivariate approach that employs independent localizer tasks to assess the activation state of specific representations during the execution of cognitive paradigms. We illustrate the benefits of this methodology in characterizing the particular content and format of task-induced representations, comparing it with standard (cross-)decoding and representational similarity analyses. Then, we discuss relevant design decisions for experiments using this analysis approach, focusing on the nature of the localizer tasks from which the canonical templates are derived. We further provide a step-by-step tutorial of this method, stressing the relevant analysis choices for functional magnetic resonance imaging and magneto/electroencephalography data. Importantly, we point out the potential pitfalls linked to canonical template tracking implementation and interpretation of the results, together with recommendations to mitigate them. To conclude, we provide some examples from previous literature that highlight the potential of this analysis to address relevant theoretical questions in cognitive neuroscience.
自多元神经数据分析能够解决有关神经认知现象的表征特征问题以来，它在认知神经科学中的影响力日益增强。在此，我们描述了典范模板追踪：一种多元方法，该方法采用独立的定位任务来评估认知范式执行过程中特定表征的激活状态。我们展示了这种方法在刻画任务诱导表征的特定内容和形式方面的优势，并将其与标准（交叉）解码和表征相似性分析进行比较。然后，我们讨论使用这种分析方法进行实验时的相关设计决策，重点关注从中导出典范模板的定位任务的性质。我们还进一步提供了该方法的分步教程，强调了针对功能磁共振成像和磁/脑电图数据的相关分析选择。重要的是，我们指出了与典范模板追踪实施和结果解释相关的潜在陷阱，并给出了减轻这些陷阱的建议。最后，我们提供了一些以往文献中的例子，突出了这种分析方法在解决认知神经科学相关理论问题方面的潜力。
