Using multivariate decoding to go beyond contrastive analyses in consciousness research
Using multivariate decoding to go beyond contrastive analyses in consciousness research
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DOI：
10.3389/fpsyg.2014.01250
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发表时间：
2014-10-30
影响因子：
3.8
通讯作者：
Overgaard, Morten
中科院分区：
文献类型：
--
作者：
Sandberg, Kristian;Andersen, Lau M.;Overgaard, Morten
几十年来，对比有意识和没有意识的情况一直是研究意识（NCC）神经相关性的首选方法，但最近有人提出，可以通过超越这种方法来获得进一步的见解，特别是通过精心控制NCC的潜在前体和后果不被误认为是NCC。在此，我们简要回顾了现有范式超越对比方法的优势和潜在缺陷，并提出了神经活动模式的多元解码作为其他方法的补充。具体来说，我们强调多元解码的能力，以检测哪些神经活动模式在单次试验水平上一致地预测意识体验。这是相关的，因为“适当的NCC”被期望具有一致的预测性，而作为意识结果的过程可能不会在每次试验中发生（使其预测性降低），并且意识的先决条件可能存在于一些没有意识经验的试验中（使其预测性降低）。
Contrasting conditions with and without awareness has been the preferred method for investigating the neural correlates of consciousness (NCC) for decades, yet recently it has been suggested that further insights can be made by moving beyond this method, specifically by meticulously controlling that potential precursors and consequences of the NCC are not mistaken for an NCC. Here, we briefly review the advantages and potential pitfalls of existing paradigms going beyond the contrastive method, and we propose multivariate decoding of neural activity patterns as a supplement to other methods. Specifically, we emphasize the ability of multivariate decoding to detect which patterns of neural activity are consistently predictive of conscious experiences at the single trial level. This is relevant as the "NCC proper" is expected to be consistently predictive whereas processes that are consequences of consciousness may not occur on every trial (making them less predictive) and prerequisites of consciousness may be present on some trials without conscious experience (making them less predictive).