Functional interactions as big data in the human brain.

Functional interactions as big data in the human brain.
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DOI:
10.1126/science.1238409
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发表时间:
2013-11-01
期刊:
Science (New York, N.Y.)
影响因子:
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通讯作者:
Turk-Browne NB
Turk-Browne NB
中科院分区:
其他
文献类型:
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作者:
Turk-Browne NB

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对人类大脑功能的非侵入性研究具有解开人类思维之谜的巨大潜力。然而,这些研究所产生的数据的复杂性促使在分析过程中作出各种简化的假设。虽然这使我们取得了相当大的进展,但我们目前的理解在一定程度上取决于这些假设。一种新兴的方法包括复杂性,解释了神经表征广泛分布,神经过程涉及区域之间的相互作用,相互作用因认知状态而异,并且相互作用的空间是巨大的。因为你所看到的取决于你如何看待,这种无偏见的方法为发现提供了最大的灵活性。
Noninvasive studies of human brain function hold great potential to unlock mysteries of the human mind. The complexity of data generated by such studies, however, has prompted various simplifying assumptions during analysis. Although this has enabled considerable progress, our current understanding is partly contingent upon these assumptions. An emerging approach embraces the complexity, accounting for the fact that neural representations are widely distributed, neural processes involve interactions between regions, interactions vary by cognitive state, and the space of interactions is massive. Because what you see depends on how you look, such unbiased approaches provide the greatest flexibility for discovery.
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