计算机科学
背景(考古学)
神经活动
认知科学
哺乳动物大脑
脑电图
比例(比率)
神经科学
人工智能
心理学
大脑活动与冥想
生物
量子力学
物理
古生物学
作者
Anne E Urai,Brent Doiron,Andrew M. Leifer,Anne K. Churchland
标识
DOI:10.1038/s41593-021-00980-9
摘要
Neuroscientists today can measure activity from more neurons than ever before, and are facing the challenge of connecting these brain-wide neural recordings to computation and behavior. In the present review, we first describe emerging tools and technologies being used to probe large-scale brain activity and new approaches to characterize behavior in the context of such measurements. We next highlight insights obtained from large-scale neural recordings in diverse model systems, and argue that some of these pose a challenge to traditional theoretical frameworks. Finally, we elaborate on existing modeling frameworks to interpret these data, and argue that the interpretation of brain-wide neural recordings calls for new theoretical approaches that may depend on the desired level of understanding. These advances in both neural recordings and theory development will pave the way for critical advances in our understanding of the brain.
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