Large-scale neural recordings call for new insights to link brain and behavior

被引:129
|
作者
Urai, Anne E. [1 ,2 ]
Doiron, Brent [3 ]
Leifer, Andrew M. [4 ]
Churchland, Anne K. [1 ,5 ]
机构
[1] Cold Spring Harbor Lab, POB 100, Cold Spring Harbor, NY 11724 USA
[2] Leiden Univ, Cognit Psychol Unit, Leiden, Netherlands
[3] Univ Chicago, Chicago, IL 60637 USA
[4] Princeton Univ, Princeton, NJ 08544 USA
[5] Univ Calif Los Angeles, Los Angeles, CA 90095 USA
基金
美国国家卫生研究院;
关键词
CELLULAR RESOLUTION; CORTICAL ACTIVITY; DIMENSIONALITY REDUCTION; CORRELATED VARIABILITY; NEURONAL-ACTIVITY; NETWORK MODELS; SINGLE-NEURON; DYNAMICS; IDENTIFICATION; COMPUTATIONS;
D O I
10.1038/s41593-021-00980-9
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Neuroscientists can measure activity from more neurons than ever before, garnering new insights and posing challenges to traditional theoretical frameworks. New frameworks may help researchers use these observations to shed light on brain function. 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.
引用
收藏
页码:11 / 19
页数:9
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