Approaches to inferring multi-regional interactions from simultaneous population recordings: Inferring multi-regional interactions from simultaneous population recordings.
Approaches to inferring multi-regional interactions from simultaneous population recordings: Inferring multi-regional interactions from simultaneous population recordings.
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DOI：
10.1016/j.conb.2020.10.004
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发表时间：
2020-12
影响因子：
5.7
通讯作者：
Druckmann S
中科院分区：
文献类型：
--
作者：
Kang B;Druckmann S
过去对神经表征和动力学的大多数研究都集中在单个大脑区域的记录上。然而，越来越多的证据表明，认知变量的全脑平行表示表明，分析单个大脑区域的神经表示和动力学可以受益于理解支持它们的多区域相互作用的背景。此外，扰动实验表明，这些平行表示相互作用的方式在不同的大脑区域对之间可能会有很大的不同。记录技术的最新进展为研究多区域相互作用如何协调单个大脑区域的神经表征，并通过同时记录多个大脑区域在一次试验的基础上支配行为提供了潜在的强大基础。我们回顾了研究多区域相互作用的实用方法，并以啮齿动物延迟反应任务范式为例进行了说明。
Most past studies of neural representations and dynamics have focused on recordings from single brain areas. However, growing evidence of brain-wide, parallel representations of cognitive variables suggests that analyzing neural representations and dynamics in individual brain areas can benefit from understanding the context of multi-regional interactions that support them. Moreover, perturbation experiments revealed that the manner in which these parallel representations interact with each other can differ dramatically across different pairs of brain areas. Recent advances in recording technology offer a potentially powerful substrate to study how multi-regional interactions coordinate neural representations in individual brain areas and dictate behavior on a single-trial basis through simultaneous recordings of multiple brain areas. We review pragmatic approaches to studying multi-regional interactions and illustrate them in the concrete context of a rodent delayed response task paradigm.
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DOI：
10.1073/pnas.0308538101
发表时间：
2004-06-29
影响因子：
11.1
作者：
Brovelli, A;Ding, MZ;Bressler, SL
通讯作者：
Bressler, SL
影响因子：
25
作者：
Cohen JD;Daw N;Engelhardt B;Hasson U;Li K;Niv Y;Norman KA;Pillow J;Ramadge PJ;Turk-Browne NB;Willke TL
通讯作者：
Willke TL
影响因子：
48
作者：
Chhetri, Raghav K.;Amat, Fernando;Kellerbeams, Philipp J.
通讯作者：
Kellerbeams, Philipp J.
影响因子：
9.8
作者：
Aimon, Sophie;Katsuki, Takeo;Greenspan, Ralph J.
通讯作者：
Greenspan, Ralph J.
影响因子：
2.5
作者：
ALEXANDER, GE;CRUTCHER, MD
通讯作者：
CRUTCHER, MD