Multi-scale neural decoding and analysis.

Multi-scale neural decoding and analysis.
复制标题

DOI:
10.1088/1741-2552/ac160f
复制
发表时间:
2021-08-16
影响因子:
4
通讯作者:
Santacruz SR
Santacruz SR
中科院分区:
工程技术2区
文献类型:
--
作者:
Lu HY;Lorenc ES;Zhu H;Kilmarx J;Sulzer J;Xie C;Tobler PN;Watrous AJ;Orsborn AL;Lewis-Peacock J;Santacruz SR

文献摘要

参考文献

被引文献

相似文献

复杂的时空神经活动编码与行为和认知相关的丰富信息。传统的研究集中在使用许多不同的测量方式之一获得的神经活动,其中每一个提供有用的,但不完整的评估的神经代码。多模态技术可以克服单一模态在空间和时间分辨率上的折衷,从而揭示对系统级神经机制更深入、更全面的理解。揭示多尺度动力学对于大脑功能的机械理解和利用神经科学的见解来开发更有效的临床治疗至关重要。我们讨论了传统的方法用于表征神经活动在不同的尺度和审查当代的例子,这些方法已经结合起来。然后,我们提出了我们的情况下,跨多个尺度的整合活动,以受益于每种方法的综合优势,并阐明了一个更全面的理解神经过程。我们研究了不同尺度下神经活动的各种组合,以及可用于整合或阐明跨尺度信息的分析技术,以及实现此类令人兴奋的研究的技术。最后,我们面临的挑战,未来的多尺度研究,并讨论这些方法的力量和潜力。该路线图将引导读者走向广泛的多尺度神经解码技术及其优于单模态分析的优势。这篇综述文章强调了多尺度分析对系统地询问认知和行为背后的复杂时空机制的重要性。
Complex spatiotemporal neural activity encodes rich information related to behavior and cognition. Conventional research has focused on neural activity acquired using one of many different measurement modalities, each of which provides useful but incomplete assessment of the neural code. Multi-modal techniques can overcome tradeoffs in the spatial and temporal resolution of a single modality to reveal deeper and more comprehensive understanding of system-level neural mechanisms. Uncovering multi-scale dynamics is essential for a mechanistic understanding of brain function and for harnessing neuroscientific insights to develop more effective clinical treatment. We discuss conventional methodologies used for characterizing neural activity at different scales and review contemporary examples of how these approaches have been combined. Then we present our case for integrating activity across multiple scales to benefit from the combined strengths of each approach and elucidate a more holistic understanding of neural processes. We examine various combinations of neural activity at different scales and analytical techniques that can be used to integrate or illuminate information across scales, as well the technologies that enable such exciting studies. We conclude with challenges facing future multi-scale studies, and a discussion of the power and potential of these approaches. This roadmap will lead the readers toward a broad range of multi-scale neural decoding techniques and their benefits over single-modality analyses. This Review article highlights the importance of multi-scale analyses for systematically interrogating complex spatiotemporal mechanisms underlying cognition and behavior.
DOI: 10.1016/j.neuroimage.2013.02.063
发表时间: 2013-08-01
期刊: NEUROIMAGE
影响因子: 5.7
作者:
Bartra, Oscar;McGuire, Joseph T.;Kable, Joseph W.
通讯作者: Kable, Joseph W.
DOI: 10.1016/j.neuron.2012.10.038
发表时间: 2012-11-21
期刊: Neuron
影响因子: 16.2
作者:
Bastos AM;Usrey WM;Adams RA;Mangun GR;Fries P;Friston KJ
通讯作者: Friston KJ
DOI: 10.1111/psyp.13462
发表时间: 2019-08-17
期刊: PSYCHOPHYSIOLOGY
影响因子: 3.7
作者:
Beldzik, Ewa;Domagalik, Aleksandra;Marek, Tadeusz
通讯作者: Marek, Tadeusz
DOI: 10.1038/s41467-020-20197-x
发表时间: 2021-01-27
影响因子: 16.6
作者:
Abbaspourazad H;Choudhury M;Wong YT;Pesaran B;Shanechi MM
通讯作者: Shanechi MM
DOI: 10.7554/elife.51322
发表时间: 2020-05-04
期刊: ELIFE
影响因子: 7.7
作者:
Berger, Michael;Agha, Naubahar Shahryar;Gail, Alexander
通讯作者: Gail, Alexander