Abstract
Objective. 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. Approach. 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. Main results. 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. Significance. 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.
Highlights
Neural recording methodologies enable us to probe neural activity and investigate how the brain implements cognitive processes and generates behavior [1, 2]
Complex spatiotemporal neural activity encodes rich information related to behavior and cognition
We commonly examine oscillatory dynamics of neural activity, which can be obtained from local field potential (LFP), electrocorticography (ECoG), and electroencephalography (EEG) signals
Summary
Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Philippe N Tobler5, Andrew J Watrous6, Amy L Orsborn7,8,10 , Jarrod Lewis-Peacock2,9 and Samantha R Santacruz1,9,∗ Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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