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Advancements in brain imaging techniques have significantly expanded the size and complexity of real-time neuroimaging and behavioral data. However, identifying patterns, trends and synchronies within these datasets presents a significant computational challenge. Here, we demonstrate an approach that can translate time-varying neuroimaging data into unique audiovisualizations consisting of audible representations of dynamic data merged with simplified, color-coded movies of spatial components and behavioral recordings. Multiple variables can be encoded as different musical instruments, letting the observer differentiate and track multiple dynamic parameters in parallel. This representation enables intuitive assimilation of these datasets for behavioral correlates and spatiotemporal features such as patterns, rhythms and motifs that could be difficult to detect through conventional data interrogation methods. These audiovisual representations provide a novel perception of the organization and patterns of real-time activity in the brain, and offer an intuitive and compelling method for complex data visualization for a wider range of applications., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: EMCH and VV have a financial interest in SCAPE microscopy, which is licensed to Leica Microsystems and Applied Scientific Instrumentation (ASI). This financial interest does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2024 Thibodeaux et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

What are the spatial and temporal scales of brainwide neuronal activity? We used swept, confocally-aligned planar excitation (SCAPE) microscopy to image all cells in a large volume of the brain of adult Drosophila with high spatiotemporal resolution while flies engaged in a variety of spontaneous behaviors. This revealed neural representations of behavior on multiple spatial and temporal scales. The activity of most neurons correlated (or anticorrelated) with running and flailing over timescales that ranged from seconds to a minute. Grooming elicited a weaker global response. Significant residual activity not directly correlated with behavior was high dimensional and reflected the activity of small clusters of spatially organized neurons that may correspond to genetically defined cell types. These clusters participate in the global dynamics, indicating that neural activity reflects a combination of local and broadly distributed components. This suggests that microcircuits with highly specified functions are provided with knowledge of the larger context in which they operate., (© 2023. Springer Nature Limited.)

Although resting-state functional magnetic resonance imaging (fMRI) studies have observed dynamically changing brain-wide networks of correlated activity, fMRI's dependence on hemodynamic signals makes results challenging to interpret. Meanwhile, emerging techniques for real-time recording of large populations of neurons have revealed compelling fluctuations in neuronal activity across the brain that are obscured by traditional trial averaging. To reconcile these observations, we use wide-field optical mapping to simultaneously record pan-cortical neuronal and hemodynamic activity in awake, spontaneously behaving mice. Some components of observed neuronal activity clearly represent sensory and motor function. However, particularly during quiet rest, strongly fluctuating patterns of activity across diverse brain regions contribute greatly to interregional correlations. Dynamic changes in these correlations coincide with changes in arousal state. Simultaneously acquired hemodynamics depict similar brain-state-dependent correlation shifts. These results support a neural basis for dynamic resting-state fMRI, while highlighting the importance of brain-wide neuronal fluctuations in the study of brain state., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Light-sheet microscopy is an imaging approach that offers unique advantages for a diverse range of neuroscience applications. Unlike point-scanning techniques such as confocal and two-photon microscopy, light-sheet microscopes illuminate an entire plane of tissue, while imaging this plane onto a camera. Although early implementations of light sheet were optimized for longitudinal imaging of embryonic development in small specimens, emerging implementations are capable of capturing light-sheet images in freely moving, unconstrained specimens and even the intact in vivo mammalian brain. Meanwhile, the unique photobleaching and signal-to-noise benefits afforded by light-sheet microscopy's parallelized detection deliver the ability to perform volumetric imaging at much higher speeds than can be achieved using point scanning. This review describes the basic principles and evolution of light-sheet microscopy, followed by perspectives on emerging applications and opportunities for both imaging large, cleared, and expanded neural tissues and high-speed, functional imaging in vivo.