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      Brain-wide mapping of neural activity controlling zebrafish exploratory locomotion

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          Abstract

          In the absence of salient sensory cues to guide behavior, animals must still execute sequences of motor actions in order to forage and explore. How such successive motor actions are coordinated to form global locomotion trajectories is unknown. We mapped the structure of larval zebrafish swim trajectories in homogeneous environments and found that trajectories were characterized by alternating sequences of repeated turns to the left and to the right. Using whole-brain light-sheet imaging, we identified activity relating to the behavior in specific neural populations that we termed the anterior rhombencephalic turning region (ARTR). ARTR perturbations biased swim direction and reduced the dependence of turn direction on turn history, indicating that the ARTR is part of a network generating the temporal correlations in turn direction. We also find suggestive evidence for ARTR mutual inhibition and ARTR projections to premotor neurons. Finally, simulations suggest the observed turn sequences may underlie efficient exploration of local environments.

          DOI: http://dx.doi.org/10.7554/eLife.12741.001

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          Much of an animal’s behavior is guided by cues in the environment: many animals follow odors to find food, for example. But even in the absence of such cues, animals continue to show spontaneous behaviors that are optimized to help them discover resources, such as food, or landmarks, such as shelter. While these behaviors have been observed in many animals, it is unclear how they are supported by the nervous system. This is partly because it is hard to know where to look for relevant signals in large brains of many animals.

          The development of whole-brain imaging techniques in zebrafish larvae offers a possible solution to this problem. Zebrafish are commonly used in laboratory studies because the zebrafish genome has been fully sequenced and they reproduce quickly. Whole-brain imaging in larval zebrafish has previously revealed widespread and complex patterns of spontaneous activity. However, it has been unclear whether or how these ‘thoughts’ are translated into behavior. Moreover, while researchers have studied how the fish respond to lights and sounds, little is known about how fish behave in the absence of guiding stimuli from their environment.

          Dunn, Mu et al. now show that spontaneous fish behavior is not random, but is instead characterized by alternating states in which the fish are more likely to repeatedly turn either left or right. Simulations show that this pattern of swimming increases the fish's local foraging efficiency. By analyzing data from across the whole brain, Dunn, Mu et al. identified specific circuits of neurons that help generate these switching chains of turns. This alternating left-right rhythm appears to be dictated by signals sent between theses sets of neurons and may be supported by feedback from the behavior itself.

          This analysis generates specific predictions about how specific neurons should connect with one another, and about the relationship between this connectivity and the activity of the rest of the brain. Future studies are required to test these predictions, and to determine how factors – such as whether an animal is hungry, for example – influence the pattern of spontaneous movements.

          DOI: http://dx.doi.org/10.7554/eLife.12741.002

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          Most cited references53

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          Random walk models in biology.

          Mathematical modelling of the movement of animals, micro-organisms and cells is of great relevance in the fields of biology, ecology and medicine. Movement models can take many different forms, but the most widely used are based on the extensions of simple random walk processes. In this review paper, our aim is twofold: to introduce the mathematics behind random walks in a straightforward manner and to explain how such models can be used to aid our understanding of biological processes. We introduce the mathematical theory behind the simple random walk and explain how this relates to Brownian motion and diffusive processes in general. We demonstrate how these simple models can be extended to include drift and waiting times or be used to calculate first passage times. We discuss biased random walks and show how hyperbolic models can be used to generate correlated random walks. We cover two main applications of the random walk model. Firstly, we review models and results relating to the movement, dispersal and population redistribution of animals and micro-organisms. This includes direct calculation of mean squared displacement, mean dispersal distance, tortuosity measures, as well as possible limitations of these model approaches. Secondly, oriented movement and chemotaxis models are reviewed. General hyperbolic models based on the linear transport equation are introduced and we show how a reinforced random walk can be used to model movement where the individual changes its environment. We discuss the applications of these models in the context of cell migration leading to blood vessel growth (angiogenesis). Finally, we discuss how the various random walk models and approaches are related and the connections that underpin many of the key processes involved.
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            Sensitive red protein calcium indicators for imaging neural activity

            Genetically encoded calcium indicators (GECIs) allow measurement of activity in large populations of neurons and in small neuronal compartments, over times of milliseconds to months. Although GFP-based GECIs are widely used for in vivo neurophysiology, GECIs with red-shifted excitation and emission spectra have advantages for in vivo imaging because of reduced scattering and absorption in tissue, and a consequent reduction in phototoxicity. However, current red GECIs are inferior to the state-of-the-art GFP-based GCaMP6 indicators for detecting and quantifying neural activity. Here we present improved red GECIs based on mRuby (jRCaMP1a, b) and mApple (jRGECO1a), with sensitivity comparable to GCaMP6. We characterized the performance of the new red GECIs in cultured neurons and in mouse, Drosophila, zebrafish and C. elegans in vivo. Red GECIs facilitate deep-tissue imaging, dual-color imaging together with GFP-based reporters, and the use of optogenetics in combination with calcium imaging. DOI: http://dx.doi.org/10.7554/eLife.12727.001
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              Intracellular dynamics of hippocampal place cells during virtual navigation

              Hippocampal place cells encode spatial information in rate and temporal codes. To examine the mechanisms underlying hippocampal coding, we measured the intracellular dynamics of place cells by combining in vivo whole cell recordings with a virtual reality system. Head-restrained mice, running on a spherical treadmill, interacted with a computer-generated visual environment to perform spatial behaviors. Robust place cell activity was present during movement along a virtual linear track. From whole cell recordings, we identified three subthreshold signatures of place fields: (1) an asymmetric ramp-like depolarization of the baseline membrane potential; (2) an increase in the amplitude of intracellular theta oscillations; and, (3) a phase precession of the intracellular theta oscillation relative to the extracellularly-recorded theta rhythm. These intracellular dynamics underlie the primary features of place cell rate and temporal codes. The virtual reality system developed here will enable new experimental approaches to study the neural circuits underlying navigation.
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                Author and article information

                Contributors
                Role: Reviewing editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                22 March 2016
                2016
                : 5
                : e12741
                Affiliations
                [1 ]deptDepartment of Molecular and Cellular Biology , Harvard University , Cambridge, United States
                [2 ]deptProgram in Neuroscience, Department of Neurobiology , Harvard Medical School , Boston, United States
                [3 ]Janelia Research Campus, Howard Hughes Medical Institute , Ashburn, United States
                [4 ]deptDepartment of Neuroscience, Physiology and Pharmacology , University College London , London, United Kingdom
                [5]Emory University , United States
                [6]Emory University , United States
                Author notes
                [†]

                These authors contributed equally to this work.

                [‡]

                These authors also contributed equally to this work.

                Author information
                http://orcid.org/0000-0003-0181-5239
                http://orcid.org/0000-0002-1671-4636
                http://orcid.org/0000-0002-5317-494X
                http://orcid.org/0000-0001-8169-2990
                http://orcid.org/0000-0002-3457-4462
                Article
                12741
                10.7554/eLife.12741
                4841782
                27003593
                3828441c-11a3-4314-98af-724f03b26992
                © 2016, Dunn et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 03 November 2015
                : 09 March 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000011, Howard Hughes Medical Institute;
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award Recipient :
                Funded by: Marie Curie Fellowship;
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Neuroscience
                Custom metadata
                2.5
                Whole-brain activity imaging in larval zebrafish reveals brain regions that influence patterns of spontaneous movement to increase local exploration efficiency.

                Life sciences
                spontaneous brain activity,whole-brain functional imaging,larval zebrafish,exploration strategies,neural basis of behavior,higher-order motor control,zebrafish

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