@article {67828, title = {A brainstem integrator for self-localization and positional homeostasis}, journal = {Cell}, volume = {185}, year = {2022}, month = {2022 Dec 22}, pages = {5011-5027.e20}, abstract = {

To accurately track self-location, animals need to integrate their movements through space. In amniotes, representations of self-location have been found in regions such as the hippocampus. It is unknown whether more ancient brain regions contain such representations and by which pathways they may drive locomotion. Fish displaced by water currents must prevent uncontrolled drift to potentially dangerous areas. We found that larval zebrafish track such movements and can later swim back to their earlier location. Whole-brain functional imaging revealed the circuit enabling this process of positional homeostasis. Position-encoding brainstem neurons integrate optic flow, then bias future swimming to correct for past displacements by modulating inferior olive and cerebellar activity. Manipulation of position-encoding or olivary neurons abolished positional homeostasis or evoked behavior as if animals had experienced positional shifts. These results reveal a multiregional hindbrain circuit in vertebrates for optic flow integration, memory of self-location, and its neural pathway to behavior.Competing Interest StatementThe authors have declared no competing interest.

}, doi = {10.1101/2021.11.26.468907}, url = {https://www.biorxiv.org/content/early/2021/11/27/2021.11.26.468907}, author = {Yang, En and Zwart, Maarten F. and Rubinov, Mikail and James, Benjamin and Wei, Ziqiang and Narayan, Sujatha and Vladimirov, Nikita and Mensh, Brett D. and Fitzgerald, James E. and Ahrens, Misha B.} } @article {49535, title = {Brain-wide circuit interrogation at the cellular level guided by online analysis of neuronal function.}, journal = {Nature Methods}, volume = {15}, year = {2018}, month = {2018 Nov 30}, pages = {1117-1125}, abstract = {

Whole-brain imaging allows for comprehensive functional mapping of distributed neural pathways, but neuronal perturbation experiments are usually limited to targeting predefined regions or genetically identifiable cell types. To complement whole-brain measures of activity with brain-wide manipulations for testing causal interactions, we introduce a system that uses measuredactivity patterns to guide optical perturbations of any subset of neurons in the same fictively behaving larval zebrafish. First, a light-sheet microscope collects whole-brain data that are rapidly analyzed by a distributed computing system to generate functional brain maps. On the basis of these maps, the experimenter can then optically ablate neurons and image activity changes across the brain. We applied this method to characterize contributions of behaviorally tuned populations to the optomotor response. We extended the system to optogenetically stimulate arbitrary subsets of neurons during whole-brain imaging. These open-source methods enable delineating the contributions of neurons to brain-wide circuit dynamics and behavior in individual animals.

}, doi = {10.1038/s41592-018-0221-x}, author = {Vladimirov, Nikita and Wang, Chen and H{\"o}ckendorf, Burkhard and Pujala, Avinash and Tanimoto, Masashi and Mu, Yu and Yang, Chao-Tsung and Wittenbach, Jason and Freeman, Jeremy and Preibisch, Stephan and Koyama, Minoru and Keller, Philipp J and Ahrens, Misha B} } @article {47299, title = {Calcium imaging of neural circuits with extended depth-of-field light-sheet microscopy.}, journal = {Optics Letters}, volume = {41}, year = {2016}, month = {2016 Feb 17}, pages = {855-8}, abstract = {

Increasing the volumetric imaging speed of light-sheet microscopy will improve its ability to detect fast changes in neural activity. Here, a system is introduced for brain-wide imaging of neural activity in the larval zebrafish by coupling structured illumination with cubic phase extended depth-of-field (EDoF) pupil encoding. This microscope enables faster light-sheet imaging and facilitates arbitrary plane scanning{\textemdash}removing constraints on acquisition speed, alignment tolerances, and physical motion near the sample. The usefulness of this method is demonstrated by performing multi-plane calcium imaging in the fish brain with a\ 416{\texttimes}832{\texttimes}160 μm\ field of view at 33\ Hz. The optomotor response behavior of the zebrafish is monitored at high speeds, and time-locked correlations of neuronal activity are resolved across its brain.

}, doi = {10.1364/OL.41.000855}, author = {Quirin, Sean and Vladimirov, Nikita and Yang, Chao-Tsung and Peterka, Darcy S and Yuste, Rafael and Ahrens, Misha B} } @article {45177, title = {Light-sheet functional imaging in fictively behaving zebrafish.}, journal = {Nature Methods}, volume = {11}, year = {2014}, month = {2014 Jul 27}, pages = {883-4}, abstract = {

The processing of sensory input and the generation of behavior involves large networks of neurons, which necessitates new technology for recording from many neurons in behaving animals. In the larval zebrafish, light-sheet microscopy can be used to record the activity of almost all neurons in the brain simultaneously at single-cell resolution. Existing implementations, however, cannot be combined with visually driven behavior because the light sheet scans over the eye, interfering with presentation of controlled visual stimuli. Here we describe a system that overcomes the confounding eye stimulation through the use of two light sheets and combines whole-brain light-sheet imaging with virtual reality for fictively behaving larval zebrafish.

}, issn = {1548-7105}, doi = {10.1038/nmeth.3040}, author = {Vladimirov, Nikita and Mu, Yu and Kawashima, Takashi and Bennett, Davis V and Yang, Chao-Tsung and Looger, Loren L and Keller, Philipp J and Freeman, Jeremy and Ahrens, Misha B} } @article {45065, title = {Mapping brain activity at scale with cluster computing.}, journal = {Nature Methods}, volume = {11}, year = {2014}, month = {2014 Jul 27}, pages = {941-950}, abstract = {

Understanding brain function requires monitoring and interpreting the activity of large networks of neurons during behavior. Advances in recording technology are greatly increasing the size and complexity of neural data. Analyzing such data will pose a fundamental bottleneck for neuroscience. We present a library of analytical tools called Thunder built on the open-source Apache Spark platform for large-scale distributed computing. The library implements a variety of univariate and multivariate analyses with a modular, extendable structure well-suited to interactive exploration and analysis development. We demonstrate how these analyses find structure in large-scale neural data, including whole-brain light-sheet imaging data from fictively behaving larval zebrafish, and two-photon imaging data from behaving mouse. The analyses relate neuronal responses to sensory input and behavior, run in minutes or less and can be used on a private cluster or in the cloud. Our open-source framework thus holds promise for turning brain activity mapping efforts into biological insights.

}, issn = {1548-7091}, doi = {10.1038/nmeth.3041}, author = {Freeman, Jeremy and Vladimirov, Nikita and Kawashima, Takashi and Mu, Yu and Sofroniew, Nicholas J. and Bennett, Davis V. and Rosen, Joshua and Yang, Chao-Tsung and Looger, Loren L. and Ahrens, Misha B.} }