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19 Janelia Publications

Showing 1-10 of 19 results
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    02/28/22 | Melding Synthetic Molecules and Genetically Encoded Proteins to Forge New Tools for Neuroscience.
    Kumar P, Lavis LD
    Annual Review of Neuroscience. 2022 Feb 28:. doi: 10.1146/annurev-neuro-110520-030031

    Unraveling the complexity of the brain requires sophisticated methods to probe and perturb neurobiological processes with high spatiotemporal control. The field of chemical biology has produced general strategies to combine the molecular specificity of small-molecule tools with the cellular specificity of genetically encoded reagents. Here, we survey the application, refinement, and extension of these hybrid small-molecule:protein methods to problems in neuroscience, which yields powerful reagents to precisely measure and manipulate neural systems. Expected final online publication date for the , Volume 45 is July 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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    02/28/22 | Melding Synthetic Molecules and Genetically Encoded Proteins to Forge New Tools for Neuroscience.
    Kumar P, Lavis LD
    Annual Review Neuroscience. 2022 Feb 28:. doi: 10.1146/annurev-neuro-110520-030031

    Unraveling the complexity of the brain requires sophisticated methods to probe and perturb neurobiological processes with high spatiotemporal control. The field of chemical biology has produced general strategies to combine the molecular specificity of small-molecule tools with the cellular specificity of genetically encoded reagents. Here, we survey the application, refinement, and extension of these hybrid small-molecule:protein methods to problems in neuroscience, which yields powerful reagents to precisely measure and manipulate neural systems. Expected final online publication date for the , Volume 45 is July 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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    02/25/22 | Online learning for orientation estimation during translation in an insect ring attractor network.
    Robinson BS, Norman-Tenazas R, Cervantes M, Symonette D, Johnson EC, Joyce J, Rivlin PK, Hwang G, Zhang K, Gray-Roncal W
    Scientific Reports. 2022 Feb 25;12(1):3210. doi: 10.1038/s41598-022-05798-4

    Insect neural systems are a promising source of inspiration for new navigation algorithms, especially on low size, weight, and power platforms. There have been unprecedented recent neuroscience breakthroughs with Drosophila in behavioral and neural imaging experiments as well as the mapping of detailed connectivity of neural structures. General mechanisms for learning orientation in the central complex (CX) of Drosophila have been investigated previously; however, it is unclear how these underlying mechanisms extend to cases where there is translation through an environment (beyond only rotation), which is critical for navigation in robotic systems. Here, we develop a CX neural connectivity-constrained model that performs sensor fusion, as well as unsupervised learning of visual features for path integration; we demonstrate the viability of this circuit for use in robotic systems in simulated and physical environments. Furthermore, we propose a theoretical understanding of how distributed online unsupervised network weight modification can be leveraged for learning in a trajectory through an environment by minimizing orientation estimation error. Overall, our results may enable a new class of CX-derived low power robotic navigation algorithms and lead to testable predictions to inform future neuroscience experiments.

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    02/24/22 | Neuromuscular embodiment of feedback control elements in Drosophila flight.
    Samuel C Whitehead , Sofia Leone , Theodore Lindsay , Matthew R Meiselman , Noah Cowan , Michael H Dickinson , Nilay Yapici , David Stern , Troy Shirangi , Itai Cohen
    bioRxiv. 2022 Feb 24:. doi: 10.1101/2022.02.22.481344

    While insects like Drosophila are flying, aerodynamic instabilities require that they make millisecond-timescale adjustments to their wing motion to stay aloft and on course. These stabilization reflexes can be modeled as a proportional-integral (PI) controller; however, it is unclear how such control might be instantiated in insects at the level of muscles and neurons. Here, we show that the b1 and b2 motor units—prominent components of the fly's steering muscles system—modulate specific elements of the PI controller: the angular displacement (integral, I) and angular velocity (proportional, P), respectively. Moreover, these effects are observed only during the stabilization of pitch. Our results provide evidence for an organizational principle in which each muscle contributes to a specific functional role in flight control, a finding that highlights the power of using top-down behavioral modeling to guide bottom-up cellular manipulation studies.

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    02/23/22 | The importance of accounting for movement when relating neuronal activity to sensory and cognitive processes.
    Edward Zagha , Jeffrey C Erlich , Soohyun Lee , Gyorgy Lur , Daniel H O'Connor , Nicholas A Steinmetz , Carsen Stringer , Hongdian Yang
    Journal of Neuroscience: The Official Journal of the Society for Neuroscience. 2022 Feb 23;42(8):1375-1382. doi: 10.1523/JNEUROSCI.1919-21.2021

    A surprising finding of recent studies in mouse is the dominance of widespread movement-related activity throughout the brain, including in early sensory areas. In awake subjects, failing to account for movement risks misattributing movement-related activity to other (e.g., sensory or cognitive) processes. In this article, we 1) review task designs for separating task-related and movement-related activity, 2) review three 'case studies' in which not considering movement would have resulted in critically different interpretations of neuronal function, and 3) discuss functional couplings that may prevent us from ever fully isolating sensory, motor, and cognitive-related activity. Our main thesis is that neural signals related to movement are ubiquitous, and therefore ought to be considered first and foremost when attempting to correlate neuronal activity with task-related processes.

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    Romani LabSvoboda Lab
    02/22/22 | Neural Algorithms and Circuits for Motor Planning.
    Inagaki HK, Chen S, Daie K, Finklestein A, Fontolan L, Romani S, Svoboda K
    Annual Reviews Neuroscience. 2022 Feb 22:. doi: 10.1146/annurev-neuro-092021-121730

    The brain plans and executes volitional movements. The underlying patterns of neural population activity have been explored in the context of movements of the eyes, limbs, tongue, and head in nonhuman primates and rodents. How do networks of neurons produce the slow neural dynamics that prepare specific movements and the fast dynamics that ultimately initiate these movements? Recent work exploits rapid and calibrated perturbations of neural activity to test specific dynamical systems models that are capable of producing the observed neural activity. These joint experimental and computational studies show that cortical dynamics during motor planning reflect fixed points of neural activity (attractors). Subcortical control signals reshape and move attractors over multiple timescales, causing commitment to specific actions and rapid transitions to movement execution. Experiments in rodents are beginning to reveal how these algorithms are implemented at the level of brain-wide neural circuits. Expected final online publication date for the , Volume 45 is July 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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    Looger Lab
    02/19/22 | Volume-transmitted GABA waves drive epileptiform rhythms in the hippocampal network.
    Vincent Magloire , Leonid P. Savtchenko , Sergyi Sylantyev , Thomas P. Jensen , Nicholas Cole , Jonathan S. Marvin , Loren L. Looger , Dimitri M. Kullmann , Matthew C. Walker , Ivan Pavlov , Dmitri A. Rusakov
    bioRxiv. 2022 Feb 19:. doi: 10.1101/2021.03.25.437016

    Synchronised rhythmic activity of the brain is thought to arise from neuronal network behaviours that rely on synaptic signalling between individual cells. This notion has been a basis to explain periodic epileptiform discharges that are driven by interneuronal networks. However, interneuronal discharges not only engage cell-cell GABAergic transmission but also control the extracellular GABA concentration ([GABA]e) and thus tonic GABAA receptor conductance (Gtonic) across the cell population. At the same time, the firing activity of interneurons shows a bell-shaped dependence on Gtonic, suggesting an innate susceptibility to self-sustained oscillations. Here, we employ patch-clamp GABA ‘sniffer’ and fast two-photon excitation imaging of GABA sensor to show that periodic epileptiform discharges are preceded by a region-wide, rising wave of extracellular GABA. Neural network simulations based on such observations reveal that it is the volume-transmitted, extrasynaptic actions of GABA targeting multiple off-target cells that drives synchronised interneuronal spiking prompting periodic epileptiform bursts. We validate this hypothesis using simultaneous patch-clamp recordings from multiple nerve cells, selective optogenetic stimulation of fast-spiking interneurons, and by revealing the role of GABA uptake. Our findings thus unveil a key role of extrasynaptic, volume-transmitted GABA actions in enabling and pacing regenerative rhythmic activity in brain networks.

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    02/18/22 | Visualizing cellular and tissue ultrastructure using Ten-fold Robust Expansion Microscopy (TREx)
    Hugo G.J. Damstra , Boaz Mohar , Mark Eddison , Anna Akhmanova , Lukas C. Kapitein , Paul W. Tillberg
    eLife. 2022 Feb 18:. doi: https://doi.org/10.1101/2021.02.03.428837

    Expansion microscopy (ExM) is a powerful technique to overcome the diffraction limit of light microscopy that can be applied in both tissues and cells. In ExM, samples are embedded in a swellable polymer gel to physically expand the sample and isotropically increase resolution in x, y and z. The maximum resolution increase is limited by the expansion factor of the polymer gel, which is four-fold for the original ExM protocol. Variations on the original ExM method have been reported that allow for greater expansion factors, for example using iterative expansion, but at the cost of ease of adoption or versatility. Here, we systematically explore the ExM recipe space and present a novel method termed Ten-fold Robust Expansion Microscopy (TREx) that, like the original ExM method, requires no specialized equipment or procedures to carry out. We demonstrate that TREx gels expand ten-fold, can be handled easily, and can be applied to both thick tissue sections and cells enabling high-resolution subcellular imaging in a single expansion step. We show that applying TREx on antibody-stained samples can be combined with off-the-shelf small molecule stains for both total protein and membranes to provide ultrastructural context to subcellular protein localization.

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    02/15/22 | Glutamate indicators with improved activation kinetics and localization for imaging synaptic transmission
    Abhi Aggarwal , Rui Liu , Yang Chen , Amelia J Ralowicz , Samuel J Bergerson , Filip Tomaska , Timothy L Hanson , Jeremy P Hasseman , Daniel Reep , Getahun Tsegaye , Pantong Yao , Xiang Ji , Marinus Kloos , Deepika Walpita , Ronak Patel , Paul W Tilberg , Boaz Mohar , GENIE , Loren L Looger , Jonathan S Marvin , Michael B Hoppa , Arthur Konnerth , David Kleinfeld , Eric R Schreiter , Kaspar Podgorski
    bioRxiv PrePrint. 2022 Feb 15:. doi: 10.1101/2022.02.13.480251

    The fluorescent glutamate indicator iGluSnFR enables imaging of neurotransmission with genetic and molecular specificity. However, existing iGluSnFR variants exhibit saturating activation kinetics and are excluded from post-synaptic densities, limiting their ability to distinguish synaptic from extrasynaptic glutamate. Using a multi-assay screen in bacteria, soluble protein, and cultured neurons, we generated novel variants with improved kinetics and signal-to-noise ratios. We also developed surface display constructs that improve iGluSnFR’s nanoscopic localization to post-synapses. The resulting indicator, iGluSnFR3, exhibits rapid non-saturating activation kinetics and reports synaptic glutamate release with improved linearity and increased specificity versus extrasynaptic signals in cultured neurons. In mouse visual cortex, imaging of iGluSnFR3 at individual boutons reported single electrophysiologically-observed action potentials with high specificity versus non-synaptic transients. In vibrissal sensory cortex Layer 4, we used iGluSnFR3 to characterize distinct patterns of touch-evoked feedforward input from thalamocortical boutons and both feedforward and recurrent input onto L4 cortical neuron dendritic spines.

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    02/13/22 | Structured random receptive fields enable informative sensory encodings
    Biraj Pandey , Marius Pachitariu , Bingni W. Brunton , Kameron Decker Harris
    bioRxiv. 2022 Feb 13:. doi: 10.1101/2021.09.09.459651

    Brains must represent the outside world so that animals survive and thrive. In early sensory systems, neural populations have diverse receptive fields structured to detect important features in inputs, yet significant variability has been ignored in classical models of sensory neurons. We model neuronal receptive fields as random, variable samples from parametrized distributions in two sensory modalities, using data from insect mechanosensors and neurons of mammalian primary visual cortex. We show that these random feature neurons perform a randomized wavelet transform on inputs which removes high frequency noise and boosts the signal. Our result makes a significant theoretical connection between the foundational concepts of receptive fields in neuroscience and random features in artificial neural networks. Further, these random feature neurons enable learning from fewer training samples and with smaller networks in artificial tasks. This structured random model of receptive fields provides a unifying, mathematically tractable framework to understand sensory encodings across both spatial and temporal domains.

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