NOSA, an Analytical Toolbox for Multicellular Optical Electrophysiology

Understanding how neural networks generate activity patterns and communicate with each other requires monitoring the electrical activity from many neurons simultaneously. Perfectly suited tools for addressing this challenge are genetically encoded voltage indicators (GEVIs) because they can be targeted to specific cell types and optically report the electrical activity of individual, or populations of neurons. However, analyzing and interpreting the data from voltage imaging experiments is challenging because high recording speeds and properties of current GEVIs yield only low signal-to-noise ratios, making it necessary to apply specific analytical tools. Here, we present NOSA (Neuro-Optical Signal Analysis), a novel open source software designed for analyzing voltage imaging data and identifying temporal interactions between electrical activity patterns of different origin. In this manuscript we explain the challenges that arise during voltage imaging experiments and provide hands-on analytical solutions. We demonstrate how NOSA’s baseline fitting, filtering algorithms and movement correction can compensate for shifts in baseline fluorescence and extract electrical patterns from low signal-to-noise recordings. Moreover, NOSA contains powerful features to identify oscillatory frequencies in electrical patterns and extract neuronal firing characteristics. NOSA is the first open-access software to provide an option for analyzing simultaneously recorded optical and electrical data derived from patch-clamp or other electrode-based recordings. To identify temporal relations between electrical activity patterns we implemented different options to perform cross correlation analysis, demonstrating their utility during voltage imaging in Drosophila and mice. All features combined, NOSA will facilitate the first steps into using GEVIs and help to realize their full potential for revealing cell-type specific connectivity and functional interactions. If you would like to test NOSA, please send an email to the lead contact.

[1]  Rafael Yuste,et al.  Comparative Evaluation of Genetically Encoded Voltage Indicators , 2019, Cell reports.

[2]  Hakan Inan,et al.  Fast, in vivo voltage imaging using a red fluorescent indicator , 2018, Nature Methods.

[3]  Srdjan D Antic,et al.  Voltage imaging to understand connections and functions of neuronal circuits. , 2016, Journal of neurophysiology.

[4]  R. Strauss.  The central complex and the genetic dissection of locomotor behaviour , 2002, Current Opinion in Neurobiology.

[5]  Mala Murthy,et al.  Whole-cell in vivo patch-clamp recordings in the Drosophila brain. , 2013, Cold Spring Harbor protocols.

[6]  Volker Hartenstein,et al.  Recurrent Circuitry for Balancing Sleep Need and Sleep , 2018, Neuron.

[7]  Michael Unser,et al.  A pyramid approach to subpixel registration based on intensity , 1998, IEEE Trans. Image Process..

[8]  Qili Liu,et al.  Sleep Drive Is Encoded by Neural Plastic Changes in a Dedicated Circuit , 2016, Cell.

[9]  R. Strauss,et al.  A higher control center of locomotor behavior in the Drosophila brain , 1993, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[10]  G. Buzsáki,et al.  Neuronal Oscillations in Cortical Networks , 2004, Science.

[11]  Gero Miesenböck,et al.  Neuronal Machinery of Sleep Homeostasis in Drosophila , 2014, Neuron.

[12]  M. Heisenberg.  Mushroom body memoir: from maps to models , 2003, Nature Reviews Neuroscience.

[13]  Lei Jin,et al.  Monitoring Brain Activity with Protein Voltage and Calcium Sensors , 2015, Scientific Reports.

[14]  Gaby Maimon,et al.  A neural circuit architecture for angular integration in Drosophila , 2017, Nature.

[15]  V. Pieribone,et al.  Genetically Targeted Optical Electrophysiology in Intact Neural Circuits , 2013, Cell.

[16]  P. Waldmeier,et al.  Presynaptic GABA Receptors , 1990, Annals of the New York Academy of Sciences.

[17]  Evan W. Miller,et al.  Voltage Imaging: Pitfalls and Potential. , 2017, Biochemistry.

[18]  Michael Z. Lin,et al.  Genetically encoded indicators of neuronal activity , 2016, Nature Neuroscience.

[19]  Brain activity. , 2014, Nature nanotechnology.

[20]  Gregory S.X.E. Jefferis,et al.  Functional and Anatomical Specificity in a Higher Olfactory Centre , 2018 .

[21]  D. Owald,et al.  Network-Specific Synchronization of Electrical Slow-Wave Oscillations Regulates Sleep Drive in Drosophila , 2019, Current Biology.

[22]  Johannes Felsenberg,et al.  Activity of Defined Mushroom Body Output Neurons Underlies Learned Olfactory Behavior in Drosophila , 2015, Neuron.

[23]  Meghana Holla,et al.  A Circadian Output Circuit Controls Sleep-Wake Arousal in Drosophila , 2018, Neuron.

[24]  Erich Schröger,et al.  Digital filter design for electrophysiological data – a practical approach , 2015, Journal of Neuroscience Methods.

[25]  Peng Zou,et al.  Genetically-encoded voltage indicators , 2017 .

[26]  Alexander Gottschalk,et al.  Rhodopsin-based voltage imaging tools for use in muscles and neurons of Caenorhabditis elegans , 2019, Proceedings of the National Academy of Sciences.

[27]  Akihiro Kusumi,et al.  Confined diffusion of transmembrane proteins and lipids induced by the same actin meshwork lining the plasma membrane , 2016, Molecular biology of the cell.

[28]  Avishek Adhikari,et al.  Cross-correlation of instantaneous amplitudes of field potential oscillations: A straightforward method to estimate the directionality and lag between brain areas , 2010, Journal of Neuroscience Methods.

[29]  Jörg R. P. Geiger,et al.  NOSA, an Analytical Toolbox for Multicellular Optical Electrophysiology , 2020, Frontiers in Neuroscience.

[30]  Rainer W Friedrich,et al.  Temporal Dynamics and Latency Patterns of Receptor Neuron Input to the Olfactory Bulb , 2006, The Journal of Neuroscience.

[31]  Michael Z. Lin,et al.  Fast two-photon imaging of subcellular voltage dynamics in neuronal tissue with genetically encoded indicators , 2017, eLife.

[32]  Pengcheng Zhou,et al.  CaImAn an open source tool for scalable calcium imaging data analysis , 2019, eLife.

[33]  R. Yuste,et al.  The Brain Activity Map Project and the Challenge of Functional Connectomics , 2012, Neuron.

[34]  Matt Wachowiak,et al.  Optical Dissection of Odor Information Processing In Vivo Using GCaMPs Expressed in Specified Cell Types of the Olfactory Bulb , 2013, The Journal of Neuroscience.

[35]  T. Miyashita,et al.  Mg2+ Block of Drosophila NMDA Receptors Is Required for Long-Term Memory Formation and CREB-Dependent Gene Expression , 2012, Neuron.

[36]  Michael Z. Lin,et al.  High-fidelity optical reporting of neuronal electrical activity with an ultrafast fluorescent voltage sensor , 2014, Nature Neuroscience.

[37]  Germán Sumbre,et al.  An integrated calcium imaging processing toolbox for the analysis of neuronal population dynamics , 2017, PLoS Comput. Biol..

[38]  Hitoshi Okamoto,et al.  Optical interrogation of neuronal circuitry in zebrafish using genetically encoded voltage indicators , 2018, Scientific Reports.

[39]  D. Owald,et al.  Network-specific synchronization of electrical slow-wave oscillations regulates sleep in Drosophila , 2019, bioRxiv.

[40]  Douglas A. Storace,et al.  Measuring the olfactory bulb input-output transformation reveals a contribution to the perception of odorant concentration invariance , 2017, Nature Communications.

[41]  Benjamin F. Grewe,et al.  High-speed recording of neural spikes in awake mice and flies with a fluorescent voltage sensor , 2015, Science.

[42]  Markus Schuelke,et al.  Gamma oscillations in the hippocampus require high complex I gene expression and strong functional performance of mitochondria. , 2011, Brain : a journal of neurology.

[43]  S. Schuchmann,et al.  Ca2+ signalling and changes of mitochondrial function during low‐Mg2+‐induced epileptiform activity in organotypic hippocampal slice cultures , 2001, The European journal of neuroscience.

[44]  Aljoscha Nern,et al.  Neural signatures of dynamic stimulus selection in Drosophila , 2017, Nature Neuroscience.

[45]  Fang Zhang,et al.  Fan-Shaped Body Neurons in the Drosophila Brain Regulate Both Innate and Conditioned Nociceptive Avoidance. , 2018, Cell reports.

[46]  Johannes D. Seelig,et al.  Feature detection and orientation tuning in the Drosophila central complex , 2013, Nature.

[47]  G. Laurent,et al.  Role of GABAergic Inhibition in Shaping Odor-Evoked Spatiotemporal Patterns in the Drosophila Antennal Lobe , 2005, The Journal of Neuroscience.

[48]  U. Heinemann,et al.  Seizure‐induced microvascular injury is associated with impaired neurovascular coupling and blood–brain barrier dysfunction , 2019, Epilepsia.

[49]  Michael Broxton,et al.  Fast near-whole–brain imaging in adult Drosophila during responses to stimuli and behavior , 2015, bioRxiv.

[50]  Helen H Yang,et al.  Genetically Encoded Voltage Indicators: Opportunities and Challenges , 2016, The Journal of Neuroscience.

[51]  Li Yan McCurdy,et al.  Presynaptic GABA Receptors Mediate Temporal Contrast Enhancement in Drosophila Olfactory Sensory Neurons and Modulate Odor-Driven Behavioral Kinetics , 2016, eNeuro.

[52]  Brian B. Avants,et al.  Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain , 2008, Medical Image Anal..

[53]  Wagner Steuer Costa,et al.  Rhodopsin-based voltage imaging tools for use in excitable cells of Caenorhabditis elegans , 2019, bioRxiv.

[54]  Bradley J. Baker,et al.  Toward Better Genetically Encoded Sensors of Membrane Potential , 2016, Trends in Neurosciences.

[55]  Maxime Descoteaux,et al.  Dipy, a library for the analysis of diffusion MRI data , 2014, Front. Neuroinform..