neurotic: Neuroscience Tool for Interactive Characterization

Abstract A software tool for synchronization of video with signals would be of broad general use to behavioral neuroscientists. A new program, called neurotic (NEUROscience Tool for Interactive Characterization), allows users to review and annotate signal data synchronized with video, performs simple initial analyses including signal filtering and spike detection, is easy to use, and supports a variety of file formats. The program also facilitates collaborations by using a portable specification for loading and processing data and retrieving data files from online sources. Two examples are shown in which the software is used to explore experimental datasets with extracellular nerve or muscle recordings and simultaneous video of behavior. The configuration specification for controlling how data are located, loaded, processed, and plotted is also summarized. Algorithms for spike detection and burst detection are demonstrated. This new program could be used in many applications in which behavior and signals need to be analyzed together.

[1]  John P. Aggleton,et al.  NeuroChaT: A toolbox to analyse the dynamics of neuronal encoding in freely-behaving rodents in vivo , 2019, Wellcome open research.

[2]  et al.,et al.  Jupyter Notebooks - a publishing format for reproducible computational workflows , 2016, ELPUB.

[3]  Wes McKinney,et al.  Data Structures for Statistical Computing in Python , 2010, SciPy.

[4]  Jeffrey P. Gill,et al.  Rapid Adaptation to Changing Mechanical Load by Ordered Recruitment of Identified Motor Neurons , 2020, eNeuro.

[5]  Jeffrey M. McManus,et al.  Extracellularly identifying motor neurons for a muscle motor pool in Aplysia californica. , 2013, Journal of visualized experiments : JoVE.

[6]  Fang-Chi Yang,et al.  Automated visual cognitive tasks for recording neural activity using a floor projection maze. , 2014, Journal of visualized experiments : JoVE.

[7]  Jeffrey P. Gill,et al.  Motor neuronal activity varies least among individuals when it matters most for behavior. , 2015, Journal of neurophysiology.

[8]  Jeffrey M. McManus,et al.  Differential activation of an identified motor neuron and neuromodulation provide Aplysia's retractor muscle an additional function. , 2014, Journal of neurophysiology.

[9]  Joel Nothman,et al.  SciPy 1.0-Fundamental Algorithms for Scientific Computing in Python , 2019, ArXiv.

[10]  H. Chiel,et al.  In vivo buccal nerve activity that distinguishes ingestion from rejection can be used to predict behavioral transitions in Aplysia , 1993, Journal of Comparative Physiology A.

[11]  Gaël Varoquaux,et al.  The NumPy Array: A Structure for Efficient Numerical Computation , 2011, Computing in Science & Engineering.

[12]  Pierre Yger,et al.  Neo: an object model for handling electrophysiology data in multiple formats , 2014, Front. Neuroinform..

[13]  Jeffrey M. McManus,et al.  Preparing the Periphery for a Subsequent Behavior: Motor Neuronal Activity during Biting Generates Little Force but Prepares a Retractor Muscle to Generate Larger Forces during Swallowing in Aplysia , 2015, The Journal of Neuroscience.

[14]  H. Chiel,et al.  Electrode fabrication and implantation in Aplysia californica for multi-channel neural and muscular recordings in intact, freely behaving animals. , 2010, Journal of visualized experiments : JoVE.

[15]  H. Chiel,et al.  Activity patterns of the B31/B32 pattern initiators innervating the I2 muscle of the buccal mass during normal feeding movements in Aplysia californica. , 1996, Journal of neurophysiology.