John Hayes

ORCID iD
https://orcid.org/0000-0003-2849-7672
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John A. Hayes

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John Hayes (2014-07-21)

  • Country
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United States

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John Hayes (2016-01-24)

  • Keywords
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neurophysiology,

Sources:
John Hayes (2014-05-26)

respiratory rhythm generation,

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John Hayes (2014-05-26)

preBötzinger Complex

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John Hayes (2014-05-26)

  • Websites
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PhysImage software

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John Hayes (2016-01-28)

Ablator software

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John Hayes (2016-01-28)

NeuronetExperimenter software

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John Hayes (2016-01-28)

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John Hayes (2015-09-03)

Biography

I consider myself mainly an experimental neurophysiologist with a strong background and aptitude for engineering and physical approaches to answering scientific questions. I also have a strong interest in models of biological behavior, especially in the neurosciences, and how these approaches/models can inform new experimental designs. My central interest has been the emergence of neuronal rhythms in the brain, with particular focus on the emergence of central respiratory rhythm generation and modulation, but I love all neuroscience and would be happy to contribute in nearly any area from molecules->cells->networks->systems->behaviors in vivo, in situ, and in vitro. PROFESSIONAL SKILLS • Advanced computational modeling, image-processing, and Unix/Linux software development including expertise in the following tools, software libraries, and programming languages: XPPAUT, Matlab/Octave, C/C++, Java, Python, BeanShell, R, Igor Pro, gnuplot, ImageJ, Micro-Manager, Adobe Illustrator/Photoshop, Zeiss LSM software, Olympus software, bash, JFreechart, Jython, OpenMPI, and many more. • Mathematical modeling of neurons and populations of neurons • Whole-cell/single-channel electrophysiological recordings of neurons within tissue slices, in situ preparations, or cultures • Nerve and field-recording of populations of neurons • Live cell Ca2+-imaging using epifluorescence, and confocal or two-photon laser-scanning microscopy • Cryostat sectioning and immunohistochemical reconstruction of brain anatomy • Manipulation of optogenetic populations of neurons through light stimulation and imaging • Advanced analyses of the above types of data using custom software and other tools • Skilled with acquiring both traditional confocal microscopy and two-photon microscopy (both static and dynamic) • I have excellent experience with manipulating lasers on optical breadboards that are used in biotechnological applications, such as digital holography (i.e., aligning lasers, sending lasers through pinholes or onto spatial light modulators [SLMs], etc.) • I have special experience building electrical circuits for custom applications (i.e., sensor/controls in normal engineering parlance) TEACHING TOPICS • Neurophysiological Data Collection and Analysis • General Data Collection and Practical Analysis • Cellular/Systems Neuroscience • Cellular Biophysics and Modeling • Biophotonics • Digital Image Processing NEUROSCIENCE-RELATED SOFTWARE PROJECTS I have been instrumental in creating and contributing to the following Open Source and Neuroscience-related software projects: • NeuronetExperimenter (http://neuronetexp.sourceforge.net/) – a suite of modeling software that migrates users of XPPAUT (http://www.math.pitt.edu/~bard/xpp/xpp.html) to multi-neuronal networks of neurons. The connectivity of these networks can form arbitrary patterns, and this package also facilitates random-access to individual neurons throughout the simulation lifecycle and fine granularity in output options for post-analysis. This software is used in my peer-reviewed articles referenced under the “Hayes et al., 2008” and “Rubin*, Hayes*, et al., 2009“ papers. *contributed equally • Ablator (http://sourceforge.net/projects/ablator/) – a Python software package that automates detection of neurons based on either Ca2+-activity or fluorescent reporter lines and laser ablates the associated neurons in an automated and sequential fashion using 2- photon microscopy. The package also allows random-access to stage positions so that neuron cells/populations can be lesioned from an extensive array of X-Y positions. This software is used in my peer-reviewed articles referenced under the “Hayes*, Wang* et al., 2012” and “Wang*, Hayes*, et al., 2014” papers. *contributed equally • PhysImage (http://physimage.sourceforge.net) – a fork of the popular NIH ImageJ program that is designed to make ImageJ and Micro-Manager more useful for neurophysiologists. This incorporates such important characteristics as providing a centralized Python console for integrating all major ImageJ functionality. It also includes many other useful components for researchers such as cycle-triggered averaging of electrophysiology and calcium-imaging physiology, importation and chart generation of the popular Axon Instruments time-series data (whether imaging or electrophysiological), and the means of auto-generating complex journal-quality figures. This has been useful for experiments that require rapid analyses and automated adjustments during the course of an experiment, such as automated detection of cellular activity and subsequent stimulation of optogenetic targets. It is anticipated that this software will be used extensively in my peer-reviewed articles listed under “Hayes et al., 2014a” and “Hayes et al., 2014b”. The software is in limited use at the Salk and Karolinska Institutes, George Mason University, and at the Université Paris Descartes.
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