Maestro

I have recently ported Maestro to run under Windows 11 Professional (update 23H2) and RTX64 4.5. The new version has been released as Maestro 5.0.0. Releases 5.0.1 and 5.0.2 implemented a number of requested features; these new features will not be backported to Maestro 4.x. The source code for the last 4.x release, Maestro 4.2.1, is available at src/maestro4.2.1_codebase.

NOTE: As of Jan 2025, I will no longer be actively developing Maestro/RMVideo. I have made this repo available for anyone in the neuroscience community that continues to use the application and might wish to fork the repo to adapt or modify the program for their own purposes.

Maestro is a Windows® application developed in Stephen G. Lisberger's laboratory at Duke University to conduct a wide variety of behavioral and neurophysiological experiments focusing on smooth pursuit eye movements, the vestibular ocular reflex (VOR), and certain other aspects of the visual system. It provides real-time data acquisition and stimulus control to meet the particular research needs of the laboratory, and it is specifically tailored to the experimental apparatus employed there.

Maestro experiments record behavioral and neuronal responses to visual stimuli. Eye movement and neurophysiological data are recorded at 1KHz. Some experimental protocols require the ability to adapt predefined target trajectories during runtime in accordance with the subject’s behavioral response. The potential complexity of experiments that animate multiple targets simultaneously, along with the need to adjust target trajectories during runtime, place a premium on efficient communications with the relevant hardware and demand sub-millisecond responsiveness.

Maestro was developed to meet these operational demands. Over the years it has evolved from a distributed program with components hosted on a UNIX workstation and two DOS PCs to an all-in-one Windows NT/2000/XP application running on a single machine. In its latest form, the application is once again distributed in nature, consisting of three functional modules. The user defines, modifies, and executes experimental protocols via a graphical user interface (GUI). The GUI module, acting as the “master”, sends protocol information and issues a variety of commands to the experiment control and hardware interface. The hardware controller is the time-intensive component of Maestro and does most of the heavy lifting: communication with PC peripheral devices, controlling frame-by-frame animation of visual targets during a trial, recording and saving data streams, and providing feedback to the GUI in the form of status messages, data traces, and current eye and target positions. The controller is spawned by the GUI module at startup and runs as a "real-time", kernel-level process within IntervalZero's RealTime Extension (RTX) to Windows. The two modules run on a Windows workstation and communicate over interprocess shared memory. A third functional module, the OpenGL application RMVideo, drives the primary visual stimulus display -- a large, high-performance CRT monitor. This module runs on a separate Linux workstation and communicates with the Maestro hardware controller over a private, dedicated Ethernet link.

User Guide

An online user's guide provides a thorough introduction to the program, detailed information about system requirements and supported hardware, usage instructions, a complete version history, and a downloads page where you can get the latest release. The online guide also covers RMVideo, which is Maestro's workhorse visual stimulus platform (running on a separate Linux workstation); JMWork, a Java application that reads and edits Maestro data files; and several Maestro-related utilities for Matlab.

Installation

Installing Maestro itself is relatively easy using the self-extracting installer that is available for download from the online guide. But there's a lot more to it than installing software to get a Maestro experiment rig up and running with RMVideo as the stimulus platform. See the Installation chapter in the online guide for full details on deploying Maestro to a Windows10/RTX64 workstation and RMVideo to a Linux 14.x or 18.x machine.

License

Maestro, RMVideo, and the related Matlab tools were created by Scott Ruffner. All of the software is free to use under the terms of the MIT license.

Credits

Maestro was developed with funding provided by the Stephen G. Lisberger laboratory in the Department of Neurobiology at Duke University. It evolved from Dr. Lisberger's UNIX-based Cntrlx application.

Repository Contents

• maestro5dev.sln : The VS 2022 "solution" file for coding and building Maestro version 5.x.
• cxdriver, maestroGUI: The maestro5dev solution contains two projects, one for developing/building cxdriver.rtss and one for maestro.exe. The VS 2022 project files for these two projects are located in these folders. NOTE that the project files contain absolute paths, which are based on the fact that the solution folder (also the root folder for the local repo) is located at C:\maestro5dev.
• external/lib : Contains two files required for Maestro's connection to the Eyelink system from SR Research. These were extracted from the latest version of the Eyelink SDK, supporting Windows 10/11:
  • eyelink_core64.dll: The DLL that must be included in the Maestro 5 installer.
  • eyelink_core64.lib: The corresponding library that is required to build maestro.exe.
• external/includes/eyelink: Eyelink-related header files required to build maestro.exe.
• external/includes/rmvideo/rmvideo_common.h : A header file required to build both maestro.exe and RMVideo. It defines structures and constants that implement the communication interface between Maestro and RMVideo.
• installer: Files needed to build the self-extracting installer for Maestro version 5.x.
• sample_experiments: Sample Maestro experiment documents (used for testing).
• src: The root source folder, containing all source code, resource and other supporting files:
  • cxdriver: Source code for building cxdriver.rtss, the hardware controller for Maestro that runs as a separate RTX64 process.
  • gui: Source code for building maestro.exe, the Maestro GUI in which user defines and runs experiments.
  • rmvideo: Root folder containing all source code and other files needed to build RMVideo.
    • Ubuntu14: For building RMVideo to run on Lubuntu 14.04. Includes a Makefile. The versions folder contains "readmes" for the most recent and past versions, indicating Maestro version compatibility. See online guide for more information on building the rmvideo executable and configuring the Linux workstation appropriately.
    • Ubuntu18: For building RMVideo to run on Lubuntu 18.04. This version has been tested successfully but is not in use in any labs, AFAIK.
    • doc: Contains some sample xorg.conf files and msimcmds.txt, a file containing a simulated Maestro command sequence. It is used to test RMVideo without connecting to Maestro.
    • media_bup: Contains some sample image and video files used to test RMVideo.
  • maestro4.2.1_codebase: For reference, this contains the state of the Maestro codebase for Version 4.2.1 (supporting Win10/RTX64 3.4), before I began porting the code to Windows 11/RTX64 4.5. In addition to the cxdriver and gui source folders, it includes:
    • installer: Files needed to build the self-extracting installer for Maestro 4.x.
    • visual_studio : Project files for building maestro.exe and cxdriver.rtss for Maestro 4.x in Visual Studio 2017.
  • utilties_for_matlab:
    • miscellaneous, rmvplaid: Matlab scripts implementing a number of Maestro/RMVideo-related tools. All of these are described in the online guide, but none are actively used AFAIK.
    • plexon: Matlab files implementing the plexmon() application, which monitors the event stream of the Plexon Multiacquisition Processor (MAP) and passes timestamp data to a 'trial handler' function. See the plexmon.m file for more details. The Plexon MAP has been superceded by the Omniplex system, and AFAIK plexmon() is no longer used.
    • readcxdata: C source code files for building the Matlab MEX functions readcxdata() and editcxdata(). The former is used to load a Maestro data file's contents into Matlab for further analysis, while the latter can be used to clear or edit analysis actions that are appended to the data file without altering the original recorded data. See the releases directory for readmes on previous versions (the MEX functions were updated each time the Maestro data file format changed), as well as instructions for building the MEX functions.