Category: Uncategorized

Pulse Pal

July 12, 2017

Josh Sanders has also shared the following with OpenBehavior regarding Pulse Pal, an open source pulse train generator. Pulse Pal and Bpod, featured earlier, were both created by Sanworks.

Pulse Pal is an Arduino-powered device that generates precise sequences of voltage pulses for neural stimulation and stimulus control. It is controlled either through its APIs in MATLAB, Python and C++, or as a stand-alone instrument using its oLED screen and a clickable thumb joystick. Pulse Pal can play independent stimulus trains on its output channels. These trains are either defined parametrically, or pulse-wise by specifying each pulse’s onset time and voltage. Two optically isolated TTL trigger channels can each be mapped to any subset of the output channels, which can range between -10V and +10V, and deliver pulses as short as 100µs. This feature set allows Pulse Pal to serve as an open-source alternative to commercial stimulation timing devices, i.e. Master 8 (AMPI), PSG-2 (ISSI), Pulsemaster A300 (WPI), BPG-1 (Bak Electronics), StimPulse PGM (FHC Inc.) and Multistim 3800 (A-M Systems).

Because Pulse Pal is an Arduino-powered device, modifying its firmware for custom applications is within the capabilities of most modern Neuroscience research labs. As an example, the Pulse Pal’s Github repository provides an alternative firmware for the device, that entirely repurposes it as a waveform generator. In this configuration, a user can specify a waveform, frequency, amplitude and max playback duration, and toggle playback by TTL pulse with ~100µs latency. The firmware can also loop custom waveforms up to 40,000 samples long.

Pulse Pal was first published in 2014, by Josh Sanders while he was a student in Kepecs Lab at Cold Spring Harbor Laboratory. A significantly improved second-generation stimulator (Pulse Pal 2) became available in early 2016, coincident with the opening of Sanworks LLC. Over the past year, >125 Pulse Pal 2 devices were sold at $545 each by the Sanworks assembly service, while several labs elected to build their own. The initial success of this product demonstrates that fully open-source hardware can make headway against closed-source competitors in the Neuroscience instrumentation niche market.

Sanworks Github page for Pulse Pal may be found here

The Wiki page for Pulse Pal, including assembly instructions, may be found here.

Bpod

July 10, 2017

Josh Sanders has shared the following with OpenBehavior regarding Bpod, an open platform for precision animal behavior measurement created by Sanworks.

Bpod is a measurement and control system for behavior research, most often used to implement operant (Go/NoGo, 2AFC) tasks. Its software controls a hierarchy of hardware modules, each powered by an Arduino-programmable microcontroller. Atop the heiarchy is a “state machine” module that accepts an abstract trial definition, relating detected behavioral events to progression through user-defined hardware states. On trial start, the module serves as a real-time controller in parallel with the non-real-time computer, reading inputs and updating outputs in 100µs cycles until it reaches an exit state. Measured events are then returned to the computer, where software updates user-defined online plots, and loads the next trial’s state machine.

The Bpod state machine has on-board hardware interfaces for TTL logic and behavior ports (a.k.a. nosepokes) containing a photogate to detect snout entry, a miniature solenoid valve for liquid reward, and a visible LED to deliver cues and feedback. Modules under state machine control specialize in larger solenoids, analog input and output, direct digital synthesis, and a gamepad interface (for human research). An Arduino shield is provided, for users to interface new sensors and actuators with the state machine.

By handling the time-critical logic relating measurements to environment control in an open-source embedded computing environment, the Bpod system provides experimenters with a powerful family of tools for rigor and automation in behavioral research.

Sanworks’ GitHub may be found here.

The Wiki page for Bpod, including assembly instructions and Bill of Materials may be found here. 

Operant Box for Auditory Tasks (OBAT)

June 2, 2017

Mariana de Araújo has shared the following regarding OBAT, an operant box designed for auditory tasks developed at the Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Macaiba, Brazil. 

Fig. 1
Overview of the OBAT, inside the sound-attenuating chamber with the door open. External sources of heating were left outside the chamber: (a) Arduino Mega 2560 and shields and (b) the power amplifier. The modules controlling sound delivery, the response bars, and reward delivery can be seen in this lateral view: (c) speaker, (d) retractable bars, (e) reward delivery system, and (f) reward dispenser. The animal was kept inside the (g) Plexiglas chamber, and monitored by an (h) internal camera mounted on the wall of the (i) sound isolation chamber

OBAT is a low cost operant box designed to train small primates in auditory tasks. The device presents auditory stimuli via a MP3 player shield connected to an Arduino Mega 2560 through an intermediate, custom-made shield. It also controls two touch-sensitive bars and a reward delivery system. A Graphical User Interface allows the experimenter to easily set the parameters of the experimental sessions. All board schematics, source code, equipment specification and design are available at GitHub and at the publication. Despite its low cost, OBAT has a high temporal accuracy and reliably sends TTL signals to other equipment. Finally, the device was tested with one marmoset, showing that it can successfully be used to train these animals in an auditory two-choice task.

Ribeiro MW, Neto JFR, Morya E, Brasil FL, de Araújo MFP (2017) OBAT: An open-source and low- cost operant box for auditory discriminative tasks. Behav Res Methods. doi: 10.3758/s13428-017-0906-6

FinchScope

May 19th, 2017 

William Liberti, from the Gardner Lab out of Boston University, has shared the following with Open Behavior regarding ‘FinchScope’. Although originally designed for finches, the 3D printed single-photon fluorescent imaging microscope has since been adapted for rodents and other avian species.

The FinchScope project aims to provide a modular in-vivo optophysiology rig for awake, freely behaving animals, with a transparent acquisition and analysis pipeline. The goal is to produce a customizable and scaleable single-photon fluorescent imaging microscope system that takes advantage of developing open-source analysis platforms. These tools are built from easily procured off-the-shelf components and 3D printed parts.
We provide designs for a 3D printed,  lightweight, wireless-capable microscope and motorized commutator, designed for multi-month monitoring the neural activity (via genetically encoded calcium indicators) of zebra finches while they sing their courtship songs. It has since been adapted for rodents, and to other birds such as canaries.
The Github project page can be found here.
Link to share: https://edspace.american.edu/openbehavior/2017/05/19/finchscope/

Nose Poke Device

April 20, 2017 

Andre Chagas, creator of OpenNeuroscience, has generously shared the following with OpenBehavior regarding an arduino-based, 3D-printed nose poke device:

“This nose poke device was built as “proof-of-principle”. The idea was to show that scientists too can leverage from the open source philosophy and the knowledge built by the community that is developing around open source hardware. Moreover, the bill of materials was kept simple and affordable. One device can be built for ~25 dollars and should take 2-3 hours to build, including the time to print parts.

The device is organised as follows: The 3D printed frame (which can also be built with other materials when a printer is not available) contains a hole where the animals are expected to insert their snouts. At the front part of the hole, an infrared led is aligned with an infrared detector. This forms an “infrared curtain” at the hole’s entrance. If this curtain is interrupted, a signal is sent to a microcontroller (an Arduino in this case), and it can be used to trigger other electronic components, such as a water pump, or an led indicator, or in this case a Piezo buzzer.
At the back of the hole, a white LED is placed to indicate that the system is active and ready for “nose pokes”.

The microcontroller, contains the code responsible for controlling the electronic parts, and can easily be changed, as it is written for Arduino and several code examples/tutorials (for begginners and experts) can be found online.”

Find more documentation on FigShare and Open Neuroscience.

Link to share:  https://edspace.american.edu/openbehavior/2017/04/20/nose-poke-device/

Pixying Behavior

APril 3, 2017 

Robert Sachdev, from the Neurocure Cluster of Excellence, Humboldt Universität Zu Berlin, Germany, has generously shared the following regarding automated optical tracking of animal movement: 

“We have developed a method for tracking the motion of whiskers, limbs and whole animals in real-time. We show how to use a plug and play Pixy camera to monitor the real-time motion of multiple colored objects and apply the same tools for post-hoc analysis of high-speed video. Our method has major advantages over currently available methods: we can track the motion of multiple adjacent whiskers in real-time, and apply the same methods post-hoc, to “recapture” the same motion at a high temporal resolution.  Our method is flexible; it can track objects that are similarly shaped like two adjacent whiskers, forepaws or even two freely moving animals. With this method it becomes possible to use the phase of movement of particular whiskers or a limb to perform closed-loop experiments.”

Link to share:  https://edspace.american.edu/openbehavior/2017/04/03/pixying-behavior/

Figure using Pixy for two adjacent whiskers A. Setup. Head-fixed mice are acclimatized to whisker painting, and trained to use their whiskers to contact a piezo-film touch sensor. A Pixy camera is used to track whiskers in real-time (left), a high-speed color camera is used simultaneously to acquire data. B. Paradigm for whisker task. A sound-cue initiates the trial. The animal whisks one of the two painted whiskers into contact with a piezo-film sensor and if contact reaches threshold, the animal obtains a liquid reward. There is a minimum inter-trial interval of 10 seconds. C, Capturing whisker motion in real-time. The movement and location of the D1 and D2 whiskers shown at two consecutive time points (20 ms apart, left & right images). Lines corresponding to the location of the two whiskers (middle panel) acquired with Spike2 software. The waveform of whisker data reflects the spatial location and the dimensions of the tracked box around the whisker, which can both change as the whisker moves
Nashaat, M. A., Oraby, H., Blanco, L., Dominiak, S., Larkum, M. E., & Sachdev, R. N. S. (2017). Pixying Behavior: A Versatile Real-Time and Post-Hoc Automated Optical Tracking Method for Freely Moving and Head Fixed Animals. eNeuro, ENEURO.0245-16.2017. https://doi.org/10.1523/ENEURO.0245-16.2017