scholarly journals Open source modules for tracking animal behavior and closed-loop stimulation based on Open Ephys and Bonsai

2018 ◽  
Author(s):  
Alessio Paolo Buccino ◽  
Mikkel Elle Lepperød ◽  
Svenn-Arne Dragly ◽  
Philipp Häfliger ◽  
Marianne Fyhn ◽  
...  
Keyword(s):  
Open Source ◽  
Real Time ◽  
Closed Loop ◽  
Low Cost ◽  
Data Formats ◽  
Behavioral Tracking ◽  
Real Time Tracking ◽  
Set Up ◽  
And Behavior ◽  
Closed Loop Stimulation

AbstractObjectiveA major goal in systems neuroscience is to determine the causal relationship between neural activity and behavior. To this end, methods that combine monitoring neural activity, behavioral tracking, and targeted manipulation of neurons in closed-loop are powerful tools. However, commercial systems that allow these types of experiments are usually expensive and rely on non-standardized data formats and proprietary software which may hinder user-modifications for specific needs. In order to promote reproducibility and data-sharing in science, transparent software and standardized data formats are an advantage. Here, we present an open source, low-cost, adaptable, and easy to set-up system for combined behavioral tracking, electrophysiology and closed-loop stimulation.ApproachBased on the Open Ephys system (www.open-ephys.org) we developed multiple modules to include real-time tracking and behavior-based closed-loop stimulation. We describe the equipment and provide a step-by-step guide to set up the system. Combining the open source software Bonsai (bonsai-rx.org) for analyzing camera images in real time with the newly developed modules in Open Ephys, we acquire position information, visualize tracking, and perform tracking-based closed-loop stimulation experiments. To analyze the acquired data we provide an open source file reading package in Python.Main resultsThe system robustly visualizes real-time tracking and reliably recovers tracking information recorded from a range of sampling frequencies (30-1000Hz). We combined electrophysiology with the newly-developed tracking modules in Open Ephys to record place cell and grid cell activity in the hippocampus and in the medial entorhinal cortex, respectively. Moreover, we present a case in which we used the system for closed-loop optogenetic stimulation of entorhinal grid cells.SignificanceExpanding the Open Ephys system to include animal tracking and behavior-based closed-loop stimulation extends the availability of high-quality, low-cost experimental setup within standardized data formats serving the neuroscience community.

scholarly journals Toolkit for Oscillatory Real-time Tracking and Estimation (TORTE)

2021 ◽  
Author(s):  
Mark Schatza ◽  
Ethan Blackwood ◽  
Sumedh Nagrale ◽  
Alik S Widge
Keyword(s):  
Open Source ◽  
Real Time ◽  
Closed Loop ◽  
Brain Activity ◽  
Loop Control ◽  
Oscillatory Phase ◽  
Wide Range ◽  
Real Time Tracking ◽  
Therapeutic Tools ◽  
And Behavior

Closing the loop between brain activity and behavior is one of the most active areas of development in neuroscience. There is particular interest in developing closed-loop control of neural oscillations. Many studies report correlations between oscillations and functional processes. Oscillation-informed closed-loop experiments might determine whether these relationships are causal and would provide important mechanistic insights which may lead to new therapeutic tools. These closed-loop perturbations require accurate estimates of oscillatory phase and amplitude, which are challenging to compute in real time. We developed an easy to implement, fast and accurate Toolkit for Oscillatory Real-time Tracking and Estimation (TORTE). TORTE operates with the open-source Open Ephys GUI (OEGUI) system, making it immediately compatible with a wide range of acquisition systems and experimental preparations. TORTE efficiently extracts oscillatory phase and amplitude from a target signal and includes a variety of options to trigger closed-loop perturbations. Implementing these tools into existing experiments is easy and adds minimal latency to existing protocols. Most labs use in-house lab-specific approaches, limiting replication and extension of their experiments by other groups. Accuracy of the extracted analytic signal and accuracy of oscillation-informed perturbations with TORTE match presented results by these groups. However, TORTE provides access to these tools in a flexible, easy to use toolkit without requiring proprietary software. We hope that the availability of a high-quality, open-source, and broadly applicable toolkit will increase the number of labs able to perform oscillatory closed-loop experiments, and will improve the replicability of protocols and data across labs.

scholarly journals An Intracortical Implantable Brain-Computer Interface for Telemetric Real-Time Recording and Manipulation of Neuronal Circuits for Closed-Loop Intervention

2021 ◽  
Vol 15 ◽  
Author(s):  
Hamed Zaer ◽  
Ashlesha Deshmukh ◽  
Dariusz Orlowski ◽  
Wei Fan ◽  
Pierre-Hugues Prouvot ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Real Time ◽  
Neuronal Activity ◽  
Closed Loop ◽  
Neural Circuit ◽  
Radio Communication ◽  
Computer Interfaces ◽  
Cerebral Mri ◽  
High Bandwidth ◽  
And Behavior

Recording and manipulating neuronal ensemble activity is a key requirement in advanced neuromodulatory and behavior studies. Devices capable of both recording and manipulating neuronal activity brain-computer interfaces (BCIs) should ideally operate un-tethered and allow chronic longitudinal manipulations in the freely moving animal. In this study, we designed a new intracortical BCI feasible of telemetric recording and stimulating local gray and white matter of visual neural circuit after irradiation exposure. To increase the translational reliance, we put forward a Göttingen minipig model. The animal was stereotactically irradiated at the level of the visual cortex upon defining the target by a fused cerebral MRI and CT scan. A fully implantable neural telemetry system consisting of a 64 channel intracortical multielectrode array, a telemetry capsule, and an inductive rechargeable battery was then implanted into the visual cortex to record and manipulate local field potentials, and multi-unit activity. We achieved a 3-month stability of the functionality of the un-tethered BCI in terms of telemetric radio-communication, inductive battery charging, and device biocompatibility for 3 months. Finally, we could reliably record the local signature of sub- and suprathreshold neuronal activity in the visual cortex with high bandwidth without complications. The ability to wireless induction charging combined with the entirely implantable design, the rather high recording bandwidth, and the ability to record and stimulate simultaneously put forward a wireless BCI capable of long-term un-tethered real-time communication for causal preclinical circuit-based closed-loop interventions.

scholarly journals Arduino based platform for process control learning

2020 ◽  
Vol 6 (5) ◽  
pp. 0585-0593
Author(s):  
Bruna Couto Molinar Henrique ◽  
Leonardo Couto Molinar Henrique ◽  
Humberto Molinar Henrique
Keyword(s):  
Open Source ◽  
Real Time ◽  
Low Cost ◽  
Control Unit ◽  
Absolute Error ◽  
Internal Model Control ◽  
Pid Controllers ◽  
Experimental Unit ◽  
Source Codes ◽  
Model Control

This work deals with implementation of an experimental flowrate control unit using free and low-cost hardware and software. The open-source software Processing was used to develop the source codes and user graphical interface and the open-source electronic prototyping platform Arduino was used to acquire data from an experimental unit. Work presents descriptions of the experimental setup, the real-time PID controllers used and theoretical/conceptual issues of Arduino. PID controllers based on internal model control, minimization of the integral of time-weighted absolute error, Ziegler-Nichols, and others were tuned for setpoint and load changes and real-time runs were carried out in order to make real-time use of  control theory learned in academy. Results showed the developed platform proved to be suitable for use in experimental setups allowing users compare their ideas and expectations with the experimental evidence in a real and low-cost fashion. In addition, the instrumentation is simple to configure with acceptable level noise and particularly useful for control/automation learning with educational purposes.

scholarly journals Real-Time Low-Cost Speed Monitoring and Control of Three-Phase Induction Motor via a Voltage/Frequency Control Approach

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Ali Hmidet ◽  
Olfa Boubaker
Keyword(s):  
Real Time ◽  
Induction Motor ◽  
Closed Loop ◽  
Low Cost ◽  
Closed Loop Control ◽  
Loop Control ◽  
Control Approach ◽  
Three Phase ◽  
Wide Range ◽  
Voltage Frequency

In this paper, a new design of a real-time low-cost speed monitoring and closed-loop control of the three-phase induction motor (IM) is proposed. The proposed solution is based on a voltage/frequency (V/F) control approach and a PI antiwindup regulator. It uses the Waijung Blockset which considerably alleviates the heaviness and the difficulty of the microcontroller’s programming task incessantly crucial for the implementation and the management of such complex applications. Indeed, it automatically generates C codes for many types of microcontrollers like the STM32F4 family, also used in this application. Furthermore, it offers a cost-effective design reducing the system components and increasing its efficiency. To prove the efficiency of the suggested design, not only simulation results are carried out for a wide range of variations in load and reference speed but also experimental assessment. The real-time closed-loop control performances are proved using the aMG SQLite Data Server via the UART port board, whereas Waijung WebPage Designer (W2D) is used for the web monitoring task. Experimental results prove the accuracy and robustness of the proposed solution.

Evaluation of a Low-Cost Microcontroller for Real-Time Control Education and Prototyping

2014 ◽  
Author(s):  
Ryan W. Krauss
Keyword(s):  
Feedback Control ◽  
Real Time ◽  
Closed Loop ◽  
Low Cost ◽  
Serial Communication ◽  
Real Time Control ◽  
Time Control ◽  
Active User ◽  
Bode Plots ◽  
Control Education

Arduino microcontrollers are popular, low-cost, easy-to-program, and have an active user community. This paper seeks to quantitatively assess whether or not Arduinos are a good fit for real-time feedback control experiments and controls education. Bode plots and serial echo tests are used to assess the use of Arduinos in two scenarios: a prototyping mode that involves bidirectional real-time serial communication with a PC and a hybrid mode that streams data in real-time over serial. The closed-loop performance with the Arduino is comparable to that of another more complicated and more expensive microcontroller for the plant considered. Some practical tips on using an Arduino for real-time feedback control are also given.

scholarly journals ROAD NETWORK COMPARISON AND MATCHING TECHNIQUES. A WORKFLOW PROPOSAL FOR THE INTEGRATION OF TRAFFIC MESSAGE CHANNEL AND OPEN SOURCE NETWORK DATASETS

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1503-1509
Author(s):  
A. Ajmar ◽  
E. Arco ◽  
P. Boccardo
Keyword(s):  
Open Source ◽  
Real Time ◽  
Road Network ◽  
Open Data ◽  
Added Value ◽  
Heterogeneous Databases ◽  
Geographic Datasets ◽  
Wide Availability ◽  
Set Up ◽  
Matching Techniques

<p><strong>Abstract.</strong> The rapid growth of methods and techniques to acquire geospatial data has led to a wide availability of overlapping geographic datasets with different characteristics. Road network data sources are today a significant number, with high differences in level of detail and modelling schemas, depending on the main purpose. In addition, continuous information about people and freight movement is today available also in real-time. This type of data is today exchanged between traffic operators using referencing standards as Traffic Message Channel. Integrating these heterogeneous databases, in order to build an added value product, is a serious task in geographical data management. The paper is focus on techniques to conflate the Traffic message Channel logical network on Open Source road network dataset, in order to allow the precise visualisation of traffic data also in real-time.</p><p>A first step of the research was the quality assessment of available Open Source (OS) road network dataset, then, a specific procedure to conflate data was set up, using an iterative process in order to reduce at every step the number of possible matching features. A first application of the enhanced OTM dataset is shown for the city of Turin: real-time open data of traffic flows recorded by road network fixed sensors, made available by the metropolitan Traffic Operation Centre (5T) and based on the TMC location referencing, are matched on the OTM road network, allowing a detailed real-time visualisation of traffic state.</p>

scholarly journals Creating and controlling visual environments using BonVision

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Gonçalo Lopes ◽  
Karolina Farrell ◽  
Edward A B Horrocks ◽  
Chi Yu Lee ◽  
Mai M Morimoto ◽  
...  
Keyword(s):  
Open Source ◽  
Real Time ◽  
Open Source Software ◽  
Brain Function ◽  
Deep Neural Networks ◽  
Closed Loop ◽  
Experimental Designs ◽  
Physiological Measurement ◽  
Graphical Programming ◽  
Time Interaction

Real-time rendering of closed-loop visual environments is important for next-generation understanding of brain function and behaviour, but is often prohibitively difficult for non-experts to implement and is limited to few laboratories worldwide. We developed BonVision as an easy-to-use open-source software for the display of virtual or augmented reality, as well as standard visual stimuli. BonVision has been tested on humans and mice, and is capable of supporting new experimental designs in other animal models of vision. As the architecture is based on the open-source Bonsai graphical programming language, BonVision benefits from native integration with experimental hardware. BonVision therefore enables easy implementation of closed-loop experiments, including real-time interaction with deep neural networks, and communication with behavioural and physiological measurement and manipulation devices.

Smart Gas Outflow Detection and Safety Circumstance System Using Cloud Technology

2017 ◽  
Vol 8 (3) ◽  
pp. 721
Author(s):  
Srikanth Kottalanka ◽  
D. Arivazhagan
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Electrical Power ◽  
Safety Device ◽  
Gas Leakage ◽  
Gas Cylinder ◽  
Cloud Server ◽  
Real Time Tracking ◽  
Precautionary Measures ◽  
E Mail

<p>The project aim is to design and develop a cloud connected smart LPG gas cylinder platform, acting as a safety device for detecting LPG gas drip at minimum levels to avoid any credible incidents. It is also capable of detect fire exists in the area and level of the gas in order to provide real time monitoring and alert over Cloud server. If an aberrant condition is detected, the device gives an alert to the smartphone app of the user and also sends an alert e-mail to other authorities. In addition to this upon detecting a gas leakage or a fire breakout, the device automatically takes safety precautionary measures, like gas valve closing, ventilation opening, fire sprinkler activation and home electrical power supply cut-off. The device connects to the internet via Wi-Fi and thus increasing the mobility of the platform within the premises of the house. A Wi-Fi capable ARM Cortex-M4 Launchpad is used to execute the system. This device proposes a complete, low-cost, powerful and accessible way of real-time tracking and distant control of gas leakages and preventive mechanisms in household and industrial areas.</p>

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