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 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 Recovery of dynamics and function in spiking neural networks by closed-loop control

2015 ◽  
Author(s):  
Ioannis Vlachos ◽  
Taskin Deniz ◽  
Ad Aertsen ◽  
Arvind Kumar
Keyword(s):  
Neural Networks ◽  
Closed Loop ◽  
Brain Activity ◽  
Open Loop ◽  
Spiking Neural Networks ◽  
Delayed Feedback Control ◽  
Loop Control ◽  
Wide Range ◽  
Underlying Network ◽  
And Function

There is a growing interest in developing novel brain stimulation methods to control disease-related aberrant neural activity and to address basic neuroscience questions. Conventional methods for manipulating brain activity rely on open-loop approaches that usually lead to excessive stimulation and, crucially, do not restore the original computations performed by the network. Thus, they are often accompanied by undesired side-effects. Here, we introduce delayed feedback control (DFC), a conceptually simple but effective method, to control pathological oscillations in spiking neural networks. Using mathematical analysis and numerical simulations we show that DFC can restore a wide range of aberrant network dynamics either by suppressing or enhancing synchronous irregular activity. Importantly, DFC besides steering the system back to a healthy state, it also recovers the computations performed by the underlying network. Finally, using our theory we isolate the role of single neuron and synapse properties in determining the stability of the closed-loop system.

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.

scholarly journals A framework for closed-loop neurofeedback for real-time EEG decoding

2019 ◽  
Author(s):  
Greta Tuckute ◽  
Sofie Therese Hansen ◽  
Troels Wesenberg Kjaer ◽  
Lars Kai Hansen
Keyword(s):  
Real Time ◽  
Closed Loop ◽  
Brain Activity ◽  
Time Signal ◽  
Software Framework ◽  
Cognitive State ◽  
Scalp Eeg ◽  
State Classification ◽  
Dry Electrode ◽  
Wide Range

AbstractNeurofeedback based on real-time brain imaging allows for targeted training of brain activity with demonstrated clinical applications. A rapid technical development of electroen-cephalography (EEG)-based systems and an increasing interest in cognitive training has lead to a call for accessible and adaptable software frameworks. Here, we present and outline the core components of a novel open-source neurofeedback framework based on scalp EEG signals for real-time neuroimaging, state classification and closed-loop feedback.The software framework includes real-time signal preprocessing, adaptive artifact rejection, and cognitive state classification from scalp EEG. The framework is implemented using exclusively Python source code to allow for diverse functionality, high modularity, and easy extendibility of software development depending on the experimenter’s needs.As a proof of concept, we demonstrate the functionality of our new software framework by implementing an attention training paradigm using a consumer-grade, dry-electrode EEG system. Twenty-two participants were trained on a single neurofeedback session with behavioral pre- and post-training sessions within three consecutive days. We demonstrate a mean decoding error rate of 34.3% (chance=50%) of subjective attentional states. Hence, cognitive states were decoded in real-time by continuously updating classification models on recently recorded EEG data without the need for any EEG recordings prior to the neurofeedback session.The proposed software framework allows a wide range of users to actively engage in the development of novel neurofeedback tools to accelerate improvements in neurofeedback as a translational and therapeutic tool.

A Playbook(trademark) for Real-Time, Closed-Loop Control

2005 ◽  
Author(s):  
Harry Funk ◽  
Robert Goldman ◽  
Christopher Miller ◽  
John Meisner ◽  
Peggy Wu
Keyword(s):  
Real Time ◽  
Closed Loop ◽  
Closed Loop Control ◽  
Loop Control

scholarly journals Evaluation of Optimal Vibrotactile Feedback for Force-Controlled Upper Limb Myoelectric Prostheses

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5209 ◽  
Author(s):  
Andrea Gonzalez-Rodriguez ◽  
Jose L. Ramon ◽  
Vicente Morell ◽  
Gabriel J. Garcia ◽  
Jorge Pomares ◽  
...  
Keyword(s):  
Real Time ◽  
Upper Limb ◽  
Closed Loop ◽  
Fine Tuning ◽  
Vibrotactile Feedback ◽  
Loop Control ◽  
Myoelectric Prostheses ◽  
Amplitude Level ◽  
Real Time Application ◽  
Selection Of

The main goal of this study is to evaluate how to optimally select the best vibrotactile pattern to be used in a closed loop control of upper limb myoelectric prostheses as a feedback of the exerted force. To that end, we assessed both the selection of actuation patterns and the effects of the selection of frequency and amplitude parameters to discriminate between different feedback levels. A single vibrotactile actuator has been used to deliver the vibrations to subjects participating in the experiments. The results show no difference between pattern shapes in terms of feedback perception. Similarly, changes in amplitude level do not reflect significant improvement compared to changes in frequency. However, decreasing the number of feedback levels increases the accuracy of feedback perception and subject-specific variations are high for particular participants, showing that a fine-tuning of the parameters is necessary in a real-time application to upper limb prosthetics. In future works, the effects of training, location, and number of actuators will be assessed. This optimized selection will be tested in a real-time proportional myocontrol of a prosthetic hand.

scholarly journals The Modelling, Simulation and FPGA-Based Implementation for Stepper Motor Wide Range Speed Closed-Loop Drive System Design

Machines ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 56 ◽  
Author(s):  
Chiu-Keng Lai ◽  
Jhang-Shan Ciou ◽  
Chia-Che Tsai
Keyword(s):  
Embedded System ◽  
High Speed ◽  
Closed Loop ◽  
Open Loop ◽  
Drive System ◽  
Stepper Motor ◽  
Motor Drive ◽  
Digital Controllers ◽  
Loop Control ◽  
Wide Range

Owing to the benefits of programmable and parallel processing of field programmable gate arrays (FPGAs), they have been widely used for the realization of digital controllers and motor drive systems. Furthermore, they can be used to integrate several functions as an embedded system. In this paper, based on Matrix Laboratory (Matlab)/Simulink and the FPGA chip, we design and implement a stepper motor drive. Generally, motion control systems driven by a stepper motor can be in open-loop or closed-loop form, and pulse generators are used to generate a series of pulse commands, according to the desired acceleration/run/deceleration, in order to the drive system to rotate the motor. In this paper, the speed and position are designed in closed-loop control, and a vector control strategy is applied to the obtained rotor angle to regulate the phase current of the stepper motor to achieve the performance of operating it in low, medium, and high speed situations. The results of simulations and practical experiments based on the FPGA implemented control system are given to show the performances for wide range speed control.

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