Proceedings #44: Closed-loop apparatus for brain state-dependent tES: a proof of principle based on SMR

2019 ◽  
Vol 12 (2) ◽  
pp. e114-e116
Author(s):  
Eliana Garcia-Cossio ◽  
Sophia Wunder ◽  
Klaus Schellhorn
Keyword(s):  
Closed Loop ◽  
Brain State ◽  
State Dependent ◽  
Proof Of Principle

Brain State-Dependent Transcranial Magnetic Closed-Loop Stimulation Controlled by Sensorimotor Desynchronization Induces Robust Increase of Corticospinal Excitability

2016 ◽  
Vol 9 (3) ◽  
pp. 415-424 ◽  
Author(s):  
Dominic Kraus ◽  
Georgios Naros ◽  
Robert Bauer ◽  
Fatemeh Khademi ◽  
Maria Teresa Leão ◽  
...  
Keyword(s):  
Closed Loop ◽  
Corticospinal Excitability ◽  
Brain State ◽  
State Dependent ◽  
Closed Loop Stimulation

Brain-state dependent non-invasive brain-stimulation with real-time closed-loop simultaneous EEG/TMS

2016 ◽  
Vol 127 (3) ◽  
pp. e41 ◽  
Author(s):  
C. Zrenner ◽  
J. Tünnerhoff ◽  
C. Zipser ◽  
F. Müller-Dahlhaus ◽  
U. Ziemann
Keyword(s):  
Real Time ◽  
Brain Stimulation ◽  
Closed Loop ◽  
Brain State ◽  
Non Invasive ◽  
State Dependent

scholarly journals Real-Time Implementation of EEG Oscillatory Phase-Informed Visual Stimulation Using a Least Mean Square-Based AR Model

2021 ◽  
Vol 11 (1) ◽  
pp. 38
Author(s):  
Aqsa Shakeel ◽  
Takayuki Onojima ◽  
Toshihisa Tanaka ◽  
Keiichi Kitajo
Keyword(s):  
Real Time ◽  
Closed Loop ◽  
Loop System ◽  
Ar Model ◽  
Brain State ◽  
Mean Square ◽  
Least Mean Square ◽  
Closed Loop System ◽  
Alpha Oscillations ◽  
State Dependent

It is a technically challenging problem to assess the instantaneous brain state using electroencephalography (EEG) in a real-time closed-loop setup because the prediction of future signals is required to define the current state, such as the instantaneous phase and amplitude. To accomplish this in real-time, a conventional Yule–Walker (YW)-based autoregressive (AR) model has been used. However, the brain state-dependent real-time implementation of a closed-loop system employing an adaptive method has not yet been explored. Our primary purpose was to investigate whether time-series forward prediction using an adaptive least mean square (LMS)-based AR model would be implementable in a real-time closed-loop system or not. EEG state-dependent triggers synchronized with the EEG peaks and troughs of alpha oscillations in both an open-eyes resting state and a visual task. For the resting and visual conditions, statistical results showed that the proposed method succeeded in giving triggers at a specific phase of EEG oscillations for all participants. These individual results showed that the LMS-based AR model was successfully implemented in a real-time closed-loop system targeting specific phases of alpha oscillations and can be used as an adaptive alternative to the conventional and machine-learning approaches with a low computational load.

scholarly journals A closed-loop optogenetic screen for neurons controlling feeding in Drosophila

2021 ◽  
Author(s):  
Celia K S Lau ◽  
Meghan Jelen ◽  
Michael D Gordon
Keyword(s):  
Drosophila Melanogaster ◽  
Expression Pattern ◽  
Sensory Neurons ◽  
Closed Loop ◽  
Higher Order ◽  
Taste Detection ◽  
Proof Of Principle ◽  
Feeding Circuits

Abstract Feeding is an essential part of animal life that is greatly impacted by the sense of taste. Although the characterization of taste-detection at the periphery has been extensive, higher order taste and feeding circuits are still being elucidated. Here, we use an automated closed-loop optogenetic activation screen to detect novel taste and feeding neurons in Drosophila melanogaster. Out of 122 Janelia FlyLight Project GAL4 lines preselected based on expression pattern, we identify six lines that acutely promote feeding and 35 lines that inhibit it. As proof of principle, we follow up on R70C07-GAL4, which labels neurons that strongly inhibit feeding. Using split-GAL4 lines to isolate subsets of the R70C07-GAL4 population, we find both appetitive and aversive neurons. Furthermore, we show that R70C07-GAL4 labels putative second-order taste interneurons that contact both sweet and bitter sensory neurons. These results serve as a resource for further functional dissection of fly feeding circuits.

scholarly journals Manipulating Single-Trial Motor Performance in Chronic Stroke Patients by Closed-Loop Brain State Interaction

2021 ◽  
Vol 29 ◽  
pp. 1806-1816
Author(s):  
Andreas Meinel ◽  
Jan Sosulski ◽  
Stephan Schraivogel ◽  
Janine Reis ◽  
Michael Tangermann
Keyword(s):  
Motor Performance ◽  
Closed Loop ◽  
Chronic Stroke ◽  
State Interaction ◽  
Brain State ◽  
Single Trial ◽  
Stroke Patients
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