Neural interfacing non-invasive brain stimulation with NIRS-EEG joint imaging for closed-loop control of neuroenergetics in ischemic stroke

2017 ◽  
Author(s):  
Alexander von Luhmann ◽  
Jessica Addesa ◽  
Sourav Chandra ◽  
Abhijit Das ◽  
Mitsuhiro Hayashibe ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Brain Stimulation ◽  
Closed Loop ◽  
Closed Loop Control ◽  
Loop Control ◽  
Non Invasive ◽  
Neural Interfacing

Closed-Loop Control of the Frequency Response of the Virtual Brain Model

2017 ◽  
Author(s):  
Christine Beauchene ◽  
Alexander Leonessa ◽  
Subhradeep Roy ◽  
James Simon ◽  
Nicole Abaid
Keyword(s):  
Large Scale ◽  
Closed Loop ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Closed Loop Control ◽  
Loop Control ◽  
Non Invasive ◽  
Frequency Mismatch ◽  
Stimulation Method ◽  
The Difference

The brain is a highly complex network and analyzing brain connectivity is a nontrivial task. Consequently, the neuroscience community created a large-scale, customizable, mathematical model which simulates brain activity called The Virtual Brain (TVB). Using TVB, we seek to control electroencephalography (EEG) measured brain states using auditory inputs, through TVB. A safe non-invasive brain stimulation method is binaural beats (BB) which arise from the brain’s interpretation of two pure tones, with a small frequency mismatch, delivered independently to each ear. A third phantom BB, whose frequency is equal to the difference of the two presented tones, is produced. This paper details the development and proof-of-concept testing of a simulation environment for an EEG-based closed-loop control of TVB using BB. Results suggest that the connectivity networks, constructed from simulated EEG, may change with certain BB stimulation frequency. In this work, we demonstrate that a linear controller can successfully modulate TVB connectivity.

The Impact of Visual Feedback Type on the Mastery of Visuo-Motor Transformations

2012 ◽  
Vol 220 (1) ◽  
pp. 3-9 ◽  
Author(s):  
Sandra Sülzenbrück
Keyword(s):  
Empirical Research ◽  
Visual Feedback ◽  
Closed Loop ◽  
Motor Planning ◽  
Visual Input ◽  
Closed Loop Control ◽  
Loop Control ◽  
Feedback Type ◽  
Effective Use ◽  
The Impact

For the effective use of modern tools, the inherent visuo-motor transformation needs to be mastered. The successful adjustment to and learning of these transformations crucially depends on practice conditions, particularly on the type of visual feedback during practice. Here, a review about empirical research exploring the influence of continuous and terminal visual feedback during practice on the mastery of visuo-motor transformations is provided. Two studies investigating the impact of the type of visual feedback on either direction-dependent visuo-motor gains or the complex visuo-motor transformation of a virtual two-sided lever are presented in more detail. The findings of these studies indicate that the continuous availability of visual feedback supports performance when closed-loop control is possible, but impairs performance when visual input is no longer available. Different approaches to explain these performance differences due to the type of visual feedback during practice are considered. For example, these differences could reflect a process of re-optimization of motor planning in a novel environment or represent effects of the specificity of practice. Furthermore, differences in the allocation of attention during movements with terminal and continuous visual feedback could account for the observed differences.

118-LB: Glucose Variability throughout the Menstrual Cycle on Closed-Loop Control in Type 1 DM

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 118-LB
Author(s):  
CAROL J. LEVY ◽  
GRENYE OMALLEY ◽  
SUE A. BROWN ◽  
DAN RAGHINARU ◽  
YOGISH C. KUDVA ◽  
...  
Keyword(s):  
Menstrual Cycle ◽  
Closed Loop ◽  
Glucose Variability ◽  
Closed Loop Control ◽  
Loop Control ◽  
Type 1 Dm

101-LB: Eighteen-Month Use of Closed-Loop Control (CLC): A Randomized, Controlled Trial

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 101-LB
Author(s):  
SUE A. BROWN ◽  
DAN RAGHINARU ◽  
BRUCE A. BUCKINGHAM ◽  
YOGISH C. KUDVA ◽  
LORI M. LAFFEL ◽  
...  
Keyword(s):  
Randomized Controlled Trial ◽  
Closed Loop ◽  
Controlled Trial ◽  
Closed Loop Control ◽  
Loop Control ◽  
Randomized Controlled
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