The Effect of Periodontal Neural Feedback on the Physiological Tremor of the Mandible in Man

1980 ◽  
Vol 7 (4) ◽  
pp. 337-337
Author(s):  
D. H. Steenberghe ◽  
J. H. Vries
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ben Somers ◽  
Christopher J. Long ◽  
Tom Francart

AbstractThe cochlear implant is one of the most successful medical prostheses, allowing deaf and severely hearing-impaired persons to hear again by electrically stimulating the auditory nerve. A trained audiologist adjusts the stimulation settings for good speech understanding, known as “fitting” the implant. This process is based on subjective feedback from the user, making it time-consuming and challenging, especially in paediatric or communication-impaired populations. Furthermore, fittings only happen during infrequent sessions at a clinic, and therefore cannot take into account variable factors that affect the user’s hearing, such as physiological changes and different listening environments. Objective audiometry, in which brain responses evoked by auditory stimulation are collected and analysed, removes the need for active patient participation. However, recording of brain responses still requires expensive equipment that is cumbersome to use. An elegant solution is to record the neural signals using the implant itself. We demonstrate for the first time the recording of continuous electroencephalographic (EEG) signals from the implanted intracochlear electrode array in human subjects, using auditory evoked potentials originating from different brain regions. This was done using a temporary recording set-up with a percutaneous connector used for research purposes. Furthermore, we show that the response morphologies and amplitudes depend crucially on the recording electrode configuration. The integration of an EEG system into cochlear implants paves the way towards chronic neuro-monitoring of hearing-impaired patients in their everyday environment, and neuro-steered hearing prostheses, which can autonomously adjust their output based on neural feedback.


1999 ◽  
Vol 32 (2) ◽  
pp. 7450-7454
Author(s):  
Keming Xie ◽  
Jianfeng Nan ◽  
T.Y. Lin

1995 ◽  
Vol 14 (1) ◽  
pp. 37-47
Author(s):  
Tiejun Miao ◽  
Kazuyoshi Sakamoto
Keyword(s):  

1998 ◽  
Vol 08 (07) ◽  
pp. 1505-1516 ◽  
Author(s):  
J. Timmer

Empirical time series often contain observational noise. We investigate the effect of this noise on the estimated parameters of models fitted to the data. For data of physiological tremor, i.e. a small amplitude oscillation of the outstretched hand of healthy subjects, we compare the results for a linear model that explicitly includes additional observational noise to one that ignores this noise. We discuss problems and possible solutions for nonlinear deterministic as well as nonlinear stochastic processes. Especially we discuss the state space model applicable for modeling noisy stochastic systems and Bock's algorithm capable for modeling noisy deterministic systems.


2014 ◽  
Vol 26 (7) ◽  
pp. 1519-1527 ◽  
Author(s):  
Marlene Meyer ◽  
Harold Bekkering ◽  
Denise J. C. Janssen ◽  
Ellen R. A. de Bruijn ◽  
Sabine Hunnius

External feedback provides essential information for successful learning. Feedback is especially important for learning in early childhood, as toddlers strongly rely on external signals to determine the consequences of their actions. In adults, many electrophysiological studies have elucidated feedback processes using a neural marker called the feedback-related negativity (FRN). The neural generator of the FRN is assumed to be the ACC, located in medial frontal cortex. As frontal brain regions are the latest to mature during brain development, it is unclear when in early childhood a functional feedback system develops. Is feedback differentiated on a neural level in toddlers and in how far is neural feedback processing related to children's behavioral adjustment? In an EEG experiment, we addressed these questions by measuring the brain activity and behavioral performance of 2.5-year-old toddlers while they played a feedback-guided game on a touchscreen. Electrophysiological results show differential brain activity for feedback with a more negative deflection for incorrect than correct outcomes, resembling the adult FRN. This provides the first neural evidence for feedback processing in toddlers. Notably, FRN amplitudes were predictive of adaptive behavior: the stronger the differential brain activity for feedback, the better the toddlers' adaptive performance during the game. Thus, already in early childhood toddlers' feedback-guided performance directly relates to the functionality of their neural feedback processing. Implications for early feedback-based learning as well as structural and functional brain development are discussed.


2021 ◽  
pp. 1-8
Author(s):  
Daniel Viggiani ◽  
Jack P. Callaghan

Viscoelastic creep generated in the lumbar spine following sustained spine flexion may affect the relationship between tissue damage and perceived pain. Two processes supporting this altered relationship include altered neural feedback and inflammatory processes. Our purpose was to determine how low back mechanical pain sensitivity changes following seated lumbar spine flexion using pressure algometry in a repeated-measures, cross-sectional laboratory design. Thirty-eight participants underwent a 10-minute sustained seated maximal flexion exposure with a 40-minute standing recovery period. Pressure algometry assessed pressure pain thresholds and the perceived intensity and unpleasantness of fixed pressures. Accelerometers measured spine flexion angles, and electromyography measured muscular activity during flexion. The flexion exposure produced 4.4° (2.7°) of creep that persisted throughout the entire recovery period. The perception of low back stimulus unpleasantness was elevated immediately following the exposure, 20 minutes before a delayed increase in lumbar erector spinae muscle activity. Women reported the fixed pressures to be more intense than men. Sustained flexion had immediate consequences to the quality of mechanical stimulus perceived but did not alter pressure pain thresholds. Neural feedback and inflammation seemed unlikely mechanisms for this given the time and direction of pain sensitivity changes, leaving a postulated cortical influence.


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