The Experts below are selected from a list of 63948 Experts worldwide ranked by ideXlab platform
P A Robinson - One of the best experts on this subject based on the ideXlab platform.
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effects of Physiological Parameter evolution on the dynamics of tonic clonic seizures
PLOS ONE, 2020Co-Authors: Farah Deeba, Paula Sanzleon, P A RobinsonAbstract:The temporal and spectral characteristics of tonic-clonic seizures are investigated using a neural field model of the corticothalamic system in the presence of a temporally varying connection strength between the cerebral cortex and thalamus. Increasing connection strength drives the system into ∼ 10 Hz seizure oscillations once a threshold is passed and a subcritical Hopf bifurcation occurs. In this study, the spectral and temporal characteristics of tonic-clonic seizures are explored as functions of the relevant properties of Physiological connection strengths, such as maximum strength, time above threshold, and the ramp rate at which the strength increases or decreases. Analysis shows that the seizure onset time decreases with the maximum connection strength and time above threshold, but increases with the ramp rate. Seizure duration and offset time increase with maximum connection strength, time above threshold, and rate of change. Spectral analysis reveals that the power of nonlinear harmonics and the duration of the oscillations increase as the maximum connection strength and the time above threshold increase. A secondary limit cycle at ∼ 18 Hz, termed a saddle-cycle, is also seen during seizure onset and becomes more prominent and robust with increasing ramp rate. If the time above the threshold is too small, the system does not reach the 10 Hz limit cycle, and only exhibits 18 Hz saddle-cycle oscillations. It is also seen that the time to reach the saturated large amplitude limit-cycle seizure oscillation from both the instability threshold and from the end of the saddle-cycle oscillations is inversely proportional to the square root of the ramp rate.
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effects of Physiological Parameter evolution on the dynamics of tonic clonic seizures
bioRxiv, 2019Co-Authors: Farah Deeba, Paula Sanzleon, P A RobinsonAbstract:The temporal and spectral characteristics of tonic-clonic seizures are investigated using a neural field model of the corticothalamic system in the presence of a temporally varying connection strength between the cerebral cortex and thalamus. Increasing connection strength drives the system into ~10 Hz seizure oscillations once a threshold is passed and a subcritical Hopf bifurcation occurs. In this study, the spectral and temporal characteristics of tonic-clonic seizures are explored as functions of the relevant properties of Physiological connection strengths, such as maximum strength, time above threshold, and the ramp rate at which the strength increases or decreases. Analysis shows that the seizure onset time decreases with the maximum connection strength and time above threshold, but increases with the ramp rate. Seizure duration and offset time increase with maximum connection strength, time above threshold, and rate of change. Spectral analysis reveals that the power of nonlinear harmonics and the duration of the oscillations increase as the maximum connection strength and the time above threshold increase. A secondary limit cycle at ~18 Hz, termed a saddle-cycle, is also seen during seizure onset and becomes more prominent and robust with increasing ramp rate. If the time above the threshold is too small, the system does not reach the 10 Hz limit cycle, and only exhibits 18 Hz saddle-cycle oscillations. It is also seen that the times to reach the saturated large amplitude limit-cycle seizure oscillation from both the instability threshold and from the end of the saddle-cycle oscillations are inversely proportional to the square root of the ramp rate.
Farah Deeba - One of the best experts on this subject based on the ideXlab platform.
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effects of Physiological Parameter evolution on the dynamics of tonic clonic seizures
PLOS ONE, 2020Co-Authors: Farah Deeba, Paula Sanzleon, P A RobinsonAbstract:The temporal and spectral characteristics of tonic-clonic seizures are investigated using a neural field model of the corticothalamic system in the presence of a temporally varying connection strength between the cerebral cortex and thalamus. Increasing connection strength drives the system into ∼ 10 Hz seizure oscillations once a threshold is passed and a subcritical Hopf bifurcation occurs. In this study, the spectral and temporal characteristics of tonic-clonic seizures are explored as functions of the relevant properties of Physiological connection strengths, such as maximum strength, time above threshold, and the ramp rate at which the strength increases or decreases. Analysis shows that the seizure onset time decreases with the maximum connection strength and time above threshold, but increases with the ramp rate. Seizure duration and offset time increase with maximum connection strength, time above threshold, and rate of change. Spectral analysis reveals that the power of nonlinear harmonics and the duration of the oscillations increase as the maximum connection strength and the time above threshold increase. A secondary limit cycle at ∼ 18 Hz, termed a saddle-cycle, is also seen during seizure onset and becomes more prominent and robust with increasing ramp rate. If the time above the threshold is too small, the system does not reach the 10 Hz limit cycle, and only exhibits 18 Hz saddle-cycle oscillations. It is also seen that the time to reach the saturated large amplitude limit-cycle seizure oscillation from both the instability threshold and from the end of the saddle-cycle oscillations is inversely proportional to the square root of the ramp rate.
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effects of Physiological Parameter evolution on the dynamics of tonic clonic seizures
bioRxiv, 2019Co-Authors: Farah Deeba, Paula Sanzleon, P A RobinsonAbstract:The temporal and spectral characteristics of tonic-clonic seizures are investigated using a neural field model of the corticothalamic system in the presence of a temporally varying connection strength between the cerebral cortex and thalamus. Increasing connection strength drives the system into ~10 Hz seizure oscillations once a threshold is passed and a subcritical Hopf bifurcation occurs. In this study, the spectral and temporal characteristics of tonic-clonic seizures are explored as functions of the relevant properties of Physiological connection strengths, such as maximum strength, time above threshold, and the ramp rate at which the strength increases or decreases. Analysis shows that the seizure onset time decreases with the maximum connection strength and time above threshold, but increases with the ramp rate. Seizure duration and offset time increase with maximum connection strength, time above threshold, and rate of change. Spectral analysis reveals that the power of nonlinear harmonics and the duration of the oscillations increase as the maximum connection strength and the time above threshold increase. A secondary limit cycle at ~18 Hz, termed a saddle-cycle, is also seen during seizure onset and becomes more prominent and robust with increasing ramp rate. If the time above the threshold is too small, the system does not reach the 10 Hz limit cycle, and only exhibits 18 Hz saddle-cycle oscillations. It is also seen that the times to reach the saturated large amplitude limit-cycle seizure oscillation from both the instability threshold and from the end of the saddle-cycle oscillations are inversely proportional to the square root of the ramp rate.
Paula Sanzleon - One of the best experts on this subject based on the ideXlab platform.
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effects of Physiological Parameter evolution on the dynamics of tonic clonic seizures
PLOS ONE, 2020Co-Authors: Farah Deeba, Paula Sanzleon, P A RobinsonAbstract:The temporal and spectral characteristics of tonic-clonic seizures are investigated using a neural field model of the corticothalamic system in the presence of a temporally varying connection strength between the cerebral cortex and thalamus. Increasing connection strength drives the system into ∼ 10 Hz seizure oscillations once a threshold is passed and a subcritical Hopf bifurcation occurs. In this study, the spectral and temporal characteristics of tonic-clonic seizures are explored as functions of the relevant properties of Physiological connection strengths, such as maximum strength, time above threshold, and the ramp rate at which the strength increases or decreases. Analysis shows that the seizure onset time decreases with the maximum connection strength and time above threshold, but increases with the ramp rate. Seizure duration and offset time increase with maximum connection strength, time above threshold, and rate of change. Spectral analysis reveals that the power of nonlinear harmonics and the duration of the oscillations increase as the maximum connection strength and the time above threshold increase. A secondary limit cycle at ∼ 18 Hz, termed a saddle-cycle, is also seen during seizure onset and becomes more prominent and robust with increasing ramp rate. If the time above the threshold is too small, the system does not reach the 10 Hz limit cycle, and only exhibits 18 Hz saddle-cycle oscillations. It is also seen that the time to reach the saturated large amplitude limit-cycle seizure oscillation from both the instability threshold and from the end of the saddle-cycle oscillations is inversely proportional to the square root of the ramp rate.
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effects of Physiological Parameter evolution on the dynamics of tonic clonic seizures
bioRxiv, 2019Co-Authors: Farah Deeba, Paula Sanzleon, P A RobinsonAbstract:The temporal and spectral characteristics of tonic-clonic seizures are investigated using a neural field model of the corticothalamic system in the presence of a temporally varying connection strength between the cerebral cortex and thalamus. Increasing connection strength drives the system into ~10 Hz seizure oscillations once a threshold is passed and a subcritical Hopf bifurcation occurs. In this study, the spectral and temporal characteristics of tonic-clonic seizures are explored as functions of the relevant properties of Physiological connection strengths, such as maximum strength, time above threshold, and the ramp rate at which the strength increases or decreases. Analysis shows that the seizure onset time decreases with the maximum connection strength and time above threshold, but increases with the ramp rate. Seizure duration and offset time increase with maximum connection strength, time above threshold, and rate of change. Spectral analysis reveals that the power of nonlinear harmonics and the duration of the oscillations increase as the maximum connection strength and the time above threshold increase. A secondary limit cycle at ~18 Hz, termed a saddle-cycle, is also seen during seizure onset and becomes more prominent and robust with increasing ramp rate. If the time above the threshold is too small, the system does not reach the 10 Hz limit cycle, and only exhibits 18 Hz saddle-cycle oscillations. It is also seen that the times to reach the saturated large amplitude limit-cycle seizure oscillation from both the instability threshold and from the end of the saddle-cycle oscillations are inversely proportional to the square root of the ramp rate.
Herve Morvan - One of the best experts on this subject based on the ideXlab platform.
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Physiological Parameter response to variation of mental workload
Human Factors, 2018Co-Authors: Adrian Cornelius Marinescu, Sarah Sharples, Alastair Campbell Ritchie, Tomas Sanchez Lopez, Michael Mcdowell, Herve MorvanAbstract:Previous studies have examined how individual Physiological measures respond to changes in mental demand and subjective reports of mental workload. This study explores the response of multiple Physiological Parameters, measured simultaneously and quantifies the added value of each of the measures when estimating the level of demand. The study presented was conducted in laboratory conditions and required participants to perform a custom-designed visual-motor task that imposed varying levels of demand. The data collected consisted of: Physiological measurements (heart inter-beat intervals, breathing rate, pupil diameter, facial thermography); subjective ratings of workload from the participants (ISA and NASA-TLX); and the performance measured within the task. Facial thermography and pupil diameter were demonstrated to be good candidates for non-invasive mental workload measurements; for 7 out of 10 participants, pupil diameter showed a strong correlation (with R values between 0.61 and 0.79 at a significance value of 0.01) with mean ISA normalized values. Facial thermography measures added on average 47.7% to the amount of variability in task performance explained by a regression model. As with the ISA ratings, the relationship between the Physiological measures and performance showed strong inter-participant differences, with some individuals demonstrating a much stronger relationship between workload and performance measures than others. The results presented in this paper demonstrate that Physiological monitoring can be used for non-invasive real-time measurement of workload, assuming models have been appropriately trained on previously recorded data from the user population. Facial thermography combined with measurement of pupil diameter are strong candidates for real-time monitoring of workload due to the availability and non-intrusive nature of current technology. The study also demonstrates the importance of identifying whether an individual is one who demonstrates a strong relationship between Physiological measures and experienced workload measures before Physiological measures are applied uniformly. This is a feasible proposition in a setting such as aircraft cockpits, where pilots are drawn from a relatively small, targeted and managed population.
Adrian Cornelius Marinescu - One of the best experts on this subject based on the ideXlab platform.
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Physiological Parameter response to variation of mental workload
Human Factors, 2018Co-Authors: Adrian Cornelius Marinescu, Sarah Sharples, Alastair Campbell Ritchie, Tomas Sanchez Lopez, Michael Mcdowell, Herve MorvanAbstract:Previous studies have examined how individual Physiological measures respond to changes in mental demand and subjective reports of mental workload. This study explores the response of multiple Physiological Parameters, measured simultaneously and quantifies the added value of each of the measures when estimating the level of demand. The study presented was conducted in laboratory conditions and required participants to perform a custom-designed visual-motor task that imposed varying levels of demand. The data collected consisted of: Physiological measurements (heart inter-beat intervals, breathing rate, pupil diameter, facial thermography); subjective ratings of workload from the participants (ISA and NASA-TLX); and the performance measured within the task. Facial thermography and pupil diameter were demonstrated to be good candidates for non-invasive mental workload measurements; for 7 out of 10 participants, pupil diameter showed a strong correlation (with R values between 0.61 and 0.79 at a significance value of 0.01) with mean ISA normalized values. Facial thermography measures added on average 47.7% to the amount of variability in task performance explained by a regression model. As with the ISA ratings, the relationship between the Physiological measures and performance showed strong inter-participant differences, with some individuals demonstrating a much stronger relationship between workload and performance measures than others. The results presented in this paper demonstrate that Physiological monitoring can be used for non-invasive real-time measurement of workload, assuming models have been appropriately trained on previously recorded data from the user population. Facial thermography combined with measurement of pupil diameter are strong candidates for real-time monitoring of workload due to the availability and non-intrusive nature of current technology. The study also demonstrates the importance of identifying whether an individual is one who demonstrates a strong relationship between Physiological measures and experienced workload measures before Physiological measures are applied uniformly. This is a feasible proposition in a setting such as aircraft cockpits, where pilots are drawn from a relatively small, targeted and managed population.
