scholarly journals Transfer Function Models for the Localization of Seizure Onset Zone From Cortico-Cortical Evoked Potentials

2020 ◽  
Vol 11 ◽  
Author(s):  
Golnoosh Kamali ◽  
Rachel June Smith ◽  
Mark Hays ◽  
Christopher Coogan ◽  
Nathan E. Crone ◽  
...  
Keyword(s):  
Transfer Function ◽  
Transfer Functions ◽  
Patient Specific ◽  
Seizure Freedom ◽  
Evoked Responses ◽  
Seizure Onset ◽  
Seizure Onset Zone ◽  
Function Models ◽  
Peak Gain ◽  
Transfer Function Models

Surgical resection of the seizure onset zone (SOZ) could potentially lead to seizure-freedom in medically refractory epilepsy patients. However, localizing the SOZ can be a time consuming and tedious process involving visual inspection of intracranial electroencephalographic (iEEG) recordings captured during passive patient monitoring. Cortical stimulation is currently performed on patients undergoing invasive EEG monitoring for the main purpose of mapping functional brain networks such as language and motor networks. We hypothesized that evoked responses from single pulse electrical stimulation (SPES) can also be used to localize the SOZ as they may express the natural frequencies and connectivity of the iEEG network. To test our hypothesis, we constructed patient specific transfer function models from the evoked responses recorded from 22 epilepsy patients that underwent SPES evaluation and iEEG monitoring. We then computed the frequency and connectivity dependent “peak gain” of the system as measured by the norm from systems theory. We found that in cases for which clinicians had high confidence in localizing the SOZ, the highest peak gain transfer functions with the smallest “floor gain” (gain at which the dipped 3dB below DC gain) corresponded to when the clinically annotated SOZ and early spread regions were stimulated. In more complex cases, there was a large spread of the peak-to-floor (PF) ratios when the clinically annotated SOZ was stimulated. Interestingly for patients who had successful surgeries, our ratio of gains, agreed with clinical localization, no matter the complexity of the case. For patients with failed surgeries, the PF ratio did not match clinical annotations. Our findings suggest that transfer function gains and their corresponding frequency responses computed from SPES evoked responses may improve SOZ localization and thus surgical outcomes.

scholarly journals Sensitivity to species selection indicates the effect of nuisance variables on marine microfossil transfer functions

2018 ◽  
Author(s):  
Lukas Jonkers ◽  
Michal Kučera
Keyword(s):  
Transfer Function ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Transfer Functions ◽  
Planktonic Foraminifera ◽  
Sea Surface ◽  
Species Selection ◽  
Training Set ◽  
Function Models ◽  
Transfer Function Models

Abstract. The species composition of many groups of marine plankton appears well predicted by sea surface temperature (SST). Consequently, fossil plankton assemblages have been widely used to reconstruct past SST. Most applications of this approach make use of the highest possible taxonomic resolution. However, not all species are sensitive to temperature and their distribution may be governed by other parameters. There are thus reasons to question the merit of including information all species, both for transfer function performance and for its effect on reconstructions. Here we investigate the effect of species selection on planktonic foraminifera transfer functions. We assess species importance for transfer function models using a random forest technique and evaluate the performance of models with increasing number of species. Irrespective of using models that use the entire training set (weighted averaging) or models that use only a subset of the training set (modern analogue technique), we find that the majority of foraminifera species does not carry useful information for temperature reconstruction. Less than one third of the species in the training set is required to provide a temperature estimate with a prediction error comparable to a transfer function that uses all species in the training set. However, species selection matters for paleotemperature estimates. We find that transfer function models with different number of species but with the same error may yield different reconstructions of sea surface temperature when applied on the same fossil assemblages. This ambiguity in the reconstructions implies that fossil assemblage change reflects a combination of temperature and other environmental factors. The contribution of the additional factors is site and time specific, indicating ecological and geological complexity in the formation of the sedimentary assemblages. The possibility of obtaining multiple different reconstructions from a single sediment record presents a previously unrecognised source of uncertainty for sea surface temperature estimates based on planktonic foraminifera assemblages. This uncertainty can be evaluated by determining the sensitivity of the reconstructions to species pruning.

Rational transfer function models for nitrifying trickling filters

1999 ◽  
Vol 39 (4) ◽  
pp. 121-128 ◽  
Author(s):  
T. Wik
Keyword(s):  
Transfer Function ◽  
Dynamic Models ◽  
Transfer Functions ◽  
Controller Design ◽  
Ammonium Concentration ◽  
Trickling Filters ◽  
Rational Transfer ◽  
Simulated Effluent ◽  
Function Models ◽  
Transfer Function Models

An important step towards optimization and control of wastewater treatment plants is the development of dynamic models and efficient methods of simulation. Using standard simplifying assumptions, non-rational transfer function models describing the fast dynamics of nitrifying trickling filters, are derived. With a method based on the location of their singularities, it is shown how low order rational transfer functions can approximate the non-rational ones. These transfer functions can be used in efficient simulation routines and in standard methods of controller design. Effluent concentrations from trace substance pulse response experiments and an experiment with varying flow and varying influent ammonium concentration carried out on a large pilot plant NTF show close agreement with simulated effluent concentrations using the rational transfer functions.

scholarly journals On the Applicability of Transfer Function Models for SSI Embedment Effects

2021 ◽  
Vol 6 (10) ◽  
pp. 137
Author(s):  
Francesco Cavalieri ◽  
António A. Correia ◽  
Rui Pinho
Keyword(s):  
Transfer Function ◽  
Transfer Functions ◽  
Numerical Study ◽  
Site Response ◽  
Free Field ◽  
Analytical Models ◽  
Nonlinear Behaviour ◽  
Embedded Foundations ◽  
Function Models ◽  
Transfer Function Models

Soil-structure interaction (SSI) effects are typically neglected for relatively lightweight buildings that are less than two-three storeys high with a limited footprint area and resting on shallow foundations (i.e., not featuring a basement). However, when the above conditions are not satisfied, and in particular when large basements are present, important kinematic SSI may develop, causing the foundation-level motion to deviate from the free-field one due to embedment effects. In the literature, transfer function models that estimate the filtering effect induced by rigid massless embedded foundations are available to “transform” foundation-level recordings into free-field ones, and vice-versa. This work describes therefore a numerical study aimed at assessing potential limits of the applicability of such transfer functions through the employment of a 3D nonlinear soil-block model representing a layered soil, recently developed and validated by the authors, and featuring on top a large heavy building with basement. A number of finite element site response analyses were carried out for different seismic input signals, soil profiles and embedment depths of the building’s basement. The numerically obtained transfer functions were compared with the curves derived using two analytical models. It was observed that the latter are able to reliably predict the embedment effects in “idealised” soil/input conditions under which they have been developed. However, in real conditions, namely when a non-homogeneous profile with nonlinear behaviour under a given seismic excitation is considered, especially in presence of a basement that is more than one storey high, they may fail in capturing some features, such as the frequency-dependent amplification of the motion at the basement level of a building with respect to the free-field one.

scholarly journals Sensitivity to species selection indicates the effect of nuisance variables on marine microfossil transfer functions

2019 ◽  
Vol 15 (3) ◽  
pp. 881-891
Author(s):  
Lukas Jonkers ◽  
Michal Kučera
Keyword(s):  
Transfer Function ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Transfer Functions ◽  
Planktonic Foraminifera ◽  
Sea Surface ◽  
Species Selection ◽  
Training Set ◽  
Function Models ◽  
Transfer Function Models

Abstract. The species composition of many groups of marine plankton appears well predicted by sea surface temperature (SST). Consequently, fossil plankton assemblages have been widely used to reconstruct past SST. Most applications of this approach make use of the highest possible taxonomic resolution. However, not all species are sensitive to temperature, and their distribution may be governed by other parameters. There are thus reasons to question the merit of including information about all species, both for transfer function performance and for its effect on reconstructions. Here we investigate the effect of species selection on planktonic foraminifera transfer functions. We assess species importance for transfer function models using a random forest technique and evaluate the performance of models with an increasing number of species. Irrespective of using models that use the entire training set (weighted averaging) or models that use only a subset of the training set (modern analogue technique), we find that the majority of foraminifera species does not carry useful information for temperature reconstruction. Less than one-third of the species in the training set is required to provide a temperature estimate with a prediction error comparable to a transfer function that uses all species in the training set. However, species selection matters for paleotemperature estimates. We find that transfer function models with a different number of species but with the same error may yield different reconstructions of sea surface temperature when applied to the same fossil assemblages. This ambiguity in the reconstructions implies that fossil assemblage change reflects a combination of temperature and other environmental factors. The contribution of the additional factors is site and time specific, indicating ecological and geological complexity in the formation of the sedimentary assemblages. The possibility of obtaining multiple different reconstructions from a single sediment record presents a previously unrecognized source of uncertainty for sea surface temperature estimates based on planktonic foraminifera assemblages. This uncertainty can be evaluated by determining the sensitivity of the reconstructions to species pruning.

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