Spectral element modeling of ultrasonic guided wave propagation in optical fibers.

Recent advancements in fiber optic methods have enabled their use for guided wave sensing. It opens up new possibilities for Structural Health Monitoring. The aim of this paper is to provide insight for the physics related to guided wave propagation and coupling between the optical fiber and solid structure. For this purpose, a new approach for non-matching interface based on Lagrange multipliers and the time domain spectral element method was developed. A parallelized code has been implemented in order to simulate the guided wave propagation in the structure, its coupling into the optical fiber and the propagation in the fiber in a computationally efficient way. The paper presents four studies showing the efficacy of the modeling approach. The paper first shows the improvement in the computation speed through the use of parallelization and a more efficient implementation. Then the results of the simulation of wave propagation in the fiber are compared with results from previous simulation studies using commercially available software. The third study shows that the spectral element method is able to capture the directional sensitivity of optical fiber based sensors. Lastly, the simulation is used for detection of simulated damage using the spectral element method based simulation. The results indicate that indeed the spectral element implementation is able to recreate the wave coupling phenomena, capture the physics of the system including directional sensitivity and reflections from damage.

Wavefield Analysis Tools for Wavenumber and Velocities Extraction in Polar Coordinates.

Experimental characterization of Lamb waves in plate-like structures overcomes the intrinsic limits of a priori semianalytical finite element simulations, where material inaccuracies and nonidealities cannot be easily considered. Unfortunately, the experimental extraction of guided wave dispersion curves, and especially their polar representation along different directions of propagation at a given frequency, is not trivial. In nonisotropic materials, such analysis is a key aspect for a reliable and robust characterization of the behavior of waves. In this work, by exploiting scanning laser Doppler vibrometer measurements with narrowband excitation, two different signal processing methods for the extraction of the wavenumber polar representation at the excitation frequency are investigated and characterized. The first method is based on a distance regularized level set (DRLSE) algorithm, widely used in image processing and computer vision but, to the best of the author's knowledge, never used in the Lamb waves' field. The second method is based on the 2-D sparse wavenumber analysis which exploits the wavefield sparse representation in the wavenumber domain. With a precise and reliable extraction of the wavenumber characteristic in the k -space, the polar representations at the excitation frequency of phase and group velocities can be estimated. The former, by exploiting the well-known wavenumber-frequency relation, the latter, instead, by computing numerical derivative among wavenumbers at multiple frequencies. The methodology has been validated on three different composite plates with different degrees of nonisotropy properties. The results show the effectiveness of the two methods, highlighting the advantages and disadvantages of both.

Decoding accelerometry for classification and prediction of critically ill patients with severe brain injury.

Our goal is to explore quantitative motor features in critically ill patients with severe brain injury (SBI). We hypothesized that computational decoding of these features would yield information on underlying neurological states and outcomes. Using wearable microsensors placed on all extremities, we recorded a median 24.1 (IQR: 22.8-25.1) hours of high-frequency accelerometry data per patient from a prospective cohort (n = 69) admitted to the ICU with SBI. Models were trained using time-, frequency-, and wavelet-domain features and levels of responsiveness and outcome as labels. The two primary tasks were detection of levels of responsiveness, assessed by motor sub-score of the Glasgow Coma Scale (GCSm), and prediction of functional outcome at discharge, measured with the Glasgow Outcome Scale-Extended (GOSE). Detection models achieved significant (AUC: 0.70 [95% CI: 0.53-0.85]) and consistent (observation windows: 12 min-9 h) discrimination of SBI patients capable of purposeful movement (GCSm > 4). Prediction models accurately discriminated patients of upper moderate disability or better (GOSE > 5) with 2-6 h of observation (AUC: 0.82 [95% CI: 0.75-0.90]). Results suggest that time series analysis of motor activity yields clinically relevant insights on underlying functional states and short-term outcomes in patients with SBI.

Model-Assisted Guided-Wave-Based Approach for Disbond Detection and Size Estimation in Honeycomb Sandwich Composites.

One of the axioms of structural health monitoring states that the severity of damage assessment can only be done in a learning mode under the supervision of an expert. Therefore, a numerical analysis was conducted to gain knowledge regarding the influence of the damage size on the propagation of elastic waves in a honeycomb sandwich composite panel. Core-skin debonding was considered as damage. For this purpose, a panel was modelled taking into account the real geometry of the honeycomb core using the time-domain spectral element method and two-dimensional elements. The presented model was compared with the homogenized model of the honeycomb core and validated in the experimental investigation. The result of the parametric study is a function of the influence of damage on the amplitude and energy of propagating waves.

Analysis of Air-Coupled Transducer-Based Elastic Waves Generation in CFRP Plates.

In this paper, the analysis of non-contact elastic waves generation in carbon fiber reinforced-polymer (CFRP) plate was conducted. Full non-contact elastic waves generation and sensing methods were also analyzed. Elastic waves generation was based on an air-coupled transducer (ACT) while waves sensing was based on a laser Doppler vibrometer. The excitation frequency was equal to 40 kHz. An optimal ACT slope angle for the generation of elastic waves mode was determined with the aid of dispersion curves calculated by using a semi-analytical model. Due to the stack sequence in the composite plate (unidirectional composite), ACT slope angles were different for waves generation in the direction along and across reinforcing fibers direction. Moreover, experimental verification of the optimal ACT slope angles was conducted. It was possible to generate A0 wave mode in the direction along and across the reinforcing fibers. Optimal angles determined using ACT were equal to 16° (along fibers) and 34° (across fibers). In the case of optimal angles, elastic waves amplitudes are almost two times higher than for the case of ACT oriented perpendicularly to the plate surface. Moreover, experimental results based on ACT showed that it was possible to generate the SH0 mode in the direction across the fiber for optimal angles equal to 10°. Finally, based on the A0 wave mode propagation, the process for localization of discontinuities was performed. Discontinuities in the form of additional mass simulating damage were investigated. A simple signal processing algorithm based on elastic wave energy was used for creating damage maps. Authors compared discontinuity localization for ACT oriented perpendicularly to the plate and at the optimal slope angle. The utilization of non-contact waves excitation at optimal ACT slope angles helped to focus the wave energy in the desired direction. Moreover, in this case, elastic waves with the highest amplitudes were generated.

Impact of gyral geometry on cortical responses to surface electrical stimulation: insights from experimental and modeling studies.

Objective.Invasive simultaneous stimulation and recording from intracranial electrodes and microwire arrays were used to investigate direct cortical responses to single pulses of electrical stimulation in humans.Approach.Microwire contacts measured surface potentials in cortical microdomains at a distance of 2-6 mm from the intracranial electrode. Direct cortical responses to stimulation (<20 ms) consisted of a larger surface negative potentials.Main results. The latencies of these responses were directly or inversely correlated with distances between the intracranial electrode and microwire contacts. We hypothesize that surface negative potentials reflected local synchronous depolarization of apical dendrites of pyramidal neurons in cortical microdomains in the superficial cortical layer and resulted from the activation of gray matter axons that delivered excitatory inputs to apical dendrites after cortical stimulation. We further hypothesized that the positive or inverse distance-latency correlations of the recorded negative responses were measured depending on whether activation of neurons originated at one (crown) or multiple (crown, lip, bank) sites throughout the gyrus simultaneously. The inverse distance-latency correlations then reflected the spatiotemporal superposition of different nearby sources of neuronal recruitment in the gyrus. To prove this hypothesis, we built an anatomically informed and biophysically realistic cortical network model and simulated early responses of cortical neurons to electrical stimulation in this cortical network model. The model simulations yielded negative potentials in simulated microdomains in the cortical model consistent with those recorded from humans. The model predicted sensitivity of cortical responses to the alignment of the stimulating electrode and microwire array with respect to the cortical gyrus and confirmed that gyral geometry has a major impact on direct neuronal recruitment, the timing, and the time course of neuronal activation in cortical microdomains.Significance.In this work, we demonstrated how the high-resolution forward network models can be used for better understanding and detailed prediction of cortical stimulation effects. Accurate predictive modeling tools are needed for the progress of brain stimulation therapies.

Phase-dependent Stimulation for Modulating Phase-amplitude Coupling: A Computational Modeling Approach.

Phase-amplitude coupling (PAC), in which the amplitude of a faster neural oscillation couples to the phase of a slower rhythm, is one of the most common representations of complex neuronal rhythmic activities. In a healthy brain, PAC accompanies cognitive function, and abnormal patterns of PAC have been linked to several neurological disorders. Among the various brain neuromodulation techniques, phase-dependent stimulation has a strong potential to modulate PAC levels. In this study, we utilize a computational model in the NEURON environment based on a detailed mathematical model of neuronal populations, consisting of networks with both excitatory and inhibitory neurons, to simulate PAC generation. The model was then used to investigate the modulatory effects of phase-dependent stimulation on the generated PAC. Simulated data from the model shows that stimulation locked to the phase of slower rhythms increased PAC level during stimulation. These results demonstrate the capacity of phase-dependent stimulation to modulate PAC, which could allow for applications in the treatment of neurological disorders associated with abnormal PAC, such as Parkinson's disease.Clinical Relevance- Analyzing the origins of neuronal PAC and developing a brain stimulation technique for modulating the level of PAC can facilitate the development of novel treatment methods for neurological disorders associated with abnormal cross-frequency coupling.

Damage Identification in Various Types of Composite Plates Using Guided Waves Excited by a Piezoelectric Transducer and Measured by a Laser Vibrometer.

Composite materials are widely used in the industry, and the interest of this material is growing rapidly, due to its light weight, strength and various other desired mechanical properties. However, composite materials are prone to production defects and other defects originated during exploitation, which may jeopardize the safety of such a structure. Thus, non-destructive evaluation methods that are material-independent and suitable for a wide range of defects identification are needed. In this paper, a technique for damage characterization in composite plates is proposed. In the presented non-destructive testing method, guided waves are excited by a piezoelectric transducer, attached to tested specimens, and measured by a scanning laser Doppler vibrometer in a dense grid of points. By means of signal processing, irregularities in wavefield images caused by any material defects are extracted and used for damage characterization. The effectiveness of the proposed technique is validated on four different composite panels: Carbon fiber-reinforced polymer, glass fiber-reinforced polymer, composite reinforced by randomly-oriented short glass fibers and aluminum-honeycomb core sandwich composite. Obtained results confirm its versatility and efficacy in damage characterization in various types of composite plates.

A Study of Sensor Placement Optimization Problem for Guided Wave-Based Damage Detection.

Guided waves (GW) allow fast inspection of a large area and hence have attracted research interest from the structural health monitoring (SHM) community. Thus, GW-based SHM is ideal for thin structures such as plates, pipes, etc., and is finding applications in several fields like aerospace, automotive, wind energy, etc. The GW propagate along the surface of the sample and get reflected from discontinuities in the structure in the form of boundaries and damage. Through proper signal processing of the reflected waves based on their time of arrival, the damage can be detected and isolated. For complex structures, a higher number of sensors may be required, which increases the cost of the equipment, as well as the mass. Thus, there is an effort to reduce the number of sensors without compromising the quality of the monitoring achieved. It is of utmost importance that the entire structure can be investigated. Hence, it is necessary to optimize the locations of the sensors in order to maximize the coverage while limiting the number of sensors used. A genetic algorithm (GA)-based optimization strategy was proposed by the authors for use in a simple aluminum plate. This paper extends the optimization methodology for other shape plates and presents experimental, analytical, and numerical studies. The sensitivity studies have been carried out by changing the relative weights of the application demands and presented in the form of a Pareto front. The Pareto front allows comparison of the relative importance of the different application demands, and an appropriate choice can be made based on the information provided.

Modeling Neural Adaptation in Auditory Cortex.

Neural responses recorded from auditory cortex exhibit adaptation, a stimulus-specific decrease that occurs when the same sound is presented repeatedly. Stimulus-specific adaptation is thought to facilitate perception in noisy environments. Although adaptation is assumed to arise independently from cortex, this has been difficult to validate directly in vivo. In this study, we used a neural network model of auditory cortex with multicompartmental cell modeling to investigate cortical adaptation. We found that repetitive, non-adapted inputs to layer IV neurons in the model elicited frequency-specific decreases in simulated single neuron, population-level and local field potential (LFP) activity, consistent with stimulus-specific cortical adaptation. Simulated recordings of LFPs, generated solely by excitatory post-synaptic inputs and recorded from layers II/III in the model, showed similar waveform morphologies and stimulus probability effects as auditory evoked responses recorded from human cortex. We tested two proposed mechanisms of cortical adaptation, neural fatigue and neural sharpening, by varying the strength and type of inter- and intra-layer synaptic connections (excitatory, inhibitory). Model simulations showed that synaptic depression modeled in excitatory (AMPA) synapses was sufficient to elicit a reduction in neural firing rate, consistent with neural fatigue. However, introduction of lateral inhibition from local layer II/III interneurons resulted in a reduction in the number of responding neurons, but not their firing rates, consistent with neural sharpening. These modeling results demonstrate that adaptation can arise from multiple neural mechanisms in auditory cortex.

Impact of Neuronal Membrane Damage on the Local Field Potential in a Large-Scale Simulation of Cerebral Cortex.

Within multiscale brain dynamics, the structure-function relationship between cellular changes at a lower scale and coordinated oscillations at a higher scale is not well understood. This relationship may be particularly relevant for understanding functional impairments after a mild traumatic brain injury (mTBI) when current neuroimaging methods do not reveal morphological changes to the brain common in moderate to severe TBI such as diffuse axonal injury or gray matter lesions. Here, we created a physiology-based model of cerebral cortex using a publicly released modeling framework (GEneral NEural SImulation System) to explore the possibility that performance deficits characteristic of blast-induced mTBI may reflect dysfunctional, local network activity influenced by microscale neuronal damage at the cellular level. We operationalized microscale damage to neurons as the formation of pores on the neuronal membrane based on research using blast paradigms, and in our model, pores were simulated by a change in membrane conductance. We then tracked changes in simulated electrical activity. Our model contained 585 simulated neurons, comprised of 14 types of cortical and thalamic neurons each with its own compartmental morphology and electrophysiological properties. Comparing the functional activity of neurons before and after simulated damage, we found that simulated pores in the membrane reduced both action potential generation and local field potential (LFP) power in the 1-40 Hz range of the power spectrum. Furthermore, the location of damage modulated the strength of these effects: pore formation on simulated axons reduced LFP power more strongly than did pore formation on the soma and the dendrites. These results indicate that even small amounts of cellular damage can negatively impact functional activity of larger scale oscillations, and our findings suggest that multiscale modeling provides a promising avenue to elucidate these relationships.

Computational Modeling of Subdural Cortical Stimulation: A Quantitative Spatiotemporal Analysis of Action Potential Initiation in a High-Density Multicompartment Model.

OBJECTIVE: Computational modeling studies were performed to identify presynaptic elements of cortical neurons that are activated by subdural electrical stimulation. MATERIALS AND METHODS: The computer model consists of layers of multicompartmental neurons arranged in 3D space in an anatomically realistic fashion inside a 4.8 × 4.8 × 3.4 mm volume of gray matter modeled as a homogenous and isotropic medium. The model was subjected to an electric field generated by a circular disk electrode. RESULTS: The initiation of presynaptic action potentials (PAPs) in neurons takes place predominantly in the axon initial segment (AIS) or ectopically in axonal branch terminals. PAPs that were initiated in only one axonal terminal were typically followed by a second PAP (spike duplet) resulting from the activation of the AIS by the antidromically propagating initial PAP. There were significant time delays (up to 0.5 ms) in the propagation of these ectopically initiated PAPs along the axons to nonactivated axonal branches and, associated with these delays, latencies in the occurrence of spike duplets in different axonal terminals. The effect of the dendritic arbor 3D structure on the AIS activation threshold was contingent on whether the net axonal and somato-dendritic current flows made an antagonistic or synergetic contribution. CONCLUSIONS: This study examines the effects of subdural electrical stimulation on a high-density network consisting of several populations of multicompartment cell types. The effect of dendritic arbor structure on the axonal activation threshold is prominent in the case of multipolar neurons with large-diameter symmetric dendrites (basal/apical) that are oriented parallel to the electric field lines. The timing of presynaptic terminal activation after stimulation is not determined solely by the axonal delay (orthodromic propagation) but depends on the details of the applied stimulation field and axonal branching structure, which may be important factors in characterizing the effects of electrical stimulation in neuromodulation systems.

A study of the dynamics of seizure propagation across micro domains in the vicinity of the seizure onset zone.

OBJECTIVE: The use of micro-electrode arrays to measure electrical activity from the surface of the brain is increasingly being investigated as a means to improve seizure onset zone (SOZ) localization. In this work, we used a multivariate autoregressive model to determine the evolution of seizure dynamics in the [Formula: see text] Hz high frequency band across micro-domains sampled by such micro-electrode arrays. We showed that a directed transfer function (DTF) can be used to estimate the flow of seizure activity in a set of simulated micro-electrode data with known propagation pattern. APPROACH: We used seven complex partial seizures recorded from four patients undergoing intracranial monitoring for surgical evaluation to reconstruct the seizure propagation pattern over sliding windows using a DTF measure. MAIN RESULTS: We showed that a DTF can be used to estimate the flow of seizure activity in a set of simulated micro-electrode data with a known propagation pattern. In general, depending on the location of the micro-electrode grid with respect to the clinical SOZ and the time from seizure onset, ictal propagation changed in directional characteristics over a 2-10 s time scale, with gross directionality limited to spatial dimensions of approximately [Formula: see text]. It was also seen that the strongest seizure patterns in the high frequency band and their sources over such micro-domains are more stable over time and across seizures bordering the clinically determined SOZ than inside. SIGNIFICANCE: This type of propagation analysis might in future provide an additional tool to epileptologists for characterizing epileptogenic tissue. This will potentially help narrowing down resection zones without compromising essential brain functions as well as provide important information about targeting anti-epileptic stimulation devices.

Determination of seizure propagation across microdomains using spectral measures of causality.

The use of microelectrode arrays to measure electrical activity from the surface of the brain is increasingly being investigated as a means to improve seizure focus localization. In this work, we determine seizure propagation across microdomains sampled by such microelectrode arrays and compare the results using two widely used frequency domain measures of causality, namely the partial directed coherence and the directed direct transfer function. We show that these two measures produce very similar propagation patterns for simulated microelectrode activity over a relatively smaller number of channels. However as the number of channels increases, partial directed coherence produces better estimates of the actual propagation pattern. Additionally, we apply these two measures to determine seizure propagation over microelectrode arrays measured from a patient undergoing intracranial monitoring for seizure focus localization and find very similar patterns which also agree with a threshold based reconstruction during seizure onset.

Epileptic seizures from abnormal networks: why some seizures defy predictability.

Seizure prediction has proven to be difficult in clinically realistic environments. Is it possible that fluctuations in cortical firing could influence the onset of seizures in an ictal zone? To test this, we have now used neural network simulations in a computational model of cortex having a total of 65,536 neurons with intercellular wiring patterned after histological data. A spatially distributed Poisson driven background input representing the activity of neighboring cortex affected 1% of the neurons. Gamma distributions were fit to the interbursting phase intervals, a non-parametric test for randomness was applied, and a dynamical systems analysis was performed to search for period-1 orbits in the intervals. The non-parametric analysis suggests that intervals are being drawn at random from their underlying joint distribution and the dynamical systems analysis is consistent with a nondeterministic dynamical interpretation of the generation of bursting phases. These results imply that in a region of cortex with abnormal connectivity analogous to a seizure focus, it is possible to initiate seizure activity with fluctuations of input from the surrounding cortical regions. These findings suggest one possibility for ictal generation from abnormal focal epileptic networks. This mechanism additionally could help explain the difficulty in predicting partial seizures in some patients.

Calcium involvement in regulation of neuronal bursting in disinhibited neuronal networks: insights from calcium studies in a spherical cell model.

Cytosolic calcium is involved in the regulation of many intracellular processes. Intracellular calcium may therefore potentially affect the behavior of both single neurons and synaptically connected neuronal assemblies. In computer model studies, we investigated calcium dynamics in spherical neurons during periods of recurrent neuronal bursting that were simulated in a disinhibited neuronal network. The model takes into account calcium influx via voltage-gated calcium channels, extrusion through the cell membrane, and binding to two different buffers representing fixed and mobile endogenous calcium buffers. Throughout the duration of the simulated recurrent neuronal bursting, the concentration of free fixed buffers shows a hyperbolic decrease in time at a rate that is not uniform inside a neuron. Recurrent calcium influxes associated with bursting lead to the formation of gradients in the concentration of the fixed buffer in the radial direction, and are accompanied by the redistribution of mobile buffers acting to compensate for these gradients. Simulated intracellular calcium transients have a slow component characterized by a gradual increase in the calcium baseline level that reaches a plateau 120-200 s after the onset of recurrent bursting. Using this model, we demonstrate what we believe is a novel mechanism of regulation of network excitability that occurs in conditions of prolonged and recurrent neuronal bursting in disinhibited networks. This mechanism is expressed via interaction of calcium clearance systems inside neurons with calcium-dependent potassium regulation of neuronal excitability in membranes. This is a network phenomenon because it arises largely by synaptic interactions. Therefore, it can serve as a network safety mechanism to prevent excessive and uncontrolled neuronal firing resulting from the lack of inhibition or after acute suppression of the inhibitory drive.

Phase-dependent stimulation effects on bursting activity in a neural network cortical simulation.

PURPOSE: A neural network simulation with realistic cortical architecture has been used to study synchronized bursting as a seizure representation. This model has the property that bursting epochs arise and cease spontaneously, and bursting epochs can be induced by external stimulation. We have used this simulation to study the time-frequency properties of the evolving bursting activity, as well as effects due to network stimulation. METHODS: The model represents a cortical region of 1.6 mm x 1.6mm, and includes seven neuron classes organized by cortical layer, inhibitory or excitatory properties, and electrophysiological characteristics. There are a total of 65,536 modeled single compartment neurons that operate according to a version of Hodgkin-Huxley dynamics. The intercellular wiring is based on histological studies and our previous modeling efforts. RESULTS: The bursting phase is characterized by a flat frequency spectrum. Stimulation pulses are applied to this modeled network, with an electric field provided by a 1mm radius circular electrode represented mathematically in the simulation. A phase dependence to the post-stimulation quiescence is demonstrated, with local relative maxima in efficacy occurring before or during the network depolarization phase in the underlying activity. Brief periods of network insensitivity to stimulation are also demonstrated. The phase dependence was irregular and did not reach statistical significance when averaged over the full 2.5s of simulated bursting investigated. This result provides comparison with previous in vivo studies which have also demonstrated increased efficacy of stimulation when pulses are applied at the peak of the local field potential during cortical after discharges. The network bursting is synchronous when comparing the different neuron classes represented up to an uncertainty of 10 ms. Studies performed with an excitatory chandelier cell component demonstrated increased synchronous bursting in the model, as predicted from experimental work. CONCLUSIONS: This large-scale multi-neuron neural network simulation reproduces many aspects of evolving cortical bursting behavior as well as the timing-dependent effects of electrical stimulation on that bursting.

Studies of stimulus parameters for seizure disruption using neural network simulations.

A large scale neural network simulation with realistic cortical architecture has been undertaken to investigate the effects of external electrical stimulation on the propagation and evolution of ongoing seizure activity. This is an effort to explore the parameter space of stimulation variables to uncover promising avenues of research for this therapeutic modality. The model consists of an approximately 800 mum x 800 mum region of simulated cortex, and includes seven neuron classes organized by cortical layer, inhibitory or excitatory properties, and electrophysiological characteristics. The cell dynamics are governed by a modified version of the Hodgkin-Huxley equations in single compartment format. Axonal connections are patterned after histological data and published models of local cortical wiring. Stimulation induced action potentials take place at the axon initial segments, according to threshold requirements on the applied electric field distribution. Stimulation induced action potentials in horizontal axonal branches are also separately simulated. The calculations are performed on a 16 node distributed 32-bit processor system. Clear differences in seizure evolution are presented for stimulated versus the undisturbed rhythmic activity. Data is provided for frequency dependent stimulation effects demonstrating a plateau effect of stimulation efficacy as the applied frequency is increased from 60 to 200 Hz. Timing of the stimulation with respect to the underlying rhythmic activity demonstrates a phase dependent sensitivity. Electrode height and position effects are also presented. Using a dipole stimulation electrode arrangement, clear orientation effects of the dipole with respect to the model connectivity is also demonstrated. A sensitivity analysis of these results as a function of the stimulation threshold is also provided.