Amplitude Variation Research Articles

Acoustic Signal Reconstruction Across Water–Air Interface Through Millimeter-Wave Radar Micro-Vibration Detection

Water surface micro-amplitude waves (WSMWs) of identical frequency are elicited as acoustic waves propagating through water. This displacement can be translated into an intermediate frequency (IF) phase shift through transmitting a frequency modulated continuous wave (FMCW) towards the water surface by a millimeter-wave radar, and information transmission across the water–air interface is achieved via the signal reconstruction method. In this paper, a novel mathematical model based on energy conversion from underwater acoustic to vibration (ECUAV) is presented. This method was able to obtain WSMW vibration information directly by measuring the sound source level (SL). An acoustic electromagnetic wave-based information transmission (AEIT) system was integrated within the water tank environment. The measured distribution of SL within the frequency range of 100 Hz to 300 Hz exhibited the same amplitude variation trend as predicted by the ECUAV model. Thus, the WSMW formation process at 135 Hz was simulated, and the phase information was extracted. The initial vibration information was retrieved through a combination of phase unwinding and Butterworth digital filtering. Fourier transform was applied to the vibrational data to accurately reproduce the acoustic frequency of underwater nodes. Finally, the dual-band binary frequency shift keying (BFSK) modulated underwater encoding acoustic signal was effectively recognized and reconstructed by the AEIT system.

Self-supervised learning for denoising of multidimensional MRI data.

To develop a fast denoising framework for high-dimensional MRI data based on a self-supervised learning scheme, which does not require ground truth clean image. Quantitative MRI faces limitations in SNR, because the variation of signal amplitude in a large set of images is the key mechanism for quantification. In addition, the complex non-linear signal models make the fitting process vulnerable to noise. To address these issues, we propose a fast deep-learning framework for denoising, which efficiently exploits the redundancy in multidimensional MRI data. A self-supervised model was designed to use only noisy images for training, bypassing the challenge of clean data paucity in clinical practice. For validation, we used two different datasets of simulated magnetization transfer contrast MR fingerprinting (MTC-MRF) dataset and in vivo DWI image dataset to show the generalizability. The proposed method drastically improved denoising performance in the presence of mild-to-severe noise regardless of noise distributions compared to previous methods of the BM3D, tMPPCA, and Patch2self. The improvements were even pronounced in the following quantification results from the denoised images. The proposed MD-S2S (Multidimensional-Self2Self) denoising technique could be further applied to various multi-dimensional MRI data and improve the quantification accuracy of tissue parameter maps.

Seismic Rock Properties and Their Significance for the Interpretation of Seismic Amplitude Variation with Angle (AVA), Offshore Liberia and Sierra Leone

Seismic Rock Properties and Their Significance for the Interpretation of Seismic Amplitude Variation with Angle (AVA), Offshore Liberia and Sierra Leone

A comprehensive study of five candidate δ Scuti-type pulsators in detached eclipsing binaries

Context. Pulsating stars in eclipsing binaries (EBs) provide an excellent opportunity to obtain precise, model-independent stellar parameters for studying these oscillations in detail. One of the most common classes of pulsators found in such EBs exhibits δ Scuti-type oscillations. Characterising these pulsators using the precise stellar parameters obtained using EB modelling can help us better understand such stars, and provide strong anchors for asteroseismic studies. Aims. We performed a comprehensive photometric and spectroscopic analysis of candidate pulsators in detached EBs, to add to the sample of such systems with accurately determined absolute parameters. Methods. We performed radial velocity and light curve modelling to estimate the absolute stellar parameters, and detailed spectroscopic modelling to obtain the global metallicity and temperatures. Frequency power spectra were obtained using residuals from binary modelling. Finally, we used isochrones to determine the age of the stars, and compared the estimated physical parameters to the theoretically obtained values. Results. We present a detailed analysis of four candidate δ Scuti-type pulsators in EBs, and update the light curve analysis of the previously studied system TIC 308953703. The masses and radii of components are constrained to a high accuracy, which helps us constrain the age of the systems. We perform a Fourier analysis of the observed oscillations, and try to explain their origin. For TIC 81702112, we report tidal effects causing amplitude variation in the oscillation frequencies over the orbital phase.

Enhanced Terahertz Characterization of Multilayer Graphene on Guided‐Mode Resonance Filter: Boosting Sensitivity and Precision in Electrical and Optical Characteristics

AbstractIn this study, terahertz time‐domain spectroscopy (THz‐TDS) is employed for the first time to explore the characteristics of mono‐, bi‐, and tri‐layer graphene coated on guided‐mode resonance filters (GMRFs). Owing to high quality‐factor (Q‐factor) resonances of GMRF, the proposed method significantly enhances the resonance depth variation by up to 9.3, 5.1, and 4.2 times at 0.58 THz in TE mode for mono‐, bi‐, and tri‐layer graphene, respectively, in contrast to conventional THz‐TDS methods relying on amplitude variation at 0.50 THz in TE mode. Excellent agreement is observed between experimental results and theoretical simulations using the Kubo formula and Drude model, even accounting for variations in sidelobes at an incident angle of 0.6 degrees. Through meticulous fitting process between measurements and simulations for the resonances formed by the GMRF and graphene, the study accurately determines the electrical and optical properties of mono‐, bi‐, and tri‐layer graphene, including frequency‐dependent sheet conductivity (σs(ω)), mobility (μ), carrier density (N), and Fermi velocity (vF). Furthermore, in the THz high‐frequency region, the observation reveals that as the number of graphene layers increases, the decrease in σs(ω) occurs more rapidly than in single‐layer graphene, attributed to the screening effect arising from electronic interactions between each graphene layer.

Interaction of driven ``cold'' electron plasma wave with thermal bulk via ion spatial inhomogeneity

Abstract Using high resolution Vlasov - Poisson simulations, evolution of driven ``cold" electron plasma wave (EPW) in the presence of stationary inhomogeneous background of ions is studied. Mode coupling dynamics between ``cold'' EPW with phase velocity $v_{\phi}$ greater than thermal velocity i.e $v_{\phi} \gg v_{thermal}$ and its inhomogeneity induced sidebands is illustrated as an initial value problem. In driven cases, formation of BGK like phase space structures corresponding to sideband modes due to energy exchange from primary mode to bulk particles via wave-wave and wave-particle interactions leading to particle trapping is demonstrated for inhomogeneous plasma. Qualitative comparison studies between initial value perturbation and driven problem is presented, which examines the relative difference in energy transfer time between the interacting modes. Effect of variation in background ion inhomogeneity amplitude as well as ion inhomogeneity scale length on the driven EPWs is reported.

Exploring LGE areas in the atria: Insights from electroanatomical voltage mapping in AF patients

Abstract Introduction Late gadolinium enhancement MRI (LGE MRI) is a common method for the evaluation of the atrial substrate in atrial fibrillation (AF) patients. The extent of LGE is associated with atrial cardiomyopathy and ablation outcomes. However, previous studies have yielded inconsistent results in detecting low voltage areas (LVA) using bipolar electroanatomical mapping (EAM) in LGE regions. Objective Conduct a thorough analysis of the bipolar and unipolar voltage in LGE areas and its relationship with the voltage in non-LGE areas, utilizing high-density (HD) EAM generated by a multipolar HD-mapping catheter. Methods In this study, 20 patients undergoing AF ablation were examined using LGE-MRI. A 3D mesh integrating LGE data was generated. HD-EAM (> 4000 points) was performed in sinus rhythm. The EAM map and MRI mesh underwent manual alignment and registration. Using a nearest neighbor algorithm, EAM points nearest to LGE areas were identified, and the corresponding unipolar and bipolar voltage values, along with LGE voxel intensity, were exported for analysis. Results LGE areas exhibited a median bipolar voltage amplitude of 0.93 mV, median unipolar voltage of 1.73 mV. In contrast, areas without enhancement displayed median bipolar voltage of 2.33 mV, unipolar voltage of 3.58 mV. We observed a variation in voltage amplitudes across the different LGE areas: bipolar voltage ranged from 0.04 to 2.51 mV and unipolar voltage from 0.22 to 3.75 mV. This variation strongly correlated with voxel intensity in LGE areas (correlation coefficient r = -0.86 [p <0.001]). Irrespective of the voltage amplitude in the examined LGE areas, a significant voltage drop was observed, with an average reduction of 54% in bipolar and 51% in unipolar voltages, compared to the amplitudes in non-LGE areas within the same atria. Conclusion Variations in bipolar and unipolar voltage within LGE areas are significantly correlated with local voxel intensity. Despite the inconsistent overlap with the predefined bipolar threshold for LVA, LGE regions exhibit a pronounced and consistent reduction in both bipolar and unipolar voltage compared to non-LGE areas. This pattern suggests notable electrophysiological changes in these areas. These insights underscore the need for further investigation to better understand the implications and mechanisms underlying these alterations in LGE regions.

Tunable topological phases in nanographene-based spin-1/2 alternating-exchange Heisenberg chains.

Unlocking the potential of topological order in many-body spin systems has been a key goal in quantum materials research. Despite extensive efforts, the quest for a versatile platform enabling site-selective spin manipulation, essential for tuning and probing diverse topological phases, has persisted. Here we utilize on-surface synthesis to construct spin-1/2 alternating-exchange Heisenberg chains by covalently linking Clar's goblets-nanographenes each hosting two antiferromagnetically coupled spins. Using scanning tunnelling microscopy, we exert atomic-scale control over chain lengths, parities and exchange-coupling terminations, and probe their magnetic response via inelastic tunnelling spectroscopy. Our investigation confirms the gapped nature of bulk excitations in the chains, known as triplons. Their dispersion relation is extracted from the spatial variation of tunnelling spectral amplitudes. Depending on the parity and termination of chains, we observe varying numbers of in-gap spin-1/2 edge excitations, reflecting the degeneracy of distinct topological ground states in the thermodynamic limit. By monitoring interactions between these edge spins, we identify the exponential decay of spin correlations. Our findings present a phase-controlled many-body platform, opening avenues toward spin-based quantum devices.

Review of Research Progress on Acoustic Test Equipment for Hydrate-Bearing Sediments

When acoustic waves propagate through hydrate samples, they carry extensive information related to their physical and mechanical properties. These details are comprehensively reflected in acoustic parameters such as velocity, attenuation coefficient, waveform, frequency, spectrum, and amplitude variations. Based on these parameters, it is possible to invert the physical and mechanical indicators and microstructural characteristics of hydrate samples, thereby addressing a series of issues in hydrate development engineering. This study first provides an overview of the current applications and prospects of acoustic testing in hydrate development. Subsequently, it systematically elaborates on the progress in research on acoustic testing systems for hydrate samples, including the principles of acoustic testing, ship-borne hydrate core acoustic detection systems, laboratory hydrate sample acoustic testing systems, and resonance column experimental systems. Based on this foundation, this study further discusses the development trends and challenges of acoustic testing equipment for hydrate-bearing sediments.

A new expression for fluid factor using AVO intercept and gradient: Theory and application on gas sand reservoirs from offshore Australia

Numerous amplitude variation with offset (AVO) fluid indicators have proven to be sensitive to the presence of hydrocarbons. Mathematically, these fluid indicators measure the deviation of seismic responses of hydrocarbon reservoirs from their background in a specific domain. We develop a new expression for the fluid factor commonly used in AVO analysis and interpretation. The expression is a function of the common AVO intercept and gradient, along with a weighting coefficient that suppresses the contribution of lithology and other factors unrelated to fluid content. The coefficient also assists in calibrating the fluid factor to the local geology. We compare the performance of our fluid factor with existing fluid factors. All the fluid factors are tested on a worldwide collection of P- and S-wave velocity and density measurements. The testing is followed by application on synthetic data before applying the attribute on real data from the Northwest Shelf of Australia. In the latter application on the real data, we use two wells for calibration purposes, and the third as a blind well. Our fluid factor demonstrated high capability in detecting the targeted gas zones at the three well locations and identifying new prospective zones.

Persistently active El Niño–Southern Oscillation since the Mesozoic

The El Niño-Southern Oscillation (ENSO), originating in the central and eastern equatorial Pacific, is a defining mode of interannual climate variability with profound impact on global climate and ecosystems. However, an understanding of how the ENSO might have evolved over geological timescales is still lacking, despite a well-accepted recognition that such an understanding has direct implications for constraining human-induced future ENSO changes. Here, using climate simulations, we show that ENSO has been a leading mode of tropical sea surface temperature (SST) variability in the past 250 My but with substantial variations in amplitude across geological periods. We show this result by performing and analyzing a series of coupled time-slice climate simulations forced by paleogeography, atmospheric CO2 concentrations, and solar radiation for the past 250 My, in 10-My intervals. The variations in ENSO amplitude across geological periods are little related to mean equatorial zonal SST gradient or global mean surface temperature of the respective periods but are primarily determined by interperiod difference in the background thermocline depth, according to a linear stability analysis. In addition, variations in atmospheric noise serve as an independent contributing factor to ENSO variations across intergeological periods. The two factors together explain about 76% of the interperiod variations in ENSO amplitude over the past 250 My. Our findings support the importance of changing ocean vertical thermal structure and atmospheric noise in influencing projected future ENSO change and its uncertainty.

Modeling the effect of dispersion and attenuation for frequency-dependent amplitude variation with offset

As research in oil and gas exploration progresses, unconventional resources, such as shale gas, are increasingly becoming the focal point in the global pursuit of oil and gas resource. Shale gas reservoirs significantly differ from conventional sandstone reservoirs in aspects such as rock composition, pore type, occurrence mode, fluid, etc., thereby amplifying the challenges associated with geophysical modeling and the prediction of sweet spots. Since the formation and storage of shale gas are positively correlated with shale fracturing, a modeling approach based on Chapman theory is introduced to complete frequency-dependent petrophysical modeling. Additionally, the Frequency-dependent Amplitude Variation with Offset (FAVO) technique can estimate velocity dispersion by using the reflection coefficient information related to incidence angle and frequency. This method can more effectively identify fluids within shale reservoir. However, current FAVO forward modeling only considers the velocity dispersion and attenuation at the interface, neglecting the attenuation dispersion effects during interlayer propagation. To this end, we utilize Chapman-based petrophysical modeling as a foundation and conduct seismic forward modeling studies employing the compound matrix method. Through experimental analysis, we meticulously examine the attenuation dispersion effects at interfaces and within layers. Finally, we conduct FAVO simulations that vividly delineate the interplay between reservoir parameters and seismic responses.

Prevalent harmonic interaction in the bat inferior colliculus.

Animal vocalizations and human speech are typically characterized by a complex spectrotemporal structure, composed of multiple harmonics, and patterned as temporally organized sequences. However, auditory research often employed simple artificial acoustic stimuli or their combinations. Here we addressed the question of whether the neuronal responses to natural echolocation call sequences can be predicted by manipulated sequences of incomplete constituents at the midbrain inferior colliculus (IC). We characterized the extracellular single-unit activity of IC neurons in the great roundleaf bat, Hipposideros armiger (both sexes), using natural call sequences, various manipulated sequences of incomplete vocalizations, and pure tones. We report that approximately two-thirds of IC neurons exhibited a harmonic interaction. Neurons with high harmonic interactions exhibited greater selectivity to natural call sequences, and the degree of harmonic interaction was robust to the natural amplitude variations between call harmonics. For 81% of the IC neurons, the responses to the natural echolocation call sequence could not be predicted by altered sequences of missing call components. Surprisingly, nearly 70% of the neurons that showed a harmonic interaction were characterized by a single excitatory response peak as revealed by pure tones. Our results suggest that prevalent harmonic processing has already emerged in the auditory midbrain inferior colliculus in the echolocating bat.Significance Statement Auditory cortex has long been suggested to be the main region for processing complex sound such as natural vocalizations. However, this cortex-centered view of complex stimuli processing was largely based on simple stimuli or their combinations, ignoring many crucial aspects of natural communication behaviors. Here, we took a neuroethological perspective to study the harmonic processing in the inferior colliculus, in the great roundleaf bat. We show that prevalent harmonic processing has already emerged in the auditory midbrain in the echolocating bat. Critically, harmonic interactions revealed by natural call sequences cannot be predicted by responses to either pure tones or altered sequences of missing call components. Our data suggest that auditory midbrain is involved in harmonic processing in the echolocating bat.

Performance evaluation of compansion-based clipped OFDM systems

The peak-to-average power ratio (PAPR), commonly used to describe the amplitude variations of an OFDM (orthogonal frequency-division multiplex) signal, does not accurately reflect its impact on the system performance. This paper applies the mutual information as a metric to assess the effects of nonlinear PAPR reduction schemes on the performance of OFDM systems. Evaluation of the achieved mutual information shows that a significant capacity loss from clipping occurs only at high SNR (signal-to-noise ratio) and a simple compression/expansion technique is proposed to achieve close to optimal performance in this regime. The effectiveness of this method is validated through WER (word error rate) simulations with several modulation and coding schemes.

Deep-Learning-Based Amplitude Variation with Angle Inversion with Multi-Input Neural Networks

Deep-learning-based (DL-based) seismic inversion has emerged as one of the state-of-the-art research areas in exploration geophysics with the development of artificial intelligence technology. Due to its good portability and high computational efficiency, this method has emerged as a data-driven approach for estimating subsurface properties. However, most of the current DL-based methods rely solely on seismic data, lacking the incorporation of prior information. In addition, these methods are usually performed trace-by-trace, resulting in insufficient horizontal constraints. These limitations make traditional methods less robust, particularly when dealing with high noise levels or limited data. To address these challenges, we propose a multi-input deep learning network for pre-stack inversion, which combines data-driven and model-driven approaches for optimization. The proposed method separately extracts features from the model and data, merging them to improve feature utilization. Moreover, by adopting a 2-D training unit, rather than a trace-by-trace approach, the method improves the horizontal continuity of the results. Tests on synthetic and real seismic data confirmed the robustness and improved stability of the proposed method, even under challenging conditions. This dual-driven approach significantly enhances the reliability of seismic inversion.

Methodological Choices Matter: A Systematic Comparison of TMS-EEG Studies Targeting the Primary Motor Cortex.

Transcranial magnetic stimulation (TMS) triggers time-locked cortical activity that can be recorded with electroencephalography (EEG). Transcranial evoked potentials (TEPs) are widely used to probe brain responses to TMS. Here, we systematically reviewed 137 published experiments that studied TEPs elicited from TMS to the human primary motor cortex (M1) in healthy individuals to investigate the impact of methodological choices. We scrutinized prevalent methodological choices and assessed how consistently they were reported in published papers. We extracted amplitudes and latencies from reported TEPs and compared specific TEP peaks and components between studies using distinct methods. Reporting of methodological details was overall sufficient, but some relevant information regarding the TMS settings and the recording and preprocessing of EEG data were missing in more than 25% of the included experiments. The published TEP latencies and amplitudes confirm the "prototypical" TEP waveform following stimulation of M1, comprising distinct N15, P30, N45, P60, N100, and P180 peaks. However, variations in amplitude were evident across studies. Higher stimulation intensities were associated with overall larger TEP amplitudes. Active noise masking during TMS generally resulted in lower TEP amplitudes compared to no or passive masking but did not specifically impact those TEP peaks linked to long-latency sensory processing. Studies implementing independent component analysis (ICA) for artifact removal generally reported lower TEP magnitudes. In summary, some aspects of reporting practices could be improved in future TEP studies to enable replication. Methodological choices, including TMS intensity and the use of noise masking or ICA, introduce systematic differences in reported TEP amplitudes. Further investigation into the significance of these and other methodological factors and their interactions is warranted.

Tides in Complex Coastal Regions: Early Case Studies From Wide‐Swath SWOT Measurements

AbstractStudying ocean tides with satellite altimetry has traditionally been difficult in coastal regions. The 1 day repeat of the Cal/Val phase of SWOT provides a unique dataset that can be exploited for tidal analysis. In this work, KaRIn data from the SWOT Cal/Val phase are analyzed in two coastal regions to present a first look at the possibilities for tidal analysis from SWOT. The areas are: (a) Bristol Channel and (b) Great South Bay. When benchmarked against in situ measurements in these regions, substantial improvements over tide models, which typically report errors exceeding tens of centimeters and degrees, are seen. Specifically, the SWOT ocean‐tide estimates exhibit amplitude discrepancies ranging from 1.75 to 3 cm and phase lag discrepancies between 1.75° and 2.75° when compared with in situ tide gauge data. These findings underscore the value of SWOT for tidal research in complex coastal regions.

Poisson’s ratio-LambdaRho rock-physics templates and a study on sensitivity of different fluid indicators

Seismic fluid indicators are highly accurate when calibrated, but when the data is scarce, an interpreter must choose between different indicators. We investigate the data from multiple basins to understand the most effective fluid indicators for use. Unlike previous studies, the data comprises a large, equal, and statistically meaningful number of hydrocarbon and brine sands from different basins. We show that Poisson’s ratio-LambdaRho templates can be used to separate different facies in synthetic and real data and can be used as a useful crossplot interpretation tool. We develop a fluid indicator, as LambdaRho Poisson’s ratio multiplication [Formula: see text], which is highly sensitive to saturation and can be potentially used as a fizz-gas discriminator. We compare the sensitivity of different fluid indicators to hydrocarbon saturation by using Bhattacharyya distance, which provides a quantitative metric for how well different indicators separate hydrocarbon and brine sands, and it is a nonparametric measure unlike other fluid indicator scores developed in similar studies. Absolute properties derived from seismic by inversion are rarely available in regional studies, whereas relative elastic properties can be easily obtained and used. Following the concepts of elastic reflectivity vectors and geometry of intercept-gradient crossplots, we show how the reflectivity of different fluid indicators can be approximated from amplitude variation with offset (AVO) parameters at various chi ([Formula: see text]) angles, enabling an interpreter to use them even when inversion products are not available. Finally, we compare the effectiveness of relative elastic parameters on different AVO classes and show that no single attribute works best across all classes but for general screening purposes fluid factor and [Formula: see text] can be good choices. The findings of this study can help better characterization of fluids in exploration, appraisal, and development of hydrocarbons, and in other areas where monitoring produced and injected fluids is important like 4D seismic or carbon capture storage.

Effect of FBG Fiber Dosimeter Division in Sensing Capability for Low Radiation Doses

ر A fiber Bragg grating (FBG) as a dosimeter is developed in this simulation study (based on Optisystem 21 software) by dividing its region into five individual regions. The division includes the same properties for all regions, which is a standard SiO2 optical fiber material. In dosimeters, it is convenient to introduce dopants to increase the fiber sensitivity. The new design accepts dopants and can work without such a dopant. Measurements for sensing deflected signals from the FBG sensor confirmed increased sensitivity for low-rate radiation doses in comparison to one bulk region in a traditional fiber dosimeter. The sensitivity of this dosimeter is based on both the FWHM line shape function and the amplitude of the deflected signals. The FBG dosimeter sensor can respond to low-dose radiation in a noticeable manner according to the type of applied simulated effect. Dosimeter body division for multi-regions gives rise to sensitivity in comparison to the traditional bulk region. The measured FWHM from the line-shape function for overall observed signals fluctuates from 0.374 MHz under applied temperature, stress x, y, z, and strain to 0.358, 0.373, 0.3733, 0.368, and 0.3737 MHz, respectively. While this range follows different fitting functions: Sin, Exp.Decay, SinSqu., Exp.Decay3, and GaussAmpl. For last effects, according to measured effect. The same measurements were carried out for signal amplitude variation, with these effects giving a variety of relationships indicating their existing contribution. Results confirmed an efficient tool for use in sensing for low x-ray and gamma ray radiation dose applications versus traditional bulk FBG sensor type.

Variability of cortico-cortical evoked potentials in the epileptogenic zone is related to seizure occurrence.

Cortico-cortical evoked potentials (CCEPs) were described as reproducible during trains of single-pulse electrical stimulations (SPES). Still, few studies described a variability of CCEPs that was higher within the epileptogenic zone (EZ). This study aimed at characterizing the relationship of CCEP variability with the occurrence of interictal/ictal epileptiform discharges at the temporal vicinity of the stimulation, but not during the stimulation, by effective connectivity modifications. We retrospectively included 20 patients who underwent SPES during their stereo-electroencephalography (SEEG). We analyzed the variability of CCEPs by using the post-stimulation time course of intertrial standard deviation (amplitude) and the timing of peak amplitude signal of CCEP epochs (latency). Values were corrected for the Euclidian distance between stimulating/recording electrodes. Receiver operating characteristics curves were used to assess the relationship with the EZ. The link between CCEP variability and interictal discharges occurrence, seizure frequency prior to the SEEG recording, and number of seizures during SEEG recording was assessed with Spearman's correlations. A relationship was demonstrated between the EZ and both the distance-corrected latency variation (area under the curve (AUC): 0.73-0.74) and the distance-corrected amplitude variation (AUC: 0.71-0.72) and both were related with the occurrence of seizures. Seizures before/during SEEG impact the dynamics of effective connectivity within the epileptogenic network by reducing the variability of CCEP latency/amplitude when the seizure frequency increases. It suggests a strengthening of the epileptogenic network with the occurrence of many seizures. These findings stress the importance of early epilepsy surgery at a time when the network organization has not yet been complete.