scholarly journals Naming-related spectral responses predict neuropsychological outcome after epilepsy surgery

2021 ◽  
Author(s):  
Masaki Sonoda ◽  
Robert Rothermel ◽  
Alanna Carlson ◽  
Jeong-Won Jeong ◽  
Min-Hee Lee ◽  
...  
Keyword(s):  
Prediction Model ◽  
Epilepsy Surgery ◽  
Picture Naming ◽  
Receptive Language ◽  
Epileptogenic Zone ◽  
Neuropsychological Outcome ◽  
Language Function ◽  
Time Frequency ◽  
Naming Tasks ◽  
Spectral Responses

SUMMARYThis prospective study determined the utility of intracranially-recorded spectral responses during naming tasks in predicting neuropsychological performance following epilepsy surgery. We recruited 65 patients with drug-resistant focal epilepsy who underwent preoperative neuropsychological assessment and intracranial EEG (iEEG) recording. The Clinical Evaluation of Language Fundamentals (CELF) evaluated the baseline and postoperative language function. During extraoperative iEEG recording, we assigned patients to undergo auditory and picture naming tasks. Time-frequency analysis determined the spatiotemporal characteristics of naming-related amplitude modulations, including high gamma augmentation (HGA) at 70-110 Hz. We surgically removed the presumed epileptogenic zone based on the extent of iEEG and MRI abnormalities while maximally preserving the eloquent areas defined by electrical stimulation mapping (ESM). The multivariate regression model incorporating auditory naming-related HGA predicted the postoperative changes in Core Language Score (CLS) on CELF with r2 of 0.37 (p = 0.015) and in Expressive Language Index (ELI) with r2 of 0.32 (p = 0.047). Independently of the effects of epilepsy and neuroimaging profiles, higher HGA at the resected language-dominant hemispheric area predicted a more severe postoperative decline in CLS (p = 0.004) and ELI (p = 0.012). Conversely, the model incorporating picture naming-related HGA predicted the change in Receptive Language Index (RLI) with r2 of 0.50 (p < 0.001). Higher HGA independently predicted a more severe postoperative decline in RLI (p = 0.03). Ancillary regression analysis indicated that naming-related low gamma augmentation as well as alpha/beta attenuation likewise independently predicted a more severe CLS decline. The machine learning-based prediction model, referred to as the boosted tree ensemble model, suggested that naming-related HGA, among all spectral responses utilized as predictors, most strongly contributed to the improved prediction of patients showing a >5-point CLS decline (reflecting the lower 25 percentile among patients). We generated the model-based atlas visualizing sites, which, if resected, would lead to such a CLS decline. The auditory naming-based model predicted patients who developed the CLS decline with an accuracy of 0.80. The model indicated that virtual resection of an ESM-defined language site would have increased the relative risk of the CLS decline by 5.28 (95%CI: 3.47 to 8.02). Especially, that of an ESM-defined receptive language site would have maximized it to 15.90 (95%CI: 9.59-26.33). In summary, naming-related spectral responses predict objectively-measured neuropsychological outcome after epilepsy surgery. We have provided our prediction model as an open-source material, which will indicate the postoperative language function of future patients and facilitate external validation at tertiary epilepsy centers.

Predicting Change Prone Classes in Open Source Software

2018 ◽  
Vol 8 (4) ◽  
pp. 1-23 ◽  
Author(s):  
Deepa Godara ◽  
Amit Choudhary ◽  
Rakesh Kumar Singh
Keyword(s):  
Prediction Model ◽  
Open Source ◽  
Open Source Software ◽  
Prediction Models ◽  
New Technology ◽  
Modern Technology ◽  
Time Frequency ◽  
Rigorous Testing ◽  
Technology Changes ◽  
Sensitivity Specificity

In today's world, the heart of modern technology is software. In order to compete with pace of new technology, changes in software are inevitable. This article aims at the association between changes and object-oriented metrics using different versions of open source software. Change prediction models can detect the probability of change in a class earlier in the software life cycle which would result in better effort allocation, more rigorous testing and easier maintenance of any software. Earlier, researchers have used various techniques such as statistical methods for the prediction of change-prone classes. In this article, some new metrics such as execution time, frequency, run time information, popularity and class dependency are proposed which can help in prediction of change prone classes. For evaluating the performance of the prediction model, the authors used Sensitivity, Specificity, and ROC Curve. Higher values of AUC indicate the prediction model gives significant accurate results. The proposed metrics contribute to the accurate prediction of change-prone classes.

scholarly journals Medically resistant pediatric insular-opercular/perisylvian epilepsy. Part 1: invasive monitoring using the parasagittal transinsular apex depth electrode

2016 ◽  
Vol 18 (5) ◽  
pp. 511-522 ◽  
Author(s):  
Alexander G. Weil ◽  
Aria Fallah ◽  
Evan C. Lewis ◽  
Sanjiv Bhatia
Keyword(s):  
Epilepsy Surgery ◽  
Electrode Placement ◽  
Epileptogenic Zone ◽  
Drug Resistant ◽  
Depth Electrodes ◽  
Depth Electrode ◽  
Age At Surgery ◽  
Feasible Alternative ◽  
The Mean ◽  
Drug Resistant Epilepsy

OBJECTIVE Insular lobe epilepsy (ILE) is an under-recognized cause of extratemporal epilepsy and explains some epilepsy surgery failures in children with drug-resistant epilepsy. The diagnosis of ILE usually requires invasive investigation with insular sampling; however, the location of the insula below the opercula and the dense middle cerebral artery vasculature renders its sampling challenging. Several techniques have been described, ranging from open direct placement of orthogonal subpial depth and strip electrodes through a craniotomy to frame-based stereotactic placement of orthogonal or oblique electrodes using stereo-electroencephalography principles. The authors describe an alternative method for sampling the insula, which involves placing insular depth electrodes along the long axis of the insula through the insular apex following dissection of the sylvian fissure in conjunction with subdural electrodes over the lateral hemispheric/opercular region. The authors report the feasibility, advantages, disadvantages, and role of this approach in investigating pediatric insular-opercular refractory epilepsy. METHODS The authors performed a retrospective analysis of all children (< 18 years old) who underwent invasive intracranial studies involving the insula between 2002 and 2015. RESULTS Eleven patients were included in the study (5 boys). The mean age at surgery was 7.6 years (range 0.5–16 years). All patients had drug-resistant epilepsy as defined by the International League Against Epilepsy and underwent comprehensive noninvasive epilepsy surgery workup. Intracranial monitoring was performed in all patients using 1 parasagittal insular electrode (1 patient had 2 electrodes) in addition to subdural grids and strips tailored to the suspected epileptogenic zone. In 10 patients, extraoperative monitoring was used; in 1 patient, intraoperative electrocorticography was used alone without extraoperative monitoring. The mean number of insular contacts was 6.8 (range 4–8), and the mean number of fronto-parieto-temporal hemispheric contacts was 61.7 (range 40–92). There were no complications related to placement of these depth electrodes. All 11 patients underwent subsequent resective surgery involving the insula. CONCLUSIONS Parasagittal transinsular apex depth electrode placement is a feasible alternative to orthogonally placed open or oblique-placed stereotactic methodologies. This method is safe and best suited for suspected unilateral cases with a possible extensive insular-opercular epileptogenic zone.

The influence of spelling on the production and storage of words with allophonic variants of /h/ in Korean

2015 ◽  
Vol 37 (4) ◽  
pp. 757-780 ◽  
Author(s):  
JEONG-IM HAN ◽  
TAE-HWAN CHOI
Keyword(s):  
Picture Naming ◽  
Phonological Representation ◽  
Recall Task ◽  
Auditory Stimuli ◽  
Auditory Input ◽  
The Third ◽  
Korean Speakers ◽  
And Storage ◽  
Naming Tasks

ABSTRACTThis study examined the role of orthography in the production and storage of spoken words. Korean speakers learned novel Korean words with potential variants of /h/, including [ɦ] and ø. They were provided with the same auditory stimuli but with varying exposure to spelling. One group was presented with the letter for ø (<ㅇ>), the second group, the letter for [ɦ] (<ㅎ>), and the third group, auditory input only. In picture-naming tasks, the participants presented with <ㅇ> produced fewer words with [ɦ] than those presented with <ㅎ>. In a spelling recall task, the participants who were not exposed to spelling displayed various types of spellings for variants, but after exposure to spelling, they began to produce spellings as provided in the task. These results suggest that orthographic information influences the production of words via an offline restructuring of the phonological representation.

scholarly journals The proportion of seizure onset zone contacts resected is not associated with outcome following SEEG-guided resective epilepsy surgery in children

2021 ◽  
Author(s):  
Mehdi Khan ◽  
Aswin Chari ◽  
Kiran Seunarine ◽  
Christin Eltze ◽  
Friederike Moeller ◽  
...  
Keyword(s):  
Epilepsy Surgery ◽  
Univariate Analysis ◽  
Seizure Outcome ◽  
Epileptogenic Zone ◽  
Imaging Data ◽  
Seizure Onset ◽  
Binary Logistic Regression Model ◽  
Primary Analysis ◽  
Seizure Onset Zone

AbstractPurposeChildren undergoing stereoelectroencephalography (SEEG)-guided epilepsy surgery represent a complex cohort. We aimed to determine whether the proportion of putative seizure onset zone (SOZ) contacts resected associates with seizure outcome in a cohort of children undergoing SEEG-guided resective epilepsy surgery.MethodsPatients who underwent SEEG-guided resective surgery over a six-year period were included. The proportion of SOZ contacts resected was determined by co-registration of pre- and post-operative imaging. Seizure outcomes were classified as seizure free (SF, Engel class I) or not seizure-free (NSF, Engel class II-IV) at last clinical follow-up.ResultsOf 94 patients undergoing SEEG, 29 underwent subsequent focal resection of whom 22 had sufficient imaging data to be included in the primary analysis (median age at surgery of 10 years, range 5-18). Fifteen (68.2%) were SF and 7 (31.8%) NSF at median follow-up of 19.5 months (range 12-46). On univariate analysis, histopathology, was the only significant factor associated with SF (p<0.05). The percentage of defined SOZ contacts resected ranged from 25-100% and was not associated with SF (p=0.89). In a binary logistic regression model, it was highly likely that histology was the only independent predictor of outcome, although the interpretation was limited by pseudo-complete separation of the data.ConclusionHistopathology is a significant predictor of surgical outcomes in children undergoing SEEG-guided resective epilepsy surgery. The percentage of SOZ contacts resected was not associated with SF. Factors such as spatial organisation of the epileptogenic zone, neurophysiological biomarkers and the prospective identification of pathological tissue may therefore play an important role.

scholarly journals Naming pictures and sounds: Stimulus type affects semantic context effects

2020 ◽  
Author(s):  
Stefan Wöhner ◽  
Andreas Mädebach ◽  
Jörg D. Jescheniak
Keyword(s):  
Picture Naming ◽  
Context Effect ◽  
Context Effects ◽  
Semantic Category ◽  
Naming Task ◽  
Semantic Context ◽  
Perceptual Processing ◽  
Semantic Interference ◽  
Lexical Processes ◽  
Naming Tasks

Semantic context effects obtained in naming tasks have been most influential in devising and evaluating models of word production. We re-investigated this effect in the frequently used blocked-cyclic naming task in which stimuli are presented repeatedly either sorted by semantic category (homogeneous context) or intermixed (heterogeneous context). Previous blocked-cyclic naming studies have shown slower picture naming responses in the homogeneous context. Our study compared this context effect in two task versions, picture naming and sound naming. Target words were identical across task versions (e.g., participants responded with the word “dog” to either the picture of that animal or to the sound [barking] produced by it). We found semantic interference in the homogeneous context also with sounds and the effect was substantially larger than with pictures (Experiments 1 and 2). This difference is unlikely to result from extended perceptual processing of sounds as compared to pictures (Experiments 3 and 4) or from stronger links between pictures and object names than between sounds and object names (Experiment 5). Overall, our results show that semantic context effects in blocked-cyclic naming generalize to stimulus types other than pictures and – in part – also reflect pre-lexical processes that depend on the nature of the stimuli used for eliciting the naming responses.

scholarly journals Association of fast ripples on intracranial EEG and outcomes after epilepsy surgery

Neurology ◽  
2020 ◽  
Vol 95 (16) ◽  
pp. e2235-e2245
Author(s):  
Päivi Nevalainen ◽  
Nicolás von Ellenrieder ◽  
Petr Klimeš ◽  
François Dubeau ◽  
Birgit Frauscher ◽  
...  
Keyword(s):  
Epilepsy Surgery ◽  
Slow Wave Sleep ◽  
Seizure Outcome ◽  
Incomplete Resection ◽  
Epileptogenic Zone ◽  
Poor Prognostic Factor ◽  
Individual Level ◽  
Poor Outcome ◽  
Surgery Outcome ◽  
The Individual

ObjectiveTo examine whether fast ripples (FRs) are an accurate marker of the epileptogenic zone, we analyzed overnight stereo-EEG recordings from 43 patients and hypothesized that FR resection ratio, maximal FR rate, and FR distribution predict postsurgical seizure outcome.MethodsWe detected FRs automatically from an overnight recording edited for artifacts and visually from a 5-minute period of slow-wave sleep. We examined primarily the accuracy of removing ≥50% of total FR events or of channels with FRs to predict postsurgical seizure outcome (Engel class I = good, classes II–IV = poor) according to the whole-night and 5-minute analysis approaches. Secondarily, we examined the association of low overall FR rates or absence or incomplete resection of 1 dominant FR area with poor outcome.ResultsThe accuracy of outcome prediction was highest (81%, 95% confidence interval [CI] 67%–92%) with the use of the FR event resection ratio and whole-night recording (vs 72%, 95% CI 56%–85%, for the visual 5-minute approach). Absence of channels with FR rates >6/min (p = 0.001) and absence or incomplete resection of 1 dominant FR area (p < 0.001) were associated with poor outcome.ConclusionsFRs are accurate in predicting epilepsy surgery outcome at the individual level when overnight recordings are used. Absence of channels with high FR rates or absence of 1 dominant FR area is a poor prognostic factor that may reflect suboptimal spatial sampling of the epileptogenic zone or multifocality, rather than an inherently low sensitivity of FRs.Classification of evidenceThis study provides Class II evidence that FRs are accurate in predicting epilepsy surgery outcome.

An intelligent prediction model of the tool wear based on machine learning in turning high strength steel

2020 ◽  
Vol 234 (13) ◽  
pp. 1580-1597
Author(s):  
Minghui Cheng ◽  
Li Jiao ◽  
Xuechun Shi ◽  
Xibin Wang ◽  
Pei Yan ◽  
...  
Keyword(s):  
Tool Wear ◽  
Prediction Model ◽  
Cutting Force ◽  
Surface Quality ◽  
Surface Texture ◽  
High Strength Steel ◽  
Prediction Models ◽  
High Strength ◽  
Support Vector ◽  
Time Frequency

In the process of high strength steel turning, tool wear will reduce the surface quality of the workpiece and increase cutting force and cutting temperature. To obtain the fine surface quality and avoid unnecessary loss, it is necessary to monitor the state of tool wear in the dry turning. In this article, the cutting force, vibration signal and surface texture of the machined surface were collected by tool condition monitoring system and signal processing techniques are being used for extracting the time-domain, frequency-domain and time-frequency features of cutting force and vibration. The gray level processing technique is used to extract the features of the gray co-occurrence matrix of the surface texture and found that these features changed simultaneously when the cutting tool broke. After this, an intelligent prediction model of tool wear was built using the support vector regression (SVR) whose kernel function parameters were optimized by the grid search algorithm (GS), the genetic algorithm (GA) and the particle swarm optimization algorithm respectively. The features extracted from the signals and surface texture are used to train the prediction model in MATLAB. It was found that after the surface texture features were fused using the intelligent prediction model on the basis of the features of cutting force and vibration, prediction accuracy of the proposed method is found as 97.32% and 96.72% respectively under the two prediction models of GA-SVR and GS-SVR. Moreover, the intelligent prediction model can not only predict the tool wear under different cutting conditions, but also the different wear stages in a single wear cycle and the absolute error between the predicted value and the actual value is less than 10 μm, the confidence coefficient of prediction curve is around 0.99.

scholarly journals A-080 Prediction Model for Verbal Memory Decline in Different Epilepsy Surgery Procedures: Temporal Lobectomy vs. Amygdalohippocampectomy

2020 ◽  
Vol 35 (6) ◽  
pp. 872-872
Author(s):  
Hageboutros K ◽  
Bono A ◽  
Johnson-Markve B ◽  
Smith K ◽  
Lee G
Keyword(s):  
Prediction Model ◽  
Epilepsy Surgery ◽  
Verbal Memory ◽  
Memory Loss ◽  
Low Risk ◽  
Temporal Lobectomy ◽  
Moderate Risk ◽  
Memory Decline ◽  
Selective Amygdalohippocampectomy ◽  
Risk Patients

Abstract Objective Mathematical models predicting risk of verbal memory decline after resective epilepsy surgery have been developed for patients undergoing temporal lobectomies. This study was undertaken to determine if application of the Stroup memory loss prediction model was as accurate in foreseeing verbal memory decline after temporal lobectomy as in the less invasive selective amygdalohippocampectomy procedure. Method This retrospective study examined the verbal memory performances of 40 left temporal lobectomy (ATL), and 16 left subtemporal approach selective amygdalohippocampectomy (SA-H), patients before and after epilepsy surgery using word list learning (Rey Auditory-Verbal Learning Test, Buschke Selective Reminding Test) and story memory (WMS Logical Memory) tests. Patients were assigned to one of four groups using the Stroup multiple regression equation: Minimal Risk (61% risk). To classify memory decline in individual patients, a pre-to-post surgery decrease of &gt; 1 SD on at least one memory test constituted memory decline. Results The prediction model accurately classified 82% (9/11) of ATL, and 75% (3/4) of SA-H, High Risk patients. Verbal memory loss was higher among ATLs than SA-Hs in the Moderate Risk (87% vs. 18%) and Low Risk (71% vs. 0%) groups. Conclusion The Stroup verbal memory loss risk model under-predicted memory loss among temporal lobectomy patients (71% of Low Risk patients showed memory decline) and over-predicted memory loss among selective amygdalohippocampectomy patients (only 18% of Moderate Risk patients showed memory decline). Results should be considered preliminary due to methodological limitation including small Ns and unequal sample sizes.

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