Electroencephalography (EEG) has emerged as a primary non-invasive and mobile modality for understanding the complex workings of the human brain, providing invaluable insights into cognitive processes, neurological disorders, and brain-computer interfaces. Nevertheless, the volume of EEG data, the presence of artifacts, the selection of optimal channels, and the need for feature extraction from EEG data present considerable challenges in achieving meaningful and distinguishing outcomes for machine learning algorithms utilized to process EEG data. Consequently, the demand for sophisticated optimization techniques has become imperative to overcome these hurdles effectively. Evolutionary algorithms (EAs) and other nature-inspired metaheuristics have been applied as powerful design and optimization tools in recent years, showcasing their significance in addressing various design and optimization problems relevant to brain EEG-based applications. This paper presents a comprehensive survey highlighting the importance of EAs and other metaheuristics in EEG-based applications. The survey is organized according to the main areas where EAs have been applied, namely artifact mitigation, channel selection, feature extraction, feature selection, and signal classification. Finally, the current challenges and future aspects of EAs in the context of EEG-based applications are discussed.

• MeSH
• algoritmy * MeSH
• artefakty MeSH
• elektroencefalografie * metody   MeSH
• lidé MeSH
• mozek * fyziologie   MeSH
• rozhraní mozek-počítač MeSH
• strojové učení MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

Objective.The proportion of patients becoming seizure-free after epilepsy surgery has stagnated. Large multi-center stereo-electroencephalography (SEEG) datasets can allow comparing new patients to past similar cases and making clinical decisions with the knowledge of how cases were treated in the past. However, the complexity of these evaluations makes the manual search for similar patients impractical. We aim to develop an automated system that electrographically and anatomically matches seizures to those in a database. Additionally, since features that define seizure similarity are unknown, we evaluate the agreement and features among experts in classifying similarity.Approach.We utilized 320 SEEG seizures from 95 consecutive patients who underwent epilepsy surgery. Eight international experts evaluated seizure-pair similarity using a four-level similarity score. As our primary outcome, we developed and validated an automated seizure matching system by employing patient data marked by independent experts. Secondary outcomes included the inter-rater agreement (IRA) and features for classifying seizure similarity.Main results.The seizure matching system achieved a median area-under-the-curve of 0.76 (interquartile range, 0.1), indicating its feasibility. Six distinct seizure similarity features were identified and proved effective: onset region, onset pattern, propagation region, duration, extent of spread, and propagation speed. Among these features, the onset region showed the strongest correlation with expert scores (Spearman's rho = 0.75,p< 0.001). Additionally, the moderate IRA confirmed the practicality of our approach with an agreement of 73.9% (7%), and Gwet's kappa of 0.45 (0.16). Further, the interoperability of the system was validated on seizures from five centers.Significance.We demonstrated the feasibility and validity of a SEEG seizure matching system across patients, effectively mirroring the expertise of epileptologists. This novel system can identify patients with seizures similar to that of a patient being evaluated, thus optimizing the treatment plan by considering the results of treating similar patients in the past, potentially improving surgery outcome.

• MeSH
• dítě MeSH
• dospělí MeSH
• elektroencefalografie * metody   MeSH
• epilepsie * chirurgie   diagnóza   patofyziologie   MeSH
• klinické rozhodování * metody   MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• reprodukovatelnost výsledků MeSH
• stereotaktické techniky MeSH
• záchvaty diagnóza   chirurgie   patofyziologie   MeSH
• Check Tag
• dítě MeSH
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

OBJECTIVE: Evidence suggests that the most promising results in interictal localization of the epileptogenic zone (EZ) are achieved by a combination of multiple stereo-electroencephalography (SEEG) biomarkers in machine learning models. These biomarkers usually include SEEG features calculated in standard frequency bands, but also high-frequency (HF) bands. Unfortunately, HF features require extra effort to record, store, and process. Here we investigate the added value of these HF features for EZ localization and postsurgical outcome prediction. METHODS: In 50 patients we analyzed 30 min of SEEG recorded during non-rapid eye movement sleep and tested a logistic regression model with three different sets of features. The first model used broadband features (1-500 Hz); the second model used low-frequency features up to 45 Hz; and the third model used HF features above 65 Hz. The EZ localization by each model was evaluated by various metrics including the area under the precision-recall curve (AUPRC) and the positive predictive value (PPV). The differences between the models were tested by the Wilcoxon signed-rank tests and Cliff's Delta effect size. The differences in outcome predictions based on PPV values were further tested by the McNemar test. RESULTS: The AUPRC score of the random chance classifier was .098. The models (broad-band, low-frequency, high-frequency) achieved median AUPRCs of .608, .582, and .522, respectively, and correctly predicted outcomes in 38, 38, and 33 patients. There were no statistically significant differences in AUPRC or any other metric between the three models. Adding HF features to the model did not have any additional contribution. SIGNIFICANCE: Low-frequency features are sufficient for correct localization of the EZ and outcome prediction with no additional value when considering HF features. This finding allows significant simplification of the feature calculation process and opens the possibility of using these models in SEEG recordings with lower sampling rates, as commonly performed in clinical routines.

• MeSH
• dítě MeSH
• dospělí MeSH
• elektroencefalografie * metody   MeSH
• epilepsie chirurgie   patofyziologie   diagnóza   MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• refrakterní epilepsie chirurgie   patofyziologie   diagnóza   MeSH
• stereotaktické techniky MeSH
• výsledek terapie MeSH
• Check Tag
• dítě MeSH
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladiství MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

AIM: Assess the prognostic ability of a non-highly malignant and reactive EEG to predict good outcome after cardiac arrest (CA). METHODS: Prospective observational multicentre substudy of the "Targeted Hypothermia versus Targeted Normothermia after Out-of-hospital Cardiac Arrest Trial", also known as the TTM2-trial. Presence or absence of highly malignant EEG patterns and EEG reactivity to external stimuli were prospectively assessed and reported by the trial sites. Highly malignant patterns were defined as burst-suppression or suppression with or without superimposed periodic discharges. Multimodal prognostication was performed 96 h after CA. Good outcome at 6 months was defined as a modified Rankin Scale score of 0-3. RESULTS: 873 comatose patients at 59 sites had an EEG assessment during the hospital stay. Of these, 283 (32%) had good outcome. EEG was recorded at a median of 69 h (IQR 47-91) after CA. Absence of highly malignant EEG patterns was seen in 543 patients of whom 255 (29% of the cohort) had preserved EEG reactivity. A non-highly malignant and reactive EEG had 56% (CI 50-61) sensitivity and 83% (CI 80-86) specificity to predict good outcome. Presence of EEG reactivity contributed (p < 0.001) to the specificity of EEG to predict good outcome compared to only assessing background pattern without taking reactivity into account. CONCLUSION: Nearly one-third of comatose patients resuscitated after CA had a non-highly malignant and reactive EEG that was associated with a good long-term outcome. Reactivity testing should be routinely performed since preserved EEG reactivity contributed to prognostic performance.

• MeSH
• elektroencefalografie * metody   MeSH
• kardiopulmonální resuscitace metody   MeSH
• kóma etiologie   patofyziologie   diagnóza   MeSH
• lidé středního věku MeSH
• lidé MeSH
• prediktivní hodnota testů MeSH
• prognóza MeSH
• prospektivní studie MeSH
• senioři MeSH
• terapeutická hypotermie * metody   MeSH
• zástava srdce mimo nemocnici * terapie   patofyziologie   MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• multicentrická studie MeSH
• pozorovací studie MeSH

Souhrn: Propojení těla a mysli a jejich vzájemná konjunkce jsou stále aktuálnějším, mnohooborovým tématem. Cíl: Cílem práce bylo zjistit, do jaké míry působí naše myšlenky v profesionálním tanečním prostředí na průběh mozkových frekvencí a jakým způsobem se propisují do našeho organizmu a pohybu. Metody: V rámci studie proběhlo měření mozkové činnosti nositelným EEG zařízením Muse a vizuální analýza pohybu z tanečního prostředí, prvku plié (flexe a extenze kolenních kloubů). Sledovanými a měřenými jedinci bylo 16 studentů Katedry tance, Hudební a taneční fakulty Akademie múzických umění v Praze. Sledovali jsme mozkové frekvence v mnoha fázích (situacích): bez konkrétní myšlenky (soustředění se) a bez pohybu, při konkrétní myšlence bez pohybu, pohyb bez konkrétní myšlenky, pohyb s konkrétní myšlenkou a na závěr opět myšlenku bez pohybu, která byla mimo obor a rámec výzkumu. Výsledky: U 14 účastníků experimentu jsme získali dostatečně kvalitní EEG signál k další analýze. U 12 účastníků byla prokázána změna v mozkových frekvencích odlišujících aktivity s nižší a vyšší vědomou koncentrací. Závěr: Výstup popisuje zjištění ohledně propojení myšlenek, těla a pohybu na základě měřitelných dat. EEG zařízení Muse je použitelné pro získávání EEG signálu dostatečné kvality v experimentech vyžadujících pohyb odehrávající se v reálných podmínkách. V získaném EEG signálu je možné detekovat změny v mozkové aktivitě účastníků při stavech uvolněné bdělosti a vědomé koncentrace. Vizuální analýza pohybu reflektuje, že syntéza specifické myšlenky a pohybu přispívá k eliminaci špatných pohybových návyků, které ruší nejen technickou čistotu provedení pohybového prvku, ale také optimální držení těla, koordinaci pohybu a jednotlivých anatomických struktur.

Summary: The connection of body and mind and their mutual conjunction is an increasingly topical topic in many fields. Objective: The aim of the work was to find out to what extent our thoughts in a professional dance environment affect the course of brain frequencies and how they are prescribed in our organism and movement. Methods: As part of the study, brain activity was measured with the Muse wearable EEG device and visual analysis of movement from the dance environment, the plié element (flexion and extension of the knee joints). The monitored and measured individuals were 16 students of the Dance Department of Music and Dance Faculty of the Music Academy of Performing Arts in Prague. We monitored brain frequencies in many phases (situations): without a specific thought (concentration) and without movement, with a specific thought without movement, movement without a specific thought, movement with a specific thought, and finally again a thought without movement, which was out of scope and research framework. Results: For 14 participants in the experiment, we obtained an EEG signal of sufficient quality so that it could be further analyzed. A change in brain frequencies distinguishing activities with lower and higher conscious concentration was demonstrated in 12 participants. Conclusion: The output describes the findings regarding the connection of thoughts, body, and movement based on measurable data. The Muse EEG device is useful for obtaining an EEG signal of sufficient quality in experiments requiring movement and taking place in real conditions. In the obtained EEG signal, it is possible to detect changes in the participant‘s brain activity during states of relaxed alertness and conscious concentration. Visual analysis of movement reflects that the synthesis of a specific thought and movement contributes to eliminating bad habits, which destroy not only the technical purity of the performance of the movement element but also optimal posture, coordination of movement, and individual anatomical structures.

• MeSH
• elektroencefalografie metody   MeSH
• lidé MeSH
• mapování mozku * MeSH
• pohyb fyziologie   MeSH
• pozornost MeSH
• tanec MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• klinická studie MeSH

INTRODUCTION: The Attention Deficit Hyperactivity Disorder (ADHD) causes serious interpersonal problems from childhood to adulthood, one of them being problematic social functioning. This phenomenon in ADHD should be associated with impairments in the Theory of Mind (ToM). Therefore, understanding the neural correlates of the ToM could be crucial for helping individuals with ADHD with their social functioning. Thus, we aimed to review published literature concerning neuroanatomical and functional correlates of ToM deficits in children and adolescents with ADHD. METHODS: We reviewed studies published between 1970 and 2023. In accordance with PRISMA guidelines, after data from three databases were collected, two authors (LN and PM) independently screened all relevant records (n=638) and consequently, both authors did the data extraction. The quality of the included studies (n=5) was measured by a modified version of The Newcastle-Ottawa Scale and by measures specific for our study. This systematic review was registered on PROSPERO (CRD42020139847). RESULTS: Results indicated that impairments in performing of the ToM tasks were negatively associated with the grey matter volume in the bilateral amygdala and hippocampus in both, ADHD and control group. In EEG studies, a significantly greater electrophysiological activity during ToM tasks was observed in the, frontal, temporal, parietal and occipital lobes in participants with ADHD as compared to healthy subjects. CONCLUSION: More research is needed to explore the ToM deficits in children with ADHD. Future research might focus on the neural circuits associated with attention and inhibition, which deficits seems to contribute to the ToM deficits in children and adolescents with ADHD.

• MeSH
• dítě MeSH
• elektroencefalografie metody   MeSH
• hyperkinetická porucha * patofyziologie   MeSH
• lidé MeSH
• mladiství MeSH
• mozek patofyziologie   MeSH
• teorie mysli * fyziologie   MeSH
• Check Tag
• dítě MeSH
• lidé MeSH
• mladiství MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH
• systematický přehled MeSH

Daydreaming, a form of spontaneous and self-generated mental process, may lead to the disintegration of attention from the immediate external environment. In extreme cases, patients may develop maladaptive daydreaming comorbid with dissociation. The examination of dissociative alterations frequently occurs within the framework of complex cognitive processes. While dissociation may be a neurological and psychological dysfunction of integration, transient dissociative occurrences, i.e., momentary dissociation may signify a dynamic interplay between attentional division and orientation within the sensory cortex. Furthermore, previous studies have recorded the interactivity of attention by stimuli onset with P3 event-related potentials and the active suppression of distractor positivity. In this context, during auditory and visual mismatch negativity, the sensory cortex may interact with attentional orientation. Additionally, distractor positivity during task-relevant stimuli may play a crucial role in predicting momentary dissociation since sensory cortices share cerebral correlates with attentional fluctuations during mental imagery. Thus, this theoretical review investigated the cerebral activities associated with attentional orientation and may be extended to mindfulness. By integrating these findings, we aim to provide a comprehensive understanding of dissociative states which may lead to a resolution for dissociative psychopathology.

• MeSH
• disociační poruchy * patofyziologie   MeSH
• elektroencefalografie metody   MeSH
• evokované potenciály fyziologie   MeSH
• lidé MeSH
• pozornost * fyziologie   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

Numerous physiological processes are cyclical, but sampling these processes densely enough to perform frequency decomposition and subsequent analyses can be challenging. Mathematical approaches for decomposition and reconstruction of sparsely and irregularly sampled signals are well established but have been under-utilized in physiological applications. We developed a basis pursuit denoising with polynomial detrending (BPWP) model that recovers oscillations and trends from sparse and irregularly sampled timeseries. We validated this model on a unique dataset of long-term inter-ictal epileptiform discharge (IED) rates from human hippocampus recorded with a novel investigational device with continuous local field potential sensing. IED rates have well established circadian and multiday cycles related to sleep, wakefulness, and seizure clusters. Given sparse and irregular samples of IED rates from multi-month intracranial EEG recordings from ambulatory humans, we used BPWP to compute narrowband spectral power and polynomial trend coefficients and identify IED rate cycles in three subjects. In select cases, we propose that random and irregular sampling may be leveraged for frequency decomposition of physiological signals. Trial Registration: NCT03946618.

• MeSH
• algoritmy MeSH
• elektroencefalografie metody   MeSH
• elektrokortikografie metody   MeSH
• epilepsie * patofyziologie   diagnóza   MeSH
• hipokampus patofyziologie   fyziologie   MeSH
• lidé MeSH
• modely neurologické MeSH
• počítačové zpracování signálu MeSH
• výpočetní biologie metody   MeSH
• záchvaty patofyziologie   diagnóza   MeSH
• Check Tag
• lidé MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Research Support, N.I.H., Extramural MeSH
• Research Support, U.S. Gov't, Non-P.H.S. MeSH

Applications of causal techniques to neural time series have increased extensively over last decades, including a wide and diverse family of methods focusing on electroencephalogram (EEG) analysis. Besides connectivity inferred in defined frequency bands, there is a growing interest in the analysis of cross-frequency interactions, in particular phase and amplitude coupling and directionality. Some studies show contradicting results of coupling directionality from high frequency to low frequency signal components, in spite of generally considered modulation of a high-frequency amplitude by a low-frequency phase. We have compared two widely used methods to estimate the directionality in cross frequency coupling: conditional mutual information (CMI) and phase slope index (PSI). The latter, applied to infer cross-frequency phase-amplitude directionality from animal intracranial recordings, gives opposite results when comparing to CMI. Both metrics were tested in a numerically simulated example of unidirectionally coupled Rössler systems, which helped to find the explanation of the contradictory results: PSI correctly estimates the lead/lag relationship which, however, is not generally equivalent to causality in the sense of directionality of coupling in nonlinear systems, correctly inferred by using CMI with surrogate data testing.

• MeSH
• elektroencefalografie * metody   MeSH
• lidé MeSH
• modely neurologické MeSH
• mozek fyziologie   MeSH
• nelineární dynamika * MeSH
• počítačová simulace MeSH
• počítačové zpracování signálu MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• srovnávací studie MeSH

Zobrazovací metody stále více přispívají k přesnější a časnější diagnostice neurodegenerativních onemocnění. Snahou je objevit citlivější biomarkery, které by umožnily kromě časnější diagnostiky také stratifikaci rizika rozvoje a prognózu neurodegenerativních onemocnění. Existuje celé spektrum přístupů od nukleární medicíny (SPECT, PET) přes MRI až po elektrofyziologii (EEG). V naší přehledové práci jsme se snažili shrnout poznatky o využití těchto technik a o charakteristických nálezech, které přispívají k diagnostice nejčastějších typů degenerativních demencí a jejich variant. Některé z těchto poznatků jsou zatím na vědecké úrovni, ale mnohé se již plně uplatňují v klinické praxi.

There has been a great development in imaging methods and their use for early diagnosis of neurodegenerative disorders. The aim is to discover more sensitive biomarkers that would enable early stratification of dementia subtypes and disease prognosis. There are various types of imaging methods such as nuclear medicine (SPECT, PET), MRI and electrophysiology (EEG), which provide complementary picture about degenerative diseases. The main purpose of this work is to review the most typical findings in neurodegenerative dementia and their most common variants and subtypes. Although some of them are suitable only for scientific purposes, many have been utilized in diagnostic guidelines.

• MeSH
• biologické markery analýza   MeSH
• demence diagnostické zobrazování   klasifikace   MeSH
• diagnostické zobrazování * klasifikace   metody   MeSH
• elektroencefalografie metody   MeSH
• lidé MeSH
• magnetická rezonanční tomografie metody   MeSH
• neurodegenerativní nemoci * diagnostické zobrazování   klasifikace   MeSH
• neurofyziologický monitoring klasifikace   metody   MeSH
• PET/CT metody   MeSH
• SPECT/CT metody   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• práce podpořená grantem MeSH
• přehledy MeSH