Detection of Language Lateralization Using Spectral Analysis of EEG.

PURPOSE: Language lateralization relies on expensive equipment and can be difficult to tolerate. We assessed if lateralized brain responses to a language task can be detected with spectral analysis of electroencephalography (EEG). METHODS: Twenty right-handed, neurotypical adults (28 ± 10 years; five males) performed a verb generation task and two control tasks (word listening and repetition). We measured changes in EEG activity elicited by tasks (the event-related spectral perturbation [ERSP]) in the theta, alpha, beta, and gamma frequency bands in two language (superior temporal and inferior frontal [ST and IF]) and one control (occipital [Occ]) region bilaterally. We tested whether language tasks elicited (1) changes in spectral power from baseline (significant ERSP) at any region or (2) asymmetric ERSPs between matched left and right regions. RESULTS: Left IF beta power (-0.37±0.53, t = -3.12, P = 0.006) and gamma power in all regions decreased during verb generation. Asymmetric ERSPs (right > left) occurred between the (1) IF regions in the beta band (right vs. left difference of 0.23±0.37, t(19) = -2.80, P = 0.0114) and (2) ST regions in the alpha band (right vs. left difference of 0.48±0.63, t(19) = -3.36, P = 0.003). No changes from baseline or hemispheric asymmetries were noted in language regions during control tasks. On the individual level, 16 (80%) participants showed decreased left IF beta power from baseline, and 16 showed ST alpha asymmetry. Eighteen participants (90%) showed one of these two findings. CONCLUSIONS: Spectral EEG analysis detects lateralized responses during language tasks in frontal and temporal regions. Spectral EEG analysis could be developed into a readily available language lateralization modality.

Interhemispheric coherence of EEG rhythms in children: Maturation and differentiation in corpus callosum dysgenesis.

OBJECTIVES: To evaluate the evolution of interhemispheric coherences (ICo) in background and spindle frequency bands during childhood and use it to identify individuals with corpus callosum dysgenesis (CCd). METHODS: A monocentric cohort of children aged from 0.25 to 15 years old, consisting of 13 children with CCd and 164 without, was analyzed. The ICo of background activity (ICOBckgrdA), sleep spindles (ICOspindles), and their sum (sICO) were calculated. The impact of age, gender, and CC status on the ICo was evaluated, and the sICO was used to discriminate children with or without CCd. RESULTS: ICOBckgrdA, ICOspindles and sICO increased significantly with age without any effect of gender (p < 10-4), in both groups. The regression equations of the different ICo were stronger, with adjusted R2 values of 0.54, 0.35, and 0.57, respectively. The ICo was lower in children with CCd compared to those without CCd (p < 10-4 for all comparisons). The area under the precision recall curves for predicting CCd using sICO was 0.992 with 98.9 % sensitivity and 87.5 % specificity. DISCUSSION: ICo of spindles and background activity evolve in parallel to brain maturation and depends on the integrity of the corpus callosum. sICO could be an effective diagnostic biomarker for screening children with interhemispheric dysfunction.

Hippocampal sharp-wave ripples correlate with periods of naturally occurring self-generated thoughts in humans.

Core features of human cognition highlight the importance of the capacity to focus on information distinct from events in the here and now, such as mind wandering. However, the brain mechanisms that underpin these self-generated states remain unclear. An emerging hypothesis is that self-generated states depend on the process of memory replay, which is linked to sharp-wave ripples (SWRs), which are transient high-frequency oscillations originating in the hippocampus. Local field potentials were recorded from the hippocampus of 10 patients with epilepsy for up to 15 days, and experience sampling was used to describe their association with ongoing thought patterns. The SWR rates were higher during extended periods of time when participants' ongoing thoughts were more vivid, less desirable, had more imaginable properties, and exhibited fewer correlations with an external task. These data suggest a role for SWR in the patterns of ongoing thoughts that humans experience in daily life.

Delineating memory reactivation in sleep with verbal and non-verbal retrieval cues.

Sleep supports memory consolidation via the reactivation of newly formed memory traces. One way to investigate memory reactivation in sleep is by exposing the sleeping brain to auditory retrieval cues; a paradigm known as targeted memory reactivation. To what extent the acoustic properties of memory cues influence the effectiveness of targeted memory reactivation, however, has received limited attention. We addressed this question by exploring how verbal and non-verbal memory cues affect oscillatory activity linked to memory reactivation in sleep. Fifty-one healthy male adults learned to associate visual stimuli with spoken words (verbal cues) and environmental sounds (non-verbal cues). Subsets of the verbal and non-verbal memory cues were then replayed during sleep. The voice of the verbal cues was either matched or mismatched to learning. Memory cues (relative to unheard control cues) prompted an increase in theta/alpha and spindle power, which have been heavily implicated in sleep-associated memory processing. Moreover, verbal memory cues were associated with a stronger increase in spindle power than non-verbal memory cues. There were no significant differences between the matched and mismatched verbal cues. Our findings suggest that verbal memory cues may be most effective for triggering memory reactivation in sleep, as indicated by an amplified spindle response.

Exploring empathic engagement in immersive media: An EEG study on mu rhythm suppression in VR.

This study investigates the influence of immersive media, particularly Virtual Reality (VR), on empathic responses, in comparison to traditional television (TV), using electroencephalography (EEG). We employed mu rhythm suppression as a measurable neural marker to gauge empathic engagement, as its increase generally signifies heightened empathic responses. Our findings exhibit a greater mu rhythm suppression in VR conditions compared to TV conditions, suggesting a potential enhancement in empathic responses with VR. Furthermore, our results revealed that the strength of empathic responses was not confined to specific actions depicted in the video clips, underscoring the possibility of broader implications. This research contributes to the ongoing discourse on the effects of different media environments on empathic engagement, particularly emphasizing the unique role of immersive technologies such as VR. It invites further investigation into how such technologies can shape and potentially enhance the empathic experience.

Neural assemblies coordinated by cortical waves are associated with waking and hallucinatory brain states.

The relationship between sensory stimuli and perceptions is brain-state dependent: in wakefulness, suprathreshold stimuli evoke perceptions; under anesthesia, perceptions are abolished; and during dreaming and in dissociated states, percepts are internally generated. Here, we exploit this state dependence to identify brain activity associated with internally generated or stimulus-evoked perceptions. In awake mice, visual stimuli phase reset spontaneous cortical waves to elicit 3-6 Hz feedback traveling waves. These stimulus-evoked waves traverse the cortex and entrain visual and parietal neurons. Under anesthesia as well as during ketamine-induced dissociation, visual stimuli do not disrupt spontaneous waves. Uniquely, in the dissociated state, spontaneous waves traverse the cortex caudally and entrain visual and parietal neurons, akin to stimulus-evoked waves in wakefulness. Thus, coordinated neuronal assemblies orchestrated by traveling cortical waves emerge in states in which perception can manifest. The awake state is privileged in that this coordination is reliably elicited by external visual stimuli.

Spatial and temporal properties of intra-operatively recorded spikes and high frequency oscillations in focal cortical dysplasia.

OBJECTIVE: Focal cortical dysplasias (FCD) are characterized by distinct interictal spike patterns and high frequency oscillations (HFOs; ripples: 80-250 Hz; fast ripples: 250-500 Hz) in the intra-operative electrocorticogram (ioECoG). We studied the temporal relation between intra-operative spikes and HFOs and their relation to resected tissue in people with FCD with a favorable outcome. METHODS: We included patients who underwent ioECoG-tailored epilepsy surgery with pathology confirmed FCD and long-term Engel 1A outcome. Spikes and HFOs were automatically detected and visually checked in 1-minute pre-resection-ioECoG. Channels covering resected and non-resected tissue were compared using a logistic mixed model, assessing event numbers, co-occurrence ratios, and time-based properties. RESULTS: We found pre-resection spikes, ripples in respectively 21 and 20 out of 22 patients. Channels covering resected tissue showed high numbers of spikes and HFOs, and high ratios of co-occurring events. Spikes, especially with ripples, have a relatively sharp rising flank with a long descending flank and early ripple onset over resected tissue. CONCLUSIONS: A combined analysis of event numbers, ratios, and temporal relationships between spikes and HFOs may aid identifying epileptic tissue in epilepsy surgery. SIGNIFICANCE: This study shows a promising method for clinically relevant properties of events, closely associated with FCD.

Neurotoxic effects of home radon exposure on oscillatory dynamics serving attentional orienting in children and adolescents.

Radon is a naturally occurring gas that contributes significantly to radiation in the environment and is the second leading cause of lung cancer globally. Previous studies have shown that other environmental toxins have deleterious effects on brain development, though radon has not been studied as thoroughly in this context. This study examined the impact of home radon exposure on the neural oscillatory activity serving attention reorientation in youths. Fifty-six participants (ages 6-14 years) completed a classic Posner cuing task during magnetoencephalography (MEG), and home radon levels were measured for each participant. Time-frequency spectrograms indicated stronger theta (3-7 Hz, 300-800 ms), alpha (9-13 Hz, 400-900 ms), and beta responses (14-24 Hz, 400-900 ms) during the task relative to baseline. Source reconstruction of each significant oscillatory response was performed, and validity maps were computed by subtracting the task conditions (invalidly cued - validly cued). These validity maps were examined for associations with radon exposure, age, and their interaction in a linear regression design. Children with greater radon exposure showed aberrant oscillatory activity across distributed regions critical for attentional processing and attention reorientation (e.g., dorsolateral prefrontal cortex, and anterior cingulate cortex). Generally, youths with greater radon exposure exhibited a reverse neural validity effect in almost all regions and showed greater overall power relative to peers with lesser radon exposure. We also detected an interactive effect between radon exposure and age where youths with greater radon exposure exhibited divergent developmental trajectories in neural substrates implicated in attentional processing (e.g., bilateral prefrontal cortices, superior temporal gyri, and inferior parietal lobules). These data suggest aberrant, but potentially compensatory neural processing as a function of increasing home radon exposure in areas critical for attention and higher order cognition.

Simultaneous EEG-fMRI Investigation of Rhythm-Dependent Thalamo-Cortical Circuits Alteration in Schizophrenia.

Schizophrenia is accompanied by aberrant interactions of intrinsic brain networks. However, the modulatory effect of electroencephalography (EEG) rhythms on the functional connectivity (FC) in schizophrenia remains unclear. This study aims to provide new insight into network communication in schizophrenia by integrating FC and EEG rhythm information. After collecting simultaneous resting-state EEG-functional magnetic resonance imaging data, the effect of rhythm modulations on FC was explored using what we term "dynamic rhythm information." We also investigated the synergistic relationships among three networks under rhythm modulation conditions, where this relationship presents the coupling between two brain networks with other networks as the center by the rhythm modulation. This study found FC between the thalamus and cortical network regions was rhythm-specific. Further, the effects of the thalamus on the default mode network (DMN) and salience network (SN) were less similar under alpha rhythm modulation in schizophrenia patients than in controls ([Formula: see text]). However, the similarity between the effects of the central executive network (CEN) on the DMN and SN under gamma modulation was greater ([Formula: see text]), and the degree of coupling was negatively correlated with the duration of disease ([Formula: see text], [Formula: see text]). Moreover, schizophrenia patients exhibited less coupling with the thalamus as the center and greater coupling with the CEN as the center. These results indicate that modulations in dynamic rhythms might contribute to the disordered functional interactions seen in schizophrenia.

A causal perspective on brainwave modeling for brain-computer interfaces.

Objective. Machine learning (ML) models have opened up enormous opportunities in the field of brain-computer Interfaces (BCIs). Despite their great success, they usually face severe limitations when they are employed in real-life applications outside a controlled laboratory setting.Approach. Mixing causal reasoning, identifying causal relationships between variables of interest, with brainwave modeling can change one's viewpoint on some of these major challenges which can be found in various stages in the ML pipeline, ranging from data collection and data pre-processing to training methods and techniques.Main results. In this work, we employ causal reasoning and present a framework aiming to breakdown and analyze important challenges of brainwave modeling for BCIs.Significance. Furthermore, we present how general ML practices as well as brainwave-specific techniques can be utilized and solve some of these identified challenges. And finally, we discuss appropriate evaluation schemes in order to measure these techniques' performance and efficiently compare them with other methods that will be developed in the future.

Functionally annotated electrophysiological neuromarkers of healthy ageing and memory function.

The unprecedented increase in life expectancy presents a unique opportunity and the necessity to explore both healthy and pathological aspects of ageing. Electroencephalography (EEG) has been widely used to identify neuromarkers of cognitive ageing due to its affordability and richness in information. However, despite the growing volume of data and methodological advancements, the abundance of contradictory and non-reproducible findings has hindered clinical translation. To address these challenges, our study introduces a comprehensive workflow expanding on previous EEG studies and investigates various static and dynamic power and connectivity estimates as potential neuromarkers of cognitive ageing in a large dataset. We also assess the robustness of our findings by testing their susceptibility to band specification. Finally, we characterise our findings using functionally annotated brain networks to improve their interpretability and multi-modal integration. Our analysis demonstrates the effect of methodological choices on findings and that dynamic rather than static neuromarkers are not only more sensitive but also more robust. Consequently, they emerge as strong candidates for cognitive ageing neuromarkers. Moreover, we were able to replicate the most established EEG findings in cognitive ageing, such as alpha oscillation slowing, increased beta power, reduced reactivity across multiple bands, and decreased delta connectivity. Additionally, when considering individual variations in the alpha band, we clarified that alpha power is characteristic of memory performance rather than ageing, highlighting its potential as a neuromarker for cognitive ageing. Finally, our approach using functionally annotated source reconstruction allowed us to provide insights into domain-specific electrophysiological mechanisms underlying memory performance and ageing. HIGHLIGHTS: We provide an open and reproducible pipeline with a comprehensive workflow to investigate static and dynamic EEG neuromarkers. Neuromarkers related to neural dynamics are sensitive and robust. Individualised alpha power characterises cognitive performance rather than ageing. Functional annotation allows cross-modal interpretation of EEG findings.

Modulation index predicts the effect of ethosuximide on developmental and epileptic encephalopathy with spike-and-wave activation in sleep.

PURPOSE: In developmental and epileptic encephalopathy with spike-and-wave activation in sleep (DEE-SWAS), the thalamocortical network is suggested to play an important role in the pathophysiology of the progression from focal epilepsy to DEE-SWAS. Ethosuximide (ESM) exerts effects by blocking T-type calcium channels in thalamic neurons. With the thalamocortical network in mind, we studied the prediction of ESM effectiveness in DEE-SWAS treatment using phase-amplitude coupling (PAC) analysis. METHODS: We retrospectively enrolled children with DEE-SWAS who had an electroencephalogram (EEG) recorded between January 2009 and September 2022 and were prescribed ESM at Okayama University Hospital. Only patients whose EEG showed continuous spike-and-wave during sleep were included. We extracted 5-min non-rapid eye movement sleep stage N2 segments from EEG recorded before starting ESM. We calculated the modulation index (MI) as the measure of PAC in pair combination comprising one of two fast oscillation types (gamma, 40-80 Hz; ripples, 80-150 Hz) and one of five slow-wave bands (delta, 0.5-1, 1-2, 2-3, and 3-4 Hz; theta, 4-8 Hz), and compared it between ESM responders and non-responders. RESULTS: We identified 20 children with a diagnosis of DEE-SWAS who took ESM. Fifteen were ESM responders. Regarding gamma oscillations, significant differences were seen only in MI with 0.5-1 Hz slow waves in the frontal pole and occipital regions. Regarding ripples, ESM responders had significantly higher MI in coupling with all slow waves in the frontal pole region, 0.5-1, 3-4, and 4-8 Hz slow waves in the frontal region, 3-4 Hz slow waves in the parietal region, 0.5-1, 2-3, 3-4, and 4-8 Hz slow waves in the occipital region, and 3-4 Hz slow waves in the anterior-temporal region. SIGNIFICANCE: High MI in a wider area of the brain may represent the epileptic network mediated by the thalamus in DEE-SWAS and may be a predictor of ESM effectiveness.

Sleep-slow oscillation-spindle coupling precedes spindle-ripple coupling during development.

STUDY OBJECTIVES: Sleep supports systems memory consolidation through the precise temporal coordination of specific oscillatory events during slow-wave sleep, i.e. the neocortical slow oscillations (SOs), thalamic spindles, and hippocampal ripples. Beneficial effects of sleep on memory are also observed in infants, although the contributing regions, especially hippocampus and frontal cortex, are immature. Here, we examined in rats the development of these oscillatory events and their coupling during early life. METHODS: EEG and hippocampal local field potentials were recorded during sleep in male rats at postnatal days (PD)26 and 32, roughly corresponding to early (1-2 years) and late (9-10 years) human childhood, and in a group of adult rats (14-18 weeks, corresponding to ~22-29 years in humans). RESULTS: SO and spindle amplitudes generally increased from PD26 to PD32. In parallel, frontocortical EEG spindles increased in density and frequency, while changes in hippocampal ripples remained nonsignificant. The proportion of SOs co-occurring with spindles also increased from PD26 to PD32. Whereas parietal cortical spindles were phase-locked to the depolarizing SO-upstate already at PD26, over frontal cortex SO-spindle phase-locking emerged not until PD32. Co-occurrence of hippocampal ripples with spindles was higher during childhood than in adult rats, but significant phase-locking of ripples to the excitable spindle troughs was observed only in adult rats. CONCLUSIONS: Results indicate a protracted development of synchronized thalamocortical processing specifically in frontocortical networks (i.e. frontal SO-spindle coupling). However, synchronization within thalamocortical networks generally precedes synchronization of thalamocortical with hippocampal processing as reflected by the delayed occurrence of spindle-ripple phase-coupling.

Brain waves and landscape settings: emotional responses to attractiveness.

Neuro-architecture is a specific branch of architecture that studies how the physical environment can change our mental processes and influence our behaviors. One of the main purposes of this field is to use changes in brain activities as a measure to quantify attractiveness of the landscapes. In this study, we investigated how changes in elements of attractiveness influence ones' emotional perception and present the related pattern of changes in brain activities. Therefore, we implied five elements of attractiveness including mystery, visual openness, landscape or greenness, walkability, and social interaction using the Delphi method. Then, we made changes in each element separately to make the landscape more attractive and assessed their effects on a group of young adults. We used the self-assessment manikin questionnaire to measure the participants' emotional perception while the participants' brain activities were recorded using a 32-channel EEG while exposed to the landscape images. The results showed that changes in attractive elements of the landscape could significantly improve ones' emotional perception of the landscape. In addition, these changes are perceived by changing the oscillatory pattern of brain activities. We hope these findings could shed a light to use of neural markers in measurement of place attractiveness.

Neural and behavioural state switching during hippocampal dentate spikes.

Distinct brain and behavioural states are associated with organized neural population dynamics that are thought to serve specific cognitive functions1-3. Memory replay events, for example, occur during synchronous population events called sharp-wave ripples in the hippocampus while mice are in an 'offline' behavioural state, enabling cognitive mechanisms such as memory consolidation and planning4-11. But how does the brain re-engage with the external world during this behavioural state and permit access to current sensory information or promote new memory formation? Here we found that the hippocampal dentate spike, an understudied population event that frequently occurs between sharp-wave ripples12, may underlie such a mechanism. We show that dentate spikes are associated with distinctly elevated brain-wide firing rates, primarily observed in higher order networks, and couple to brief periods of arousal. Hippocampal place coding during dentate spikes aligns to the mouse's current spatial location, unlike the memory replay accompanying sharp-wave ripples. Furthermore, inhibiting neural activity during dentate spikes disrupts associative memory formation. Thus, dentate spikes represent a distinct brain state and support memory during non-locomotor behaviour, extending the repertoire of cognitive processes beyond the classical offline functions.

Resting-state EEG rhythms are abnormal in post COVID-19 patients with brain fog without cognitive and affective disorders.

OBJECTIVES: Several persons experiencing post-covid-19 (post-COVID) with "brain fog" (e.g., fatigue, cognitive and psychiatric disorders, etc.) show abnormal resting-state electroencephalographic (rsEEG) rhythms reflecting a vigilance dysfunction. Here, we tested the hypothesis that in those post-COVID persons, abnormal rsEEG rhythms may occur even when cognitive and psychiatric disorders are absent. METHODS: The experiments were performed on post-COVID participants about one year after hospitalization for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Inclusion criteria included a "brain fog" claim, no pre-infection, and actual organic chronic disease. Matched controls (no COVID) were also enrolled. All participants underwent clinical/neuropsychological assessment (including fatigue assessment) and rsEEG recordings. The eLORETA freeware estimated regional rsEEG cortical sources at individual delta (<4 Hz), theta (4-7 Hz), and alpha (8-13 Hz) bands. Beta (14-30 Hz) and gamma (30-40 Hz) bands were pre-fixed. RESULTS: More than 90% of all post-COVID participants showed no cognitive or psychiatric disorders, and 75% showed ≥ 2 fatigue symptoms. The post-COVID group globally presented lower posterior rsEEG alpha source activities than the Control group. This effect was more significant in the long COVID-19 patients with ≥ 2 fatigue symptoms. CONCLUSIONS: In post-COVID patients with no chronic diseases and cognitive/psychiatric disorders, "brain fog" can be associated with abnormal posterior rsEEG alpha rhythms and subjective fatigue. SIGNIFICANCE: These abnormalities may be related to vigilance and allostatic dysfunctions.

Coupling of Sharp Wave Events between Zebrafish Hippocampal and Amygdala Homologs.

The mammalian hippocampus exhibits spontaneous sharp wave events (1-30 Hz) with an often-present superimposed fast ripple oscillation (120-220 Hz) to form a sharp wave ripple (SWR) complex. During slow-wave sleep or quiet restfulness, SWRs result from the sequential spiking of hippocampal cell assemblies initially activated during learned or imagined experiences. Additional cortical/subcortical areas exhibit SWR events that are coupled to hippocampal SWRs, and studies in mammals suggest that coupling may be critical for the consolidation and recall of specific memories. In the present study, we have examined juvenile male and female zebrafish and show that SWR events are intrinsically generated and maintained within the telencephalon and that their hippocampal homolog, the anterodorsolateral lobe (ADL), exhibits SW events with ∼9% containing an embedded ripple (SWR). Single-cell calcium imaging coupled to local field potential recordings revealed that ∼10% of active cells in the dorsal telencephalon participate in any given SW event. Furthermore, fluctuations in cholinergic tone modulate SW events consistent with mammalian studies. Moreover, the basolateral amygdala (BLA) homolog exhibits SW events with ∼5% containing an embedded ripple. Computing the SW peak coincidence difference between the ADL and BLA showed bidirectional communication. Simultaneous coupling occurred more frequently within the same hemisphere, and in coupled events across hemispheres, the ADL more commonly preceded BLA. Together, these data suggest conserved mechanisms across species by which SW and SWR events are modulated, and memories may be transferred and consolidated through regional coupling.

Neuronal dynamics direct cerebrospinal fluid perfusion and brain clearance.

The accumulation of metabolic waste is a leading cause of numerous neurological disorders, yet we still have only limited knowledge of how the brain performs self-cleansing. Here we demonstrate that neural networks synchronize individual action potentials to create large-amplitude, rhythmic and self-perpetuating ionic waves in the interstitial fluid of the brain. These waves are a plausible mechanism to explain the correlated potentiation of the glymphatic flow1,2 through the brain parenchyma. Chemogenetic flattening of these high-energy ionic waves largely impeded cerebrospinal fluid infiltration into and clearance of molecules from the brain parenchyma. Notably, synthesized waves generated through transcranial optogenetic stimulation substantially potentiated cerebrospinal fluid-to-interstitial fluid perfusion. Our study demonstrates that neurons serve as master organizers for brain clearance. This fundamental principle introduces a new theoretical framework for the functioning of macroscopic brain waves.

Epileptic tissue localization using graph-based networks in the high frequency oscillation range of intracranial electroencephalography.

PURPOSE: High frequency oscillations (HFOs) are an emerging biomarker of epilepsy. However, very few studies have investigated the functional connectivity of interictal iEEG signals in the frequency range of HFOs. Here, we study the corresponding functional networks using graph theory, and we assess their predictive value for automatic electrode classification in a cohort of 20 drug resistant patients. METHODS: Coherence-based connectivity analysis was performed on the iEEG recordings, and six different local graph measures were computed in both sub-bands of the HFO frequency range (80-250 Hz and 250-500 Hz). Correlation analysis was implemented between the local graph measures and the ripple and fast ripple rates. Finally, the WEKA software was employed for training and testing different predictive models on the aforementioned local graph measures. RESULTS: The ripple rate was significantly correlated with five out of six local graph measures in the functional network. For fast ripples, their rate was also significantly (but negatively) correlated with most of the local metrics. The results from WEKA showed that the Logistic Regression algorithm was able to classify highly HFO-contaminated electrodes with an accuracy of 82.5 % for ripples and 75.4 % for fast ripples. CONCLUSION: Functional connectivity networks in the HFO band could represent an alternative to the direct use of distinct HFO events, while also providing important insights about hub epileptic areas that can represent possible surgical targets. Automatic electrode classification through FC-based classifiers can help bypass the burden of manual HFO annotation, providing at the same time similar amount of information about the epileptic tissue.