Aperiodic and periodic components of oscillatory brain activity in relation to cognition and symptoms in pediatric ADHD.

Children with attention-deficit/hyperactivity disorder show deficits in processing speed, as well as aberrant neural oscillations, including both periodic (oscillatory) and aperiodic (1/f-like) activity, reflecting the pattern of power across frequencies. Both components were suggested as underlying neural mechanisms of cognitive dysfunctions in attention-deficit/hyperactivity disorder. Here, we examined differences in processing speed and resting-state-Electroencephalogram neural oscillations and their associations between 6- and 12-year-old children with (n = 33) and without (n = 33) attention-deficit/hyperactivity disorder. Spectral analyses of the resting-state EEG signal using fast Fourier transform revealed increased power in fronto-central theta and beta oscillations for the attention-deficit/hyperactivity disorder group, but no differences in the theta/beta ratio. Using the parameterization method, we found a higher aperiodic exponent, which has been suggested to reflect lower neuronal excitation-inhibition, in the attention-deficit/hyperactivity disorder group. While fast Fourier transform-based theta power correlated with clinical symptoms for the attention-deficit/hyperactivity disorder group only, the aperiodic exponent was negatively correlated with processing speed across the entire sample. Finally, the aperiodic exponent was correlated with fast Fourier transform-based beta power. These results highlight the different and complementary contribution of periodic and aperiodic components of the neural spectrum as metrics for evaluation of processing speed in attention-deficit/hyperactivity disorder. Future studies should further clarify the roles of periodic and aperiodic components in additional cognitive functions and in relation to clinical status.

Aberrant Brain Networks and Relative Band Power in Patients with Acute Anti-NMDA Receptor Encephalitis: A Study of Resting-State EEG.

OBJECTIVE: The alterations of the functional network (FN) in anti-N-methyl-Daspartate receptor (NMDAR) encephalitis have been recognized by functional magnetic resonance imaging studies. However, few studies using the electroencephalogram (EEG) have been performed to explore the possible FN changes in anti-NMDAR encephalitis. In this study, the aim was to explore any FN changes in patients with anti-NMDAR encephalitis. METHODS: Twenty-nine anti-NMDAR encephalitis patients and 29 age- and gender-matched healthy controls (HC) were assessed using 19-channel EEG examination. For each participant, five 10-second epochs of resting state EEG with eyes closed were extracted. The cortical source signals of 84 Brodmann areas were calculated using the exact low resolution brain electromagnetic tomography (eLORETA) inverse solution by LORETA-KEY. Phase Lag Index (PLI) matrices were then obtained and graph and relative band power (RBP) analyses were performed. RESULTS: Compared with healthy controls, functional connectivity (FC) in the delta, theta, beta 1 and beta 2 bands significantly increased within the 84 cortical source signals of anti-NMDAR encephalitis patients (p < 0.05) and scalp FC in the alpha band decreased within the 19 electrodes. Additionally, the anti-NMDAR encephalitis group exhibited higher local efficiency and clustering coefficient compared to the healthy control group in the four bands. The slowing band RBP increased while the fast band RBP decreased in multiple-lobes and some of these changes in RBP were correlated with the modified Rankin Scale (mRS) and Mini-mental State Examination (MMSE) in anti-NMDAR encephalitis patients. CONCLUSIONS: This study further deepens the understanding of related changes in the abnormal brain network and power spectrum of anti-NMDA receptor encephalitis. The decreased scalp alpha FC may indicate brain dysfunction, while the increased source beta FC may indicate a compensatory mechanism for brain function in anti-NMDAR encephalitis patients. These findings extend understanding of how the brain FN changes from a cortical source perspective. Further studies are needed to detect correlations between altered FNs and clinical features and characterize their potential value for the management of anti-NMDAR encephalitis.

Neural oscillations guiding action during effects imagery.

Goal-directed acting requires the integration of sensory information but can also be performed without direct sensory input. Examples of this can be found in sports and can be conceptualized by feedforward processes. There is, however, still a lack of understanding of the temporal neural dynamics and neuroanatomical structures involved in such processes. In the current study, we used EEG beamforming methods and examined 37 healthy participants in two well-controlled experiments varying the necessity of anticipatory processes during goal-directed action. We found that alpha and beta activity in the medial and posterior cingulate cortex enabled feedforward predictions about the position of an object based on the latest sensorimotor state. On this basis, theta band activity seems more related to sensorimotor representations, while beta band activity would be more involved in setting up the structure of the neural representations themselves. Alpha band activity in sensory cortices reflects an intensified gating of the anticipated perceptual consequences of the to-be-executed action. Together, the findings indicate that goal-directed acting through the anticipation of the predicted state of an effector is based on accompanying processes in multiple frequency bands in midcingulate and sensory brain regions.

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.

Antiseizure Medications Normalize Electroencephalographic Functional Connectivity and Power in Children With Benign Epilepsy With Centrotemporal Spikes.

BACKGROUND: The decision to treat children with benign epilepsy with centrotemporal spikes (BECTS) using antiseizure medications (ASM) is controversial. Our goal is to compare the effect of ASM treatment on the alteration of electroencephalographic (EEG) functional connectivity and power across four frequency bands in children with BECTS. METHODS: Children with BECTS with two-year follow-up were retrospectively divided into ASM versus non-ASM groups. The network properties of the EEGs as based on network-based statistic and graph theory were evaluated by the following indices: global efficiency, clustering coefficient, betweenness centrality, and nodal strength in four frequency bands (delta, theta, alpha, and beta). EEG power including absolute power (AP) and relative power (RP) was analyzed in four frequency bands. RESULTS: In children with BECTS with ASM treatment, there was no significant change in EEG connectivity across all bands before and after two years of ASM. In children with BECTS without ASM treatment, there was a significant increase of global efficiency, clustering coefficient, and nodal strength but not the betweenness centrality in the delta band after two years of follow-up. A decrease in AP in the delta and theta bands and a decrease in RP in the theta band were found in the ASM group after two years of treatment. CONCLUSIONS: Our results suggest that ASM may play a role in modulating the development of increasing overall brain connectivity and in downregulating overt synaptic activity, but not intrinsic focal connectivity, in the early years of BECTS. The changes in the EEG power indicate that ASM significantly normalized slow-wave band power.

Identifying epileptogenic abnormality by decomposing intracranial EEG and MEG power spectra.

BACKGROUND: Accurate identification of abnormal electroencephalographic (EEG) activity is pivotal for diagnosing and treating epilepsy. Recent studies indicate that decomposing brain activity into periodic (oscillatory) and aperiodic (trend across all frequencies) components can illuminate the drivers of spectral activity changes. NEW METHODS: We analysed intracranial EEG (iEEG) data from 234 subjects, creating a normative map. This map was compared to a cohort of 63 patients with refractory focal epilepsy under consideration for neurosurgery. The normative map was computed using three approaches: (i) relative complete band power, (ii) relative band power with the aperiodic component removed, and (iii) the aperiodic exponent. Abnormalities were calculated for each approach in the patient cohort. We evaluated the spatial profiles, assessed their ability to localize abnormalities, and replicated the findings using magnetoencephalography (MEG). RESULTS: Normative maps of relative complete band power and relative periodic band power exhibited similar spatial profiles, while the aperiodic normative map revealed higher exponent values in the temporal lobe. Abnormalities estimated through complete band power effectively distinguished between good and bad outcome patients. Combining periodic and aperiodic abnormalities enhanced performance, like the complete band power approach. COMPARISON WITH EXISTING METHODS AND CONCLUSIONS: Sparing cerebral tissue with abnormalities in both periodic and aperiodic activity may result in poor surgical outcomes. Both periodic and aperiodic components do not carry sufficient information in isolation. The relative complete band power solution proved to be the most reliable method for this purpose. Future studies could investigate how cerebral location or pathology influences periodic or aperiodic abnormalities.

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.

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.

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.

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.

Diagnosis of Autism Spectrum Disorder by Dynamic Local Graph-Theory Indicators Based on Electroencephalogram.

BACKGROUND: Autism Spectrum Disorder (ASD) is a complex neurodevelopment disease characterized by impaired social and cognitive abilities. Despite its prevalence, reliable biomarkers for identifying individuals with ASD are lacking. Recent studies have suggested that alterations in the functional connectivity of the brain in ASD patients could serve as potential indicators. However, previous research focused on static functional-connectivity analysis, neglecting temporal dynamics and spatial interactions. To address this gap, our study integrated dynamic functional connectivity, local graph-theory indicators, and a feature-selection and ranking approach to identify biomarkers for ASD diagnosis. METHODS: The demographic information, as well as resting and sleeping electroencephalography (EEG) data, were collected from 20 ASD patients and 25 controls. EEG data were pre-processed and segmented into five sub-bands (Delta, Theta, Alpha-1, Alpha-2, and Beta). Functional-connection matrices were created by calculating coherence, and static-node-strength indicators were determined for each channel. A sliding-window approach, with varying widths and moving steps, was used to scan the EEG series; dynamic local graph-theory indicators were computed, including mean, standard deviation, median, inter-quartile range, kurtosis, and skewness of the node strength. This resulted in 95 features (5 sub-bands × 19 channels) for each indicator. A support-vector-machine recurrence-feature-elimination method was used to identify the most discriminative feature subset. RESULTS: The dynamic graph-theory indicators with a 3-s window width and 50% moving step achieved the highest classification performance, with an average accuracy of 95.2%. Notably, mean, median, and inter-quartile-range indicators in this condition reached 100% accuracy, with the least number of selected features. The distribution of selected features showed a preference for the frontal region and the Beta sub-band. CONCLUSIONS: A window width of 3 s and a 50% moving step emerged as optimal parameters for dynamic graph-theory analysis. Anomalies in dynamic local graph-theory indicators in the frontal lobe and Beta sub-band may serve as valuable biomarkers for diagnosing autism spectrum disorders.

Correlation Analysis of Multi-Scale Ictal EEG Signals in Juvenile Myoclonic Epilepsy.

BACKGROUND: To explore the time-frequency structure and cross-scale coupling of electroencephalography (EEG) signals during seizure in juvenile myoclonic epilepsy (JME), correlations between different leads, as well as dynamic evolution in epileptic discharge, progression and end of seizure were examined. METHODS: EEG data were obtained for 10 subjects with JME and 10 normal controls and were decomposed using gauss continuous wavelet transform (CWT). The phase amplitude coupling (PAC) relationship between the 11th (4.57 Hz) and 17th (0.4 Hz) scale was investigated. Correlations were examined between the 11th and 17th scale EEG signals in different leads during seizure, using multi-scale cross correlation analysis. RESULTS: The time-frequency structure of JME subjects showed strong rhythmic activity in the 11th and 17th scales and a close PAC was identified. Correlation analysis revealed that the ictal JME correlation first increased in the anterior head early in seizure and gradually expanded to the posterior head. CONCLUSION: PAC was exhibited between the 11th and 17th scales during JME seizure. The results revealed that the correlation in the anterior leads was higher than the posterior leads. In the perictal period, the 17th scale EEG signal preceded the 11th scale signal and remained for some time after a seizure. This suggests that the 17th scale signal may play an important role in JME seizure.

Disrupted Functional Brain Network Architecture in Sufferers with Boxing-Related Repeated Mild Traumatic Brain Injury: A Resting-State EEG Study.

BACKGROUND: Repetitive mild traumatic brain injury (rmTBI) often occurs in individuals engaged in contact sports, particularly boxing. This study aimed to elucidate the effects of rmTBI on phase-locking value (PLV)-based graph theory and functional network architecture in individuals with boxing-related injuries in five frequency bands by employing resting-state electroencephalography (EEG). METHODS: Twenty-fore professional boxers and 25 matched healthy controls were recruited to perform a resting-state task, and their noninvasive scalp EEG data were collected simultaneously. Based on the construction of PLV matrices for boxers and controls, phase synchronization and graph-theoretic characteristics were identified in each frequency band. The significance of the calculated functional brain networks between the two populations was analyzed using a network-based statistical (NBS) approach. RESULTS: Compared to controls, boxers exhibited an increasing trend in PLV synchronization and notable differences in the distribution of functional centers, especially in the gamma frequency band. Additionally, attenuated nodal network parameters and decreased small-world measures were observed in the theta, beta, and gamma bands, suggesting that the functional network efficiency and small-world characteristics were significantly weakened in boxers. NBS analysis revealed that boxers exhibited a significant increase in network connectivity strength compared to controls in the theta, beta, and gamma frequency bands. The functional connectivity of the significance subnetworks exhibited an asymmetric distribution between the bilateral hemispheres, indicating that the optimized organization of information integration and segregation for the resting-state networks was imbalanced and disarranged for boxers. CONCLUSIONS: This is the first study to investigate the underlying deficits in PLV-based graph-theoretic characteristics and NBS-based functional networks in patients with rmTBI from the perspective of whole-brain resting-state EEG. Joint analyses of distinctive graph-theoretic representations and asymmetrically hyperconnected subnetworks in specific frequency bands may serve as an effective method to assess the underlying deficiencies in resting-state network processing in patients with sports-related rmTBI.

Decoding familiar visual object categories in the mu rhythm oscillatory response.

Whilst previous research has linked attenuation of the mu rhythm to the observation of specific visual categories, and even to a potential role in action observation via a putative mirror neuron system, much of this work has not considered what specific type of information might be coded in this oscillatory response when triggered via vision. Here, we sought to determine whether the mu rhythm contains content-specific information about the identity of familiar (and also unfamiliar) graspable objects. In the present study, right-handed participants (N = 27) viewed images of both familiar (apple, wine glass) and unfamiliar (cubie, smoothie) graspable objects, whilst performing an orthogonal task at fixation. Multivariate pattern analysis (MVPA) revealed significant decoding of familiar, but not unfamiliar, visual object categories in the mu rhythm response. Thus, simply viewing familiar graspable objects may automatically trigger activation of associated tactile and/or motor properties in sensorimotor areas, reflected in the mu rhythm. In addition, we report significant attenuation in the central beta band for both familiar and unfamiliar visual objects, but not in the mu rhythm. Our findings highlight how analysing two different aspects of the oscillatory response - either attenuation or the representation of information content - provide complementary views on the role of the mu rhythm in response to viewing graspable object categories.

Brain states as wave-like motifs.

There is ample evidence of wave-like activity in the brain at multiple scales and levels. This emerging literature supports the broader adoption of a wave perspective of brain activity. Specifically, a brain state can be described as a set of recurring, sequential patterns of propagating brain activity, namely a wave. We examine a collective body of experimental work investigating wave-like properties. Based on these works, we consider brain states as waves using a scale-agnostic framework across time and space. Emphasis is placed on the sequentiality and periodicity associated with brain activity. We conclude by discussing the implications, prospects, and experimental opportunities of this framework.

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.

Brain oscillations during emotion regulation and the two-dimensional model of adult attachment.

Emotion Regulation (ER) refers to the processes by which individuals influence their own emotions. It is a crucial aspect of human behavior, affecting everything from interpersonal relationships to mental health. The relationship between ER and Attachment Theory (AT) is pivotal. AT suggests that early bonds with primary caregivers influence future relationship expectations and behaviors. These initial experiences shape internal models of self and others, affecting how individuals regulate their emotions. Understanding the interplay between ER and AT is essential for comprehending the human affective system. In this study, we explored the neural underpinnings of ER, focusing on two distinct strategies: cognitive reappraisal and expressive suppression. Using electroencephalography (EEG), we examined changes in neural oscillations from 52 adults during an ER task. Specifically, we observed increased frontal theta activity (3-6 Hz) during reappraisal compared to suppression strategies. This frontal theta activity suggests enhanced cognitive control engagement. Conversely, during suppression, we noted a decrease in beta frequency (15-30 Hz) activity from central electrodes, indicative of differing neural processes. Further integrating psychological theories, we explored the relationship between these neural markers and dimensions of human attachment. Employing the Experiences in Close Relationships-12 scale (ECR-12), we identified a negative correlation between attachment anxiety and frontal theta activity. Lower levels of attachment anxiety were associated with increased theta activity, reflecting potentially more effective emotion regulation. Additionally, we found that higher theta activity corresponded with fewer difficulties in emotional control measured by the Difficulties in Emotion Regulation Scale (DERS). Regarding central beta activity, our findings revealed an interesting correlation with Emotional Inattention, a concept tied to Attachment Avoidance. This suggests that central beta activity may serve as a neural marker for specific attachment-related ER processing. These results highlight the distinct neural pathways involved in different ER strategies and their relationship with the AT and neural responses during emotional processing.

Altered spreading of fast aperiodic brain waves relates to disease duration in Amyotrophic Lateral Sclerosis.

OBJECTIVE: To test the hypothesis that patients affected by Amyotrophic Lateral Sclerosis (ALS) show an altered spatio-temporal spreading of neuronal avalanches in the brain, and that this may related to the clinical picture. METHODS: We obtained the source-reconstructed magnetoencephalography (MEG) signals from thirty-six ALS patients and forty-two healthy controls. Then, we used the construct of the avalanche transition matrix (ATM) and the corresponding network parameter nodal strength to quantify the changes in each region, since this parameter provides key information about which brain regions are mostly involved in the spreading avalanches. RESULTS: ALS patients presented higher values of the nodal strength in both cortical and sub-cortical brain areas. This parameter correlated directly with disease duration. CONCLUSIONS: In this work, we provide a deeper characterization of neuronal avalanches propagation in ALS, describing their spatio-temporal trajectories and identifying the brain regions most likely to be involved in the process. This makes it possible to recognize the brain areas that take part in the pathogenic mechanisms of ALS. Furthermore, the nodal strength of the involved regions correlates directly with disease duration. SIGNIFICANCE: Our results corroborate the clinical relevance of aperiodic, fast large-scale brain activity as a biomarker of microscopic changes induced by neurophysiological processes.

Motor-related cortical oscillations distinguish one's own from a partner's contributions to a joint action.

The ability to distinguish between one's own and others' actions is a requirement for successful joint action. Such a distinction might be supported by dissociable motor activity underlying each partner's individual contributions to the joint action. However, little research has directly compared motor activity associated with one's own vs. others' actions during joint action. The current study investigated whether motor-related cortical oscillations distinguish between self- and partner-produced actions when partners take turns producing taps to meet a joint timing goal. Across two experiments, the degree of beta suppression differentiated one's own from a partner's actions, with more suppression occurring during one's own actions than during a partner's actions. Self-partner differences in mu suppression were also evident, particularly when partners produced actions in succession. Increased beta suppression was also observed during partners' actions when they were followed by one's own actions, suggesting that the coordination demands imposed by the joint action could affect the pattern of beta reactivity during a turn-taking joint action. Together, these findings demonstrate that dynamic patterns of motor activity underpin successful joint action and that periods of distinct motor activity are associated with one's own contributions to a joint action.