Resting-state EEG Study Research Articles

Impact of sleep deprivation on aperiodic activity: a resting-state EEG study.

Sleep deprivation (SD) has been shown to have a negative impact on alertness, as evidenced by behavioral and electroencephalographic studies. Nevertheless, conventional fixed-bandwidth spectral analysis confused the aperiodic and periodic components, and ignored some important periodic parameters (i.e., center frequency, bandwidth). Here, based on a large open access dataset of SD, we employed a standardized process for multiple electrode analysis and group inference. We found that, compared to SC, the aperiodic offset shifted overall after SD, primarily in the occipital region. And this shift was associated with a reduction in subjective alertness. For periodic component, we did not found any power change in alpha rhythm, but there is an increase in bandwidth of alpha. And the increased regions distributed in the occipital and temporal lobes. These findings highlight the potential significance and value of aperiodic parameters in behavioral and electrophysiological researches.

Anxiety and neural correlates of attention and self-regulation in pregnancy: a resting-state EEG study.

Pregnant women are particularly vulnerable to experiencing mental health difficulties, especially anxiety. Anxiety in pregnancy can be characterized as having two components: general symptomology experienced in the general population, and pregnancy-related anxiety more focused on pregnancy, delivery, and the future child. In addition, women also commonly report experiencing attentional control and self-regulation difficulties across the peripartum period. However, links between anxiety and neural and cognitive functioning in pregnancy remain unclear. The present study investigated whether anxiety is associated with neural markers of attention and self-regulation measured using electroencephalography (EEG). Specifically, we examined associations between general and pregnancy-related anxiety and (1) beta oscillations, a neural marker of attentional processing; and (2) the coupling of beta and delta oscillations, a neural marker of self-regulation, in frontal and prefrontal regions. A sample of 135 women in the third trimester of their pregnancy completed a resting-state EEG session. General anxiety was associated with increased beta oscillations, in line with research in the general population, interpreted as reflecting hyperarousal. Pregnancy-related anxiety was associated with decreased beta oscillations, interpreted as reflecting inattention and mind-wandering. Moreover, pregnancy-related anxiety, but not general anxiety, was linked to stronger delta-beta coupling, suggesting anxiety specifically related to the pregnancy is associated with investing greater effort in self-regulation. Our results suggest that general and pregnancy-related anxiety may differentially relate to neural patterns underlying attention and self-regulation in pregnancy.

Investigating Cortical Complexity in Mixed Dementia through Nonlinear Dynamic Analyses: A Resting-State EEG Study.

Objective: Dementia is a broad term referring to a decline in problem-solving abilities, language skills, memory, and other cognitive functions to a degree that it significantly disrupts everyday activities. The underlying cause of dementia is the impairment or loss of nerve cells and their connections within the brain. The particular symptoms experienced are contingent upon specific regions of the brain affected by this damage. In this research, we aimed to investigate the nonlinear dynamics of the mixed demented brain compared to healthy subjects using electroencephalogram (EEG) analysis. Method : For this purpose, EEG was recorded from 66 patients with mixed dementia and 65 healthy subjects during rest. After signal preprocessing, sample entropy and Katz fractal dimension analyses were applied to the preprocessed EEG data. Analysis of variance with repeated measures was utilized to compare the nonlinear dynamics of brain activity between dementia and healthy states and partial correlation analysis was employed to explore the relationship between EEG complexity measures and cognitive and neuropsychiatric symptoms of patients. Results: Based on repeated measures ANOVA, there was a significant main effect between groups for both Katz fractal dimension (F = 4.10, P = 0.01) and sample entropy (F = 4.81, P = 0.009) measures. Post hoc comparisons revealed that EEG complexity was significantly reduced in dementia mainly in the occipitoparietal and temporal areas (P < 0.05). MMSE scores were positively correlated with EEG complexity measures, while NPI scores were negatively correlated with EEG complexity measures, mainly in the occipitoparietal and temporal areas (P < 0.05). Moreover, using a KNN classifier, all significant complexity measures yielded the best classification performance with an accuracy of 98.05%, sensitivity of 97.03% and specificity of 99.16% in detecting dementia. Conclusion: This study demonstrated a unique dynamic system within the brain impacted by dementia that results in more predictable patterns of cortical activity mainly in the occipitoparietal and temporal areas. These abnormal patterns were associated with patients' cognitive capacity and neuropsychiatric symptoms.

Vulnerable at rest? A resting-state EEG study and psychosocial factors of young adult offspring of alcohol-dependent parents

BackgroundOffspring of parents with alcohol use disorder (AUD) are more susceptible to developing AUD, with an estimated heritability of around 50%. Vulnerability to AUD in first-degree relatives is influenced by biological factors, such as spontaneous brain activity, and high-risk psychosocial characteristics. However, existing resting-state EEG studies in AUD offspring have shown inconsistent findings regarding theta, alpha, and beta band frequencies. Additionally, research consistently demonstrates an increased risk of internalizing and externalizing disorders, self-regulation difficulties, and interpersonal issues among AUD offspring. MethodsThis study aimed to investigate the absolute power of theta, alpha, and beta frequencies in young adult offspring with a family history of AUD compared to individuals without family history. The psychosocial profiles of the offspring were also examined in relation to individuals without a family history of AUD. Furthermore, the study sought to explore the potential association between differences in frequency bands and psychosocial variables. Resting-state EEG recordings were obtained from 31 young adult healthy offspring of alcohol-dependent individuals and 43 participants with no family history of AUD (age range: 16–25 years). Participants also completed self-report questionnaires assessing anxiety and depressive symptoms, impulsivity, emotion regulation, and social involvement. ResultsThe results revealed no significant differences in spontaneous brain activity between the offspring and participants without a family history of AUD. However, in terms of psychosocial factors, the offspring exhibited significantly lower social involvement than the control group. ConclusionsThis study does not provide evidence suggesting vulnerability in offspring based on differences in spontaneous brain activity. Moreover, this investigation highlights the importance of interventions aimed at enhancing social connections in offspring. Such interventions can not only reduce the risk of developing AUD, given its strong association with increased feelings of loneliness but also improve the overall well-being of the offspring.

Negative emotions mediate the association between the topology of the complex brain network and smartphone use disorder: A resting-state EEG study.

Increasing research has examined the factors related to smartphone use disorder. However, limited research has explored its neural basis. We aimed to examine the relationship between the topology of the resting-state electroencephalography (rs-EEG) brain network and smartphone use disorder using minimum spanning tree analysis. Furthermore, we examined how negative emotions mediate this relationship. This study included 113 young, healthy adults (mean age = 20.87 years, 46.9% males). The results showed that the alpha- and delta-band kappas and delta-band leaf fraction were positively correlated with smartphone use disorder. In contrast, the alpha-band diameter was negatively correlated with smartphone use disorder. Negative emotions fully mediated the relationship between alpha-band kappa and alpha-band diameter and smartphone use disorder. Furthermore, negative emotions partially mediated the relationship between delta-band kappa and smartphone use disorder. The findings suggest that excessive scale-free alpha- and delta-band brain networks contribute to the emergence of smartphone use disorder. In addition, the findings also demonstrate that negative emotions and smartphone use disorder share the same neural basis. Negative emotions play a mediating role in the association between topological deviations and smartphone use disorder. To the best of our knowledge, this is the first study to examine the neural basis of smartphone use disorder from the perspective of the topology of the rs-EEG brain network. Therefore, neuromodulation may be a potential intervention for smartphone use disorder.

Long-term HD-tDCS modulates dynamic changes of brain activity on patients with disorders of consciousness: A resting-state EEG study

ObjectiveHigh-definition transcranial direct current stimulation (HD-tDCS) has been an effective neurostimulation method in the treatment of disorders of consciousness (DOC). However, the effects and mechanism of HD-tDCS are still unclear. MethodsThis study recruited 8 DOC patients and applied 20-min sessions of 2 mA HD-tDCS (central anode electrode at Pz) for 14 consecutive days. We record DOC patients' EEG data and Coma Recovery Scale–Revised (CRS-R) values at four time point: baseline (T0), after 1 day's and 7,14 days' parietal HD-tDCS treatment (T1, T2, T3). Power spectral density (PSD), relative power (RP), spectral entropy and spectral exponent were calculated to evaluate the EEG dynamic changes of DOC patients during long-term parietal HD-tDCS. At last, we calculated the correlation between changes of EEG features and changes of CRS-R values. ResultAfter 1 day's parietal HD-tDCS, DOC patients' CRS-R value had not changed (8.25 ± 1.91). HD-tDCS improved DOC patients' CRS-R value at T2 (9.75 ± 1.91, p < 0.05) and at T3 (11.38 ± 2.77, p < 0.05), compared with that at T0 (8.25 ± 1.91). As the treatment time increased, the EEG PSD decayed more slowly. Specifically, the delta frequency band RP decreased, while the alpha, beta, and gamma frequency bands RP increased. EEG oscillation characteristics changed but not significant at T1 (p > 0.05), and showed significant changes at T2 and T3 (p < 0.05). The spectral entropy continuously increased and the spectral exponent continuously decreased from T0 to T3. Specifically, the spectral entropy and spectral exponent of the parietal and occipital regions were significantly higher at T2 and T3 than that at T0 (p < 0.05). In addition, The changes in EEG features of the parietal and occipital lobes were correlated with changes in CRS-R value, especially between T2 and T0. ConclusionLong-term parietal HD-tDCS can improve the consciousness level and brain activity in DOC patients. Resting-state EEG can evaluate the dynamic changes of brain activity in DOC patients during HD-tDCS. EEG oscillation and non-oscillatory activity might be used to explain the mechanism of HD-tDCS on DOC patients.

Temporal hyper-connectivity and frontal hypo-connectivity within gamma band in schizophrenia: A resting state EEG study

ObjectiveThe brain network serves as the physiological foundation for information processing of the brain. Many studies have reported abnormalities of gamma oscillations in Schizophrenia. The aim of this study was to investigate the gamma-band connectivity in Schizophrenia patients. MethodsWe recorded the resting state electroencephalogram (EEG) for 15 schizophrenia patients with refractory auditory hallucinations and 14 healthy controls, with eyes open and closed. The brain network was constructed based on weighted phase lag index for gamma band. Whole scalp metrics (clustering coefficient, global efficiency and local efficiency) and local region metrics (degree and betweenness centrality) in the frontal and temporal lobes were computed. Correlation analyses between network metrics and symptom scales were examined to find associations with symptom severity. ResultsSchizophrenia patients had larger global efficiency and local efficiency (p < 0.05) with eyes closed, probably representing greater brain activity and information exchange. For degree and betweenness centrality, schizophrenia patients showed an increase (p < 0.05) in the temporal lobe but a decrease (p < 0.05) in the frontal lobe with eyes closed and open, potentially account for the patients' symptoms such as hallucinations and thought disorders. Local efficiency and frontal lobe degree were positively and negatively correlated with the scales, respectively (both p < 0.05). ConclusionsAltered connectivity of the resting state brain network has been revealed and may be associated with the core symptoms of schizophrenia. Our study provides promising evidence for the investigation of the pathological basis of Schizophrenia and could aid in objective diagnosis.

Prolonged Disease Course Leads to Impaired Brain Function in Anxiety Disorder: A Resting State EEG Study.

Anxiety disorder (AD) is a common disabling disease. The prolonged disease course may lead to impaired cognitive performance, brain function, and a bad prognosis. Few studies have examined the effect of disease course on brain function by electroencephalogram (EEG). Resting-state EEG analysis was performed in 34 AD patients. The 34 patients with AD were divided into two groups according to the duration of their illness: anxious state (AS) and generalized anxiety disorder (GAD). Then, EEG features, including univariate power spectral density (PSD), fuzzy entropy (FE), and multivariable functional connectivity (FC), were extracted and compared between AS and GAD. These features were evaluated by three previously validated machine learning methods to test the accuracy of classification in AS and GAD. Significant decreased PSD and FE in GAD were detected compared with AS, especially in the Alpha 2 band. In addition, FC analysis indicated that GAD patients' connection between the left and right hemispheres decreased. Based on machine learning, AS and GAD are classified on a six-month criterion with the highest classification accuracy of up to 0.99 ± 0.0015. The brain function of patients is more severely impaired in AD patients with longer illness duration. Resting-state EEG demonstrated to be a promising examination in the classification in GAD and AS using machine learning methods with better classification accuracy.

Neurophysiological patterns reflecting vulnerability to delirium subtypes: a resting-state EEG and event-related potential study.

Delirium is a common and acute neurocognitive disorder in older adults associated with increased risk of dementia and death. Understanding the interaction between brain vulnerability and acute stressors is key to delirium pathophysiology, but the neurophysiology of delirium vulnerability is not well defined. This study aimed to identify pre-operative resting-state EEG and event-related potential markers of incident delirium and its subtypes in older adults undergoing elective cardiac procedures. This prospective observational study included 58 older participants (mean age = 75.6 years, SD = 7.1; 46 male/12 female); COVID-19 restrictions limited recruitment. Baseline assessments were conducted in the weeks before elective cardiac procedures and included a 4-min resting-state EEG recording (2-min eyes open and 2-min eyes closed), a 5-min frequency auditory oddball paradigm recording, and cognitive and depression examinations. Periodic peak power, peak frequency and bandwidth measures, and aperiodic offsets and exponents were derived from resting-state EEG data. Event-related potentials were measured as mean component amplitudes (first positive component, first negative component, early third positive component, and mismatch negativity) following standard and deviant auditory stimuli. Incident delirium occurred in 21 participants: 10 hypoactive, 6 mixed, and 5 hyperactive. Incident hyperactive delirium was associated with higher pre-operative eyes open (P = 0.045, d = 1.0) and closed (P = 0.036, d = 1.0) aperiodic offsets. Incident mixed delirium was associated with significantly larger pre-operative first positive component amplitudes to deviants (P = 0.037, d = 1.0) and larger third positive component amplitudes to standards (P = 0.025, d = 1.0) and deviants (P = 0.041, d = 0.9). Other statistically non-significant but moderate-to-large effects were observed in relation to all subtypes. We report evidence of neurophysiological markers of delirium risk weeks prior to elective cardiac procedures in older adults. Despite being underpowered due to COVID-19-related recruitment impacts, these findings indicate pre-operative dysfunction in neural excitation/inhibition balance associated with different delirium subtypes and warrant further investigation on a larger scale.

Increased Delta and Theta Power Density in Sickle Cell Disease Individuals with Chronic Pain Secondary to Hip Osteonecrosis: A Resting-State Eeg Study.

Identify the presence of a dysfunctional electroencephalographic (EEG) pattern in individuals with sickle cell disease (SCD) and hip osteonecrosis, and assess its potential associations with depression, anxiety, pain severity, and serum levels of brain-derived neurotrophic factor (BDNF). In this cross-sectional investigation, 24 SCD patients with hip osteonecrosis and chronic pain were matched by age and sex with 19 healthy controls. Resting-state EEG data were recorded using 32 electrodes for both groups. Power spectral density (PSD) and peak alpha frequency (PAF) were computed for each electrode across Delta, Theta, Alpha, and Beta frequency bands. Current Source Density (CSD) measures were performed utilizing the built-in Statistical nonparametric Mapping Method of the LORETA-KEY software. Our findings demonstrated that SCD individuals exhibited higher PSD in delta and theta frequency bands when compared to healthy controls. Moreover, SCD individuals displayed increased CSD in delta and theta frequencies, coupled with decreased CSD in the alpha frequency within brain regions linked to pain processing, motor function, emotion, and attention. In comparison to the control group, depression symptoms, and pain intensity during hip abduction were positively correlated with PSD and CSD in the delta frequency within the parietal region. Depression symptoms also exhibited a positive association with PSD and CSD in the theta frequency within the same region, while serum BDNF levels showed a negative correlation with CSD in the alpha frequency within the left insula. This study indicates that individuals with SCD experiencing hip osteonecrosis and chronic pain manifest a dysfunctional EEG pattern characterized by the persistence of low-frequency PSD during a resting state. This dysfunctional EEG pattern may be linked to clinical and biochemical outcomes, including depression symptoms, pain severity during movement, and serum BDNF levels.

A resting state EEG study on depressed persons with suicidal ideation.

Major Depressive Disorder (MDD) is a psychiatric illness that is often associated with potentially life-threatening physiological changes and increased risk for suicidal behavior. Electroencephalography (EEG) research suggests an association between depression and specific frequency imbalances in the frontal brain region. Further, while recently developed technology has been proposed to simplify EEG data acquisition, more research is still needed to support its use in patients with MDD. Using the 14-channel EMOTIV EPOC cap, we recorded resting state EEG from 15 MDD patients with and MDD persons with suicidal ideation (SI) vs. 12 healthy controls (HC) to investigate putative power spectral density (PSD) between-group differences at the F3 and F4 electrode sites. Specifically, we explored 1) between-group alpha power asymmetries (AA), 2) between-group differences in delta, theta, alpha and beta power, 3) between PSD data and the scores in the Beck's Depression Inventory-II (BDI-II), Beck's Anxiety Inventory (BAI), Reasons for Living Inventory (RFL), and Self-Disgust Questionnaire (SDS). When compared to HC, patients had higher scores on the BAI (p=0.0018), BDI-II (p=0.0001) or SDS (p=0.0142) scale and lower scores in the RFL (p=0.0006) scale. The PSD analysis revealed no between-group difference or correlation with questionnaire scores for any of the measures considered. The present study could not confirm previous research suggesting frequency-specific anomalies in depressed persons with SI but might suggest that frontal EEG imbalances reflect greater anxiety and negative self-referencing. Future studies should confirm these findings in a larger population sample.

A parahippocampal-sensory Bayesian vicious circle generates pain or tinnitus: a source-localized EEG study.

Pain and tinnitus share common pathophysiological mechanisms, clinical features, and treatment approaches. A source-localized resting-state EEG study was conducted in 150 participants: 50 healthy controls, 50 pain, and 50 tinnitus patients. Resting-state activity as well as functional and effective connectivity was computed in source space. Pain and tinnitus were characterized by increased theta activity in the pregenual anterior cingulate cortex, extending to the lateral prefrontal cortex and medial anterior temporal lobe. Gamma-band activity was increased in both auditory and somatosensory cortex, irrespective of the pathology, and extended to the dorsal anterior cingulate cortex and parahippocampus. Functional and effective connectivity were largely similar in pain and tinnitus, except for a parahippocampal-sensory loop that distinguished pain from tinnitus. In tinnitus, the effective connectivity between parahippocampus and auditory cortex is bidirectional, whereas the effective connectivity between parahippocampus and somatosensory cortex is unidirectional. In pain, the parahippocampal-somatosensory cortex is bidirectional, but parahippocampal auditory cortex unidirectional. These modality-specific loops exhibited theta-gamma nesting. Applying a Bayesian brain model of brain functioning, these findings suggest that the phenomenological difference between auditory and somatosensory phantom percepts result from a vicious circle of belief updating in the context of missing sensory information. This finding may further our understanding of multisensory integration and speaks to a universal treatment for pain and tinnitus-by selectively disrupting parahippocampal-somatosensory and parahippocampal-auditory theta-gamma activity and connectivity.

Does intermittent theta burst stimulation change oscillatory activity in the targeted left dorsolateral prefrontal cortex? - a resting-state EEG study

Does intermittent theta burst stimulation change oscillatory activity in the targeted left dorsolateral prefrontal cortex? - a resting-state EEG study

Brain rhythmic abnormalities in convalescent patients with anti-NMDA receptor encephalitis: a resting-state EEG study.

Anti-N-methyl-D-aspartate receptor encephalitis (anti-NMDARE) is autoimmune encephalitis with a characteristic neuropsychiatric syndrome and persistent cognition deficits even after clinical remission. The objective of this study was to uncover the potential noninvasive and quantified biomarkers related to residual brain distortions in convalescent anti-NMDARE patients. Based on resting-state electroencephalograms (EEG), both power spectral density (PSD) and brain network analysis were performed to disclose the persistent distortions of brain rhythms in these patients. Potential biomarkers were then established to distinguish convalescent patients from healthy controls. Oppositely configured spatial patterns in PSD and network architecture within specific rhythms were identified, as the hyperactivated PSD spanning the middle and posterior regions obstructs the inter-regional information interactions in patients and thereby leads to attenuated frontoparietal and frontotemporal connectivity. Additionally, the EEG indexes within delta and theta rhythms were further clarified to be objective biomarkers that facilitated the noninvasive recognition of convalescent anti-NMDARE patients from healthy populations. Current findings contributed to understanding the persistent and residual pathological states in convalescent anti-NMDARE patients, as well as informing clinical decisions of prognosis evaluation.

Applying Deep Learning on a Few EEG Electrodes during Resting State Reveals Depressive States. A Data Driven Study.

The growing number of depressive people and the overload in primary care services make it necessary to identify depressive states with easily accessible biomarkers such as mobile electroencephalography (EEG). Some studies have addressed this issue by collecting and analyzing EEG resting state in a search of appropriate features and classification methods. Traditionally, EEG resting state classification methods for depression were mainly based on linear or a combination of linear and non-linear features. We hypothesize that participants with ongoing depressive states differ from controls in complex patterns of brain dynamics that can be captured in EEG resting state data, using only nonlinear measures on a few electrodes, making it possible to develop cheap and wearable devices that could be even monitored through smartphones. To validate such a perspective, a resting-state EEG study was conducted with 50 participants, half with depressive state (DEP) and half controls (CTL). A data-driven approach was applied to select the most appropriate time window and electrodes for the EEG analyses, as suggested by Giacometti⁠, as well as the most efficient nonlinear features and classifiers, to distinguish between CTL and DEP participants. Nonlinear features showing temporo-spatial and spectral complexity were selected. The results confirmed that computing nonlinear features from a few selected electrodes in a 15 s time window are sufficient to classify DEP and CTL participants accurately. Finally, after training and testing internally the classifier, the trained machine was applied to EEG resting state data (CTL and DEP) from a publicly available database, validating the capacity of generalization of the classifier with data from different equipment, population, and environment obtaining an accuracy near 100%.

Altered functional and directed connectivity in propofol-induced loss of consciousness: A source-space resting-state EEG study

ObjectiveGeneral anesthesia might disrupt neuronal network communications measured by functional connectivity (FC; undirected connectivity) and directional information flow (directed connectivity). We sought to characterize the state-dependent effects of propofol on cortico-cortical undirected and directed FC. MethodsWe collected 256-channel high-density EEGs from 14 patients undergoing surgery while awake (AWA) or in propofol-induced moderate sedation (SED) or loss of consciousness (LOC) states. Using source-space EEG, we estimated neuronal oscillatory activity for 68 cortical regions of interest. FC was analyzed using the weighted phase lag index. Directed connectivity was computed using directed phase transfer entropy (dPTE) as a measure of information flow in the bilateral prefrontal, frontal, parietal, and occipital areas. ResultsFC strength evidently reduced during LOC compared with those during the AWA and SED states. The dPTE analysis showed significant propofol-induced changes in directed connectivity. In the alpha band, the prefrontal-to-frontal information flow was significantly stronger in the AWA than in the SED (p = 0.033) and LOC states (p = 0.033). The parietal-to-frontal dPTE was significantly weaker during LOC than during the AWA (p = 0.033) and SED states (p = 0.007). Finally, a loss of occipital-to-frontal connectivity occurred during LOC but not the AWA state (p = 0.001). In the beta band, the dominant occipital-to-frontal direction of information flow in the AWA state was gradually converted to a frontal-to-occipital direction during LOC. ConclusionsPropofol-induced unconsciousness is marked by a decrease in FC and posterior-to-anterior (feedforward) directed connectivity, which may be useful as a measure to discriminate different conscious states caused by propofol administration. SignificanceThe study demonstrates that propofol produces state-dependent effects on cortico-cortical undirected and directed FC, supporting the idea that propofol induces loss of consciousness may through disrupting network interactions and cortical coordination.

Quantitative electroencephalography changes in patients with mild cognitive impairment after choline alphoscerate administration

There is limited evidence on the effectiveness of choline alphoscerate for mild cognitive impairment (MCI) in studies using neuropsychological markers. The aim of this study was to evaluate the spectral change at a source level using quantitative electroencephalography (qEEG) as a biomarker for cognitive function after choline alphoscerate administration to patients with MCI. This study used the qEEG data of patients with MCI who visited the Department of Neurology of the Chung-Ang University Hospital between April 2017 and December 2018. Resting-state EEG studies were performed on 33 patients with MCI at baseline and compared with those of the 18 normal controls selected from the community. After baseline qEEG, choline alphoscerate 400 mg was administered twice daily for 2 months to the patients with MCI. Follow-up qEEG was performed in 20 subjects. Baseline qEEG of patients with MCI was compared to qEEG after choline alphoscerate administration. We found that the MCI group exhibited a decreased alpha power compared to that of the control group. Patients with MCI treated with choline alphoscerate exhibited a decrease in the theta and delta power of the parietal and temporal lobe and an increase in the alpha power spectrum of the occipital lobes. We also identified the trend of default mode network enhancement after choline alphoscerate administration. Our results suggest that choline alphoscerate may have a positive effect in patients with MCI and support the usefulness of qEEG for monitoring the therapeutic effect of nootropics.

Need for cognitive closure is associated with different intra-network functional connectivity patterns: A resting state EEG study

ABSTRACT Need for Cognitive Closure (NCC) is a construct referring to the desire for predictability, unambiguity and firm answers to issues. Neuroscientific literature about NCC processes has mainly focused on task-related brain activity. According to the Triple Network model (TN), the main aim of the current study was to investigate resting state (RS) electroencephalographic (EEG) intra-network dynamics associated with NCC. Fifty-two young adults (39 females) were enrolled and underwent EEG recordings during RS. Functional connectivity analysis was computed through exact Low-Resolution Electromagnetic Tomography (eLORETA) software. Our results showed that higher levels of NCC were associated with both i) decreased alpha EEG connectivity within the Central Executive Network (CEN), and ii) increased delta connectivity within the Default Mode Network (DMN). No significant correlations were observed between NCC and functional connectivity in the Salience Network (SN). Our data would seem to suggest that high levels of NCC are characterized by a specific communication pattern within the CEN and the DMN during RS. These neurophysiological patterns might reflect several typical NCC-related cognitive characteristics (e.g., lower flexibility and preference for habitual and rigid response schemas).

Asthma induces psychiatric impairments in association with default mode and salience networks alteration: A resting-state EEG study

Asthma is a chronic inflammatory disease associated with a high prevalence of psychiatric disorders. There are specific brain networks responsible for emotional processes, including two important networks associated with psychiatric problems: the default mode network (DMN), which is more active in the resting state, and the salience network (SN), which is structurally connected to DMN. Although previous studies suggested that neuro-phenotypes of asthma may be recognizable by the neural activity of brain circuits, an association between the brain's functional alterations and psychiatric impairments induced by asthma remains unknown. We aimed to assess DMN and SN activity and its association with psychiatric indices and clinical parameters in asthmatic patients. Electroencephalography was recorded during the resting state with an awake and eyes-open condition in thirty-eight sex and age-matched subjects (19 atopic asthma patients and 19 healthy participants). Power spectrum and functional connectivity were computed for DMN and SN. We examined psychiatric disorders (including depression, anxiety, and stress) and pulmonary function using the DASS questionnaire and spirometry test, respectively. The results showed that DASS scores were significantly higher in asthmatic patients compared to healthy subjects. Asthmatic patients also demonstrate a significant enhancement in power and functional connectivity in the two networks. Notably, these power enhancements of the networks were correlated with psychiatric problems scores, pulmonary function, asthma duration, and poor asthma control. These results introduce new evidence for the association between altered brain activity, the existence of psychiatric disorders, and asthma-related features, including pulmonary function. Also, we provide new insights into asthma-induced inflammatory response and the importance of developing novel interventions and therapeutic strategies for managing allergic inflammation patients who suffer from concurrent psychiatric disorders.

Default Mode Network and Neural Phase Synchronization in Healthy Aging: A Resting State EEG Study

Aging is associated with altered brain connectivity within the default mode network (DMN). Although research using functional magnetic resonance imaging has quantified age-related alterations in functional connectivity within this network during resting state, it is less clear how this may be reflected in electrophysiological measures, and how this relates to cognitive performance in older adults. The aim of this study was to quantify age differences in phase synchrony of the DMN during resting state, with particular focus on connectivity between the anterior node (i.e., medial prefrontal cortex, or mPFC) and other associated regions in this network. Electroencephalography was recorded from 55 younger adults (18–30 years, 28 females) and 34 older adults (64–88 years, 16 females) in two resting state conditions (eyes-open and -closed). Source-level functional connectivity was quantified using phase-locking value (PLV) with a spatial filter of six sources of interest, and were subjected to data-driven permutation testing between groups from 1 to 50 Hz. Older adults also completed tests of memory, language, executive functioning, and processing speed. Findings indicated decreased connectivity in the alpha2 range for older than younger adults between the mPFC and other DMN regions including the left angular gyrus and bilateral lateral temporal cortices, the latter of which were associated with lower performance in semantic fluency and executive functioning in older adults. Furthermore, greater PLV in theta and beta bands between the mPFC and posterior cingulate regions were found in older than younger adults. These results suggest age-related changes in DMN functional connectivity are non-uniform and frequency-dependent, and may reflect poorer performance in cognitive domains thought to decline with aging.