Altered executive control network and default model network topology are linked to acute electronic cigarette use: A resting-state fNIRS study.

In recent years, electronic cigarettes (e-cigs) have gained popularity as stylish, safe, and effective smoking cessation aids, leading to widespread consumer acceptance. Although previous research has explored the acute effects of combustible cigarettes or nicotine replacement therapy on brain functional activities, studies on e-cigs have been limited. Using fNIRS, we conducted graph theory analysis on the resting-state functional connectivity of 61 male abstinent smokers both before and after vaping e-cigs. And we performed Pearson correlation analysis to investigate the relationship between alterations in network metrics and changes in craving. E-cig use resulted in increased degree centrality, nodal efficiency, and local efficiency within the executive control network (ECN), while causing a decrease in these properties within the default model network (DMN). These alterations were found to be correlated with reductions in craving, indicating a relationship between differing network topologies in the ECN and DMN and decreased craving. These findings suggest that the impact of e-cig usage on network topologies observed in male smokers resembles the effects observed with traditional cigarettes and other forms of nicotine delivery, providing valuable insights into their addictive potential and effectiveness as aids for smoking cessation.

Why did my seizures start now? Influences of lesion connectivity and genetic etiology on age at seizure onset in focal epilepsy.

OBJECTIVE: Patients with focal, lesional epilepsy present with seizures at variable ages. Larger lesion size and overlap with sensorimotor or default mode network (DMN) have been associated with younger age at seizure onset in cohorts with mixed types of focal cortical dysplasia (FCD). Here, we studied determinants of age at seizure onset in patients with bottom-of-sulcus dysplasia (BOSD), a discrete type of FCD with highly localized epileptogenicity. METHODS: Eighty-four patients (77% operated) with BOSD were studied. Demographic, histopathologic, and genetic findings were recorded. BOSD volume and anatomical, primary versus association, rostral versus caudal, and functional network locations were determined. Normative functional connectivity analyses were performed using each BOSD as a region of interest in resting-state functional magnetic resonance imaging data of healthy children. Variables were correlated with age at seizure onset. RESULTS: Median age at seizure onset was 5.4 (interquartile range = 2-7.9) years. Of 50 tested patients, 22 had somatic and nine had germline pathogenic mammalian target of rapamycin (mTOR) pathway variants. Younger age at seizure onset was associated with greater BOSD volume (p = .002), presence of a germline pathogenic variant (p = .04), DMN overlap (p = .04), and increased functional connectivity with the DMN (p < .05, false discovery rate corrected). Location within sensorimotor cortex and networks was not associated with younger age at seizure onset in our relatively small but homogenous cohort. SIGNIFICANCE: Greater lesion size, pathogenic mTOR pathway germline variants, and DMN connectivity are associated with younger age at seizure onset in small FCD. Our findings strengthen the suggested role of DMN connectivity in the onset of FCD-related focal epilepsy and reveal novel contributions of genetic etiology.

Data-driven connectivity profiles relate to smoking cessation outcomes.

At a group level, nicotine dependence is linked to differences in resting-state functional connectivity (rs-FC) within and between three large-scale brain networks: the salience network (SN), default mode network (DMN), and frontoparietal network (FPN). Yet, individuals may display distinct patterns of rs-FC that impact treatment outcomes. This study used a data-driven approach, Group Iterative Multiple Model Estimation (GIMME), to characterize shared and person-specific rs-FC features linked with clinically-relevant treatment outcomes. 49 nicotine-dependent adults completed a resting-state fMRI scan prior to a two-week smoking cessation attempt. We used GIMME to identify group, subgroup, and individual-level networks of SN, DMN, and FPN connectivity. Regression models assessed whether within- and between-network connectivity of individual rs-FC models was associated with baseline cue-induced craving, and craving and use of regular cigarettes (i.e., "slips") during cessation. As a group, participants displayed shared patterns of connectivity within all three networks, and connectivity between the SN-FPN and DMN-SN. However, there was substantial heterogeneity across individuals. Individuals with greater within-network SN connectivity experienced more slips during treatment, while individuals with greater DMN-FPN connectivity experienced fewer slips. Individuals with more anticorrelated DMN-SN connectivity reported lower craving during treatment, while SN-FPN connectivity was linked to higher craving. In conclusion, in nicotine-dependent adults, GIMME identified substantial heterogeneity within and between the large-scale brain networks. Individuals with greater SN connectivity may be at increased risk for relapse during treatment, while a greater positive DMN-FPN and negative DMN-SN connectivity may be protective for individuals during smoking cessation treatment.

Measurements of Functional Network Connectivity Using Resting State Arterial Spin Labeling During Neurosurgery.

In neurosurgery, an exact delineation of functional areas is of great interest to spare important regions to ensure the best possible outcome for the patient (i.e., maximum removal while maintaining the highest possible quality of life). Preoperative imaging is routinely performed, including the visualization of not only structural but also functional information. During surgery, however, brain shift can occur, leading to an offset between the previously defined and the real position. Real-time imaging during the procedure is therefore desired to obtain this information while performing surgery. In this study 15 patients suffering from glioblastoma multiforme were included. These patients underwent structural and perfusion imaging using arterial spin labeling during the procedure. The latter has been used for gathering information about tumor residual perfusion. However, special postprocessing of this data allows for additional mapping of resting state networks and is intended to be used to gather deeper insights to aid the surgeon in planning the procedure. The data of each patient could be successfully postprocessed and used to map different resting state networks alongside the default mode network. On the basis of this study, it is feasible to use the information obtained from perfusion imaging to visualize not only vascular signal but also functional activation of resting state networks without acquiring any additional data besides the already available information. This may help guide the neurosurgeon in real time to adjust the surgical plan.

Effects of bariatric surgery on functional connectivity of the reward and default mode network: A pre-registered analysis.

Obesity imposes serious health risks and involves alterations in resting-state functional connectivity of brain networks involved in eating behavior. Bariatric surgery is an effective treatment, but its effects on functional connectivity are still under debate. In this pre-registered study, we aimed to determine the effects of bariatric surgery on major resting-state brain networks (reward and default mode network) in a longitudinal controlled design. Thirty-three bariatric surgery patients and 15 obese waiting-list control patients underwent magnetic resonance imaging at baseline, after 6 and 12 months. We conducted a pre-registered whole-brain time-by-group interaction analysis, and a time-by-group interaction analysis on within-network connectivity. In exploratory analyses, we investigated the effects of weight loss and head motion. Bariatric surgery compared to waiting did not significantly affect functional connectivity of the reward network and the default mode network (FWE-corrected p > .05), neither whole-brain nor within-network. In exploratory analyses, surgery-related BMI decrease (FWE-corrected p = .041) and higher average head motion (FWE-corrected p = .021) resulted in significantly stronger connectivity of the reward network with medial posterior frontal regions. This pre-registered well-controlled study did not support a strong effect of bariatric surgery, compared to waiting, on major resting-state brain networks after 6 months. Exploratory analyses indicated that head motion might have confounded the effects. Data pooling and more rigorous control of within-scanner head motion during data acquisition are needed to substantiate effects of bariatric surgery on brain organization.

The spontaneous brain activity of disgust: Perspective from resting state fMRI and resting state EEG.

In recent years, more and more studies on disgust have shown the association between disgust and various psychopathologies. Revealing the spontaneous brain activity patterns associated with disgust sensitivity from the perspective of individual differences will give us an insight into the neurologic nature of disgust and its psychopathological vulnerability. Here, we used two modal brain imaging techniques (resting fMRI and resting EEG) to reveal spontaneous brain activity patterns closely related to disgust sensitivity. The amplitude of low-frequency fluctuation results showed that disgust sensitivity is negatively correlated with the spontaneous activity of the right cerebellum crus II and positively correlated with the spontaneous activity of the right superior frontal cortex, which are inhibition-related brain regions. Furthermore, the microstate results of rest EEG indicated that the corrected duration, occurrence rate, and contribution of Class C, which is related to the anterior default mode network and is considered to be related to subjective representation of one' own body by combining interoceptive information with affective salience, were significantly positively correlated with the disgust sensitivity level. This data-driven approach provides the first evidence on the intrinsic brain features of disgust sensitivity based on two resting-state brain modalities. The results represent an initial effort to uncover the neurological basis of disgust sensitivity and its connection to psychopathology.

Nicotinic receptor modulation of the default mode network.

RATIONALE: Previous neuroimaging studies of cognition involving nicotinic acetylcholine receptor (nAChR) agonist administration have repeatedly found enhanced task-induced deactivation of regions of the default mode network (DMN), a group of brain systems that is more active at rest and mediates task-independent thought processes. This effect may be related to pro-cognitive nAChR agonist effects OBJECTIVES: The present study sought to test whether nAChR modulation of the DMN is bi-directional, i.e., whether a nAChR antagonist would reduce task-induced deactivation. METHODS: Eighteen healthy non-smokers underwent functional magnetic resonance imaging while performing a letter N-back task. Scans were performed after nicotine administration (7 mg/24 h, transdermally), after administration of the nAChR antagonist mecamylamine (7.5 mg, p.o.), and after double placebo, in counterbalanced sequence. Blood-oxygen-level-dependent (BOLD) signal was analyzed within ventromedial prefrontal cortex (vmPFC) and posterior cingulate cortex (PCC) regions of interest-central hubs of the DMN in which consistent nAChR agonist-induced changes had previously been identified. RESULTS: Nicotine enhanced hit rate in both the 0-back and 2-back condition, while mecamylamine slowed reaction time in the 2-back condition. Mecamylamine reduced task-induced deactivation of vmPFC and PCC. Nicotine had no significant effects on the BOLD signal. CONCLUSIONS: The finding that nAChR tone reduction by mecamylamine weakened task-induced DMN deactivation indicates that a constant tone of nAChR activation helps regulate DMN activity in healthy individuals. This suggests that low nAChR tone may play a causal role in DMN dysregulation seen in conditions such as mild cognitive impairment or Alzheimer's disease.

Asymmetric tumor-related alterations of network-specific intrinsic functional connectivity in glioma patients.

Resting-state functional MRI (rs-fMRI) allows mapping temporally coherent brain networks, and intra- and inter-network alterations have been described in different diseases. This prospective study investigated hemispheric resting-state functional connectivity (RSFC) differences in the default-mode network (DMN) and fronto-parietal network (FPN) between patients with left- and right-hemispheric gliomas (LH PAT, RH PAT), addressing asymmetry effects the tumor might have on network-specific intrinsic functional connectivity under consideration of the prognostically relevant isocitrate-dehydrogenase (IDH) mutation status. Twenty-seven patients (16 LH PAT, 12 IDH-wildtype) and 27 healthy controls underwent anatomical and rs-fMRI as well as neuropsychological assessment. Independent component analyses were performed to identify the DMN and FPN. Hemispheric DMN- and FPN-RSFC were computed, compared across groups, and correlated with cognitive performance. Patient groups did not differ in tumor volume, grade or location. RH PAT showed higher contra-tumoral DMN-RSFC than controls and LH PAT. With regard to the FPN, contra-tumoral RSFC was increased in both patient groups as compared to controls. Higher contra-tumoral RSFC was associated with worse cognitive performance in patients, which, however, seemed to apply mainly to IDH-wildtype patients. The benefit of RSFC alterations for cognitive performance varied depending on the affected hemisphere, cognitive demand, and seemed to be altered by IDH-mutation status. At the time of study initiation, a clinical trial registration was not mandatory at our faculty, but it can be applied for if requested.

Functional reorganization of brain networks across the human menstrual cycle.

The brain is an endocrine organ, sensitive to the rhythmic changes in sex hormone production that occurs in most mammalian species. In rodents and nonhuman primates, estrogen and progesterone's impact on the brain is evident across a range of spatiotemporal scales. Yet, the influence of sex hormones on the functional architecture of the human brain is largely unknown. In this dense-sampling, deep phenotyping study, we examine the extent to which endogenous fluctuations in sex hormones alter intrinsic brain networks at rest in a woman who underwent brain imaging and venipuncture for 30 consecutive days. Standardized regression analyses illustrate estrogen and progesterone's widespread associations with functional connectivity. Time-lagged analyses examined the temporal directionality of these relationships and suggest that cortical network dynamics (particularly in the Default Mode and Dorsal Attention Networks, whose hubs are densely populated with estrogen receptors) are preceded-and perhaps driven-by hormonal fluctuations. A similar pattern of associations was observed in a follow-up study one year later. Together, these results reveal the rhythmic nature in which brain networks reorganize across the human menstrual cycle. Neuroimaging studies that densely sample the individual connectome have begun to transform our understanding of the brain's functional organization. As these results indicate, taking endocrine factors into account is critical for fully understanding the intrinsic dynamics of the human brain.

Default mode network changes in fibromyalgia patients are largely dependent on current clinical pain.

Differences in fMRI resting-state connectivity of the default mode network (DMN) seen in chronic pain patients are often interpreted as brain reorganization due to the chronic pain condition. Nevertheless, patients' pain at the time of fMRI might influence the DMN because pain, like cognitive stimuli, engages attentional mechanisms and cognitive engagement is known to alter DMN activity. Here, we aimed to dissociate the influence of chronic pain condition (trait) from the influence of current pain experience (state) on DMN connectivity in patients with fibromyalgia (FM). We performed resting-state fMRI scans to test DMN connectivity in FM patients and matched healthy controls in two separate cohorts: (1) in a cohort not experiencing pain during scanning (27 FM patients and 27 controls), (2) in a cohort with current clinical pain during scanning (16 FM patients and 16 controls). In FM patients without pain during scanning, the connectivity of the DMN did not differ significantly from controls. By contrast, FM patients with current clinical pain during the scan had significantly increased DMN connectivity to bilateral anterior insula (INS) similar to previous studies. Regression analysis showed a positive relationship between DMN-midINS connectivity and current pain. We therefore suggest that transient DMN disruptions due to current clinical pain during scanning (current pain state) may be a substantial contributor to DMN connectivity disruptions observed in chronic pain patients.

Maximizing dissimilarity in resting state detects heterogeneous subtypes in healthy population associated with high substance use and problems in antisocial personality.

Patterns in resting-state fMRI (rs-fMRI) are widely used to characterize the trait effects of brain function. In this aspect, multiple rs-fMRI scans from single subjects can provide interesting clues about the rs-fMRI patterns, though scan-to-scan variability pose challenges. Therefore, rs-fMRI's are either concatenated or the functional connectivity is averaged. This leads to loss of information. Here, we use an alternative way to extract the rs-fMRI features that are common across all the scans by applying common-and-orthogonal-basis-extraction (COBE) technique. To address this, we employed rs-fMRI of 788 subjects from the human connectome project and estimated the common-COBE-component of each subject from the four rs-fMRI runs. Since the common-COBE-component is specific to a subject, the pattern was used to classify the subjects based on the similarity/dissimilarity of the features. The subset of subjects (n = 107) with maximal-COBE-dissimilarity (MCD) was extracted and the remaining subjects (n = 681) formed the COBE-similarity (CS) group. The distribution of weights of the common-COBE-component for the two groups across rs-fMRI networks and subcortical regions was evaluated. We found the weights in the default mode network to be lower in the MCD compared to the CS. We compared the scores of 69 behavioral measures and found six behaviors related to the use of marijuana, illicit drugs, alcohol, and tobacco; and including a measure of antisocial personality to differentiate the two groups. Gender differences were also significant. Altogether the findings suggested that subtypes exist even in healthy control population, and comparison studies (case vs. control) need to be mindful of it.