Intrinsic organization of cortical networks predicts state anxiety: an functional near-infrared spectroscopy (fNIRS) study

Shared and Distinctive Brain Networks Underlying Trait and State Rumination

Although trait and state rumination play a central role in the exacerbation of negative affect, evidence suggests that they are weakly correlated and exert distinct influences on emotional reactivity to stressors. Whether trait and state rumination share a common or distinct neural substrate remains unclear. In this study, we utilized functional near-infrared spectroscopy (fNIRS) combined with connectome-based predictive modeling (CPM) to identify neural fingerprints associated with trait and state rumination. CPM identified distinctive functional connectivity (FC) profiles that contribute to the prediction of trait rumination, primarily involving FC within the default mode network (DMN) and the dorsal attention network (DAN) as well as FC between the DMN, control network (CN), DAN, and salience network (SN). Conversely, state rumination was predominantly associated with FC between the DMN and CN. Furthermore, the predictive features of trait rumination can be robustly generalized to predict state rumination, and vice versa. In conclusion, this study illuminates the importance of both DMN and non-DMN systems in the emergence and persistence of rumination. While trait rumination was associated with stronger and broader FC than state rumination, the generalizability of the predictive features underscores the presence of shared neural mechanisms between the two forms of rumination. These identified connectivity fingerprints may hold promise as targets for innovative therapeutic interventions aimed at mitigating rumination-related negative affect.

Dynamic Organization of Large-scale Functional Brain Networks Supports Interactions Between Emotion and Executive Control

Emotion and executive control are often conceptualized as two distinct modes of human brain functioning. Little, however, is known about how the dynamic organization of large-scale functional brain networks that support flexible emotion processing and executive control, especially their interactions. The amygdala and prefrontal systems have long been thought to play crucial roles in these processes. Recent advances in human neuroimaging studies have begun to delineate functional organization principles among the large-scale brain networks underlying emotion, executive control, and their interactions. Here, we propose a dynamic brain network model to account for interactive competition between emotion and executive control by reviewing recent resting-state and task-related neuroimaging studies using network-based approaches. In this model, dynamic interactions among the executive control network, the salience network, the default mode network, and sensorimotor networks enable dynamic processes of emotion and support flexible executive control of multiple processes; neural oscillations across multiple frequency bands and the locus coeruleus-norepinephrine pathway serve as communicational mechanisms underlying dynamic synergy among large-scale functional brain networks. This model has important implications for understanding how the dynamic organization of complex brain systems and networks empowers flexible cognitive and affective functions.

Differential effects of hypnotherapy and cognitive behavioral therapy on the default mode network of depressed patients

Hypnosis has been applied in healing procedures since the earliest of recorded history and today it is implemented in a wholesome concept Hypnotherapy (HT1). On a neurophysiological level, hypnosis has been associated with parts of the Default Mode Network (DMN2), but its effects on this network when induced in a treatment setting of a widespread disorder, namely depression, have never been investigated. Depression is associated with abnormal functional connectivity (FC3) of the DMN. Cognitive Behavioral Therapy (CBT4) has proven itself to be an effective treatment for depression; effects of CBT on DMN-related regions are heterogeneous. In the past years, HT was found to be a promising alternative or helpful adjunction. Yet, its underlying mechanisms remain to be unclear. In this original study 75 depressed patients receiving either CBT or HT were included and measured during resting-state before and after therapy with functional near-infrared-spectroscopy (fNIRS5). On symptom level, results show a significant reduction in both groups. On a neurophysiological level, first exploratory analyses hint toward treatment effects in two components of the DMN. However, these effects do not withstand correction for multiple testing. Still, our study is a first stepstone in the investigation of neural mechanisms of HT and offers first ideas about possible implications.

Charitable crowdfunding donation-intention estimation depending on emotional project images using fNIRS-based functional connectivity

Charitable fundraising increasingly relies on online crowdfunding platforms. Project images of charitable crowdfunding use emotional appeals to promote helping behavior. Negative emotions are commonly used to motivate helping behavior because the image of a happy child may not motivate donors to donate as willingly. However, some research has found that happy images can be more beneficial. These contradictory results suggest that the emotional valence of project imagery and how fundraisers frame project images effectively remain debatable. Thus, we compared and analyzed brain activation differences in the prefrontal cortex governing human emotions depending on donation decisions using functional near-infrared spectroscopy, a neuroimaging device. We advance existing theory on charitable behavior by demonstrating that little correlation exists in donation intentions and brain activity between negative and positive project images, which is consistent with survey results on donation intentions by victim image. We also discovered quantitative brain hemodynamic signal variations between donors and nondonors, which can predict and detect donor mental brain functioning using functional connectivity, that is, the statistical dependence between the time series of electrophysiological activity and oxygenated hemodynamic levels in the prefrontal cortex. These findings are critical in developing future marketing strategies for online charitable crowdfunding platforms, especially project images.

Identification of abnormal closed-loop pathways in patients with MRI-negative pharmacoresistant epilepsy

Epilepsy is a disorder of brain networks, that is usually combined with cognitive and emotional impairment. However, most of the current research on closed-loop pathways in epilepsy is limited to the neuronal level or has focused only on known closed-loop pathways, and studies on abnormalities in closed-loop pathways in epilepsy at the whole-brain network level are lacking. A total of 26 patients with magnetic resonance imaging-negative pharmacoresistant epilepsy (MRIneg-PRE) and 26 healthy controls (HCs) were included in this study. Causal brain networks and temporal-lag brain networks were constructed from resting-state functional MRI data, and the Johnson algorithm was used to identify stable closed-loop pathways. Abnormal closed-loop pathways in the MRIneg-PRE cohort compared with the HC group were identified, and the associations of these pathways with indicators of cognitive and emotional impairments were examined via Pearson correlation analysis. The results revealed that the abnormal stable closed-loop pathways were distributed across the frontal, parietal, and occipital lobes and included altered functional connectivity values both within and between cerebral hemispheres. Four abnormal closed-loop pathways in the occipital lobe were associated with emotional and cognitive impairments. These abnormal pathways may serve as biomarkers for the diagnosis and guidance of individualized treatments for MRIneg-PRE patients.

A comparison of anxiety levels before and during the COVID-19 pandemic

The COVID-19 Pandemic upended the lives of nearly everyone worldwide, and recent studies have reported higher rates of anxiety, depression, and other mental health problems. Using a repeated crosssectional design, the current study compares anxiety levels from a representative sample of college students prior-to and during the COVID-19 Pandemic. Additionally, differences in anxiety prior to and following U.S. approval for use of the Pfizer-BioNTtech COVID-19 vaccine were also compared. Findings indicate that state-anxiety levels did not differ significantly prior to and during the Pandemic as well as before the vaccine and during and after the vaccine (M = 43.01, 44.10, 44.77, respectively). Surprisingly, trait anxiety levels were significantly higher during the Pandemic than before (p = .003), and anxiety levels trend down after the approval of the vaccine, but not significantly (M = 45.10, 48.85, 47.58, respectively). Future research should continue to investigate and compare anxiety levels during the COVID-19 Pandemic.

Differential effects of generalized anxiety and separation anxiety on brain structural development during adolescence

Excessive anxiety is highly prevalent during childhood and adolescence, with detrimental effects on somatic and mental health, and quality of life. Although structural abnormalities in the brain have been found in people with anxiety disorders, whether anxiety affects the brain development of children and adolescents remains unknown. Here, we applied a multivariate approach to two single-site MRI datasets consisting of 733 and 775 participants aged 5-18 years. Using linear support vector regression and cross-validation, brain age is estimated by predicting the chronological age from the features that combine cortical thickness and surface area of 68 brain regions. We found that gray matter can predict the chronological age of children and adolescents with a low mean absolute error. Compared to specific brain network, the whole structural brain measures predicted brain age better. Importantly, adolescents with higher generalized anxiety and those with lower separation anxiety showed lower brain age, indicating a slow development of brain structures. The relationship between anxiety and brain age of youths could also be found in parent-reported separation anxiety. The findings highlight differential effects of different anxiety types on brain structural development and suggest that different types of anxiety during childhood and adolescence should be treated differently.

Brain development mediates the relationship between self-reported poor parental monitoring and adolescent anxiety

Adolescence is the peak period for the onset of generalized anxiety disorder (GAD). Brain networks of cognitive and affective control in adolescents are not well developed when their exposure to external stimuli suddenly increases.Reasonable parental monitoring is especially important during this period.To examine the role of parental monitoring in the development of functional brain networks of GAD, we conducted a cross-validation-based predictive study based on the functional brain networks of 192 participants. We found that a set of functional brain networks, especially the default mode network and its connectivity with the frontoparietal network, could predict the ages of adolescents, which was replicated in three independent samples.Importantly, the difference between predicted age and chronological age significantly mediated the relationship between parental monitoring and anxiety levels. These findings suggest that inadequate parental monitoring plays a crucial role in the delayed development of specific brain networks associated with GAD in adolescents. Our work highlights the important role of parental monitoring in adolescent development.

The impact of sensation seeking personality trait on acute alcohol-induced disinhibition

BACKGROUND

Acute alcohol-related behavioral disinhibition has been well studied. But whether individual differences in the personality trait sensation seeking affect alcohol-induced behavioral disinhibition remains uncertain.

METHODS

The present study used functional near-infrared spectroscopy (fNIRS) technique and a response inhibition task (i.e., Go/No-Go) to determine the impact of the sensation seeking trait on the relationship between acute alcohol administration and inhibitory control capacity, and further investigate the neural mechanisms underlying this behavioral effect. Twenty-five high-sensation seekers and twenty-six low-sensation seekers were enrolled in this study. These participants attended two sessions: once for alcohol intake (0.5g/kg) and once for placebo intake (0g/kg).

RESULTS

Our results showed that high-sensation seekers relative to low-sensation seekers showed a significant decrease in inhibition accuracy under alcohol versus the placebo condition. Moreover, reduced prefrontal activity following acute alcohol consumption was more pronounced in high-sensation seekers compared with low-sensation seekers.

CONCLUSIONS

These findings showed that alcohol-induced behavioral disinhibition was affected by the personality trait sensation seeking and that recruitment of the prefrontal cortex contributed to the observed behavioral effect.

How Discrimination Gets Under the Skin: Biological Determinants of Discrimination Associated With Dysregulation of the Brain-Gut Microbiome System and Psychological Symptoms

BACKGROUND

Discrimination is associated with negative health outcomes as mediated in part by chronic stress, but a full understanding of the biological pathways is lacking. Here we investigate the effects of discrimination involved in dysregulating the brain-gut microbiome (BGM) system.

METHODS

A total of 154 participants underwent brain magnetic resonance imaging to measure functional connectivity. Fecal samples were obtained for 16S ribosomal RNA profiling and fecal metabolites and serum for inflammatory markers, along with questionnaires. The Everyday Discrimination Scale was administered to measure chronic and routine experiences of unfair treatment. A sparse partial least squares-discriminant analysis was conducted to predict BGM alterations as a function of discrimination, controlling for sex, age, body mass index, and diet. Associations between discrimination-related BGM alterations and psychological variables were assessed using a tripartite analysis.

RESULTS

Discrimination was associated with anxiety, depression, and visceral sensitivity. Discrimination was associated with alterations of brain networks related to emotion, cognition and self-perception, and structural and functional changes in the gut microbiome. BGM discrimination-related associations varied by race/ethnicity. Among Black and Hispanic individuals, discrimination led to brain network changes consistent with psychological coping and increased systemic inflammation. For White individuals, discrimination was related to anxiety but not inflammation, while for Asian individuals, the patterns suggest possible somatization and behavioral (e.g., dietary) responses to discrimination.

CONCLUSIONS

Discrimination is attributed to changes in the BGM system more skewed toward inflammation, threat response, emotional arousal, and psychological symptoms. By integrating diverse lines of research, our results demonstrate evidence that may explain how discrimination contributes to health inequalities.

Multi-modality connectome-based predictive modeling of individualized compulsions in obsessive-compulsive disorder

BACKGROUND

While previous neuroimaging studies are mainly focused on dichotomous classification of obsessive-compulsive disorder (OCD) from controls, predicting continuous severity of specific symptom is also pivotal to clinical diagnosis and treatment.

METHODS

We applied a machine-learning approach, connectome-based predictive modeling, on functional and structural brain networks constructed from resting-state functional magnetic resonance imaging and diffusion tensor imaging data to decode compulsions and obsessions of fifty-four patients with OCD.

RESULTS

We successfully predicted individualized compulsions with a positive model of structural brain network and with a negative model of functional brain network. The structural predictive brain network comprises the motor cortex, cerebellum and limbic lobe, which are involved in basic motor control, motor execution and emotion processing, respectively. The functional predictive brain network is composed by the prefrontal and limbic systems which are related to cognitive and affective control. Computational lesion analysis shows that functional connectivity among the salience network (SN), the frontal parietal network and the default mode network, as well as structural connectivity within the SN are vital in the individualized prediction of compulsions in OCD.

LIMITATIONS

There was no external validation of large samples to test the robustness of our predictive model.

CONCLUSIONS

These findings provide the first evidence for the predictive role of the triple network model in individualized compulsions and have important implications in diagnosis, prognosis and treatment of patients with OCD.

Effects of pharmacological treatments on neuroimaging findings in borderline personality disorder: A review of FDG-PET and fNIRS studies

BACKGROUND

Borderline personality disorder (BPD) is a serious mental condition characterized by instability in identity, interpersonal relationships, emotion regulation and impulsivity. These symptoms seem to be associated to specific brain alterations, which have been largely investigated. In particular, positron emission tomography (PET) and functional near-infrared spectroscopy (fNIRS) have demonstrated abnormalities in brain metabolism and hemodynamics in BPD, specifically in the fronto-limbic system. However, the role of medications on brain metabolism and hemodynamics in BPD is still largely unknown.

METHODS

We conducted a search on PubMed, Scopus and Web of Science of PET and fNIRS studies exploring the effect of medications on brain metabolism and hemodynamics in BPD. A total of 10 studies met the inclusion criteria.

RESULTS

Overall, PET studies showed an effect of psychotropic agents on brain metabolism, especially in frontal and temporal areas. Also, higher metabolic rates in frontal areas were found to correlate with clinical improvements. In contrast, fNIRS investigations reported an inconclusive or absent effects on brain hemodynamics in BPD patients.

LIMITATIONS

The small sample size, the elevated percentage of women, the heterogeneity in pharmacological agents and the presence of comorbidities limit the conclusions of the present review.

CONCLUSIONS

Serotoninergic agents and second-generation antipsychotics produce changes in frontal and temporal metabolism in BPD, which appear to correlate with clinical improvements. Differently, brain hemodynamics do not seem to be significantly affected by the most commonly prescribed drugs in BPD, suggesting that the therapeutic actions of medications are not mediated by changes in neural hemodynamics.