The brain's default network: anatomy, function, and relevance to disease

Altered structural node of default mode network mediated general cognitive ability in young adults with obesity

BACKGROUND

Obesity, characterized by excessive adiposity, is associated with brain structural abnormalities. Nevertheless, the relationships between altered structural nodes of default mode network (DMN), body mass index (BMI), general cognitive ability remained unclear in young adults.

METHODS

In this study, we divided a large sample of young adults into three BMI-based groups. We then conducted one-way analyses of variance and post-hoc tests with Bonferroni corrections to investigate abnormal structural brain regions associated with obesity. Furthermore, mediation effects models were built to explore whether the structural alterations influenced the relationship between BMI and general cognitive ability.

RESULTS

Compared to their lean and overweight counterparts, young adults with obesity exhibited significantly lower general cognitive ability, higher impulsivity traits, and worse sleep quality. Furthermore, compared with lean group, young adults with obesity exhibited altered cortical thickness of both the left temporal pole and right superior parietal lobule, and abnormal cortical surface area (CSA) of the left entorhinal cortex (EC), a hub within DMN. Moreover, CSA of the left EC mediated the relationship between BMI and general cognitive ability.

CONCLUSION

Obesity was linked to altered structural node of DMN, which mediated general cognitive ability in young adults. These findings indicated the negative effect of obesity on DMN and general cognitive ability in young adults.

Functional connectome gradient predicts clinical symptoms of chronic insomnia disorder

Insomnia is the second most prevalent psychiatric disorder worldwide, but the understanding of the pathophysiology of insomnia remains fragmented. In this study, we calculated the connectome gradient in 50 chronic insomnia disorder (CID) patients and 38 healthy controls (HC) to assess changes due to insomnia and utilized these gradients in a connectome-based predictive modeling (CPM) to predict clinical symptoms associated with insomnia. The results suggested that insomnia led to significant alterations in the functional gradients of some brain areas. Specifically, the gradient scores in the middle frontal gyrus, superior anterior cingulate gyrus, and right nucleus accumbens were significantly higher in the CID patients than in the HC group, whereas the scores in the middle occipital gyrus, right fusiform gyrus, and right postcentral gyrus were significantly lower than in the HC group. Further correlation analysis revealed that the right middle frontal gyrus is positively correlated with the self-rating anxiety scale (r=0.3702). Additionally, the prediction model built with functional gradients could well predict the sleep quality (r=0.5858), anxiety (r=0.6150), and depression (r=0.4022) levels of insomnia patients. This offers an objective depiction of the clinical diagnosis of insomnia, yielding a beneficial impact on the identification of effective biomarkers and the comprehension of insomnia.

Associations between Japanese calligraphy practice and sleep quality in community-dwelling older adults: A cross-sectional Study

Background

Sleep disturbances, such as insomnia, are common among the elderly population and have been associated with negative health outcomes. Japanese calligraphy is a traditional art practice previously associated with various health benefits, such as stress reduction and improved cognitive function; however, its association with sleep quality has not been fully explored.

Methods

This cross-sectional study included 21,207 subjects with basic attributes, health status, depressive symptoms, artistic practices, and sleep habits. Individuals who satisfied the chronic insomnia criteria were categorized into the following subtypes: sleep onset latency (SOL) insomnia, early morning awakening (EMA) insomnia, and wake after sleep offset (WASF) insomnia. The t-test, chi-square test, and logistic regression analysis were used to determine the association between Japanese calligraphy practice and sleep quality.

Results

In this study, 17,597 elderly Japanese individuals were included, among whom 13.7 % practiced Japanese calligraphy. Regarding sleep characteristics, 32.0 % had chronic insomnia, 13.1 % had SOL insomnia, 9.1 % had EMA insomnia, and 14.2 % had WASF insomnia. Japanese calligraphy practice was associated with lower rates of chronic insomnia (odds ratio [OR] = 0.85, 95 % confidence interval (CI) = 0.76-0.95), including SOL insomnia (OR = 0.84, 95 % CI = 0.71-0.98), and EMA insomnia (OR = 0.80, 95 % CI = 0.66-0.97) but had no significant association with WASF insomnia.

Conclusions

This study suggests that Japanese calligraphy practice is associated with lower odds of insomnia, particularly SOL and EMA insomnia. Calligraphy may be an effective nonpharmacological intervention for insomnia and poor sleep quality among elderly Japanese individuals.

The surface-based degree centrality of patients with lifelong premature ejaculation: A resting-state fMRI study

The aim of this study was to investigate alterations in the resting-state brain functional network characteristics of lifelong premature ejaculation (PE) patients using surface-based degree centrality (DC), and to analyze the correlation between these alterations and clinical symptoms in PE patients. The study included individuals with lifelong PE (patient group, n = 36) and a control group matched by age and education level (control group, n = 22). Resting-state functional magnetic resonance imaging (fMRI) scans were performed on all participants. Surface-based degree centrality analysis was conducted and the differences between the two groups were compared using t-tests. Further, the DC values of brain regions showing significant differences were correlated with clinical symptoms. Compared to the control group, the patient group exhibited significantly reduced degree centrality (DC) values in the left precuneus and significantly increased DC values in the right supplementary motor area (SMA). Furthermore, intravaginal ejaculatory latency time (IELT) and Chinese Index of Premature Ejaculation (CIPE) values were positively correlated with left precuneus DC values and negatively correlated with right SMA DC values. Patients with primary lifelong ejaculation demonstrate abnormalities in key brain network nodes and their connections with relevant brain regions, which are strongly associate with clinical symptoms. These findings enhance our understanding of the neuronal pathological changes in PE patients.

A Novel Directed Seed-Based Connectivity Analysis Toolbox Applied to Human and Marmoset Resting-State FMRI

Estimating the direction of functional connectivity (FC) can help further elucidate complex brain function. However, the estimation of directed FC at the voxel level in fMRI data, and evaluating its performance, has yet to be done. We therefore developed a novel directed seed-based connectivity analysis (SCA) method based on normalized pairwise Granger causality that provides greater detail and accuracy over ROI-based methods. We evaluated its performance against 145 cortical retrograde tracer injections in male and female marmosets that were used as ground truth cellular connectivity on a voxel-by-voxel basis. The receiver operating characteristic (ROC) curve was calculated for each injection, and we achieved area under the ROC curve of 0.95 for undirected and 0.942 for directed SCA in the case of high cell count threshold. This indicates that SCA can reliably estimate the strong cellular connections between voxels in fMRI data. We then used our directed SCA method to analyze the human default mode network (DMN) and found that dlPFC (dorsolateral prefrontal cortex) and temporal lobe were separated from other DMN regions, forming part of the language-network that works together with the core DMN regions. We also found that the cerebellum (Crus I-II) was strongly targeted by the posterior parietal cortices and dlPFC, but reciprocal connections were not observed. Thus, the cerebellum may not be a part of, but instead a target of, the DMN and language-network. Summarily, our novel directed SCA method, visualized with a new functional flat mapping technique, opens a new paradigm for whole-brain functional analysis.

Causal relationship between cortical structural changes and onset of anxiety disorder: evidence from Mendelian randomization

Previous studies have reported a correlation between anxiety disorders and changes in brain structure, yet the specific alterations in brain region volumes remain unclear. This study aimed to infer the causal relationship between anxiety disorders and changes in brain structure volume through Mendelian Randomization analysis. We selected 63 cortical structure volumes from the GWAS database as exposure data and anxiety disorder data from the FinnGen and UK Biobank databases as outcomes. We found a significant correlation between atrophy in the Left precentral volume area (Odds Ratio [OR] = 0.935, 95% Confidence intervals [CI]: 0.891-0.981, P value, P = 0.007) and an increased risk of anxiety disorders. Additionally, changes identified in specific brain regions, such as atrophy in the Right rostral anterior cingulate area (OR = 0.993, 95% CI: 0.987-0.999, P = 0.025) and increased volume in the Left superior parietal area (OR = 1.001, 95% CI: 1.000-1.001, P = 0.028), may correlate with an increased risk of anxiety disorders. Furthermore, both phenotypes demonstrated directional consistency in their respective and overall meta-analyzed OR values pre- and post-merger, enhancing the reliability of the results. This study elucidates the causal relationship between anxiety disorders and specific brain structures, providing new insights for further research into psychiatric disorders.

Changes in resting-state functional connectivity of large-scale brain networks in bulimia nervosa: evidence from causal analysis

Bulimia nervosa (BN) has been observationally linked to the functional connectivity (FC) of large-scale brain networks, but the biological mechanisms remain unclear. This study used two-sample Mendelian randomization (MR) with genetic variations as instrumental variables (IVs) to explore potential causal relationships between FC and BN. Summary data from genome-wide association studies (GWAS) involving 2,564 individuals were analyzed to identify genetically predicted BN. Functional magnetic resonance imaging parameters and materials were sourced from the UK Biobank. The variables underwent independent component analysis processing by the database to generate the final GWAS dataset. Various methods, including MR Pleiotropy RESidual Sum and Outlier, MR Egger, and weighted median, were employed to detect heterogeneity and pleiotropy, with inverse variance weighting serving as the principal estimation method (P < 0.05). The FC imaging-derived phenotypes revealed that BN exerted a causal influence on the FC between large-scale networks, including the visual network, default mode network (DMN), frontoparietal network, somatosensory network (SSN), and ventral attention network. Additionally, BN had a causal impact on the within-network FC of both the DMN and SSN. The study provides evidence that BN leads to further changes in FC patterns within and between large-scale brain networks.

Thalamocortical dysrhythmia and reward deficiency syndrome as uncertainty disorders

A common anatomical core has been described for psychiatric disorders, consisting of the dorsal anterior cingulate cortex (dACC) and anterior insula, processing uncertainty. A common neurophysiological core has been described for other brain related disorders, called thalamocortical dysrhythmia (TCD), consisting of persistent cross-frequency coupling between low and high frequencies. And a common genetic core has been described for yet another set of hypodopaminergic pathologies called reward deficiency syndromes (RDS). Considering that some RDS have the neurophysiological features of TCD, it can be hypothesized that TCD and RDS have a common anatomical core, yet a differentiating associated neurophysiological mechanism. The EEGs of 683 subjects are analysed in source space for both differences and conjunction between TCD and healthy controls, RDS and healthy controls, and between TCD and RDS. A balance between current densities of the pregenual anterior cingulate cortex (pgACC) extending into the ventromedial prefrontal cortex (vmPFC) and dACC is calculated as well. TCD and RDS share a common anatomical and neurophysiological core, consisting of beta activity in the dACC and theta activity in dACC extending into precuneus and dorsolateral prefrontal cortex. TCD and RDS differ in pgACC/vmPFC activity and demonstrate an opposite balance between pgACC/vmPFC and dACC. Based on the Bayesian brain model TCD and RDS can be defined as uncertainty disorders in which the pgACC/vmPFC and dACC have an opposite balance, possibly explained by an inverted-U curve profile of both pgACC/vmPFC and dACC.

Travelling beyond time: shared brain system for self-projection in the temporal, political and moral domains

Mental time travel (MTT), a cornerstone of human cognition, enables individuals to mentally project themselves into their past or future. It was shown that this self-projection may extend beyond the temporal domain to the spatial and social domains. What about higher cognitive domains? Twenty-eight participants underwent functional magnetic resonance imaging (fMRI) while self-projecting to different political, moral and temporal perspectives. For each domain, participants were asked to judge their relationship to various people (politicians, moral figures, personal acquaintances) from their actual or projected self-location. Findings showed slower, less accurate responses during self-projection across all domains. fMRI analysis revealed self-projection elicited brain activity at the precuneus, medial and dorsolateral prefrontal cortex, temporoparietal junction and anterior insula, bilaterally and right lateral temporal cortex. Notably, 23.5% of active voxels responded to all three domains and 27% to two domains, suggesting a shared brain system for self-projection. For ordinality judgement (self-reference), 52.5% of active voxels corresponded to the temporal domain specifically. Self-projection activity overlapped mostly with the frontoparietal control network, followed by the default mode network, while self-reference showed a reversed pattern, demonstrating MTT's implication in spontaneous brain activity. MTT may thus be regarded as a 'mental-experiential travel', with self-projection as a domain-general construct and self-reference related mostly to time. This article is part of the theme issue 'Elements of episodic memory: lessons from 40 years of research'.

Scoping review on shamanistic trances practices

BACKGROUND

Shamanism is a spiritual tradition in which trance practitioners deliberately modify their state of consciousness to seemingly interact with an invisible world to resolve their community members' problems. This review aims to provide a multidisciplinary overview of scientific research on shamanic trance.

METHODS

The search was performed using PubMed and Google Scholar databases. Twenty-seven articles were found to be eligible, and their data were classified into four dimensions, namely, a) phenomenology, b) psychology, c) neuro-physiological functions, and d) clinical applications.

RESULTS

These studies suggest that these trances are non-pathological, different from normal states of consciousness in terms of phenomenology and neurophysiology, and influenced by multiple personal and environmental variables. Furthermore, while trances may offer therapeutic potential, their scope should be approached cautiously, underscoring the need for rigorous studies to assess the effectiveness of shamanic approaches for complementary therapies.

CONCLUSION

Overall, shamanic trance and its potential benefits remain an intriguing and multifaceted area of scientific study, offering insights into the intersections of consciousness, spirituality, and possibly therapy.

The effects of APOEe4 allele on cerebral structure, function, and related interactions with cognition in young adults

In the last decade, extensive research has emerged into understanding the impact of risk factors for Alzheimer's Disease (AD) on brain in pre-symptomatic stages. We investigated the neuroimaging correlates of the APOEe4 genetic risk factor for AD in young adulthood, its relationship with cognition, and potential effects of other variables on the findings. While conventional volumetric analyses revealed no consistent differences, more sophisticated analyses identified subtle structural differences between APOEe4 carriers and non-carriers. Findings from diffusion studies were limited, but functional studies demonstrated consistent alterations in connectivity and activity. The complex relationship between APOE genotype, neuroimaging variables, and cognition revealed no consensus on the directionality of findings. Methodological choices, including analytical approaches, sample size, and the influence of other genes, gender, and ethnicity, varied across studies, impacting comparability and generalizability. Recommendations for future research include multimodal and longitudinal imaging, standardisation of pipelines, advanced analytical techniques, and collaborative data pooling.

MQGA: A Quantitative Analysis of Brain Network Hubs Using Multi-Graph Theoretical Indices

Recent advancements in large-scale network studies have shown that connector hubs and provincial hubs are vital for coordinating complex cognitive tasks by facilitating information transfer between and within specialized modules. However, current methods for identifying these hubs often lack standardized measurement criteria, hindering quantitative analysis. This study proposes a novel computational method utilizing multi-graph theoretical index calculations to quantitatively analyze hub attributes in brain networks. Using benchmark network, random simulation network (N = 100), resting fMRI data from the ADHD-200 NYU dataset (HC = 110, ADHD = 146), and the Peking dataset (HC = 120, ADHD = 83), we introduce the Multi-criteria Quantitative Graph Analysis (MQGA) method, which employs betweenness centrality, degree centrality, and participation coefficient to determine the connector (con) hub index and provincial (pro) hub index. The method's accuracy, reliability, and stability were validated through correlation analysis of hub indices and labels, vulnerability tests, and consistency analysis across subjects. Results indicate that as network sparsity increases, the con hub index increases while the pro hub index decreases, with the optimal hub node index at 4% sparsity. Vulnerability tests revealed that removing con nodes had a greater impact on network integrity than removing pro nodes. Both con and pro exhibited stability in consistency analyses, but con was more stable. The stability of hub scores in disease groups was significantly lower than in the healthy control group. High con values were found in the precuneus, postcentral gyrus, and precentral gyrus, whereas high pro values were identified in the precentral gyrus, postcentral gyrus, superior parietal lobule, precuneus, and superior temporal gyrus. This approach enhances the accuracy and sensitivity of hub node identification, facilitating precise comparisons and producing consistent, replicable results, advancing our understanding of brain network hub nodes, their roles in cognitive processes, and their implications for brain disease research.

Modulation of Posterior Default Mode Network Activity During Interoceptive Attention and Relation to Mindfulness

Background

Interoceptive attention to internal sensory signals, such as the breath, is fundamental to mindfulness. However, interoceptive attention can be difficult to study, with many studies relying on subjective and retrospective measures. Response consistency is an established method for evaluating variability of attention on exteroceptive attention tasks, but it has rarely been applied to interoceptive attention tasks.

Methods

In this study, we measured consistency of response times on a breath-monitoring task with simultaneous electroencephalography in individuals across the life span (15-91 years of age, N = 324).

Results

We found that consistency on the breath-monitoring task was positively correlated with attentive performance on an exteroceptive inhibitory control task. Electroencephalography source reconstruction showed that on-task alpha band (8-12 Hz) activity was greater than that measured at rest. Low-consistency/longer breath responses were associated with elevated brain activity compared with high-consistency responses, particularly in posterior default mode network (pDMN) brain regions. pDMN activity was inversely linked with functional connectivity to the frontoparietal network and the cingulo-opercular network on task but not at rest, suggesting a role for these frontal networks in on-task regulation of pDMN activity. pDMN activity within the precuneus region was greater in participants who reported low subjective mindfulness and was adaptively modulated by task difficulty in an independent experiment.

Conclusions

Elevated pDMN alpha activity serves as an objective neural marker for low-consistency responding during interoceptive breath attention, scales with task difficulty, and is associated with low subjective mindfulness.

Resting-state EEG microstates predict mentalizing ability as assessed by the Reading the Mind in the Eyes test

Microstates analysis of electroencephalography (EEG) has gained increasing attention among researchers and clinicians as a valid tool for investigating temporal dynamics of large-scale brain networks with a millisecond time resolution. Although microstates analysis has been widely applied to elucidate the neurophysiological basis of various cognitive functions in both clinical and non-clinical samples, its application in relation to socio-affective processing has been relatively under-researched. Therefore, the main aim of the current study was to investigate the relationship between EEG microstates and mentalizing (i.e., the ability to understand the mental states of others). Eighty-two participants (thirty-six men; mean age: 24.28 ± 7.35 years; mean years of education: 15.82 ± 1.77) underwent a resting-state EEG recording and performed the Reading the Mind in the Eyes Test (RMET). The parameters of the microstates were then calculated using Cartool v. 4.09 software. Our results showed that the occurrence of microstate map C was independently and positively associated with the RMET total score and contributed to the prediction of mentalizing performance, even when controlling for potential confounding variables (i.e., age, sex, education level, tobacco and alcohol use). Since microstate C is involved in self-related processes, our findings may reflect the link between self-awareness of one's own thoughts/feelings and the enhanced ability to recognize the mental states of others at the neurophysiological level. This finding extends the functions traditionally attributed to microstate C, i.e. mind-wandering, self-related thoughts, prosociality, and emotional and interoceptive processing, to include mentalizing ability.

Neuromodulation and meditation: A review and synthesis toward promoting well-being and understanding consciousness and brain

The neuroscience of meditation is providing insight into meditation's beneficial effects on well-being and informing understanding of consciousness. However, further research is needed to explicate mechanisms linking brain activity and meditation. Non-invasive brain stimulation (NIBS) presents a promising approach for causally investigating neural mechanisms of meditation. Prior NIBS-meditation research has predominantly targeted frontal and parietal cortices suggesting that it might be possible to boost the behavioral and neural effects of meditation with NIBS. Moreover, NIBS has revealed distinct neural signatures in long-term meditators. Nonetheless, methodological variations in NIBS-meditation research contributes to challenges for definitive interpretation of previous results. Future NIBS studies should further investigate core substrates of meditation, including specific brain networks and oscillations, and causal neural mechanisms of advanced meditation. Overall, NIBS-meditation research holds promise for enhancing meditation-based interventions in support of well-being and resilience in both non-clinical and clinical populations, and for uncovering the brain-mind mechanisms of meditation and consciousness.

Aging, brain plasticity, and motor learning

Motor skill learning, the process of acquiring new motor skills, is critically important across the lifespan, from early development through adulthood and into older age, as well as in pathological conditions (i.e., rehabilitation). Extensive research has demonstrated that motor skill acquisition in young adults is accompanied by significant neuroplastic changes, including alterations in brain structure (gray and white matter), function (i.e., activity and connectivity), and neurochemistry (i.e., levels of neurotransmitters). In the aging population, motor performance typically declines, characterized by slower and less accurate movements. However, despite these age-related changes, older adults maintain the capacity for skill improvement through training. In this review, we explore the extent to which the aging brain retains the ability to adapt in response to motor learning, specifically whether skill acquisition is accompanied by neural changes. Furthermore, we discuss the associations between inter-individual variability in brain structure and function and the potential for future learning in older adults. Finally, we consider the use of non-invasive brain stimulation techniques aimed at optimizing motor learning in this population. Our review provides insights into the neurobiological underpinnings of motor learning in older adults and emphasizes strategies to enhance their motor skill acquisition.

Complex emotion processing and early life adversity in the Healthy Brain Network sample

OBJECTIVE

Early life adversity (ELA) has shown to have negative impacts on mental health. One possible mechanism is through alterations in neural emotion processing. We sought to characterize how multiple indices of ELA were related to naturalistic neural socio-emotional processing.

METHOD

In 521 5-15-year-old participants from the Healthy Brain Network Biobank, we identified scenes that elicited activation of the Default Mode Network (DMN), Ventral Attention Network (VAN), Cingulo-Opercular Network (CON) and amygdala, all of which are networks shown to be associated with ELA. We used linear regression to examine associations between activation and ELA: negative parenting, social status, financial insecurity, neighborhood disadvantage, negative experiences, and parent psychopathology.

RESULTS

We found DMN, VAN, CON and amygdala activation during sad/emotional, bonding, action, conflict, sad, or fearful scenes. Greater inconsistent discipline was associated with greater VAN activation during sad or emotional scenes.

CONCLUSION

Findings suggest that the DMN, VAN, CON networks and the amygdala support socio-emotional processing consistent with prior literature. Individuals who experienced inconsistent discipline may have greater sensitivity to parent-child separation signals. Since no other ELA-activation associations were found, it is possible that unpredictability may be more strongly associated with complex neural emotion processing than socio-economic status or negative life events.

Topological organization of the brain network in thyroid-associated ophthalmopathy using graph theoretical analysis

Mounting neuroimaging evidence indicates that patients with thyroid-associated ophthalmopathy (TAO) demonstrate altered brain function and structure. Nonetheless, the alterations in the topological properties of the functional brain connectome in TAO patients are not yet fully understood. This study aimed to investigate the topological organization of the functional brain connectome in TAO patients using graph-theoretic methods. Twenty-five TAO patients (10 males and 15 females) and 25 age-, sex-, and education-matched healthy controls (HCs) (10 males and 15 females) (the TAO and HC data are from the same dataset in previous studies) underwent resting-state MRI scans. Graph-theoretic analysis was used to study the global, nodal, and edge topological properties of the brain's functional connectome. Both the TAO and HC groups exhibited high-efficiency small-world networks in their brain functional networks. However, there were no significant differences in small-world properties (Cp, γ, λ, Lp, and σ) and network efficiency [global and local efficiencies (Eloc)] between the two groups. In addition, the TAO group demonstrated reduced betweenness centrality in the right fusiform and increased nodal Eloc in the right intraparietal sulcus (P < 0.05, Bonferroni-corrected). Furthermore, the TAO group displayed altered functional connections among the default-mode network (DMN), visual network (VN), sensorimotor network (SMN), and cingulo-opercular network (CON). Patients with TAO exhibited abnormal topological organization of the human brain connectome, including decreased betweenness centrality and increased nodal Eloc. Moreover, the TAO group displayed altered functional connections primarily within the DMN, VN, SMN, and CON. These findings provide crucial insights into the neural mechanisms underlying visual loss, abnormal emotion regulation, and cognitive deficits in TAO patients.

The phobic brain: Morphometric features correctly classify individuals with small animal phobia

Specific phobia represents an anxiety disorder category characterized by intense fear generated by specific stimuli. Among specific phobias, small animal phobia (SAP) denotes a particular condition that has been poorly investigated in the neuroscientific literature. Moreover, the few previous studies on this topic have mostly employed univariate analyses, with limited and unbalanced samples, leading to inconsistent results. To overcome these limitations, and to characterize the neural underpinnings of SAP, this study aims to develop a classification model of individuals with SAP based on gray matter features, by using a machine learning method known as the binary support vector machine. Moreover, the contribution of specific structural macro-networks, such as the default mode, the salience, the executive, and the affective networks, in separating phobic subjects from controls was assessed. Thirty-two subjects with SAP and 90 matched healthy controls were tested to this aim. At a whole-brain level, we found a significant predictive model including brain structures related to emotional regulation, cognitive control, and sensory integration, such as the cerebellum, the temporal pole, the frontal cortex, temporal lobes, the amygdala and the thalamus. Instead, when considering macro-networks analysis, we found the Default, the Affective, and partially the Central Executive and the Sensorimotor networks, to significantly outperform the other networks in classifying SAP individuals. In conclusion, this study expands knowledge about the neural basis of SAP, proposing new research directions and potential diagnostic strategies.

Dissociable Default Mode Network Connectivity Patterns Underlie Distinct Symptoms in Psychosis Risk

The Clinical High Risk (CHR) stage of psychosis is characterized by subthreshold symptoms of schizophrenia including negative symptoms, dysphoric mood, and functional deterioration. Hyperconnectivity of the default-mode network (DMN) has been observed in early schizophrenia, but the extent to which hyperconnectivity is present in CHR, and the extent to which such hyperconnectivity may underlie transdiagnostic symptoms, is not clear. As part of the Shanghai At-Risk for Psychosis (SHARP) program, resting-state fMRI data were collected from 251 young adults (158 CHR and 93 controls, M = 18.72, SD = 4.68, 129 male). We examined functional connectivity of the DMN by performing a whole-brain seed-to-voxel analysis with the MPFC as the seed. Symptom severity across a number of dimensions, including negative symptoms, positive symptoms, and affective symptoms were assessed. Compared to controls, CHRs exhibited significantly greater functional connectivity (p < 0.001 uncorrected) between the MPFC and 1) other DMN nodes including the posterior cingulate cortex (PCC), and 2) auditory cortices (superior and middle temporal gyri, STG/MTG). Furthermore, these two patterns of hyperconnectivity were differentially associated with distinct symptom clusters. Within CHR, MPFC-PCC connectivity was significantly correlated with anxiety (r= 0.23, p=0.006), while MPFC-STG/MTG connectivity was significantly correlated with negative symptom severity (r=0.26, p=0.001). Secondary analyses using item-level symptom scores confirmed a similar dissociation. These results demonstrate that two dissociable patterns of DMN hyperconnectivity found in the CHR stage may underlie distinct dimensions of symptomatology.

Default at fault? Exploring neural correlates of default mode network in children with ADHD, their unaffected siblings versus neurotypical controls: A quantitative EEG study

BACKGROUND

Sustained activation of default mode network has been implicated for momentary lapses of attention and higher errors during performance of cognitive tasks in attention deficit hyperactive disorder (ADHD) children. Despite emerging evidence indicating the genetic basis of ADHD, there is paucity of literature investigating the alteration of DMN in children with ADHD and their unaffected siblings.

AIM

To study the cortical sources of DMN in children with ADHD compared to their siblings and neurotypical controls.

METHODS

Eighty-six participants (35 ADHD (12.4(±2.7) years), 16 unaffected siblings (11.8(±4.3) years) and 35 matched neurotypical controls (12.6 (±3.6) years) participated in the study. 128 channel EEG data was acquired during rest and Stroop cognitive task and analyzed for cortical source estimation using LORETA software.

RESULTS

Higher activation of DMN and DMN associated areas were observed during encoding of the color-word stimuli in children with ADHD. Sustained activation of core DMN areas namely medial frontal gyrus, posterior cingulate gyrus, parahippocampal gyrus and inferior parietal lobule was observed across all groups. Among the three groups, distinct cortical source activation differences were identified solely in the DMN and its associated areas among children with ADHD during the task encoding phase compared to baseline. In contrast, both siblings and neurotypical controls displayed activation in fronto-parieto-temporal areas subserving executive function were also observed.

CONCLUSION

Sustained activity of DMN areas with minimal activity in executive network in ADHD children and unaffected siblings during encoding of stimulus implies potential endophenotypic marker in children with ADHD compared to neurotypical controls.

Daily high-frequency transcranial random noise stimulation (hf-tRNS) for sleep disturbances and cognitive dysfunction in patients with mild vascular cognitive impairments: A study protocol for a pilot randomized controlled trial

BACKGROUND

Poor sleep quality is increasingly considered to be an underlying cause of cerebrovascular diseases. This is a slowly progressing condition that gradually leads to vascular cognitive impairment and stroke during ageing. At present, randomized clinical trials examining the non-pharmacological therapies in the management of this comorbidity are very limited. Transcranial current stimulation (tCS) is a non-invasive technology for promoting cognitive function and treating brain disorders. As advanced modalities of tCS, transcranial random noise stimulation (tRNS) and transcranial alternating current stimulation (tACS), could deliver frequency-specific waveforms of currents that can modulate brain activities in a more specific manner.

METHODS AND DESIGN

Chinese individuals between the ages of 60 and 90 years, who are right-handed and have mild vascular cognitive impairment (VCI) with sleep disturbances, will participate in a randomized study. They will undergo a 2-week intervention period where they will be randomly assigned to one of three groups: high-frequency (hf)-tRNS, 40 Hz tACS, or sham tCS. Each group will consist of 15 participants. Before the intervention, high-resolution magnetic resonance imaging (MRI) data will be used to create a computational head model for each participant. This will help identify the treatment target of left inferior parietal lobe (IPL). Throughout the study, comprehensive assessments will be conducted at multiple time points, including baseline, 2nd week, 6th week, and 12th week. These assessments will evaluate various factors such as sleep quality, domain-specific cognitive performance, and actigraphic records. In addition, the participants' adherence to the program and any potential adverse effects will be closely monitored throughout the duration of the intervention.

CONCLUSIONS

The primary objective of this study is to examine the safety, feasibility, and effectiveness of hf-tRNS and 40 Hz tACS interventions targeting left IPL in individuals with mild vascular cognitive impairment (VCI) who experience sleep disturbances and cognitive dysfunction. Additionally, the study seeks to evaluate the program's adherence, tolerability, and any potential adverse effects associated with frequency-specific transcranial current stimulation (tCS). The findings from this research will contribute to a deeper understanding of the intricate relationship between oscillation, sleep, and cognition. Furthermore, the results will provide valuable insights to guide future investigations in the field of sleep medicine and neurodegenerative diseases.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT06169254.

Exploring the impact of biological sex on intrinsic connectivity networks in PTSD: A data-driven approach

INTRODUCTION

Sex as a biological variable (SABV) may help to account for the differential development and expression of post-traumatic stress disorder (PTSD) symptoms among trauma-exposed males and females. Here, we investigate the impact of SABV on PTSD-related neural alterations in resting-state functional connectivity (rsFC) within three core intrinsic connectivity networks (ICNs): the salience network (SN), central executive network (CEN), and default mode network (DMN).

METHODS

Using an independent component analysis (ICA), we compared rsFC of the SN, CEN, and DMN between males and females, with and without PTSD (n = 47 females with PTSD, n = 34 males with PTSD, n = 36 healthy control females, n = 20 healthy control males) via full factorial ANCOVAs. Additionally, linear regression analyses were conducted with clinical variables (i.e., PTSD and depression symptoms, childhood trauma scores) in order to determine intrinsic network connectivity characteristics specific to SABV. Furthermore, we utilized machine learning classification models to predict the biological sex and PTSD diagnosis of individual participants based on intrinsic network activity patterns.

RESULTS

Our findings revealed differential network connectivity patterns based on SABV and PTSD diagnosis. Males with PTSD exhibited increased intra-SN (i.e., SN-anterior insula) rsFC and increased DMN-right superior parietal lobule/precuneus/superior occipital gyrus rsFC as compared to females with PTSD. There were also differential network connectivity patterns for comparisons between the PTSD and healthy control groups for males and females, separately. We did not observe significant correlations between clinical measures of interest and brain region clusters which displayed significant between group differences as a function of biological sex, thus further reinforcing that SABV analyses are likely not confounded by these variables. Furthermore, machine learning classification models accurately predicted biological sex and PTSD diagnosis among novel/unseen participants based on ICN activation patterns.

CONCLUSION

This study reveals groundbreaking insights surrounding the impact of SABV on PTSD-related ICN alterations using data-driven methods. Our discoveries contribute to further defining neurobiological markers of PTSD among females and males and may offer guidance for differential sex-related treatment needs.

Deciphering the neural responses to a naturalistic persuasive message

Effective health promotion may benefit from understanding how persuasion emerges. While earlier research has identified brain regions implicated in persuasion, these studies often relied on event-related analyses and frequently simplified persuasive communications. The present study investigates the neural basis of valuation change induced by a persuasive healthy eating call, employing naturalistic stimuli. Fifty healthy participants performed two blocks of a bidding task, in which they had to bid on sugar-containing, sugar-free, and nonedible products during functional MRI. In between the two blocks, they listened to a persuasive healthy eating call that influenced their bidding behavior. Intriguingly, participants who resisted persuasion exhibited increased synchronization of brain activity during listening in several regions, including default mode network structures. Additionally, intersubject functional connectivity among these brain regions was found to be weaker in persuaded individuals. These results emphasize the individualized nature of processing persuasive messages, challenging conventional interpretations of synchronized neural activity. Our findings support the emerging practice of tailoring persuasive messages in health promotion campaigns.

Developmental dynamics of brain network modularity and temporal co-occurrence diversity in childhood

OBJECTIVE

Brain development during childhood involves significant structural, functional, and connectivity changes, reflecting the interplay between modularity, information interaction, and functional segregation. This study aims to understand the dynamic properties of brain connectivity and their impact on cognitive development, focusing on temporal co-occurrence diversity patterns.

METHODS

We recruited 481 children aged 6 to 12 years from the Healthy Brain Network database. Functional MRI data were used to construct dynamic functional connectivity matrices with a sliding window approach. Modular structures were identified using multilayer network community detection, and the Dagum Gini coefficient decomposition technique, which uniquely allows for multi-faceted exploration of modular temporal co-occurrence diversities, quantified these diversities. Mediation analysis assessed the impact on small-world properties.

RESULTS

Temporal co-occurrence diversity in brain networks increased with age, especially in the default mode, frontoparietal, and salience networks. These changes were driven by disparities within and between communities. The small-world coefficient increased with age, indicating improved information processing efficiency. To validate the impact of changes in spatiotemporal interaction disparities during childhood on information transmission within brain networks, we used mediation analysis to verify its effect on alterations in small-world properties.

CONCLUSION

This study highlights the critical developmental changes in brain modularity and spatiotemporal interaction patterns during childhood, emphasizing their role in cognitive maturation. These insights into neural mechanisms can inform the diagnosis and intervention of developmental disorders.

EEG oscillations in recent suicide attempters: Assessing responses to positive and negative future imagination tasks

BACKGROUND

Our goal is to uncover Electroencephalography (EEG) power spectrum patterns during imagination tasks in individuals who attempted suicide within the past 1-4 weeks, addressing gaps in understanding the neural correlates of future imagination in suicidal behavior.

METHODS

This case-control study comprised a total of 60 participants, consisting of 47 females and 13 males. The sample comprised three groups: Attempted Suicide + Major Depressive Disorder (SA+MDD), Major Depressive Disorder (MDD), and Healthy Controls (HC). To assess participants' future imagination, a unique approach called the Positive and Negative Future Imagination Task was designed, which involved scenario visualization concurrent with EEG recording. Statistical analyses included ANOVA with post-hoc pairwise comparisons to compare EEG power spectrum between three groups.

RESULTS

It was observed that the SA+MDD group experienced significantly increased theta frequency band in the right frontocentral regions when compared to the MDD group during both positive and negative imagination tasks (P-value < 0.05). Furthermore, increased gamma activity was observed in the SA+MDD group compared to the HC group, predominantly in the right frontocentral areas during both imagination tasks.

CONCLUSION

The results of this study indicate that individuals who have recently attempted suicide exhibit heightened neural activity in the frontocentral regions of the right hemisphere of the brain, specifically in theta and gamma band frequencies, when contemplating both positive and negative aspects of the future. These findings, in the context of behavioral tasks may indicate a decrease in the ability to envision a positive future and an increase in visualizing a negative future.

Adhesion G protein-coupled receptor ADGRG1 promotes protective microglial response in Alzheimer's disease

Germline genetic architecture of Alzheimer's disease (AD) indicates microglial mechanisms of disease susceptibility and outcomes. However, the mechanisms that enable microglia to mediate protective responses to AD pathology remain elusive. Adgrg1 is specifically expressed in yolk-sac-derived microglia. This study reveals the role of yolk-sac-derived microglia in AD pathology, highlighting the function of ADGRG1 in modulating microglial protective responses to amyloid deposition. Utilizing both constitutive and inducible microglial Adgrg1 knockout 5xFAD models, we demonstrate that Adgrg1 deficiency leads to increased amyloid deposition, exacerbated neuropathology, and accelerated cognitive impairment. Transcriptomic analyses reveal a distinct microglial state characterized by downregulated genes associated with homeostasis, phagocytosis, and lysosomal functions. Functional assays in mouse models and human embryonic stem cells-derived microglia support that microglial ADGRG1 is required for efficient Aβ phagocytosis. Together, these results uncover a GPCR-dependent microglial response to Aβ, pointing towards potential therapeutic strategies to alleviate disease progression by enhancing microglial functional competence.

Aging-dependent loss of functional connectivity in a mouse model of Alzheimer's disease and reversal by mGluR5 modulator

Amyloid accumulation in Alzheimer's disease (AD) is associated with synaptic damage and altered connectivity in brain networks. While measures of amyloid accumulation and biochemical changes in mouse models have utility for translational studies of certain therapeutics, preclinical analysis of altered brain connectivity using clinically relevant fMRI measures has not been well developed for agents intended to improve neural networks. Here, we conduct a longitudinal study in a double knock-in mouse model for AD (AppNL-G-F/hMapt), monitoring brain connectivity by means of resting-state fMRI. While the 4-month-old AD mice are indistinguishable from wild-type controls (WT), decreased connectivity in the default-mode network is significant for the AD mice relative to WT mice by 6 months of age and is pronounced by 9 months of age. In a second cohort of 20-month-old mice with persistent functional connectivity deficits for AD relative to WT, we assess the impact of two-months of oral treatment with a silent allosteric modulator of mGluR5 (BMS-984923/ALX001) known to rescue synaptic density. Functional connectivity deficits in the aged AD mice are reversed by the mGluR5-directed treatment. The longitudinal application of fMRI has enabled us to define the preclinical time trajectory of AD-related changes in functional connectivity, and to demonstrate a translatable metric for monitoring disease emergence, progression, and response to synapse-rescuing treatment.

Altered dynamic large-scale brain networks and combined machine learning in primary angle-closure glaucoma

Primary angle-closure glaucoma (PACG) is a severe and irreversible blinding eye disease characterized by progressive retinal ganglion cell death. However, prior research has predominantly focused on static brain activity changes, neglecting the exploration of how PACG impacts the dynamic characteristics of functional brain networks. This study enrolled forty-four patients diagnosed with PACG and forty-four age, gender, and education level-matched healthy controls (HCs). The study employed Independent Component Analysis (ICA) techniques to extract resting-state networks (RSNs) from resting-state functional magnetic resonance imaging (rs-fMRI) data. Subsequently, the RSNs was utilized as the basis for examining and comparing the functional connectivity variations within and between the two groups of resting-state networks. To further explore, a combination of sliding time window and k-means cluster analyses identified seven stable and repetitive dynamic functional network connectivity (dFNC) states. This approach facilitated the comparison of dynamic functional network connectivity and temporal metrics between PACG patients and HCs for each state. Subsequently, a support vector machine (SVM) model leveraging functional connectivity (FC) and FNC was applied to differentiate PACG patients from HCs. Our study underscores the presence of modified functional connectivity within large-scale brain networks and abnormalities in dynamic temporal metrics among PACG patients. By elucidating the impact of changes in large-scale brain networks on disease evolution, researchers may enhance the development of targeted therapies and interventions to preserve vision and cognitive function in PACG.

Multi-omics insights into the microbiota-gut-brain axis and cognitive improvement post-bariatric surgery

BACKGROUND

Although numerous studies have shown that bariatric surgery results in sustained weight loss and modifications in gut microbiota composition and cognitive function, the exact underlying mechanisms are unclear. This study aimed to investigate the effects of bariatric surgery on cognitive function through the microbiota-gut-brain axis (MGBA).

METHODS

Demographic data, serum samples, fecal samples, cognitive assessment scales, and resting-state functional connectivity magnetic resonance imaging (rs-fMRI) scans were obtained from 39 obese patients before and after (6 months) laparoscopic sleeve gastrectomy (LSG). PCA analysis, OPLS-DA analysis, and permutation tests were used to conduct fecal 16 S microbiota profiling, serum metabolomics, and neuroimaging analyses, and a bariatric surgery-specific rs-fMRI brain functional connectivity network was constructed. Spearman correlation analysis and Co-inertia analysis were employed to correlate significant alterations in cognitive assessment scales and resting-state functional connectivity difference networks with differential serum metabolites and 16 S microbiota data to identify key gut microbiota and serum metabolic factors.

RESULTS

LSG significantly reduced the weight of obese patients, with reductions of up to 28%. Furthermore, cognitive assessment scale measurements revealed that LSG enhanced cognitive functions, including memory (HVLT, p = 0.000) and executive function (SCWT, p = 0.008). Also, LSG significantly altered gut microbiota composition (p = 0.001), with increased microbial abundance and diversity (p < 0.05). Moreover, serum metabolite levels were significantly altered, revealing intergroup differences in 229 metabolites mapped to 72 metabolic pathways (p < 0.05, VIP > 1). Spearman correlation analysis among cognitive assessment scales, gut microbiota species, and serum metabolites revealed correlations with 68 gut microbiota species and 138 serum metabolites (p < 0.05). Furthermore, pairwise correlations were detected between gut microbiota and serum metabolites (p < 0.05). Functional neuroimaging analysis revealed that LSG increased functional connectivity in cognitive-related frontotemporal networks (FPN, p < 0.01). Additionally, normalization of the default mode network (DMN) and salience network (SN) connectivity was observed after LSG (p < 0.001). Further canonical correlation and correlation analysis suggested that the cognitive-related brain network changes induced by LSG were associated with key gut microbiota species (Akkermansia, Blautia, Collinsella, Phascolarctobacterium, and Ruminococcus, p < 0.05) and neuroactive metabolites (Glycine, L-Serine, DL-Dopa, SM (d18:1/24:1(15Z), p < 0.05).

CONCLUSION

These findings indicate the pathophysiological role of the microbiota-gut-brain axis in enhancing cognitive function after bariatric surgery, and the study provides a basis for clinical dietary adjustments, probiotic supplementation, and guidance for bariatric surgery, but further research is still needed.

TRIAL REGISTRATION

Chinese Clinical Trial Registry, ChiCTR2100049403. Registered 02 August 2021, https://www.chictr.org.cn/ .

White matter engagement in brain networks assessed by integration of functional and structural connectivity

Current models of brain networks may potentially be improved by integrating our knowledge of structural connections, within and between circuits, with metrics of functional interactions between network nodes. The former may be obtained from diffusion MRI of white matter (WM), while the latter may be derived by measuring correlations between resting state BOLD signals from pairs of gray matter (GM) regions. From inspection of diffusion MRI data, it is clear that each WM voxel within a 3D image array may be traversed by multiple WM structural tracts, each of which connects a pair of GM nodes. We hypothesized that by appropriately weighting and then integrating the functional connectivity of each such connected pair, the overall engagement of any WM voxel in brain functions could be evaluated. This model introduces a structural constraint to earlier studies of WM engagement and addresses some limitations of previous efforts to relate structure and function. Using concepts derived from graph theory, we obtained spatial maps of WM engagement which highlight WM regions critical for efficient communications across the brain. The distributions of WM engagement are highly reproducible across subjects and depict a notable interdependence between the distribution of GM activities and the detailed organization of WM. Additionally, we provide evidence that the engagement varies over time and shows significant differences between genders. These findings suggest the potential of WM engagement as a measure of the integrity of normal brain functions and as a biomarker for neurological and cognitive disorders.

Neural, genetic, and cognitive signatures of creativity

Creativity is typically operationalized as divergent thinking (DT) ability, a form of higher-order cognition which relies on memory, attention, and other component processes. Despite recent advances, creativity neuroscience lacks a unified framework to model its complexity across neural, genetic, and cognitive scales. Using task-based fMRI from two independent samples and MVPA, we identified a neural pattern that predicts DT, validated through cognitive decoding, genetic data, and large-scale resting-state fMRI. Our findings reveal that DT neural patterns span brain regions associated with diverse cognitive functions, with positive weights in the default mode and frontoparietal control networks and negative weights in the visual network. The high correlation with the primary gradient of functional connectivity suggests that DT involves extensive integration from concrete sensory information to abstract, higher-level cognition, distinguishing it from other advanced cognitive functions. Moreover, neurobiological analyses show that the DT pattern is positively correlated with dopamine-related neurotransmitters and genes influencing neurotransmitter release, advancing the neurobiological understanding of creativity.

Investigate Effects of Music Therapy on Functional Connectivity in Papez Circuit of Breast Cancer Patients Using fMRI

The aim of this study is to investigate activity and functional connectivity (FC) of Papez circuit networks associated with music processing using functional magnetic resonance imaging (fMRI) in depressed breast cancer patients. Twenty-three breast cancer patients listened to four different Iranian/Persian music paradigms during the resting-state fMRI scanning session: negative stimulation of traditional music, negative stimulation of pop music, positive stimulation of traditional music and positive stimulation of pop music. The amplitude of low-frequency fluctuation (ALFF) was used to evaluate the local characteristics of spontaneous brain activity. FC maps were created using multivariate ROI-to-ROI connectivity (mRRC) and Papez circuit-based regions of interest (ROIs) selection. We found that music increases FC within various brain networks which are involved in memory, emotion, and cognitive function, including the limbic system, the default mode network (DMN), salience network (SN), and central executive network (CEN). Moreover, it seems that the traditional types (both positive and negative) of Iranian music may be more effective to affect brain activity in the patients with breast cancer, than the Iranian pop music. These findings demonstrate that music therapy, as an effective and easily applicable approach, supports the neuropsychological recovery and can contribute to standard treatment protocols in patients with breast cancer.

Modulation of neural oscillations in escitalopram treatment: a Canadian biomarker integration network in depression study

Current pharmacological agents for depression have limited efficacy in achieving remission. Developing and validating new medications is challenging due to limited biological targets. This study aimed to link electrophysiological data and symptom improvement to better understand mechanisms underlying treatment response. Longitudinal changes in neural oscillations were assessed using resting-state electroencephalography (EEG) data from two Canadian Biomarker Integration Network in Depression studies, involving pharmacological and cognitive behavioral therapy (CBT) trials. Patients in the pharmacological trial received eight weeks of escitalopram, with treatment response defined as ≥ 50% decrease in Montgomery-Åsberg Depression Rating Scale (MADRS). Early (baseline to week 2) and late (baseline to week 8) changes in neural oscillation were investigated using relative power spectral measures. An association was found between an initial increase in theta and symptom improvement after 2 weeks. Additionally, late increases in delta and theta, along with a decrease in alpha, were linked to a reduction in MADRS after 8 weeks. These late changes were specifically observed in responders. To assess specificity, we extended our analysis to the independent CBT cohort. Responders exhibited an increase in delta and a decrease in alpha after 2 weeks. Furthermore, a late (baseline to week 16) decrease in alpha was associated with symptom improvement following CBT. Results suggest a common late decrease in alpha across both treatments, while modulatory effects in theta may be specific to escitalopram treatment. This study offers insights into electrophysiological markers indicating a favorable response to antidepressants, enhancing our comprehension of treatment response mechanisms in depression.

Processing of social closeness in the human brain

Healthy social life requires relationships in different levels of personal closeness. Based on ethological, sociological, and psychological evidence, social networks have been divided into five layers, gradually increasing in size and decreasing in personal closeness. Is this division also reflected in brain processing of social networks? During functional MRI, 21 participants compared their personal closeness to different individuals. We examined the brain volume showing differential activation for varying layers of closeness and found that a disproportionately large portion of this volume (80%) exhibited preference for individuals closest to participants, while separate brain regions showed preference for all other layers. Moreover, this bipartition reflected cortical preference for different sizes of physical spaces, as well as distinct subsystems of the default mode network. Our results support a division of the neurocognitive processing of social networks into two patterns depending on personal closeness, reflecting the unique role intimately close individuals play in our social lives.

Mapping the mentalizing brain: An ALE meta-analysis to differentiate the representation of social scenes and ages on theory of mind

Theory of mind (ToM) involves understanding others' mental states and relies on brain regions like the temporoparietal junction (TPJ) and medial prefrontal cortex (mPFC). This meta-analytic review categorizes ToM studies into six sub-components across three pairs: (1) Theory of collective mind (ToCM) and individualized theory of mind (iToM), (2) Social intention ToM and private intention ToM, and (3) ToM in adults and ToM in children. We conducted coordinate-based activation likelihood estimation (ALE) analyses and meta-analytic connectivity modeling (MACM) for each sub-component. We found that the ToM components utilized in social or group situations were associated with both the dorsomedial PFC (dmPFC) and right superior temporal sulcus (STS), whereas the ToM components focused on personal concentration were associated with both the lateral PFC and the left STS. The coactivation patterns for the group and age sub-component pairs showed significant spatial overlap with the language networks. These findings indicate that ToM is a multidimensional construct that is related to distinct functional networks for processing each of the ToM sub-components.

Alterations in orbitofrontal cortex communication relate to suicidal attempts in patients with major depressive disorder

BACKGROUND

Investigating how the interaction between the orbitofrontal cortex (OFC) and various brain regions/functional networks in major depressive disorder (MDD) patients with a history of suicide attempt (SA) holds importance for understanding the neurobiology of this population.

METHODS

We employed resting-state functional magnetic resonance imaging (rs-fMRI) to analyze the OFC's functional segregation in 586 healthy individuals. A network analysis framework was then applied to rs-fMRI data from 86 MDD-SA patients and 85 MDD-Control patients, utilizing seed mappings of OFC subregions and a multi-connectivity-indicator strategy involving cross-correlation, total interdependencies, Granger causality, and machine learning.

RESULTS

Four functional subregions of left and right OFC, were designated as seed regions of interest. Relative to the MDD-Control group, the MDD-SA group exhibited enhanced functional connectivity (FC) and attenuated interaction between the OFC and the sensorimotor network, imbalanced communication between the OFC and the default mode network, enhanced FC and interaction between the OFC and the ventral attention network, enhanced interaction between the OFC and the salience network, and attenuated FC between the OFC and the frontoparietal network.

LIMITATIONS

The medication and treatment condition of patients with MDD was not controlled, so the medication effect on the alteration model cannot be affirmed.

CONCLUSION

The findings suggest an imbalanced interaction pattern between the OFC subregions and a set of cognition- and emotion-related functional networks/regions in the MDD-SA group.

Altered Functional Coupling of the Bed Nucleus of the Stria Terminalis and Amygdala in Spider Phobic Fear

Background: Individuals with spider phobic (SP) fear show hypervigilance and amygdala hyperactivity toward fear-associated stimuli, which may promote the development of other anxiety disorders. The amygdala is a key region within the fear network, which is connected to the anxiety system, where the bed nucleus of the stria terminalis (BNST) plays a crucial role. However, the BNST's involvement in phobic fear is unknown. Therefore, this study investigated the association of phobic fear and anxiety on these regions' functional connectivity (FC) in SP compared to healthy controls (HC). Methods: 7T-functional MRI resting-state FC of 30 individuals with SP and 45 HC was assessed to detect network differences between these groups. The association of phobic fear severity, trait anxiety, and social anxiety on FC was explored using linear regressions combined with seed-to-voxel analyses with amygdala and BNST as primary seeds, corrected for age and sex. Results: In SP, phobic fear was associated with reduced FC between the left amygdala and the right supramarginal gyrus. In contrast, anxiety severity was related to increased FC between the right BNST and the left inferior frontal gyrus. Moreover, social anxiety was related to decreased FC between bilateral BNST and left precuneus. Conclusions: These findings show changes in FC in SP, connecting fear with altered activity in the BNST and amygdala. The results suggest that persistent anxiety in phobic fear is associated with abnormal brain function in these regions, potentially explaining susceptibility to anxiety disorders and processes involved in phobic fear, such as threat perception, avoidance, and salience. Impact statement This is the first study to report altered FC mechanisms of BNST and amygdala in individuals with SP using 7T ultra-high field resting-state data. So far, only distinct characterization of brain regions, especially of BNST and amygdala, involved in those disorders exists. Our results contribute to closing this knowledge gap by providing the first evidence that deviant BNST and amygdala function in SP might elucidate the susceptibility to other anxiety disorders.

Compensation versus deterioration across functional networks in amnestic mild cognitive impairment subtypes

Functional connectivity studies to detect neurophysiological correlates of amnestic mild cognitive impairment (aMCI), a prodromal stage of Alzheimer's disease, have generated contradictory results in terms of compensation and deterioration, as most of the studies did not distinguish between the different aMCI subtypes: single-domain aMCI (sd-aMCI) and multiple-domain aMCI (md-aMCI). The present study aimed to characterize the neurophysiological correlates of aMCI subtypes by using resting-state functional magnetic resonance imaging. The study included sd-aMCI (n = 29), md-aMCI (n = 26), and control (n = 30) participants. The data were subjected to independent component analysis (ICA) to explore the default mode network (DMN) and the fronto-parietal control network (FPCN). Additionally, seed-based and moderation analyses were conducted to investigate the connectivity of the medial temporal lobe and functional networks. aMCI subtypes presented differences in functional connectivity relative to the control group: sd-aMCI participants displayed increased FPCN connectivity and reduced connectivity between the posterior parahippocampal gyrus (PHG) and medial structures; md-aMCI participants exhibited lower FPCN connectivity, higher anterior PHG connectivity with frontal structures and lower posterior PHG connectivity with central-parietal and temporo-occipital areas. Additionally, md-aMCI participants showed higher posterior PHG connectivity with structures of the DMN than both control and sd-aMCI participants, potentially indicating more severe cognitive deficits. The results showed gradual and qualitative neurofunctional differences between the aMCI subgroups, suggesting the existence of compensatory (sd-aMCI) and deterioration (md-aMCI) mechanisms in functional networks, mainly originated in the DMN. The findings support consideration of the subgroups as different stages of MCI within the Alzheimer disease continuum.

Salience network segregation mediates the effect of tau pathology on mild behavioral impairment

INTRODUCTION

A recently developed mild behavioral impairment (MBI) diagnostic framework standardizes the early characterization of neuropsychiatric symptoms in older adults. However, the joint contributions of Alzheimer's disease (AD) pathology and brain function to MBI remain unclear.

METHODS

We test a novel model assessing direct relationships between AD biomarker status and MBI symptoms, as well as mediated effects through segregation of the salience and default-mode networks, using data from 128 participants with diagnosis of amnestic mild cognitive impairment or mild dementia-AD type.

RESULTS

We identified a mediated effect of tau positivity on MBI through functional segregation of the salience network from the other high-level, association networks. There were no direct effects of AD biomarkers status on MBI.

DISCUSSION

Our findings suggest that tau pathology contributes to MBI primarily by disrupting salience network function and emphasize the role of the salience network in mediating relationships between neuropathological changes and behavioral manifestations.

HIGHLIGHTS

Network segregation mediates Alzheimer's disease (AD) pathology impact on mild behavioral impairment (MBI). The salience network is pivotal in linking tau pathology and MBI. This study used path analysis with AD biomarkers and network integrity. The study evaluated the roles of salience, default mode, and frontoparietal networks. This is the first study to integrate MBI with AD biomarkers and network functionality.

Default mode network electrophysiological dynamics and causal role in creative thinking

The default mode network (DMN) is a widely distributed, intrinsic brain network thought to play a crucial role in internally directed cognition. The present study employs stereo-EEG in 13 human patients, obtaining high resolution neural recordings across multiple canonical DMN regions during two processes that have been associated with creative thinking: spontaneous and divergent thought. We probe these two DMN-associated higher cognitive functions through mind wandering and alternate uses tasks, respectively. Our results reveal DMN recruitment during both tasks, as well as a task-specific dissociation in spatiotemporal response dynamics. When compared to the fronto-parietal network, DMN activity was characterized by a stronger increase in gamma band power (30-70 Hz) coupled with lower theta band power (4-8 Hz). The difference in activity between the two networks was especially strong during the mind wandering task. Within the DMN, we found that the tasks showed different dynamics, with the alternate uses task engaging the DMN more during the initial stage of the task, and mind wandering in the later stage. Gamma power changes were mainly driven by lateral DMN sites, while theta power displayed task-specific effects. During alternate uses task, theta changes did not show spatial differences within the DMN, while mind wandering was associated to an early lateral and late dorsomedial DMN engagement. Furthermore, causal manipulations of DMN regions using direct cortical stimulation preferentially decreased the originality of responses in the alternative uses task, without affecting fluency or mind wandering. Our results suggest that DMN activity is flexibly modulated as a function of specific cognitive processes and supports its causal role in divergent thinking. These findings shed light on the neural constructs supporting different forms of cognition and provide causal evidence for the role of DMN in the generation of original connections among concepts.

Intrinsic functional networks for distinct sources of error in visual working memory

Visual working memory (VWM) is a core cognitive function wherein visual information is stored and manipulated over short periods. Response errors in VWM tasks arise from the imprecise memory of target items, swaps between targets and nontargets, and random guesses. However, it remains unclear whether these types of errors are underpinned by distinct neural networks. To answer this question, we recruited 80 healthy adults to perform delayed estimation tasks and acquired their resting-state functional magnetic resonance imaging scans. The tasks required participants to reproduce the memorized visual feature along continuous scales, which, combined with mixture distribution modeling, allowed us to estimate the measures of memory precision, swap errors, and random guesses. Intrinsic functional connectivity within and between different networks, identified using a hierarchical clustering approach, was estimated for each participant. Our analyses revealed that higher memory precision was associated with increased connectivity within a frontal-opercular network, as well as between the dorsal attention network and an angular-gyrus-cerebellar network. We also found that coupling between the frontoparietal control network and the cingulo-opercular network contributes to both memory precision and random guesses. Our findings demonstrate that distinct sources of variability in VWM performance are underpinned by different yet partially overlapping intrinsic functional networks.

Brain structural differences in cocaine use disorder: Insights from multivariate and neurotransmitter analyses

Cocaine use disorder (CUD) is a chronic and relapsing neuropsychiatric disorder characterized by structural and functional brain lesions, posing a significant public health challenge. While the disruptive effects of cocaine on neurotransmitter systems (receptors/transporters) have been well established, the patterns of brain structural abnormalities in CUD and its interaction with other factors remain an ongoing topic of investigation. We employed source-based morphometry (SBM), a multivariate approach on 50 CUD participants and 50 matched healthy controls from the public SUDMEX CONN dataset. This method allowed us to identify co-varying patterns of brain tissue volume differences, and further explore the effect of average cocaine dosage through moderation analysis. Spatial correlation analysis was also performed to examine micro-macro structural consistency between tissue volume variations and chemoarchitectural distribution of dopamine and serotonin. Our SBM analysis findings were consistent with reward-related neuroadaptations in the striato-thalamo-cortical and limbic pathways and also exhibited co-localization with the distribution of dopamine and serotonin systems. The moderation analysis suggested that the average dosage positively strengthens cocaine consumption years' effect on brain structures. By integrating our findings of gray and white matter volume differences and corresponding neurotransmitter profiles, this comprehensive view not only strengthens our understanding of the brain's structural abnormalities in CUD, but also reveals potential mechanisms underlying its development and progression.

Can weekend catch-up sleep decrease the risk of cognitive dysfunction in older adults?

PURPOSE

This study investigated whether weekend catch-up sleep was related to a decreased risk of cognitive dysfunction in older Taiwanese adults by using self-reported diaries and objective accelerometer measurements.

METHODS

This cross-sectional study enrolled participants who were aged ≥ 65 years and had the capability to walk independently from a medical center in Taipei City, Taiwan, between September 2020 and December 2022. Self-reported sleep diaries and tri-axial accelerometers were used to record and measure sleep-related data for 7 consecutive nights. Weekend catch-up sleep was defined as the mean of weekend sleep time minus the mean of weekdays sleep time. Mini-Mental State Examination (MMSE) was evaluated the risk of cognitive dysfunction. The association between weekend catch-up sleep and the MMSE score was examined using a binary logistic regression model.

RESULTS

A total of 215 older adults (53.0% female; 80.5 ± 7.1 years old; 11.6% at risk of cognitive dysfunction) were included. In the adjusted model (adjusted for sex, education level, moderate-to-vigorous physical activity and total accelerometer wear time), both the self-reported sleep diaries (odds ratio [OR] = 0.26, 95% confidence interval [CI] = 0.09-0.69, P = 0.007) and the accelerometer data (OR = 0.27, 95% CI = 0.10-0.70, P = 0.007) indicated that weekend catch-up sleep could decrease the risk of cognitive dysfunction by 73-74%.

CONCLUSION

The study findings suggest that there is an association between weekend catch-up sleep and lower risk for cognitive decline. The causal relationship between weekend catch-up sleep and cognitive function in older adults should be further investigated in a study with longitudinal design.

Task-based default mode network connectivity predicts cognitive impairment and negative symptoms in first-episode schizophrenia

Individuals diagnosed with schizophrenia (SZ) demonstrate difficulty distinguishing between internally and externally generated stimuli. These aberrations in "source monitoring" have been theorized as contributing to symptoms of the disorder, including hallucinations and delusions. Altered connectivity within the default mode network (DMN) of the brain has been proposed as a mechanism through which discrimination between self-generated and externally generated events is disrupted. Source monitoring abnormalities in SZ have additionally been linked to impairments in selective attention and inhibitory processing, which are reliably observed via the N100 component of the event-related brain potential elicited during an auditory paired-stimulus paradigm. Given overlapping constructs associated with DMN connectivity and N100 in SZ, the present investigation evaluated relationships between these measures of disorder-related dysfunction and sought to clarify the nature of task-based DMN function in SZ. DMN connectivity and N100 measures were assessed using EEG recorded from SZ during their first episode of illness (N = 52) and demographically matched healthy comparison participants (N = 25). SZ demonstrated less evoked theta-band connectivity within DMN following presentation of pairs of identical auditory stimuli than HC. Greater DMN connectivity among SZ was associated with better performance on measures of sustained attention (p = .03) and working memory (p = .09), as well as lower severity of negative symptoms, though it was not predictive of N100 measures. Together, present findings provide EEG evidence of lower task-based connectivity among first-episode SZ, reflecting disruptions of DMN functions that support cognitive processes. Attentional processes captured by N100 appear to be supported by different neural mechanisms.

Linking the neural signature of response time variability to Alzheimer's disease pathology and cognitive functioning

Promising evidence has suggested potential links between mind-wandering and Alzheimer's disease (AD). Yet, older adults with diagnosable neurocognitive disorders show reduced meta-awareness, thus questioning the validity of probe-assessed mind-wandering in older adults. In prior work, we employed response time variability as an objective, albeit indirect, marker of mind-wandering to identify patterns of functional connectivity that predicted mind-wandering. In the current study, we evaluated the association of this connectome-based, mind-wandering model with cerebral spinal fluid (CSF) p-tau/Aβ 42 ratio in 289 older adults from the Alzheimer's Disease NeuroImaging Initiative (ADNI). Moreover, we examined if this model was similarly associated with individual differences in composite measures of global cognition, episodic memory, and executive functioning. Edges from the high response time variability model were significantly associated with CSF p-tau/Aβ ratio. Furthermore, connectivity strength within edges associated with high response time variability was negatively associated with global cognition and episodic memory functioning. This study provides the first empirical support for a link between an objective neuromarker of mind-wandering and AD pathophysiology. Given the observed association between mind-wandering and cognitive functioning in older adults, interventions targeted at reducing mind-wandering, particularly before the onset of AD pathogenesis, may make a significant contribution to the prevention of AD-related cognitive decline.

Cortical hubs of highly superior autobiographical memory

Highly Superior Autobiographical Memory (HSAM) is a rare form of enhanced memory in which individuals demonstrate an extraordinary ability to remember details of their personal lives with high levels of accuracy and vividness. Neuroimaging studies have identified brain regions - specifically, midline areas within the default network - associated with remembering events from one's past. Extending this research on the neural underpinnings of autobiographical memory, the present study utilizes graph theory analyses to compare functional brain connectivity in a cohort of HSAM (n = 12) and control participants (n = 29). We perform seed-based analysis in resting-state fMRI data to assess how specific cortical regions within the autobiographical memory network are differentially connected in HSAM individuals. Additionally, we apply a whole-brain connectivity analysis to identify differences in brain hub-network topology associated with enhanced autobiographical memory. Seed-based results show converging patterns of increased connectivity in HSAM across midline areas. Whole-brain analysis also reveals enhanced connectivity across medial prefrontal and posterior cingulate cortex in HSAM individuals. Together, these results extend prior research, highlighting cortical hubs within the default network associated with enhanced autobiographical memory.

The moderating role of information processing speed in the relationship between brain remodeling and episodic memory in amnestic mild cognitive impairment

INTRODUCTION

The role of information processing speed (IPS) on relationships between episodic memory (EM) and central remodeling features in amnestic mild cognitive impairment (aMCI) was investigated.

METHODS

Neuropsychological evaluations and multimodal magnetic resonance imaging were performed on 48 patients diagnosed with aMCI and 50 healthy controls (HC). Moderation models explored the moderating effect of IPS on associations between EM and imaging features at single-region, connectivity, and network levels.

RESULTS

IPS significantly enhanced the positive correlations between recall and cortical thickness of left inferior temporal gyrus. IPS also notably amplified negative correlations between recognition and functional connectivity (FC) of left inferior parietal lobe and right occipital, as well as between recall/recognition and nodal clustering coefficient of left anterior cingulate cortex.

DISCUSSION

IPS functioned as a moderator of associations between recall and neuroimaging metrics at the "single region-connectivity-network" level, providing new insights for cognitive rehabilitation in aMCI patients.

HIGHLIGHTS

aMCI patients exhibited brain functional and structural remodeling alterations. IPS moderated relations between episodic memory and brain remodeling metrics. Therapy targeted at IPS can be considered for improving episodic memory in aMCI.

Association of a DASH diet and magnetoencephalography in dementia-free adults with different risk levels of Alzheimer's disease

This study explored how adherence to the DASH diet relates to electrophysiological measures in individuals at varying Alzheimer's disease (AD) risk due to family history (FH). There were 179 dementia-free subjects. DASH index was calculated, and participants were classified into different DASH adherence groups. Tertiles of relative alpha power in default mode network (DMN) regions were calculated. Multivariate logistic regression models were used to examine the association. Lower DASH adherence was associated with decreased odds of higher relative alpha power in the DMN, observed across the entire sample and specifically among those without a FH of AD. Logistic regression models indicated that participants with poorer DASH adherence had a reduced likelihood of elevated DMN alpha power, potentially influenced by vascular and amyloid-beta mechanisms. These findings underscore the dietary pattern's potential role in neural activity modulation, particularly in individuals not genetically predisposed to AD.

Functional Connectivity of the Auditory Cortex in Women With Trauma-Related Disorders Who Hear Voices

BACKGROUND

Voice hearing (VH) is a transdiagnostic experience that is common in trauma-related disorders. However, the neural substrates that underlie trauma-related VH remain largely unexplored. While auditory perceptual dysfunction is among the abnormalities implicated in VH in schizophrenia, whether VH in trauma-related disorders also involves auditory perceptual alterations is unknown.

METHODS

We investigated auditory cortex (AC)-related functional connectivity (FC) in 65 women with trauma-related disorders stemming from childhood abuse with varying severities of VH. Using a novel, computationally driven and individual-specific method of functionally parcellating the brain, we calculated the FC of 2 distinct AC subregions-Heschl's gyrus (corresponding to the primary AC) and lateral superior temporal gyrus (in the nonprimary AC)-with both the cerebrum and cerebellum. Then, we measured the association between VH severity and FC using leave-one-out cross-validation in the cerebrum and voxelwise multiple regression analyses in the cerebellum.

RESULTS

We found that VH severity was positively correlated with left lateral superior temporal gyrus-frontoparietal network FC, while it was negatively correlated with FC between the left lateral superior temporal gyrus and both cerebral and cerebellar representations of the default mode network. VH severity was not predicted by FC of the left Heschl's gyrus or right AC subregions.

CONCLUSIONS

Our findings point to altered interactions between auditory perceptual processing and higher-level processes related to self-reference and executive functioning. This is the first study to show alterations in auditory cortical connectivity in trauma-related VH. While VH in trauma-related disorders appears to be mediated by brain networks that are also implicated in VH in schizophrenia, the results suggest a unique mechanism that could distinguish VH in trauma-related disorders.