Functional-anatomic fractionation of the brain's default network

The impact of cognitive bias modification of interpretation on hostile attribution bias, reactive aggression and neural mechanisms

Hostile Attribution Bias (HAB) has been demonstrated to exert adverse impacts on reactive aggression (RA). Consequently, it is essential to investigate its prevention strategies and the brain-level alterations induced by these strategies. Cognitive Bias Modification of Interpretation (CBMI) has exhibited potential in modifying HAB. The current objective of this research is to explore its influence on individuals' hostile attributions bias and reactive aggression, and conduct an exploratory study on the underlying brain change mechanisms associated with behavioral alterations. The college students with high HAB and aggression levels were randomly assigned to a trained group and a control group. The trained group participated in a one-month-long CBM-I program, whereas the control group completed one-month-long reading tasks. The results indicated significant HAB and reactive aggression reductions within the trained group. In the trained group, the resting-state functional connectivity (rs-FC) between the anterior medial prefrontal cortex (amPFC) and the calcarine exhibited a remarkable increase, and this augmentation was positively correlated with the decrease in HAB. In contrast, no significant changes were detected in the control group after training. Our results suggest that the CBM-I has an effect on ameliorating individuals' hostile attributions bias and reactive aggression and has exploratorily uncovered the corresponding changes at the brain level.

Mapping the lung-brain axis: Causal relationships between brain network connectivity and respiratory disorders

BACKGROUND

The mechanistic relationship between respiratory disorders and brain function remains poorly understood, despite growing evidence of cognitive and neurological manifestations in respiratory diseases. We aim to identify whether specific brain network connectivity patterns causally influence respiratory disease susceptibility, while respiratory conditions might reciprocally affect brain network architecture.

METHODS

We performed bidirectional Mendelian randomization (MR) analyses using genome-wide association studies (GWAS) of brain network connectivity from UK Biobank resting-state functional MRI (rs-fMRI) data (N = 31,453) and GWAS data from ten major respiratory conditions: chronic obstructive pulmonary disease (COPD), asthma, idiopathic pulmonary fibrosis (IPF), sleep apnea syndrome (SAS), lung squamous carcinoma (LUSC), lung adenocarcinoma (LUAD), small cell lung carcinoma (SCLC), hospitalized COVID-19, very severe COVID-19, and bronchiectasis. Five MR methods, inverse variance weighted (IVW) with multiplicative random-effect model, weighted median, weighted mode, MR Egger, and MR-robust adjusted profile score (MR-RAPS) were employed to ensure causal inference.

RESULTS

In forward analysis, five respiratory disorders - asthma, IPF, SAS, LUSC, and very severe COVID-19 - showed significant causal associations (p < 1.31 ×10-4) with 11 rs-fMRI phenotypes, spanning multiple brain networks including the central executive, subcortical-cerebellum, motor, limbic, attention, salience, visual, and default mode networks. In reverse analysis, twelve brain functional networks demonstrated genetic associations with eight respiratory conditions (COPD, asthma, IPF, SAS, LUSC, SCLC, hospitalized COVID-19, and very severe COVID-19), predominantly involving attention, salience, default mode, visual, and central executive networks.

CONCLUSIONS

Our study provides preliminary genetic evidence suggesting potential causal relationships between brain network connectivity and respiratory disorders, contributing to our understanding of the lung-brain axis. While the identification of disease-specific network alterations offers promising insights, further clinical validation is needed before these findings can be translated into therapeutic interventions.

Self-referential encoding in the developing brain

Episodic memory is closely linked to the self and information related to the self tends to be better remembered. In adults, the brain's default mode network (DMN) supports self-referential thought and memory, with the medial prefrontal cortex (mPFC) being important for both functions. How the DMN supports self-referential encoding in children, and where in the mPFC the processes of self-referencing and episodic memory interact, is unknown. We investigated the neural development of self-referential encoding in 83 participants ages 7-25. While undergoing MRI, participants viewed objects and answered self-referential or semantic questions. Self-referential compared to semantic encoding resulted in better recollection across all ages. Self-referential encoding was associated with greater activation across the DMN and inferior frontal gyrus (IFG), with age-related increases in the dorsal mPFC and left IFG. Region-of-interest analyses revealed the interaction of self-referential episodic memory in the anterior mPFC and left hippocampus. The dorsal and anterior mPFC showed a counteraction effect of self-related thinking with the previously demonstrated age-related increase in DMN deactivation for subsequent memory encoding. These results suggest that self-referential facilitation matures and interacts with the episodic memory system in the brain to support the development of episodic memory from childhood to adulthood.

Network-targeted transcranial magnetic stimulation (TMS) for mild cognitive impairment (MCI)

BACKGROUND

Transcranial magnetic stimulation (TMS) is a promising non-pharmacological intervention for treatment of mild cognitive impairment (MCI) and early Alzheimer's disease (AD). Yet, we know little about precisely where stimulation would be ideal to improve cognitive function.

OBJECTIVE

To examine the network functional connectivity (fc) characteristics of prefrontal and parietal stimulation sites, given that these sites have led to improved cognitive function in TMS studies involving MCI-AD and unimpaired participants.

METHODS

Resting-state functional MRI data were acquired from 32 MCI participants at the baseline visit of an ongoing TMS trial and used to compute connectivity with prefrontal and parietal stimulation locations, selected on the basis of previous TMS studies. The TMS seed maps were examined for extent of spatial overlap with eight canonical networks. After identifying the network most likely to be targeted by TMS, we applied strategies that may provide purer targeting. Finally, we examined network connectivity in relation to participants' behavioral characteristics because of the potential for TMS treatment to be personalized.

RESULTS

The prefrontal TMS seed map overlapped primarily with the salience network. The prefrontal site is also notable for its anti-correlated connectivity with the AD-vulnerable posterior cingulate cortex (PCC). The parietal TMS seed map showed the expected strong positive connectivity with the PCC and other default network regions. Nonetheless, this particular parietal site may simultaneously modulate the fronto-parietal network. Strategies to improve network targeting and to personalize TMS are reported as secondary findings.

CONCLUSION

These results can be applied to network-targeted brain stimulation for MCI and early AD treatment. Greater precision and personalization of TMS offer the promise of achieving better outcomes for individuals with MCI or mild AD dementia.

Disrupted default mode network connectivity and its role in negative symptoms of schizophrenia

Schizophrenia is a complex mental disorder characterised by positive symptoms, negative symptoms, and cognitive deficits, with recent studies suggesting that disruptions in the default mode network (DMN) may underlie many of these symptoms. In this study, we used graph theory analysis of resting-state functional magnetic resonance imaging data to investigate differences in the topological organisation and functional connectivity of the DMN in patients with schizophrenia, using two independent datasets of patients and healthy controls. The findings revealed significant group differences in the DMN of patients with schizophrenia, particularly within the core-medial temporal lobe (MTL) subsystem, characterised by lower shortest path length, clustering coefficient, and small-worldness, indicating less efficient network organisation. Weaker functional connectivity in the core-MTL subsystem was correlated with higher avolition-apathy scores, highlighting the role of DMN connectivity patterns in negative symptoms. These results, validated across two independent datasets, emphasise the robust and generalisable association between schizophrenia and DMN network features, less efficient topological properties, and weaker functional connectivity. This underscores the importance of targeting DMN connectivity to alleviate negative symptoms, improve clinical outcomes, and potentially serve as a biomarker for monitoring symptom severity and guiding treatment.

Decomposing Cognitive Processes in the mPFC during Self-Thinking

Past cognitive neuroscience research has demonstrated that thinking about both the self and other activates the medial prefrontal cortex (mPFC), a central hub of the default mode network. The mPFC is also implicated in other cognitive processes, such as introspection and autobiographical memory, rendering elusive its exact role during thinking about the self. Specifically, it is unclear whether the same cognitive process explains the common mPFC involvement or distinct processes are responsible for the mPFC activation overlap. In this preregistered functional magnetic resonance imaging study with 35 male and female human participants, we investigated whether and to what extent mPFC activation patterns during self-reference judgment could be explained by activation patterns during the tasks of other-reference judgment, introspection, and autobiographical memory. Multivoxel pattern analysis showed that only in the mPFC were neural responses both concurrently different and similar across tasks. Furthermore, multiple regression and variance partitioning analyses indicated that each task (i.e., other-reference, introspection, and memory) uniquely and jointly explained significant variances in mPFC activation during self-reference. These findings suggest that the self-reference task engages multiple cognitive processes shared with other tasks, with the mPFC serving as a crucial hub where essential information is integrated to support judgments based on internally constructed representations.

Type-1 Diabetes Impacts Brain Microstructure and Anatomical Associations in Young and Well-Controlled Individuals

Type 1 Diabetes Mellitus (T1DM) progression has a direct impact on brain microstructural integrity and typical functional organization from the early stages of neurodevelopment. Diffusion Tensor Imaging (DTI) is a neuroimaging method that has proven sensitive to changes in white matter microstructure. Using diffusion-weighted probabilistic tractography methods, we aim to evaluate the white matter integrity and anatomical relationships within the Default Mode Network (DMN) brain regions, which have been proven to be particularly affected by T1DM in a group of eighteen carefully selected clinically well-controlled young T1DM patients versus eighteen healthy matched controls according to sex, age, and education level. Results showed no relevant differences in the anatomical distribution of DMN between the groups. However, the transitivity graph metric was significantly lower in T1DM patients, who also showed weaker connectivity between the left ventral prefrontal cortex and the left medial temporal gyrus, representing the anatomical trajectory of the arcuate fasciculus. Considering that neural myelination is affected by language input and the critical role of language-related structures on brain development, the current findings denote early ill-driven brain modifications to better adapt to the increasing daily demands.

Neural mechanisms of disease pathology and cognition in young-onset Alzheimer's disease variants

BackgroundLate-onset Alzheimer's disease is consistently associated with alterations in the default-mode network (DMN)-a large-scale brain network associated with self-related processing and memory. However, the functional organization of DMN is far less clear in young-onset Alzheimer's disease (YOAD).ObjectiveThe current study aimed to identify effective connectivity changes in the core DMN nodes between YOAD variants and healthy controls.MethodsWe assessed resting-state DMN effective connectivity in two common YOAD variants (i.e., amnestic variant (n = 26) and posterior cortical atrophy (n = 13) and healthy participants (n = 24) to identify disease- and variant-specific connectivity differences using spectral dynamic causal modelling.ResultsPatients with the amnestic variant showed increased connectivity from prefrontal cortex to posterior DMN nodes relative to healthy controls, whereas patients with posterior cortical atrophy exhibited decreased posterior DMN connectivity. Right hippocampus connectivity differentiated the two patient groups. Furthermore, disease-related connectivity alterations were also predictive of group membership and cognitive performance.ConclusionsThese findings suggest that resting-state DMN effective connectivity provides a new understanding of neural mechanisms underlying the disease pathology and cognition in YOAD.

How do brain regions specialised for concrete and abstract concepts align with functional brain networks? A neuroimaging meta-analysis

Identifying the brain regions that process concrete and abstract concepts is key to understanding the neural architecture of thought, memory and language. We review current theories of concreteness effects and test their neural predictions in a meta-analysis of 72 neuroimaging studies (1400 participants). Our analysis includes more than twice as many studies as previous meta-analyses, allowing for a more sensitive mapping of these effects across the brain. We also conducted a quantitative assessment of the degree to which concreteness effects aligned with a range of large-scale functional brain networks. Our results suggest that concrete and abstract concepts vary both in the information-processing modalities they engage and in the demands they place on cognitive control processes. Abstract concepts preferentially activated networks for social cognition (particularly for sentences), language and semantic control (particularly when presented as single words). Concrete concepts preferentially activated action processing regions when presented in sentences, though we found no evidence that they activated visual networks. Specialisation for both concept types was present in different parts of the default mode network (DMN), with effects dissociating along a social-spatial axis. Concrete concepts generated greater activation in a medial temporal DMN component, implicated in constructing mental models of spatial contexts and scenes. In contrast, abstract concepts showed greater activation in frontotemporal DMN regions involved in social and language processing. These results align with prior claims that generating models of situations and events is a core DMN function and indicate specialisation within DMN for different aspects of these models.

Transcriptionally downregulated GABAergic genes associated with synaptic density network dysfunction in temporal lobe epilepsy

PURPOSE

Temporal lobe epilepsy (TLE) is a brain network disorder closely associated with synaptic loss and has a genetic basis. However, the in vivo whole-brain synaptic changes at the network-level and the underlying gene expression patterns in patients with TLE remain unclear.

METHODS

In this study, we utilized a positron emission tomography with the synaptic vesicle glycoprotein 2 A radioligand [18F]SynVesT-1 cohort and two independent transcriptome datasets to investigate the topological properties of the synaptic density similarity network (SDSN) in TLE and its correlation with significantly dysregulated risk genes.

RESULTS

We observed an overall decrease in strength, reduced clustering coefficient, and increased path length of SDSN in TLE, suggesting a loss of connectivity that is accompanied by network reorganization. These changes were predominantly distributed in the temporo-limbic circuit and fronto-parietal networks. Moreover, connectivity changes in SDSN were found to be spatially correlated with the brain-wide expression of TLE risk genes, and the transcriptional correlate of SDSN changes showed a significant relationship with gene dysregulation. In particular, we identified a total of 183 downregulated genes that were functionally enriched for synaptic transmission pathways, forming a highly connected genetic interaction network. Within this set of genes, GABAergic genes such as RBFOX1 play a central role.

DISCUSSION

Our study provides the first evidence that the spatial expression patterns of downregulated risk genes underlie in vivo synaptic density network dysfunction in TLE. These imaging-transcriptomic findings have the potential to guide the development of molecular and genetic network-based therapeutic approaches for TLE.

Functional connectivity of the default mode network subsystems alterations in suicide attempters with major depressive disorder

Default mode network (DMN) abnormalities are common in patients with major depressive disorder and suicide attempts (MDD-SA). We aimed to investigate the abnormal functional connectivity (FC) patterns of DMN in MDD-SA. Seventeen DMN components were extracted from 55 MDD-SA, 94 patients with MDD but without suicide attempts (MDD-NoSA), and 71 healthy controls (HC). Compared with HC and MDD-NoSA, patients with MDD-SA revealed reduced FC between the dorsomedial prefrontal cortex (dMPFC) seed and middle frontal gyrus (MFG). Patients with MDD-SA also showed specific increased FC between ventral medial prefrontal cortex (vMPFC) seed and medial superior frontal gyrus. MDD-NoSA showed specific increased FC between dMPFC and cerebellum crus Ⅱ. Both patients with MDD-SA and MDD-NoSA demonstrated increased FC between the vMPFC seed and inferior parietal lobule (IPL) and impaired FC between the anterior medial prefrontal cortex and cerebellum crus Ⅱ than HC. Furthermore, the abnormal FC between the vMPFC seed and IPL was correlated with Montgomery-Asberg Depression Scale in the MDD-NoSA group. Our findings highlighted that these abnormal FC patterns of DMN were associated with pathological mechanisms in patients with MDD-SA and MDD-NoSA.

Embedding emotion concepts in cognitive maps

Emotion knowledge is organized in a two-dimensional space known as the affective circumplex, which is thought to develop from core affective feelings and the co-occurrence of emotional events. Neural studies reveal that emotion concepts and cognitive maps of space and abstract concepts are represented in hippocampal-prefrontal systems. We propose that the circumplex is formed by learning the transitions between emotion concepts, a process mediated by a reciprocal network involving hippocampal cells that encode emotion concepts and grid cells in medial entorhinal and ventral prefrontal cortices that encode the relations between them. We anticipate that testing this hypothesis will shed light on the debate about whether emotions are biologically basic or constructed from core affective dimensions.

The generalizability of cortical area parcellations across early childhood

The cerebral cortex consists of distinct areas that develop through intrinsic embryonic patterning and postnatal experiences. Accurate parcellation of these areas in neuroimaging studies improves statistical power and cross-study comparability. Given significant brain changes in volume, microstructure, and connectivity during early life, we hypothesized that cortical areas in 1- to 3-year-olds would differ markedly from neonates and increasingly resemble adult patterns as development progresses. Here, we parcellated the cerebral cortex into putative areas using local functional connectivity (FC) gradients in 92 toddlers at 2 years old. We demonstrate high reproducibility of these cortical areas across 1- to 3-year-olds in two independent datasets. The area boundaries in 1- to 3-year-olds were more similar to those in adults than those in neonates. While the age-specific group area parcellation better fits the underlying FC in individuals during the first 3 years, adult area parcellations still have utility in developmental studies, especially in children older than 6 years. Additionally, we provide connectivity-based community assignments of the area parcels, showing fragmented anterior and posterior components based on the strongest connectivity, yet alignment with adult systems when weaker connectivity was included.

Cortical Gradients Support Mental Time Travel into the Past and Future: Evidence from Activation Likelihood Estimation Meta-analysis

A longstanding issue concerns the extent to which episodic autobiographical memory (EAM) and episodic future thinking (EFT) are the expression of the same cognitive ability and may be dissociated at the neural level. Here, we provided an updated picture of overlaps and dissociations between brain networks supporting EAM and EFT, using Activation Likelihood Estimation. Moreover, we tested the hypothesis that spatial gradients characterize the transition between activations associated with the two domains, in line with accounts positing a transition in the relative predominance of their features and process components. We showed the involvement of a core network across EAM and EFT, including midline structures, the bilateral hippocampus/parahippocampus, angular gyrus and anterior middle temporal gyrus (aMTG) and the left superior frontal gyrus (SFG). Contrast analyses highlighted a cluster in the right aMTG significantly more activated during EFT compared with EAM. Finally, gradiental transitions were found in the ventromedial prefrontal cortex, left SFG, and bilateral aMTG. Results show that differences between EAM and EFT may arise at least partially through the organization of specific regions of common activation along functional gradients, and help to advocate between different theoretical accounts.

Neural connectivity biotypes: predictors of clinical outcomes and improvement patterns of iTBS treatment in adolescents and young adults with depression

Background

The heterogeneity of depression limits the treatment outcomes of intermittent theta burst stimulation (iTBS) and hinders the identification of predictive factors. This study investigated functional network connectivity and predictors of iTBS treatment outcomes in adolescents and young adults with depression.

Aim

This study aimed to identify default mode network (DMN)-based connectivity patterns associated with varying iTBS treatment outcomes in depression.

Methods

Data from a randomised controlled trial of iTBS in depression (n=82) were analysed using a data-driven approach to classify homogeneous subgroups based on the DMN. Connectivity subgroups were compared on depressive symptoms and cognitive function at pretreatment and post-treatment. Furthermore, the predictive significance of baseline inflammatory cytokines on post-treatment outcomes was evaluated.

Results

Two distinct subgroups were identified. Subgroup 1 exhibited high heterogeneity and greater centrality in the posterior cingulate cortex and retrosplenial cortex, while subgroup 2 showed more homogeneous connectivity patterns and greater centrality in the temporoparietal junction and posterior inferior parietal lobule. No main effect for subgroup, treatment or subgroup×treatment interaction was revealed in the improvement of depressive symptoms. A significant subgroup×treatment interaction related to symbol coding improvement was detected (F=5.22, p=0.026). Within subgroup 1, the active group showed significantly greater improvement in symbol coding compared with the sham group (t=2.30, p=0.028), while baseline levels of interleukin-6 and C-reactive protein emerged as significant indicators for predicting improvements in symbolic coding (R2=0.35, RMSE (root-mean-square error)=5.72, p=0.013). Subgroup 2 showed no significant findings in terms of cognitive improvement or inflammatory cytokines predictions.

Conclusions

Data-driven network analyses offer valuable insights into iTBS treatment outcomes in depression, providing clues for predicting cognitive improvements from an inflammatory perspective.

Trial registration number

ChiCTR2100042346.

Comparative efficacy of rTMS on different targets in Alzheimer's disease: a systematic review and meta-analysis

Background

Repetitive transcranial magnetic stimulation (rTMS) is emerging as a promising non-invasive intervention for Alzheimer's disease (AD), yet therapeutic outcomes remain inconsistent across studies. This meta-analysis aimed to evaluate the cognitive benefits of rTMS in AD patients, with a specific focus on stimulation targets and protocols variations.

Methods

A systematic literature search was conducted in PubMed, Web of Science, Embase, and Cochrane Library for relevant English-language studies published up to 31 May 2024. Cognitive outcomes were assessed using the Mini-Mental State Examination (MMSE) and Alzheimer's Disease Assessment Scale-Cognitive Section (ADAS-Cog). Data were pooled using a random-effects model, with standardized mean difference (SMD) or mean differences (MD) and 95% confidence intervals (CI) calculated. Subgroup analyses were performed to examine the effects of stimulation targets, protocol variations and population demographics on rTMS efficacy.

Results

Twenty-two studies involving 874 participants were included in this meta-analysis. Overall, rTMS significantly improved cognitive function (SMD = 0.27; 95% CI = 0.14-0.41; p < 0.0001), showing that the efficacy of rTMS varied by stimulation target and protocol. Stimulation of the dorsolateral prefrontal cortex (DLPFC) led to significant cognitive improvement (SMD = 0.49, 95% CI = -0.26 to 0.73; p < 0.0001), whereas bilateral DLPFC stimulation showed no significant improvement (SMD = 0.13; 95% CI = -0.40 to 0.66; p = 0.62). Stimulating the parietal lobe or associated regions produced moderate cognitive benefits (SMD = 0.29; 95% CI = 0.03-0.55; p = 0.03). Notably, multi-target stimulation over the bilateral DLPFC, parietal lobes, Wernicke's area, and Broca's area also showed substantial cognitive improvement (MD = 2.85; 95% CI = 1.69-4.00; p < 0.00001). Additionally, subgroup analysis based on geographical background revealed greater effects in studies conducted in Asia (SMD = 0.40, 95% CI = 0.14-0.65; p < 0.003).

Conclusion

rTMS is an effective intervention for cognitive enhancement in AD, with its efficacy significantly influenced by stimulation target and protocol. Notably, the greater cognitive benefits observed in Asian populations suggest a potential role of genetic and demographic factors that warrant further investigation. These findings contribute to the development of optimized, personalized rTMS protocols for AD treatment.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/recorddashboard, CRD42023434084.

Standardized low-resolution brain electromagnetic tomography does not improve EEG Alzheimer's disease assessment

Quantitative EEG has been shown to reflect neurodegenerative processes in Alzheimer's disease (AD) and may provide non-invasive and widely available biomarkers to enhance the objectivization of disease assessment. To address EEG's major drawback - its low spatial resolution - many studies have employed 3D source localization. However, none have investigated whether this complex mapping into 3D space actually adds value over standard surface derivation. In fact, we found no prior study - in any disease - that quantitatively compared the results of a 3D source localization method with those achieved by surface derivation. We analyzed data from one of the largest prospective AD EEG studies ever conducted (four study centers, 188 patients, 100 female). Thousands of distinct quantitative EEG markers of slowing, complexity, and functional connectivity were computed and regressed against disease severity, with rigorous control for multiple testing. We found highly significant associations between quantitative EEG markers and disease severity. However, standardized low-resolution electromagnetic tomography (sLORETA), a widely used 3D source localization method, did not improve results. Furthermore, a surface derivation marker (auto-mutual information of the left hemisphere during the eyes-closed condition) was the best performing marker across our entire sample. While our findings strongly support that quantitative EEG markers reflect neurodegenerative processes in AD, they do not demonstrate additional benefit from sLORETA. Importantly, our results are specific to AD and sLORETA. Therefore, they should not be generalized to other neurological or psychiatric disorders or to other 3D source localization methods without further validation. Finally, these findings do not diminish the value of 3D source localization for visual EEG inspection.

The evolution of N, N-Dimethyltryptamine: from metabolic pathways to brain connectivity

RATIONALE

N, N-Dimethyltryptamine (DMT), a potent serotonergic psychedelic, bridges ancient wisdom and modern science. The mechanisms underlying its powerful psychedelic effects and out-of-body experiences continue to intrigue scientists. The functional role of DMT remains ambiguous. This paper explores the endogenous presence of DMT in the human body and its diverse neuroregulatory functions, which influence hierarchical brain connectivity, and the mechanisms driving its psychedelic effects.

OBJECTIVE

This paper aims to analyze DMT-receptor binding, its effects on neuronal modulation, brain oscillations, and connectivity, and its influence on hallucinations, out-of-body experiences, and cognitive functions.

RESULTS

DMT administration induces significant changes in brain wave dynamics, including reduced alpha power, increased delta power, and heightened Lempel-Ziv complexity, reflecting enhanced neural signal diversity. Functional neuroimaging studies reveal that DMT enhances global functional connectivity (GFC), particularly in transmodal association cortices such as the salience network, frontoparietal network, and default mode network, correlating with ego dissolution. The receptor density-dependent effects of DMT were mapped to brain regions rich in serotonin 5-HT2A receptors, supporting its role in modulating consciousness and neuroplasticity.

CONCLUSION

This integrated analysis provides insights into the profound effects of DMT on human cognition, and consciousness, and its role in enhancing natural well-being. As we uncover the endogenous functions of DMT, it becomes clear that the study of its biology reveals a complex interplay between brain chemistry and consciousness.

Self-related thought alterations associated with intrinsic brain dysfunction in mild cognitive impairment

The subjective experience of self-awareness is attributed to the human capacity for introspective thought during periods of mind-wandering. However, how this cognitive function is impacted in individuals with mild cognitive impairment (MCI) still needs to be better understood. To address this gap, we investigated alterations in self-referential thinking in a cohort of 30 MCI patients, comparing them to 60 healthy old-aged and 60 healthy younger controls. MCI patients exhibited a notable decline in overall cognitive function, as evidenced by significantly lower scores on the Montreal Cognitive Assessment (MoCA), with particular deficits in Memory subscore and Memory Index Score (MIS). Employing the Amsterdam Resting-State Questionnaire (ARSQ) to assess mind-wandering, we observed diminished self-related thoughts relating to personal past experiences and future thinking among MCI patients. Notably, using high-density electroencephalography (hdEEG) microstate analysis, we detected reduced neural activity for microstate C associated with self-related thoughts in MCI patients and healthy older relative to healthy younger controls, and an increase in neural activity for microstate A in MCI patients compared to healthy older and younger controls. This aberrant temporal activity was localized within brain regions implicated in episodic autobiographical memory and the default mode network. Our results highlight a link between impaired mind-wandering ability and dysfunction within the intrinsic neural networks of MCI patients, underscoring its implications for disruptions in the sense of self within this clinical population.

The Journey of the Default Mode Network: Development, Function, and Impact on Mental Health

The Default Mode Network has been extensively studied in recent decades due to its central role in higher cognitive processes and its relevance for understanding mental disorders. This neural network, characterized by synchronized and coherent activity at rest, is intrinsically linked to self-reflection, mental exploration, social interaction, and emotional processing. Our understanding of the DMN extends beyond humans to non-human animals, where it has been observed in various species, highlighting its evolutionary basis and adaptive significance throughout phylogenetic history. Additionally, the DMN plays a crucial role in brain development during childhood and adolescence, influencing fundamental cognitive and emotional processes. This literature review aims to provide a comprehensive overview of the DMN, addressing its structural, functional, and evolutionary aspects, as well as its impact from infancy to adulthood. By gaining a deeper understanding of the organization and function of the DMN, we can advance our knowledge of the neural mechanisms that underlie cognition, behavior, and mental health. This, in turn, can lead to more effective therapeutic strategies for a range of neuropsychiatric conditions.

Effective connectivity analysis of response inhibition functional network

Introduction

Inhibition mechanisms are essential in daily life, helping individuals adapt to environmental demands. However, the causal interactions between large-scale functional networks involved in response inhibition remain poorly understood.

Methods

In this study, we examined the effective connectivity (EC) underlying inhibitory processes in the brain using dynamic causal modeling (DCM) and independent component analysis (ICA). We conducted a Go-NoGo fMRI task with 19 healthy participants to investigate these networks.

Results

Our results identified four functional networks activated during correct motor response inhibition: the salience network (SN), the right and left executive control networks (ECNs), and the ventral default mode network (vDMN). We observed a significant causal inhibitory influence from the vDMN to the left ECN (lECN). Under conditions of unsuccessful response inhibition, the SN, bilateral ECNs, and somatomotor network (SMN) were found to be prominently activated. Furthermore, we identified a significant correlation between the inhibitory influence from the SMN to the SN and the commission error rate. Finally, correlation analyses between self-reported impulsivity levels and causal network interactions revealed that highly impulsive individuals require greater interhemispheric integration between the right and left ECNs for effective inhibition, as well as a causal excitatory modulation from the right executive control network (rECN) to the vDMN.

Discussion

In summary, our study reveals complex hierarchical dynamics among functional networks during response inhibition. These findings offer valuable insight into the neural mechanisms supporting inhibition and provide avenues for future research on the neural underpinnings of this critical cognitive function across the lifespan.

Transcranial focused ultrasound targeting the default mode network for the treatment of depression

Introduction

Up to 50% of individuals fail to respond to current depression treatments. Repetitive negative thought and default mode network hyperconnectivity are central in depression and can potentially be targeted using novel neuromodulation techniques. This community-based study assessed whether a treatment using non-invasive transcranial focused ultrasound targeting the default mode network can decrease depression symptoms and repetitive negative thought, and improve quality of life.

Methods

Study recruitment began in August 2023 and ended in February 2024. Twenty individuals aged 18 - 50 were enrolled from among 247 screened. Exclusion criteria included history of psychosis/mania, acute suicidality, MRI contraindications, pregnancy, and medical and neurological factors that may complicate diagnosis or brain function. Participants completed up to three weeks of transcranial ultrasound (11 sessions) targeting the anterior medial prefrontal cortex; ten minutes per session. Depression severity (Beck Depression Inventory - II and the Hamilton Depression Rating Scale), repetitive negative thought (Perseverative Thinking Questionnaire), and quality of life (World Health Organization Quality of Life Scale) were outcomes.

Results

This sample was young (mean 30.4 years ± 10.0), predominantly female (75%), with moderate to severe depression and high comorbidity. Fifty percent of participants endorsed current psychiatric medication use. Ten percent of subjects dropped out of the study due to time constraints. Significant decreases in depression were observed over the course of treatment on self-report, 10.9 (p < 0.001, CI = -13.55, -7.92) and interview depression ratings, 4.2 (p < 0.001, CI = -5.85, -2.62), as well as significant decreases in repetitive negative thought, 8.4 (p <0.001, CI = -10.55, -6.03). Improvements in physical and psychological well-being were also observed over the course of treatment, 7.2 (p < 0.001, CI = 3.64, 10.63) and 11.2 (p < 0.001, CI = 7.79, 14.49), respectively, as well as improvements in environment satisfaction, 5.0 (p =0.001, CI = 2.24, 7.56).

Discussion

Non-invasive transcranial focused ultrasound holds promise as a treatment for depression holds promise as a treatment for depression, however, future work including control arms is required to ascertain its causal role in depression.

Clinical trial registration

https://clinicaltrials.gov/study/NCT06320028intr=Ultrasound&cond=depression&locStr=Arizona&country=United%20States&state=Arizona&rank=1, identifier NCT06320028.

Temporal lobe dysfunction for comorbid depressive symptoms in postherpetic neuralgia patients

Depression often occurs concurrently with postherpetic neuralgia (PHN), yet the neural mechanism underlying pain-depression comorbidity remains poorly understood. For this observational study, we recruited 17 depressed PHN patients, 19 non-depressed PHN patients, and 34 healthy controls (HCs) for resting-state functional MRI scans. We firstly investigated the differences in fractional amplitude of low-frequency fluctuation and regional homogeneity values among the three groups to identify a characteristic brain signal of pain-depression comorbidity. Abnormal voxel-wised functional connectivity was then compared across groups and correlated with clinical variables in each group. One-way analysis of covariance results revealed the fractional amplitude of low-frequency fluctuation values differences in the right temporal lobe (TL) and its voxel-wised connectivity with the inferior frontal gyrus (IFG) among three groups. Furthermore, the TL-IFG connectivity was positively associated with the positive emotional scores and life quality scores among depressed PHN patients, but not non-depressed PHN patients and HCs. In summary, these findings highlighted the TL dysfunction in pain-depression comorbidity among PHN population and may offer heuristic cues for central therapeutic targets that could disrupt the pain-depression vicious circle.

Dev-Atlas: A reference atlas of functional brain networks for typically developing adolescents

It is well accepted that the brain is functionally organized into multiple networks and extensive literature has demonstrated that the organization of these networks shows major changes during adolescence. Yet, there is limited option for a reference functional brain atlas derived from typically-developing adolescents, which is problematic as the reliable identification of functional brain networks crucially depends on the use of such reference functional atlases. In this context, we utilized resting-state functional MRI data from 1391 typically-developing youth aged 8-17 years to create an adolescent-specific reference atlas of functional brain networks. We further investigated the impact of age and sex on these networks. Using a multiscale individual component clustering algorithm, we identified 24 reliable functional brain networks, classified within six domains: Default-Mode (5 networks), Control (4 networks), Salience (3 networks), Attention (4 networks), Somatomotor (5 networks), and Visual (3 networks). We identified reliable and large effects of age on the spatial topography of these majority of networks, as well as on the functional network connectivity. Sex effects were not as widespread. We created a novel brain atlas, named Dev-Atlas, focused on a typically-developing sample, with the hope that this atlas can be used in future developmental neuroscience studies.

Default Mode Network Functional Connectivity As a Transdiagnostic Biomarker of Cognitive Function

The default mode network (DMN) is intricately linked with processes such as self-referential thinking, episodic memory recall, goal-directed cognition, self-projection, and theory of mind. In recent years, there has been a surge in the number of studies examining its functional connectivity, particularly its relationship with frontoparietal networks involved in top-down attention, executive function, and cognitive control. The fluidity in switching between these internal and external modes of processing, which is highlighted by anticorrelated functional connectivity, has been proposed as an indicator of cognitive health. Due to the ease of estimation of functional connectivity-based measures through resting-state functional magnetic resonance imaging paradigms, there is now a wealth of large-scale datasets, paving the way for standardized connectivity benchmarks. In this review, we explore the promising role of DMN connectivity metrics as potential biomarkers of cognitive state across attention, internal mentation, mind wandering, and meditation states and investigate deviations in trait-level measures across aging and in clinical conditions such as Alzheimer's disease, Parkinson's disease, depression, attention-deficit/hyperactivity disorder, and others. We also tackle the issue of reliability of network estimation and functional connectivity and share recommendations for using functional connectivity measures as a biomarker of cognitive health.

Mindfulness as a Way of Reducing Automatic Constraints on Thought

The number of mindfulness-based wellness promotion programs offered by institutions, by governments, and through mobile apps has grown exponentially in the last decade. However, the scientific understanding of what mindfulness is and how it works is still evolving. Here, I focus on 2 common mindfulness practices: focused attention (FA) and open monitoring (OM). First, I summarize what is known about FA and OM meditation at the psychological level. While they share similar emotion regulation goals, they differ in terms of some of their attention regulation goals. Second, I turn to the neuroscientific literature, showing that FA meditation is associated with consistent activations of cortical control network regions and deactivations of cortical default network regions. In contrast, OM meditation seems to be most consistently associated with changes in the functional connectivity patterns of subcortical structures, including the basal ganglia and cerebellum. Finally, I present a novel account of the mental changes that occur during FA and OM meditation as understood from within the Dynamic Framework of Thought-a conceptual framework that distinguishes between deliberate and automatic constraints on thought. Although deliberate self-regulation processes are often emphasized in scientific and public discourse on mindfulness, here I argue that mindfulness may primarily involve changes in automatic constraints on thought. In particular, I argue that mindfulness reduces the occurrence of automatized sequences of mental states or habits of thought. In this way, mindfulness may increase the spontaneity of thought and reduce automatically constrained forms of thought such as rumination and obsessive thought.

Task-based neural correlates of self-focused attention associated with cognitive behavioral therapy response

Self-focused attention (SFA), a form of self-referential processing, is maladaptive in various psychiatric disorders and may be associated with poor treatment response. This study examined SFA in individuals with social anxiety disorder (SAD) and body dysmorphic disorder (BDD), testing the hypothesis that SFA is associated with hyperactivity within default network (DN) regions and with treatment response during cognitive-behavioral therapy. Participants included 30 patients with primary SAD or BDD and 28 healthy controls, who displayed above average and below average scores (respectively) on the Public Self-Consciousness Scale, which measured trait SFA. SFA was also measured by a self-referential encoding task, which yielded both behavioral reaction time measures and task-related fMRI measures of SFA. Results indicated significantly longer reaction times at pre-treatment for self vs. other trials in patients compared to controls, with patients showing notable improvement post-treatment. Neuroimaging revealed greater activation in DN regions, including the medial prefrontal cortex, during self vs. other trials in all participants; however, there were no significant group differences at pre- or post-treatment, nor in the changes from pre- to post-treatment. Neural measures of SFA were significantly associated with treatment response, whereas behavioral measures were not. These findings suggest that activity in DN regions may serve as a transdiagnostic biomarker of maladaptive SFA that is associated with treatment response.

Effects of bright light therapy on cingulate cortex dynamic functional connectivity and neurotransmitter activity in young adults with subthreshold depression

BACKGROUND

The neurobiological mechanisms behind the antidepressant effect of bright light therapy (BLT) are unclear. We aimed to explore the dynamic functional connectivity (dFC) changes of the cingulate cortex (CC) in subthreshold depression (StD).

METHODS

The StD participants (38 BLT and 39 placebo) underwent resting-state functional magnetic resonance imaging (rs-fMRI) and mood assessment before and after eight-week BLT. Seed-based whole-brain dFC analysis was conducted and multivariate regression model was adopted to predict Hamilton Depression Rating Scale (HDRS) and Centre for Epidemiologic Studies Depression Scale (CESD) scores changes after BLT. JuSpace toolbox was used to calculate the associations between dFC and neurotransmitter activity in the BLT group.

RESULTS

BLT group showed decreased CESD and HDRS scores. Also, BLT group showed increased dFC of the right supracallosal anterior cingulate cortex (supACC)-right temporal pole (TP), left middle cingulate cortex (MCC)-right insula, and left supACC-pons, and decreased dFC of the right supACC- right middle frontal gyrus (MFG). Changes in dFC of the right supACC-right TP showed positive correlation with changes in CESD and HDRS. Moreover, combining the baseline dFC variability of the CC could predict HDRS changes in BLT. Finally, compared to baseline, the supACC and MCC dFC changes showed significant correlations with the neurotransmitter activities.

CONCLUSIONS

BLT alleviates depressive symptoms and changes the CC dFC variability in StD, and pre-treatment dFC variability of the CC could be used as a biomarker for improved BLT treatment in StD. Furthermore, dFC changes with specific neurotransmitter systems after BLT may underline the antidepressant mechanisms of BLT.

DMN network and neurocognitive changes associated with dissociative symptoms in major depressive disorder: a research protocol

Introduction

Depression is a heterogeneous disorder with diverse clinical presentations and etiological underpinnings, necessitating the identification of distinct subtypes to enhance targeted interventions. Dissociative symptoms, commonly observed in major depressive disorder (MDD) and linked to early life trauma, may represent a unique clinical dimension associated with specific neurocognitive deficits. Although emerging research has begun to explore the role of dissociation in depression, most studies have provided only descriptive analyses, leaving the mechanistic interplay between these phenomena underexplored. The primary objective of this study is to determine whether MDD patients with prominent dissociative symptoms differ from those without such symptoms in clinical presentation, neurocognitive performance, and markers of functional connectivity. This investigation will be the first to integrate comprehensive clinical evaluations, advanced neurocognitive testing, and high-resolution brain imaging to delineate the contribution of dissociative symptoms in MDD.

Methods

We will recruit fifty participants for each of three groups: (1) depressive patients with dissociative symptoms, (2) depressive patients without dissociative symptoms, and (3) healthy controls. Diagnostic assessments will be performed using the Structured Clinical Interview for DSM-5 (SCID) alongside standardized scales for depression severity, dissociation, and childhood trauma. Neurocognitive performance will be evaluated through a battery of tests assessing memory, attention, executive function, and processing speed. Structural and functional magnetic resonance imaging (MRI) will be conducted on a 3 Tesla scanner, focusing on the connectivity of the Default Mode Network with key regions such as the orbitofrontal cortex, insula, and posterior cingulate cortex. Data analyses will employ SPM-12 and Matlab-based CONN and PRONTO tools, with multiclass Gaussian process classification applied to differentiate the three groups based on clinical, cognitive, and imaging data.

Discussion

The results of this study will introduce a novel perspective on understanding the connection between major depressive disorder and dissociation. It could also aid in pinpointing a distinct form of depression associated with dissociative symptoms and early childhood stressors.

Conclusion

Future research, aiming to forecast the response to biological and psychological interventions for depression, anticipates this subtype and provides insights.

Spliceosome protein alterations differentiate hubs of the default mode connectome during the progression of Alzheimer's disease

Default mode network (DMN) is comprised in part of the frontal (FC), precuneus (PreC), and posterior cingulate (PCC) cortex and displays amyloid and tau pathology in Alzheimer's disease (AD). The PreC hub appears the most resilient to AD pathology, suggesting differential vulnerability within the DMN. However, the mechanisms that underlie this differential pathobiology remain obscure. Here, we investigated changes in RNA polymerase II (RNA pol II) and splicing proteins U1-70K, U1A, SRSF2, and hnRNPA2B1, phosphorylated AT8 tau, 3R and 4Rtau isoforms containing neurons and amyloid plaques in layers III and V-VI in FC, PreC, and PCC obtained from individuals with a preclinical diagnosis of no cognitive impairment (NCI), mild cognitive impairment (MCI), and mild/moderate mAD. We found a significant increase in pS5-RNA pol II levels in FC NCI, U1-70K in PreC MCI and mAD, and hnRNPA2B1 and SRSF2 levels in PCC mAD. 1N3Rtau levels were significantly increased in FC, decreased in PreC in mAD, and unchanged in PCC, whereas 1N4Rtau increased in mAD across the hubs. SRSF2, U1-70K, U1A, and hnRNPA2B1 nuclear optical density (OD), size, and number were unchanged across groups in FC and PCC, while PreC OD hnRNPA2B1 was significantly greater in mAD. Mislocalized U1A and U1-70K tangle-like structures were found in a few PCC cases and colocalized with AT8-bearing neurofibrillary tangles (NFTs). FC pS5-RNA pol II, PreC U1-70K, Pre pS5,2-RNA pol II, and PCC hnRNPA2B1 and SRSF2 protein levels were associated with cognitive decline but not neuropathology across clinical groups. By contrast, splicing protein nuclear OD measures, size, counts, and mislocalized U1-70K and U1A NFT-like structures were not correlated with NFT or plaque density, cognitive domains, and neuropathological criteria in DMN hubs. Findings suggest that RNA splicing protein alterations and U1 mislocalization contribute differentially to DMN pathogenesis and cognitive deterioration in AD.

Large-scale functional network connectivity mediate the associations of white matter lesions with executive functions and information processing speed in asymptomatic cerebral small vessels diseases

OBJECTIVE

To examine the role of the large-scale functional network connectivity between white matter lesions (WMLs) and cognitive behaviors in patients of asymptomatic cerebral small vascular diseases (CSVD).

METHODS

The study sample consisted of 211 asymptomatic CSVD patients with WMLs. Large-scale internetwork and intranetwork functional connectivity (FC) were calculated using a combination of resting-state functional MRI data and independent component analysis. Neuropsychological tests involve cognitive functions were also measured. Then, potential correlations between WMLs, functional network connectivity and cognitive behaviors were tested. Mediation analysis was used to explore the role of functional network connectivity between WMLs and cognitive behaviors.

RESULTS

We successfully identified fourteen meaningful resting-state functional networks. Internetwork FC between dorsal sensorimotor network (dSMN) and right frontoparietal network (rFPN), dSMN and left frontoparietal network (lFPN), auditory network (AN) and posterior default network (pDMN), AN and executive control network (ECN), ECN and salience network (SN), dorsal attention network (DAN) and ECN were significant correlated with volumes of WMLs. Executive function were associated with internetwork FC between AN and pDMN, ECN and SN. Moreover, internetwork FC between AN and pDMN, ECN and SN mediated the relations of WMLs with executive function (for AN and pDMN, indirect effect: -0.0371, 95% CI: -0.0829 to -0.0073; for ECN and SN, indirect effect: -0.03191, 95% CI: -0.0807 to -0.0047). Moreover, left inferior parietal lobule in rFPN, right precentral gyrus in anterior default network (aDMN), right paracentral lobue in pDMN and left precunues in ECN were related to volumes of WMLs. There is a significant association of WMLs with intranetwork FC in left precunues, which could mediate the link between WMLs and information processing speed (indirect effect: -0.0437, 95% CI: -0.1055 to -0.0081).

CONCLUSION

WMLs in asymptomatic CSVD patients may induce large-scale connectivity changes including the internetwork FC and intranetwork FC, which might further influence executive function and information processing speed.

Graded changes in local functional connectivity of the cerebral cortex in young people with depression

BACKGROUND

Major depressive disorder (MDD) is marked by significant changes to the local synchrony of spontaneous neural activity across various brain regions. However, many methods for assessing this local connectivity use fixed or arbitrary neighborhood sizes, resulting in a decreased capacity to capture smooth changes to the spatial gradient of local correlations. A newly developed method sensitive to classical anatomo-functional boundaries, Iso-Distant Average Correlation (IDAC), was therefore used to examine depression associated alterations to the local functional connectivity of the brain.

METHOD

One-hundred and forty-seven adolescents and young adults with MDD and 94 healthy controls underwent a resting-state functional magnetic resonance imaging (fMRI) scan. Whole-brain functional connectivity maps of intracortical neural activity within iso-distant local areas (5-10, 15-20, and 25-30 mm) were generated to characterize local fMRI signal similarities.

RESULTS

Across all spatial distances, MDD participants demonstrated greater local functional connectivity of the bilateral posterior hippocampus, retrosplenial cortex, dorsal insula, fusiform gyrus, and supplementary motor area. Local connectivity alterations in short and medium distances (5-10 and 15-20 mm) in the mid insula cortex were additionally associated with expressive suppression use, independent of depressive symptom severity.

CONCLUSIONS

Our study identified increased synchrony of the neural activity in several regions commonly implicated in the neurobiology of depression. These effects were relatively consistent across the three distances examined. Longitudinal investigation of this altered local connectivity will clarify whether these differences are also found in other age groups and if this relationship is modified by increased disease chronicity.

Brain neuromarkers predict self- and other-related mentalizing across adult, clinical, and developmental samples

Human social interactions rely on the ability to reflect on one's own and others' internal states and traits-a psychological process known as mentalizing. Impaired or altered self- and other-related mentalizing is a hallmark of multiple psychiatric and neurodevelopmental conditions. Yet, replicable and easily testable brain markers of mentalizing have so far been lacking. Here, we apply an interpretable machine learning approach to multiple datasets (total N=281) to train and validate fMRI brain signatures that predict 1) mentalizing about the self, 2) mentalizing about another person, and 3) both types of mentalizing. We test their generalizability across healthy adults, adolescents, and adults diagnosed with schizophrenia and bipolar disorder. The classifier trained across both types of mentalizing showed 98% predictive accuracy in independent validation datasets. Self-mentalizing and other-mentalizing classifiers had positive weights in anterior/medial and posterior/lateral brain areas respectively, with accuracy rates of 82% and 77% for out-of-sample prediction. Classifier patterns across cohorts revealed better self/other separation in 1) healthy adults compared to individuals with schizophrenia and 2) with increasing age in adolescence. Together, our findings reveal consistent and separable neural patterns subserving mentalizing about self and others-present at least from the age of adolescence and functionally altered in severe neuropsychiatric disorders. These mentalizing signatures hold promise as mechanistic neuromarkers to measure social-cognitive processes in different contexts and clinical conditions.

Functional differentiation of the default and frontoparietal control networks predicts individual differences in creative achievement: evidence from macroscale cortical gradients

Much of the research on the neural correlates of creativity has emphasized creative cognition, and growing evidence suggests that creativity is related to functional properties of the default and frontoparietal control networks. The present work expands on this body of evidence by testing associations of creative achievement with connectivity profiles of brain networks assessed using macroscale cortical gradients. Using resting-state connectivity functional magnetic resonance imaging in 2 community samples (N's = 236 and 234), we found evidence that creative achievement is positively associated with greater functional dissimilarity between core regions of the default and frontoparietal control networks. These results suggest that creative achievement is supported by the ability of these 2 networks to carry out distinct cognitive roles. This research provides further evidence, using a cortical gradient approach, that individual differences in creative achievement can be predicted from functional properties of brain networks involved in higher-order cognition, and it aligns with past research on the functional connectivity correlates of creative task performance.

Initial evidence for neural correlates following a therapeutic intervention: altered resting state functional connectivity in the default mode network following attention training technique

Introduction

The Attention Training Technique (ATT) is a psychotherapeutic intervention in Metacogntive Therapy (MCT) and aims at reducing maladaptive processes by strengthening attentional flexibility. ATT has demonstrated efficacy in treating depression on a clinical level. Here, we evaluated ATT at the neural level. We examined functional connectivity (FC) of the default mode network (DMN).

Method

48 individuals diagnosed with Major Depressive Disorder (MDD) and 51 healthy controls (HC) participated in a resting-state (rs) functional magnetic resonance imaging (fMRI) experiment. The participants received either one week of ATT or a sham intervention. Rs-fMRI scans before and after treatment were compared using seed-to-voxel analysis.

Results

The 2x2x2 analysis did not reach significance. Nevertheless, a resting-state connectivity effect was found on the basis of a posttest at the second measurement time point in MDD. After one week, MDD patients who had received ATT intervention presented lower functional connectivity between the left posterior cingulate cortex (PCC) and the bilateral middle frontal gyrus (MFG) as well as between the right PCC and the left MFG compared to the MDD patients in the sham group. In HC we observed higher rsFC in spatially close but not the same brain regions under the same experimental condition.

Conclusion

We found a first hint of a change at the neural level on the basis of ATT. Whether the changes in rsFC found here indicate an improvement in the flexible shift of attentional focus due to ATT needs to be investigated in further research paradigms. Further experiments have to show whether this change in functional connectivity can be used as a specific outcome measure of ATT treatment.

Dynamic brain states underlying advanced concentrative absorption meditation: A 7-T fMRI-intensive case study

Advanced meditation consists of states and stages of practice that unfold with mastery and time. Dynamic functional connectivity (DFC) analysis of fMRI could identify brain states underlying advanced meditation. We conducted an intensive DFC case study of a meditator who completed 27 runs of jhāna advanced absorptive concentration meditation (ACAM-J), concurrently with 7-T fMRI and phenomenological reporting. We identified three brain states that marked differences between ACAM-J and nonmeditative control conditions. These states were characterized as a DMN-anticorrelated brain state, a hyperconnected brain state, and a sparsely connected brain state. Our analyses indicate higher prevalence of the DMN-anticorrelated brain state during ACAM-J than control states, and the prevalence increased significantly with deeper ACAM-J states. The hyperconnected brain state was also more common during ACAM-J and was characterized by elevated thalamocortical connectivity and somatomotor network connectivity. The hyperconnected brain state significantly decreased over the course of ACAM-J, associating with self-reports of wider attention and diminished physical sensations. This brain state may be related to sensory awareness. Advanced meditators have developed well-honed abilities to move in and out of different altered states of consciousness, and this study provides initial evidence that functional neuroimaging can objectively track their dynamics.

Variation in brain aging: A review and perspective on the utility of individualized approaches to the study of functional networks in aging

Healthy aging is associated with cognitive decline across multiple domains, including executive function, memory, and attention. These cognitive changes can often influence an individual's ability to function and quality of life. However, the degree to which individuals experience cognitive decline, as well as the trajectory of these changes, exhibits wide variability across people. These cognitive abilities are thought to depend on the coordinated activity of large-scale networks. Like behavioral effects, large variation can be seen in brain structure and function with aging, including in large-scale functional networks. However, tracking this variation requires methods that reliably measure individual brain networks and their changes over time. Here, we review the literature on age-related cognitive decline and on age-related differences in brain structure and function. We focus particularly on functional networks and the individual variation that exists in these measures. We propose that novel individual-centered fMRI approaches can shed new light on patterns of inter- and intra-individual variability in aging. These approaches may be instrumental in understanding the neural bases of cognitive decline.

The architecture of the human default mode network explored through cytoarchitecture, wiring and signal flow

The default mode network (DMN) is implicated in many aspects of complex thought and behavior. Here, we leverage postmortem histology and in vivo neuroimaging to characterize the anatomy of the DMN to better understand its role in information processing and cortical communication. Our results show that the DMN is cytoarchitecturally heterogenous, containing cytoarchitectural types that are variably specialized for unimodal, heteromodal and memory-related processing. Studying diffusion-based structural connectivity in combination with cytoarchitecture, we found the DMN contains regions receptive to input from sensory cortex and a core that is relatively insulated from environmental input. Finally, analysis of signal flow with effective connectivity models showed that the DMN is unique amongst cortical networks in balancing its output across the levels of sensory hierarchies. Together, our study establishes an anatomical foundation from which accounts of the broad role the DMN plays in human brain function and cognition can be developed.

Unraveling the neural dichotomy of consensus and idiosyncratic experiences in short video viewing

Human experiences are inherently shaped by individual perspectives, leading to diverse interpretations of the same events. However, shared activities, such as communal film watching or sports viewing, underscore the dual nature of these experiences: collective joy arises through social interactions, while individual emotional responses are influenced by personal preferences. The neural mechanisms underlying this interplay between shared and idiosyncratic experiences, particularly in the context of reward processing, remain insufficiently explored. In this study, we investigated the neural basis of both communal enjoyment and individual anticipatory responses during short video viewing. Using functional MRI, we measured brain activity in participants as they watched 90 short videos and provided ratings of their reward expectations and experienced pleasure. By integrating intersubject correlation (ISC) and individual-specific analyses, we identified shared and unique neural activity patterns. Our findings reveal that synchronized activity within the default mode network (DMN) and reward-related regions underlies shared experiences of collective pleasure. In contrast, distinct activations in the frontal cortex and caudate nucleus were associated with personal preferences and reward anticipation, highlighting a neural dichotomy between communal enjoyment and individualized reward processing during digital media engagement.

Abnormal Functional Attributes of Central Executive Network in Patients with Mild Cognitive Impairment Associated with End-Stage Renal Disease

RATIONALE AND OBJECTIVES

To assess changes in the central executive network (CEN) of patients with mild cognitive impairment (MCI) associated with end-stage renal disease (ESRD).

METHODS

A total of 121 patients with ESRD and 66 healthy controls (HCs) were enrolled. Patients were divided into an MCI group (n = 67) and a cognitively unimpaired group (n = 54). All participants underwent resting-state functional magnetic resonance imaging and were evaluated using the Montreal Cognitive Assessment (MoCA). The functional attributes of the CEN were calculated using three methods of functional connectivity (FC) analysis. Relationships among imaging features, cognitive scale scores, and clinical data were assessed, and a model was constructed to diagnose MCI in patients with ESRD.

RESULTS

The comparison of the three groups showed that there were significant differences in the FC values of five connection pairs within the CEN, and the CEN demonstrated significant differences in connectivity to ten brain regions. In patients with MCI associated with ESRD, the information transmission efficiency of the CEN was reduced, which demonstrates the characteristics of a random network to some extent. Significant correlations were observed among imaging parameters, cognitive scale scores, and clinical data. The diagnostic model constructed based on these results demonstrated excellent discrimination and calibration.

CONCLUSION

Alterations in the function of the CEN provide relevant bases for revealing the neuropathological mechanism of MCI in patients with ESRD. The diagnostic model developed in this study may help to establish more reliable imaging markers for detecting early cognitive impairment in this patient population.

Rumination induction task in fMRI: Effects of rumination focused cognitive behavioral therapy and stability in youth

BACKGROUND

Rumination is implicated in the onset and maintenance of major depressive disorder (MDD). Rumination-Focused Cognitive Behavioral Therapy (RF-CBT) effectively targets rumination and may change resting-state brain connectivity and change in activation during a rumination induction task (RIT) post-intervention predicts depressive symptoms two years later. We examined brain activation changes during an RIT in adolescents with remitted MDD following RF-CBT and evaluated RIT reliability (or stability) during treatment as usual (TAU).

METHOD

Fifty-five adolescents ages 14-17 completed an RIT at baseline, were randomized to 10-14 sessions of RF-CBT (n = 30) or treatment as usual (n = 25) and completed an RIT at post-treatment or equivalent time delay. The RIT includes recalling negative memories (Rumination Instruction), dwelling on their meaning/consequences (Rumination Prompt), and imagining unrelated scenes and objects (Distraction). We assessed activation change in the RF-CBT group using paired-samples t-tests. We assessed reliability (or stability) via intraclass correlation coefficients (ICCs) of five rumination-related ROIs for TAU and RF-CBT separately across task blocks.

RESULTS

Following treatment, participants receiving RF-CBT demonstrated increased activation of left precuneus during Rumination Instruction and of left angular and superior temporal gyri during Rumination Prompt blocks (p < .01). From baseline to post-treatment, across most ROIs and task blocks, the RF-CBT group demonstrated poor stability (M = 0.21, range = -0.19-0.69), while the TAU group demonstrated fair-to-excellent stability (M = 0.52, range = 0.27-0.86).

CONCLUSION

RF-CBT changes activation of rumination-related circuitry during state-induced rumination, offering exciting avenues for future interventions. The RIT has fair-to-excellent stability among individuals not explicitly treated for rumination, and as expected, RIT stability is disrupted by RF-CBT.

Distinct distributed brain networks dissociate self-generated mental states

Human cognition relies on two modes: a perceptually-coupled mode where mental states are driven by sensory input and a perceptually-decoupled mode featuring self-generated mental content. Past work suggests that imagined states are supported by the reinstatement of activity in sensory cortex, but transmodal systems within the canonical default network are also implicated in mind-wandering, recollection, and imagining the future. We identified brain systems supporting self-generated states using precision fMRI. Participants imagined different scenarios in the scanner, then rated their mental states on several properties using multi-dimensional experience sampling. We found that thinking involving scenes evoked activity within or near the default network, while imagining speech evoked activity within or near the language network. Imagining-related regions overlapped with activity evoked by viewing scenes or listening to speech, respectively; however, this overlap was predominantly within transmodal association networks, rather than adjacent unimodal sensory networks. The results suggest that different association networks support imagined states that are high in visual or auditory vividness.

Arousal threshold reveals novel neural markers of sleep depth independently from the conventional sleep stages

Reports of sleep-specific brain activity patterns have been constrained by assessing brain function as it related to the conventional polysomnographic sleep stages. This limits the variety of sleep states and underlying activity patterns that one can discover. The current study used all-night functional MRI sleep data and defined sleep behaviorally with auditory arousal threshold (AAT) to characterize sleep depth better by searching for novel neural markers of sleep depth that are neuroanatomically localized and temporally unrelated to the conventional stages. Functional correlation values calculated in a four-min time window immediately before the determination of AAT were entered into a linear mixed effects model, allowing multiple arousals across the night per subject into the analysis, and compared to models with sleep stage to determine the unique relationships with AAT. These unique relationships were for thalamocerebellar correlations, the relationship between the right language network and the right "default-mode network dorsal medial prefrontal cortex subsystem," and the relationship between thalamus and ventral attention network. These novel neural markers of sleep depth would have remained undiscovered if the data were merely analyzed with the conventional sleep stages.

Within-Individual Precision Mapping of Brain Networks Exclusively Using Task Data

Precision mapping of brain networks within individuals has become a widely used tool that prevailingly relies on functional connectivity analysis of resting-state data. Here we explored whether networks could be precisely estimated solely using data acquired during active task paradigms. The straightforward strategy involved extracting residualized data after application of a task-based general linear model (GLM) and then applying standard functional connectivity analysis. Functional correlation matrices estimated from task data were highly similar to those derived from traditional resting-state fixation data. The largest factor affecting similarity between correlation matrices was the amount of data. Networks estimated within-individual from task data displayed strong spatial overlap with those estimated from resting-state fixation data and predicted the same triple functional dissociation in independent data. The implications of these findings are that (1) existing task data can be reanalyzed to estimate within-individual network organization, (2) resting-state fixation and task data can be pooled to increase statistical power, and (3) future studies can exclusively acquire task data to both estimate networks and extract task responses. Most broadly, the present results suggest that there is an underlying, stable network architecture that is idiosyncratic to the individual and persists across task states.

The Generalizability of Cortical Area Parcellations Across Early Childhood

The cerebral cortex consists of distinct areas that develop through intrinsic embryonic patterning and postnatal experiences. Accurate parcellation of these areas in neuroimaging studies improves statistical power and cross-study comparability. Given significant brain changes in volume, microstructure, and connectivity during early life, we hypothesized that cortical areas in 1- to 3-year-olds would differ markedly from neonates and increasingly resemble adult patterns as development progresses. Here, we parcellated the cerebral cortex into putative areas using local functional connectivity gradients in 92 toddlers at 2 years old. We demonstrate high reproducibility of these cortical regions across 1- to 3-year-olds in two independent datasets. The area boundaries in 1- to 3-year-olds were more similar to those in adults than those in neonates. While the age-specific group area parcellation better fit the underlying functional connectivity in individuals during the first 3 years, adult area parcellations might still have some utility in developmental studies, especially in children older than 6 years. Additionally, we provide connectivity-based community assignments of the parcels, showing fragmented anterior and posterior components based on the strongest connectivity, yet alignment with adult systems when weaker connectivity was included.

The Brain That Understands Diversity: A Pilot Study Focusing on the Triple Network

Background/Objectives: Interest in diversity is growing worldwide. Today, an understanding and social acceptance of diverse people is becoming increasingly important. Therefore, in this study, we aimed to clarify the relationship between an individual's gray matter volume (GMV), which is thought to reflect brain health, and their understanding of diversity (gender, sexuality (LGBTQ), and origin). Methods: GMV was determined as the value of the Gray Matter Brain Healthcare Quotient (GM-BHQ) based on MRI image analysis. Meanwhile, participants' understanding and acceptance of diversity was calculated based on their answers to the psychological questions included in the World Values Survey Wave 7 (WVS7). Results: Our analysis indicated that, in the group of participants with the highest understanding of diversity (PHUD. n = 11), not only the GMV at the whole brain level (t = 2.587, p = 0.027, Cohen's d = 0.780) but also the GMV of the central executive network (CEN: t = 2.700, p= 0.022, Cohen's d = 0.814) and saliency network (SN: t = 3.100, p = 0.011, Cohen's d = 0.935) were shown to be significantly higher than the theoretical value estimated from sex, age, and BMI at the 5% level. In addition, the GMV of the default mode network (DMN: t = 2.063, p = 0.066, Cohen's d = 0.622) was also higher than the theoretical value at the 10% level. Meanwhile, in the group of others (n = 10), there was no significant difference from the theoretical value. These differences between PHUD and others were also observed when comparing the two with and without controlling for educational and occupational covariates at the 5% or 10% levels. Conclusions: These results suggest that understanding diversity requires a healthy brain, centered on three networks that govern rational judgment, emotion regulation, other-awareness, self-awareness, and the valuing of actions. This is the first study to show that brain structure is related to an understanding and acceptance of the diversity of people.

Multiple brain activation patterns for the same perceptual decision-making task

Meaningful variation in internal states that impacts cognition and behavior remains challenging to discover and characterize. Here we leverage trial-to-trial fluctuations in the brain-wide signal recorded using functional MRI to test if distinct sets of brain regions are activated on different trials when accomplishing the same task. Across three different perceptual decision-making experiments, we estimate the brain activations for each trial. We then cluster the trials based on their similarity using modularity-maximization, a data-driven classification method. In each experiment, we find multiple distinct but stable subtypes of trials, suggesting that the same task can be accomplished in the presence of widely varying brain activation patterns. Surprisingly, in all experiments, one of the subtypes exhibits strong activation in the default mode network, which is typically thought to decrease in activity during tasks that require externally focused attention. The remaining subtypes are characterized by activations in different task-positive areas. The default mode network subtype is characterized by behavioral signatures that are similar to the other subtypes exhibiting activation with task-positive regions. These findings demonstrate that the same perceptual decision-making task is accomplished through multiple brain activation patterns.

Abnormal Alterations of the White Matter Structural Network in Patients with Herpes Zoster and Postherpetic Neuralgia

PHN is one of the most common clinical complications of herpes zoster (HZ), the pathogenesis of which is unclear and poorly treated clinically, and many studies now suggest that postherpetic neuralgia (PHN) pain may be related to central neurologic mechanisms. This study aimed to investigate the white matter structural networks and changes in the organization of the rich-club in HZ and PHN. Diffusion imaging (DTI) data from 89 PHN patients, 76 HZ patients, and 66 healthy controls (HCs) were used to construct corresponding structural networks. Using graph-theoretic analysis, changes in the overall and local characteristics of the structural networks and rich-club organization were analyzed, and their correlations with clinical scales were analyzed. Compared with HCs, PHN patients had reduced global efficiency (Eg), reduced local efficiency (Eloc), a reduced clustering coefficient (Cp), a longer characteristic path length (Lp), and reduced nodal efficiency (Ne) in several brain regions, including the right posterior cingulate gyrus, the right supraoccipital gyrus, the bilateral postcentral gyrus, and the right precuneus; HZ patients had reduced Eg, a longer Lp, and reduced right orbital frontalis suprachiasmatic Ne. Moreover, HZ and PHN patients showed a significant reduction in the strength of rich-club connections. Compared with HZ patients, the intensities of the rich-club and feeder connections were lower in the PHN patients. Moreover, the changes in the structural networks and rich-club organization topology indices of the patients in the HZ and PHN patients were significantly correlated with disease duration, pain scores, and emotional changes. The structural networks of HZ and PHN patients exhibited reduced network transmission efficiency and rich-club connectivity, possibly due to structural damage to the white matter, and this was more obvious in PHN patients. The rich-club connectivity of HZ patients showed incomplete compensation in the acute pain stage.

Differential links in 16p11.2 deletion carriers reveal aberrant connections between large-scale networks

Qualitatively different topographical patterns of connections are thought to underlie individual differences in thought and behavior, particularly at heteromodal association areas. As such, we hypothesized that connections unique to 16p11.2 deletion carriers compared to controls, rather than hyper- or hypo-connectivity, would serve as a better model to explain the cognitive and behavioral changes observed in individuals carrying this autism-risk copy number variation. Using a spatially-unbiased, data-driven approach we found that differential links clustered non-uniformly across the cortex-particularly at the superior temporal gyrus and sulcus, posterior insula, cingulate sulcus, and inferior parietal lobule bilaterally. At these hotspots, altered local connectivity that spanned across the borders of cortical large-scale networks coincided with aberrant distant interconnectivity between large-scale networks. This was most evident between the auditory and the dorsomedial default (DNb) networks-such that greater between-network interconnectivity was associated with greater communication and social impairment. Entangled connectivity between large-scale networks may preclude each network from having the necessary fidelity to operate properly, particularly when the 2 networks have opposing organization principles-namely, local specialization (segregation) versus global coherency (integration).

Increased default mode network activation in depression and social anxiety during upward social comparison

Social comparisons are a core feature of human life. Theories posit that social comparisons play a critical role in depression and social anxiety triggering negative evaluations about the self, as well as negative emotions. We investigated the neural basis of social comparisons in participants with major depression and/or social anxiety (MD-SA, n = 56) and healthy controls (n = 47) using functional magnetic resonance imaging. While being scanned participants performed a social comparison task, during which they received feedback about their performance and the performance of a coplayer. Upward social comparisons (being worse than the coplayer) elicited high levels of negative emotions (shame, guilt, and nervousness) across participants, with this effect being enhanced in the MD-SA group. Notably, during upward comparison the MD-SA group showed greater activation than the control group in regions of the default mode network (DMN). Specifically, for upward comparison MD-SA participants demonstrated increased activation in the dorsomedial prefrontal cortex and reduced deactivation in the posteromedial cortex, regions linked to self-referential processing, inferences about other people's thoughts, and rumination. Findings suggest that people with depression and social anxiety react to upward comparisons with a more negative emotional response, which may be linked to introspective processes related to the DMN.