Functional-anatomic fractionation of the brain's default network

Episodic recombination and the role of time in mental travel

Mental time travel is often presented as a singular mechanism, but theoretical and empirical considerations suggest that it is composed of component processes. What are these components? Three hypotheses about the major components of mental time travel are commonly considered: (i) remembering and imagining might, respectively, rely on different processes, (ii) past- and future-directed forms of mental time travel might, respectively, rely on different processes, and (iii) the creation of episodic representations and the determination of their temporal orientation might, respectively, rely on different processes. Here, we flesh out the last of these proposals. First, we argue for 'representational continuism': the view that different forms of mental travel are continuous with regard to their core representational contents. Next, we propose an updated account of episodic recombination (the mechanism generating these episodic contents) and review evidence in its support. On this view, episodic recombination is a natural kind best viewed as a form of compositional computation. Finally, we argue that episodic recombination should be distinguished from mechanisms determining the temporal orientation of episodic representations. Thus, we suggest that mental travel is a singular capacity, while mental time travel has at least two major components: episodic representations and their temporal orientation. This article is part of the theme issue 'Elements of episodic memory: lessons from 40 years of research'.

The promise of precision functional mapping for neuroimaging in psychiatry

Precision functional mapping (PFM) is a neuroimaging approach to reliably estimate metrics of brain function from individual people via the collection of large amounts of fMRI data (hours per person). This method has revealed much about the inter-individual variation of functional brain networks. While standard group-level studies, in which we average brain measures across groups of people, are important in understanding the generalizable neural underpinnings of neuropsychiatric disorders, many disorders are heterogeneous in nature. This heterogeneity often complicates clinical care, leading to patient uncertainty when considering prognosis or treatment options. We posit that PFM methods may help streamline clinical care in the future, fast-tracking the choice of personalized treatment that is most compatible with the individual. In this review, we provide a history of PFM studies, foundational results highlighting the benefits of PFM methods in the pursuit of an advanced understanding of individual differences in functional network organization, and possible avenues where PFM can contribute to clinical translation of neuroimaging research results in the way of personalized treatment in psychiatry.

The dorsomedial prefrontal cortex promotes self-control by inhibiting the egocentric perspective

The dorsomedial prefrontal cortex (dmPFC) plays a crucial role in social cognitive functions, including perspective-taking. Although perspective-taking has been linked to self-control, the mechanism by which the dmPFC might facilitate self-control remains unclear. Using the multimodal neuroimaging dataset from the Human Connectome Project (Study 1, N =978 adults), we established a reliable association between the dmPFC and self-control, as measured by discounting rate-the tendency to prefer smaller, immediate rewards over larger, delayed ones. Experiments (Study 2, N = 36 adults) involving high-definition transcranial direct current stimulation showed that anodal stimulation of the dmPFC reduces the discounting of delayed rewards and decreases the congruency effect in egocentric but not allocentric perspective in the visual perspective-taking tasks. These findings suggest that the dmPFC promotes self-control by inhibiting the egocentric perspective, offering new insights into the neural underpinnings of self-control and perspective-taking, and opening new avenues for interventions targeting disorders characterized by impaired self-regulation.

Breakthroughs and challenges for generating brain network-based biomarkers of treatment response in depression

Treatment outcomes widely vary for individuals diagnosed with major depressive disorder, implicating a need for deeper understanding of the biological mechanisms conferring a greater likelihood of response to a particular treatment. Our improved understanding of intrinsic brain networks underlying depression psychopathology via magnetic resonance imaging and other neuroimaging modalities has helped reveal novel and potentially clinically meaningful biological markers of response. And while we have made considerable progress in identifying such biomarkers over the last decade, particularly with larger, multisite trials, there are significant methodological and practical obstacles that need to be overcome to translate these markers into the clinic. The aim of this review is to review current literature on brain network structural and functional biomarkers of treatment response or selection in depression, with a specific focus on recent large, multisite trials reporting predictive accuracy of candidate biomarkers. Regarding pharmaco- and psychotherapy, we discuss candidate biomarkers, reporting that while we have identified candidate biomarkers of response to a single intervention, we need more trials that distinguish biomarkers between first-line treatments. Further, we discuss the ways prognostic neuroimaging may help to improve treatment outcomes to neuromodulation-based therapies, such as transcranial magnetic stimulation and deep brain stimulation. Lastly, we highlight obstacles and technical developments that may help to address the knowledge gaps in this area of research. Ultimately, integrating neuroimaging-derived biomarkers into clinical practice holds promise for enhancing treatment outcomes and advancing precision psychiatry strategies for depression management. By elucidating the neural predictors of treatment response and selection, we can move towards more individualized and effective depression interventions, ultimately improving patient outcomes and quality of life.

Intersubject Dynamic Conditional Correlation: A Novel Method to Track the Framewise Network Implication during Naturalistic Stimuli

Background: Naturalistic stimuli have become increasingly popular in modern cognitive neuroscience. These stimuli have high ecological validity due to their rich and multilayered features. However, their complexity also presents methodological challenges for uncovering neural network reconfiguration. Dynamic functional connectivity using the sliding-window technique is commonly used but has several limitations. In this study, we introduce a new method called intersubject dynamic conditional correlation (ISDCC). Method: ISDCC uses intersubject analysis to remove intrinsic and non-neuronal signals, retaining only intersubject-consistent stimuli-induced signals. It then applies dynamic conditional correlation (DCC) based on the generalized autoregressive conditional heteroskedasticity to calculate the framewise functional connectivity. To validate ISDCC, we analyzed simulation data with known network reconfiguration patterns and two publicly available narrative functional Magnetic Resonance Imaging (fMRI) datasets. Results: (1) ISDCC accurately unveiled the underlying network reconfiguration patterns in simulation data, demonstrating greater sensitivity than DCC; (2) ISDCC identified synchronized network reconfiguration patterns across listeners; (3) ISDCC effectively differentiated between stimulus types with varying temporal coherence; and (4) network reconfigurations unveiled by ISDCC were significantly correlated with listener engagement during narrative comprehension. Conclusion: ISDCC is a precise and dynamic method for tracking network implications in response to naturalistic stimuli.

Could Relationship-Based Learnt Beliefs and Expectations Contribute to Physiological Vulnerability of Chronic Pain? Making a Case to Consider Attachment in Pain Research

Pain is an interpersonal and inherently social experience. Pain perception and administration of medical treatment all occur in a particular environmental and social context. Early environmental influences and early learning experiences and interactions condition the body's response to different threats (like pain), ultimately shaping the underlying neurophysiology. These early interactions and experiences also determine what situations are perceived as threatening, as well as our belief in our own ability to self-manage, and our belief in others to offer support, during perceived threats. These beliefs intrinsically drive the combination of behaviors that emerge in response to perceived threats, including pain. Such behaviors can be categorized into attachment styles. In this interdisciplinary review, we synthesize and summarize evidence from the neurobiological, psychobiological, psychosocial, and psychobehavioral fields, to describe how these beliefs are embedded in the brain's prediction models to generate a series of expectations/perceptions around the level of safety/threat in different contexts. As such, these beliefs may predict how one experiences and responds to pain, with potentially significant implications for the development and management of chronic pain. Little attention has been directed to the effect of adult attachment style on pain in research studies and in the clinical setting. Using interdisciplinary evidence, we argue why we think this interaction merits further consideration and research. PERSPECTIVE: This review explores the influence of attachment styles on pain perception, suggesting a link between social connections and chronic pain development. It aligns with recent calls to emphasize the social context in pain research and advocates for increased focus on adult attachment styles in research and clinical practice.

Impact of moderate aerobic exercise on small-world topology and characteristics of brain networks after sport-related concussion: an exploratory study

Sport-related concussion (SRC) is a complex brain injury. By applying graph-theoretical analysis to networks derived from neuroimaging techniques, studies have shown that despite an overall retention of small-world topology, changes in small-world properties occur after brain injury. Less is known about how exercise during athletes' return to sport (RTS) influences these brain network properties. Therefore, in the present study dense electroencephalography (EEG) datasets were collected pre- and post-moderate aerobic exercise. Small-world properties of whole brain (WB) and the default mode network (DMN) were extracted from the EEG datasets of 21 concussed athletes and 21 healthy matched controls. More specifically, path length (LP), clustering coefficient (CP), and small-world index (SWI) in binary and weighted graphs were calculated in the alpha frequency band (7-13 Hz). Pre-exercise, SRC athletes had higher DMN-CP values compared to controls, while post-exercise SRC athletes had higher WB-LP compared to controls. Weighted WB analysis revealed a significant association between SRC and the absence of small-world topology (SWI ≤ 1) post-exercise. This explorative study provides preliminary evidence that moderate aerobic exercise during athletes' RTS induces an altered network response. Furthermore, this altered response may be related to the clinical characteristics of the SRC athlete.

Structural and functional alterations in MRI-negative drug-resistant epilepsy and associated gene expression features

Neuroimaging techniques have been widely used in the study of epilepsy. However, structural and functional changes in the MRI-negative drug-resistant epilepsy (DRE) and the genetic mechanisms behind the structural alterations remain poorly understood. Using structural and functional MRI, we analyzed gray matter volume (GMV) and regional homogeneity (ReHo) in DRE, drug-sensitive epilepsy (DSE) and healthy controls. Gene expression data from Allen human brain atlas and GMV/ReHo were evaluated to obtain drug resistance-related and epilepsy-associated gene expression and compared with real transcriptional data in blood. We found structural and functional alterations in the cerebellum of DRE patients, which may be related to the mechanisms of drug resistance in DRE. Our study confirms that changes in brain morphology and regional activity in DRE patients may be associated with abnormal gene expression related to nervous system development. And SP1, as an important transcription factor, plays an important role in the mechanism of drug resistance.

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.

A Wearable, Steerable, Transcranial Low-Intensity Focused Ultrasound System

OBJECTIVES

Transcranial low-intensity focused ultrasound (LIFU) offers unique opportunities for precisely neuromodulating small and/or deep targets within the human brain, which may be useful for treating psychiatric and neurological disorders. This article presents a novel ultrasound system that delivers focused ultrasound through the forehead to anterior brain targets and evaluates its safety and usability in a volunteer study.

METHODS

The ultrasound system and workflow are described, including neuronavigation, LIFU planning, and ultrasound delivery components. Its capabilities are analyzed through simulations and experiments in water to establish its safe steering range. A cohort of 20 healthy volunteers received a LIFU protocol aimed at the anterior medial prefrontal cortex (amPFC), using imaging and questionnaires to screen for adverse effects. Additional development after the study also analyzes the effect of the skull and sinus cavities on delivered ultrasound energy.

RESULTS

Simulations and hydrophone readings agreed with <5% error, and the safe steering range was found to encompass a 1.8 cm × 2.5 cm × 2 cm volume centered at a depth 5 cm from the surface of the skin. There were no adverse effects evident on qualitative assessments, nor any signs of damage in susceptibility-weighted imaging scans. All participants tolerated the treatment well. The interface effectively enabled the users to complete the workflow with all participants. In particular, the amPFC of every participant was within the steering limits of the system. A post hoc analysis showed that "virtual fitting" could aid in steering the beams around subjects' sinuses.

CONCLUSIONS

The presented system safely delivered LIFU through the forehead while targeting the amPFC in all volunteers, and was well-tolerated. With the capabilities validated here and positive results of the study, this technology appears well-suited to explore LIFU's efficacy in clinical neuromodulation contexts.

Frequent absent mindedness and the neural mechanism trapped by mobile phone addiction

INTRODUCTION

With the increased availability and sophistication of digital devices in the last decade, young people have become mainstream mobile phone users. Heavy mobile phone dependence causes affective problems (depression, anxiety) and loss of attention on current activities, leading to more cluttered thoughts. Problematic mobile phone use has been found to increase the occurrence of mind wandering, but the neural mechanism underlying this relationship remains unclear.

METHOD

The current study aimed to investigate the neural mechanism between mobile phone use and mind wandering. 459 university students (averaged age, 19.26 years) from datasets (ongoing research project named Gene-Brain-Behavior project, GBB) completed psychological assessments of mobile phone addiction and mind wandering and underwent resting-state functional connectivity (FC) scanning. FC matrix was constructed to further conduct correlation and mediation analyses.

RESULTS

Students with high mobile phone addiction scores were more likely to have high mind wandering scores. Functional connectivity among the default mode, motor, frontoparietal, basal ganglia, limbic, medial frontal, visual association, and cerebellar networks formed the neural basis of mind wandering. Functional connectivity between the frontoparietal and motor networks, between the default mode network and cerebellar network, and within the cerebellar network mediated the relationship between mobile phone addiction and mind wandering.

CONCLUSION

The findings of this study confirm that mobile phone addiction is a risk factor for increased mind wandering and reveal that FC in several brain networks underlies this relationship. They contribute to research on behavioral addiction, education, and mental health among young adults.

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.

Reduced resting-state functional connectivity of default mode network subsystems in patients with obsessive-compulsive disorder

OBJECTIVES

Neuroimaging studies have reported extensive resting-state functional connectivity (rsFC) abnormalities in the default mode network (DMN) in patients with obsessive-compulsive disorder (OCD), but findings are inconsistent. DMN can be divided into three subsystems: core, dorsal medial prefrontal cortex (dMPFC), and medial temporal lobe (MTL). This study aimed to explore abnormalities in rsFC strength within and between DMN subsystems in OCD patients, and their relationship with clinical symptoms.

METHODS

This study recruited 39 OCD patients and 45 healthy controls (HCs). OCD symptoms were assessed using the Yale-Brown Obsessive-Compulsive Scale (YBOCS). The seed-to-seed method was used to construct rsFC matrix. The rsFC strength within and between the three DMN subsystems were calculated.

RESULTS

Compared to the HC group, the OCD group exhibited reduced rsFC strength within core subsystem (F = 7.799, p = 0.007, Bonferroni corrected p = 0.042). Further, this reduction was also observed in the unmedicated OCD group (n = 19), but not in the medicated OCD group (n = 18). In addition, rsFC strength within core subsystem was negatively correlated with the obsession subscale of YBOCS in the OCD group (r = -0.512, p = 0.004, Bonferroni corrected p = 0.008). Further, this correlation was also significant in the unmedicated OCD group, but not in the medicated OCD group.

CONCLUSIONS

Our findings suggest that reduced rsFC strength within core subsystem is a feature of OCD patients and may serve as a potential biomarker of obsession severity. Moreover, pharmacological treatments may affect rsFC strength in DMN.

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.

Social and emotional learning in the cerebellum

The posterior cerebellum has a critical role in human social and emotional learning. Three systems and related neural networks support this cerebellar function: a biological action observation system as part of an extended sensorimotor integration network, a mentalizing system for understanding a person's mental and emotional state subserved by a mentalizing network, and a limbic network supporting core emotional (dis)pleasure and arousal processes. In this Review, I describe how these systems and networks support social and emotional learning via functional reciprocal connections initiating and terminating in the posterior cerebellum and cerebral neocortex. It is hypothesized that a major function of the posterior cerebellum is to identify and encode temporal sequences of events, which might help to fine-tune and automatize social and emotional learning. I discuss research using neuroimaging and non-invasive stimulation that provides converging evidence for this hypothesized function of cerebellar sequencing, but also other potential functional accounts of the posterior cerebellum's role in these social and emotional processes.

Functional activity and connectivity signatures of ketamine and lamotrigine during negative emotional processing: a double-blind randomized controlled fMRI study

Ketamine is a highly effective antidepressant (AD) that targets the glutamatergic system and exerts profound effects on brain circuits during negative emotional processing. Interestingly, the effects of ketamine on brain measures are sensitive to modulation by pretreatment with lamotrigine, which inhibits glutamate release. Examining the antagonistic effects of ketamine and lamotrigine on glutamate transmission holds promise to identify effects of ketamine that are mediated through changes in the glutamatergic system. Investigating this modulation in relation to both the acute and sustained effects of ketamine on functional activity and connectivity during negative emotional processing should therefore provide novel insights. 75 healthy subjects were investigated in a double-blind, single-dose, randomized, placebo-controlled, parallel-group study with three treatment conditions (ketamine, lamotrigine pre-treatment, placebo). Participants completed an emotional face viewing task during ketamine infusion and 24 h later. Acute ketamine administration decreased hippocampal and Default Mode Network (DMN) activity and increased fronto-limbic coupling during negative emotional processing. Furthermore, while lamotrigine abolished the ketamine-induced increase in functional connectivity, it had no acute effect on activity. Sustained (24 h later) effects of ketamine were only found for functional activity, with a significant reduction in the posterior DMN. This effect was blocked by pretreatment with lamotrigine. Our results suggest that both the acute increases in fronto-limbic coupling and the delayed decrease in posterior DMN activity, but not the attenuated limbic and DMN recruitment after ketamine, are mediated by altered glutamatergic transmission.

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.

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.

Cerebral glucose metabolism in Alzheimer's disease

18F-fluoro-deoxy-glucose positron emission tomography (FDG-PET) is a useful paraclinical exam for the diagnosis of Alzheimer's disease (AD). In this narrative review, we report seminal studies in clinically probable AD that have shown the importance of posterior brain metabolic decrease and the paradoxical variability of the hippocampal metabolism. The FDG-PET pattern was a sensitive indicator of AD in pathologically confirmed cases and it was used for differential diagnosis of dementia conditions. In prodromal AD, the AD FDG-PET pattern was observed in converters and predicted conversion. Automated data analysis techniques provided variable accuracy according to the reported indices and machine learning methods showed variable reliability of results. FDG-PET could confirm AD clinical heterogeneity and image data driven analyses identified hypometabolic subtypes with variable involvement of the hippocampus, reminiscent if the paradoxical FDG uptake. In studies dedicated to clinical and metabolic correlations, episodic memory was related to metabolism in the default mode network (and Papez's circuit) in prodromal and mild AD stages, and specific cognitive processes were associated to precisely distributed brain metabolism. Cerebral metabolic correlates of anosognosia could also be related to current neuropsychological models. AD FDG-PET pattern was reported in preclinical AD stages and related to cognition or to conversion to mild cognitive impairment (MCI). Using other biomarkers, the AD FDG-PET pattern was confirmed in AD participants with positive PET-amyloid. Intriguing observations reported increased metabolism related to brain amyloid and/or tau deposition. Preserved glucose metabolism sometimes appear as a compensation, but it was frequently detrimental and the nature of such a preservation of glucose metabolism remains an open question. Limbic metabolic involvement was frequently related to non-AD biomarkers profile and clinical stability, and it was reported in non-AD pathologies, such as the limbic predominant age-related encephalopathy (LATE). FDG-PET abnormalities observed in the absence of classical AD proteinopathies can be useful to search for pathological mechanisms and differential diagnosis of AD.

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.

Individual variability in neural representations of mind-wandering

Mind-wandering is a frequent, daily mental activity, experienced in unique ways in each person. Yet neuroimaging evidence relating mind-wandering to brain activity, for example in the default mode network (DMN), has relied on population- rather than individual-based inferences owing to limited within-person sampling. Here, three densely sampled individuals each reported hundreds of mind-wandering episodes while undergoing multi-session functional magnetic resonance imaging. We found reliable associations between mind-wandering and DMN activation when estimating brain networks within individuals using precision functional mapping. However, the timing of spontaneous DMN activity relative to subjective reports, and the networks beyond DMN that were activated and deactivated during mind-wandering, were distinct across individuals. Connectome-based predictive modeling further revealed idiosyncratic, whole-brain functional connectivity patterns that consistently predicted mind-wandering within individuals but did not fully generalize across individuals. Predictive models of mind-wandering and attention that were derived from larger-scale neuroimaging datasets largely failed when applied to densely sampled individuals, further highlighting the need for personalized models. Our work offers novel evidence for both conserved and variable neural representations of self-reported mind-wandering in different individuals. The previously unrecognized interindividual variations reported here underscore the broader scientific value and potential clinical utility of idiographic approaches to brain-experience associations.

Symptomatology after damage to the angular gyrus through the lenses of modern lesion-symptom mapping

Brain-behavior relationships are complex. For instance, one might know a brain region's function(s) but still be unable to accurately predict deficit type or severity after damage to that region. Here, I discuss the case of damage to the angular gyrus (AG) that can cause left-right confusion, finger agnosia, attention deficit, and lexical agraphia, as well as impairment in sentence processing, episodic memory, number processing, and gesture imitation. Some of these symptoms are grouped under AG syndrome or Gerstmann's syndrome, though its exact underlying neuronal systems remain elusive. This review applies recent frameworks of brain-behavior modes and principles from modern lesion-symptom mapping to explain symptomatology after AG damage. It highlights four major issues for future studies: (1) functionally heterogeneous symptoms after AG damage need to be considered in terms of the degree of damage to (i) different subdivisions of the AG, (ii) different AG connectivity profiles that disconnect AG from distant regions, and (iii) lesion extent into neighboring regions damaged by the same infarct. (2) To explain why similar symptoms can also be observed after damage to other regions, AG damage needs to be studied in terms of the networks of regions that AG functions with, and other independent networks that might subsume the same functions. (3) To explain inter-patient variability on AG symptomatology, the degree of recovery-related brain reorganisation needs to account for time post-stroke, demographics, therapy input, and pre-stroke differences in functional anatomy. (4) A better integration of the results from lesion and functional neuroimaging investigations of AG function is required, with only the latter so far considering AG function in terms of a hub within the default mode network. Overall, this review discusses why it is so difficult to fully characterize the AG syndrome from lesion data, and how this might be addressed with modern lesion-symptom mapping.

The "limbic network," comprising orbitofrontal and anterior temporal cortex, is part of an extended default network: Evidence from multi-echo fMRI

Resting-state functional magnetic resonance imaging (fMRI) investigations have provided a view of the default network (DN) as composed of a specific set of frontal, parietal, and temporal cortical regions. This spatial topography is typically defined with reference to an influential network parcellation scheme that designated the DN as one of seven large-scale networks (Yeo et al., 2011). However, the precise functional organization of the DN is still under debate, with studies arguing for varying subnetwork configurations and the inclusion of subcortical regions. In this vein, the so-called limbic network-defined as a distinct large-scale network comprising the bilateral temporal poles, ventral anterior temporal lobes, and orbitofrontal cortex-is of particular interest. A large multi-modal and multi-species literature on the anatomical, functional, and cognitive properties of these regions suggests a close relationship to the DN. Notably, these regions have poor signal quality with conventional fMRI acquisition, likely obscuring their network affiliation in most studies. Here, we leverage a multi-echo fMRI dataset with high temporal signal-to-noise and whole-brain coverage, including orbitofrontal and anterior temporal regions, to examine the large-scale network resting-state functional connectivity of these regions and assess their associations with the DN. Consistent with our hypotheses, our results support the inclusion of the majority of the orbitofrontal and anterior temporal cortex as part of the DN and reveal significant heterogeneity in their functional connectivity. We observed that left-lateralized regions within the temporal poles and ventral anterior temporal lobes, as well as medial orbitofrontal regions, exhibited the greatest resting-state functional connectivity with the DN, with heterogeneity across DN subnetworks. Overall, our findings suggest that, rather than being a functionally distinct network, the orbitofrontal and anterior temporal regions comprise part of a larger, extended default network.

Metabolic syndrome is associated with reduced default mode network functional connectivity in young post-9/11 Veterans

Metabolic syndrome is a collection of health factors that increases risk for cardiovascular disease. A condition of aging, metabolic syndrome is associated with reduced brain network integrity, including functional connectivity alterations among the default mode, regions vulnerable to neurodegeneration. Prevalence of metabolic syndrome is elevated in younger populations including post-9/11 Veterans and individuals with posttraumatic stress disorder, but it is unclear whether metabolic syndrome affects brain function in earlier adulthood. Identifying early effects of metabolic syndrome on brain network integrity is critical, as these impacts could contribute to increased risk for cognitive disorders later in life for Veterans. The current study examined whether metabolic syndrome and its individual components were associated with default mode functional connectivity. We also explored the contribution of posttraumatic stress disorder and traumatic brain injury on these metabolic syndrome-brain relationships. Post-9/11 Veterans with combat deployment history (95 with and 325 without metabolic syndrome) underwent functional magnetic resonance imaging to capture seed-based resting-state functional connectivity within the default mode. The metabolic syndrome group demonstrated reduced positive functional connectivity between the posterior cingulate cortex seed and the bilateral superior frontal gyrus. Data-driven analyses demonstrated that metabolic syndrome components, particularly cholesterol and central adiposity, were associated with widespread reductions in default mode network connectivity. Functional connectivity was also reduced in participants with metabolic syndrome but without current posttraumatic stress disorder diagnosis and with traumatic brain injury history. These results suggest that metabolic syndrome disrupts resting-state functional connectivity decades earlier than prior work has shown.

Retinotopic coding organizes the opponent dynamic between internally and externally oriented brain networks

How the human brain integrates internally- (i.e., mnemonic) and externally-oriented (i.e., perceptual) information is a long-standing puzzle in neuroscience. In particular, the internally-oriented networks like the default network (DN) and externally-oriented dorsal attention networks (dATNs) are thought to be globally competitive, which implies DN disengagement during cognitive states that drive the dATNs and vice versa. If these networks are globally opposed, how is internal and external information integrated across these networks? Here, using precision neuroimaging methods, we show that these internal/external networks are not as dissociated as traditionally thought. Using densely sampled high-resolution fMRI data, we defined individualized whole-brain networks from participants at rest, and the retinotopic preferences of individual voxels within these networks during an independent visual mapping task. We show that while the overall network activity between the DN and dATN is opponent at rest, a latent retinotopic code structures this global opponency. Specifically, the anti-correlation (i.e., global opponency) between the DN and dATN at rest is structured at the voxel-level by each voxel's retinotopic preferences, such that the spontaneous activity of voxels preferring similar visual field locations are more anti-correlated than those that prefer different visual field locations. Further, this retinotopic scaffold integrates with the domain-specific preferences of subregions within these networks, enabling efficient, parallel processing of retinotopic and domain-specific information. Thus, DN and dATN dynamics are opponent, but not competitive: voxel-scale anti-correlation between these networks preserves and encodes information in the negative BOLD responses, even in the absence of visual input or task demands. These findings suggest that retinotopic coding may serve as a fundamental organizing principle for brain-wide communication, providing a new framework for understanding how the brain balances and integrates internal cognition with external perception.

The Neural Correlates of Alcohol Approach Bias - New Insights from a Whole-Brain Network Analysis Perspective

Alcohol approach bias, a tendency to approach rather than to avoid alcohol and alcohol-related cues regardless of associated negative consequences, is an emerging key characteristic of alcohol use disorder (AUD). Reaction times from the Approach-Avoidance Task (AAT) can be used to quantify alcohol approach bias. However, only a handful of studies have investigated the neural correlates of implicit alcohol approach behavior. Graph Theory Analysis (GTA) metrics, specifically, weighted global efficiency (wGE), community detection, and inter-community information integration were used to analyze functional magnetic resonance imaging (fMRI) data of an in-scanner version of the AAT from 31 heavy drinking Veterans with AUD (HDV) engaged in out-patient treatment and 19 healthy Veterans as controls (HC). We found a functional imprint of alcohol approach bias in HDVs. HDVs showed significantly higher wGE values for approaching than for avoiding alcohol, indicating that their brain was more efficiently organized or functionally set to approach alcohol in the presence to alcohol-related external cues. In contrast, Brains of HCs did not show such a processing advantage for either the approach or avoid condition. Further post-hoc analyses revealed that HDVs and HCs differed in how they implemented top-down control when approaching/avoiding alcohol and in how the fronto-parietal control network interacted with subsystems of the default mode network. These findings contribute to understanding the complex neural underpinnings of alcohol approach bias and lay the foundation for developing more potent and targeted interventions to modify these neural patterns in AUD patients.

High-resolution awake mouse fMRI at 14 Tesla

High-resolution awake mouse fMRI remains challenging despite extensive efforts to address motion-induced artifacts and stress. This study introduces an implantable radiofrequency (RF) surface coil design that minimizes image distortion caused by the air/tissue interface of mouse brains while simultaneously serving as a headpost for fixation during scanning. Furthermore, this study provides a thorough acclimation method used to accustom animals to the MRI environment minimizing motion induced artifacts. Using a 14T scanner, high-resolution fMRI enabled brain-wide functional mapping of visual and vibrissa stimulation at 100×100×200μm resolution with a 2s per frame sampling rate. Besides activated ascending visual and vibrissa pathways, robust BOLD responses were detected in the anterior cingulate cortex upon visual stimulation and spread through the ventral retrosplenial area (VRA) with vibrissa air-puff stimulation, demonstrating higher-order sensory processing in association cortices of awake mice. In particular, the rapid hemodynamic responses in VRA upon vibrissa stimulation showed a strong correlation with the hippocampus, thalamus, and prefrontal cortical areas. Cross-correlation analysis with designated VRA responses revealed early positive BOLD signals at the contralateral barrel cortex (BC) occurring 2 seconds prior to the air-puff in awake mice with repetitive stimulation, which was not detected using a randomized stimulation paradigm. This early BC activation indicated a learned anticipation through the vibrissa system and association cortices in awake mice under continuous training of repetitive air-puff stimulation. This work establishes a high-resolution awake mouse fMRI platform, enabling brain-wide functional mapping of sensory signal processing in higher association cortical areas.

Neural Activity Differentiates Novel and Learned Event Boundaries

People parse continuous experiences at natural breakpoints called event boundaries, which is important for understanding an environment's causal structure and for responding to uncertainty within it. However, it remains unclear how different forms of uncertainty affect the parsing of continuous experiences and how such uncertainty influences the brain's processing of ongoing events. We exposed human participants of both sexes (N = 34) to a continuous sequence of semantically meaningless images. We generated sequences from random walks through a graph that grouped images into temporal communities. After learning, we asked participants to segment another sequence at natural breakpoints (event boundaries). Participants segmented the sequence at learned transitions between communities, as well as at novel transitions, suggesting that people can segment temporally extended experiences into events based on learned structure as well as prediction error. Greater segmentation at novel boundaries was associated with enhanced parietal scalp electroencephalography (EEG) activity between 250 and 450 ms after the stimulus onset. Multivariate classification of EEG activity showed that novel and learned boundaries evoked distinct patterns of neural activity, particularly theta band power in posterior electrodes. Learning also led to distinct neural representations for stimuli within the temporal communities, while neural activity at learned boundary nodes showed predictive evidence for the adjacent community. The data show that people segment experiences at both learned and novel boundaries and suggest that learned event boundaries trigger retrieval of information about the upcoming community that could underlie anticipation of the next event in a sequence.

Disconnection of alpha oscillations within default mode network associated with memory dysfunction in amnestic MCI

OBJECTIVE

Episodic memory dysfunction and alterations of functional connectivity (FC) in default mode network (DMN) were found in patients with amnestic mild cognitive impairment (aMCI). However, previous studies were limited in probing certain oscillations within the DMN. This study employed measures of resting-state FC across various oscillations within the DMN to comprehensively examine the FC and its association with episodic memory performance in aMCI.

METHODS

Twenty-six healthy controls (HC) and 30 patients with aMCI were recruited to perform resting-state magnetoencephalographic recordings. We compared the spectral powers and peak frequency values in each frequency band and FC within the DMN between these two groups. The associations of FC values with memory performance were also examined.

RESULTS

No significant between-group differences in spectral powers and peak frequency values were observed in the regional nodes. Patients with aMCI exhibited diminished alpha-band FC as compared to HC. Furthermore, lower alpha-band FC between the medial temporal cortex - and the posterior cingulate cortex/precuneus was correlated with poorer memory performance.

CONCLUSIONS

Aberrant DMN connectivity, particularly in the alpha frequency range, might be a neural correlate of episodic memory impairment.

SIGNIFICANCE

Our results inform the potential development of brain stimulation in managing memory impairments in aMCI.

Functional connectivity of the default mode network in first-episode drug-naïve patients with major depressive disorder

BACKGROUND

Alterations in the default mode network (DMN) have been reported in major depressive disorder (MDD), well-replicated robust alterations of functional connectivity (FC) of DMN remain to be established. Investigating the functional connections of DMN at the overall and subsystem level in early MDD patients has the potential to advance our understanding of the physiopathology of this disorder.

METHODS

We recruited 115 first-episode drug-naïve patients with MDD and 137 demographic-matched healthy controls (HCs). We first compared FC within the DMN, within/between the DMN subsystems, and from DMN subsystems to the whole brain between groups. Subsequently, we explored correlations between clinical features and identified alterations in FC.

RESULTS

First-episode drug-naïve patients with MDD showed significantly increased FC within the DMN, dorsal DMN and medial DMN. Each subsystem showed a distinct FC pattern with other brain networks. Increased FC between the subsystems (core DMN, dorsal DMN) and other networks was associated with more severe depressive symptoms, while medial DMN-related connectivity correlated with memory performance.

LIMITATIONS

The relatively large "pure" MDD sample could only be generalized to a limited population. And, atypical asymmetric FCs in the DMN related to MDD might be missed for only left-lateralized ROIs were used to avoid strong correlations between mirrored (right/left) seed regions.

CONCLUSION

These findings suggest patients with early MDD showed distinct patterns of FC alterations throughout DMN and its subsystems, which were related to illness severity and illness-associated cognitive impairment, highlighting their clinical significance.

Operatic voices engage the default mode network in professional opera singers

Extensive research with musicians has shown that instrumental musical training can have a profound impact on how acoustic features are processed in the brain. However, less is known about the influence of singing training on neural activity during voice perception, particularly in response to salient acoustic features, such as the vocal vibrato in operatic singing. To address this gap, the present study employed functional magnetic resonance imaging (fMRI) to measure brain responses in trained opera singers and musically untrained controls listening to recordings of opera singers performing in two distinct styles: a full operatic voice with vibrato, and a straight voice without vibrato. Results indicated that for opera singers, perception of operatic voice led to differential fMRI activations in bilateral auditory cortical regions and the default mode network. In contrast, musically untrained controls exhibited differences only in bilateral auditory cortex. These results suggest that operatic singing training triggers experience-dependent neural changes in the brain that activate self-referential networks, possibly through embodiment of acoustic features associated with one's own singing style.

Early Life Neuroimaging: The Generalizability of Cortical Area Parcellations Across Development

The cerebral cortex comprises discrete cortical areas that form during development. Accurate area parcellation in neuroimaging studies enhances statistical power and comparability across studies. The formation of cortical areas is influenced by intrinsic embryonic patterning as well as extrinsic inputs, particularly through postnatal exposure. Given the substantial changes in brain volume, microstructure, and functional connectivity during the first years of life, we hypothesized that cortical areas in 1-to-3-year-olds would exhibit major differences from those in neonates and progressively resemble adults 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 demonstrated 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 adults than neonates. While the age-specific group parcellation fitted better to 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 provided 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.

Resting-state functional abnormalities in ischemic stroke: a meta-analysis of fMRI studies

Ischemic stroke is a leading neurological cause of severe disabilities and death in the world and has a major negative impact on patients' quality of life. However, the neural mechanism of spontaneous fluctuating neuronal activity remains unclear. This meta-analysis explored brain activity during resting state in patients with ischemic stroke including 22 studies of regional homogeneity, amplitude of low-frequency fluctuation, and fractional amplitude of low-frequency fluctuation (692 patients with ischemic stroke, 620 healthy controls, age range 35-80 years, 41% female, 175 foci). Results showed decreased regional activity in the bilateral caudate and thalamus and increased regional activity in the left superior occipital gyrus and left default mode network (precuneus/posterior cingulate cortex). Meta-analysis of the amplitude of low-frequency fluctuation studies showed that increased activity in the left inferior frontal gyrus was reduced across the progression from acute to chronic phases. These findings may indicate that disruption of the subcortical areas and default mode network could be one of the core functional abnormalities in ischemic stroke. Altered brain activity in the inferior frontal gyrus could be the imaging indicator of brain recovery/plasticity after stroke damage, which offers potential insight into developing prediction models and therapeutic strategies for ischemic stroke rehabilitation and recovery.

Neuroimaging correlates of Alzheimer's disease biomarker concentrations in a racially diverse high-risk cohort of middle-aged adults

INTRODUCTION

In this study, we investigated biomarkers in a midlife, racially diverse, at-risk cohort to facilitate early identification and intervention. We examined neuroimaging measures, including resting state functional magnetic resonance imaging (fMRI), white matter hyperintensity vo (WMH), and hippocampal volumes, alongside cerebrospinal fluid (CSF) markers.

METHODS

Our data set included 76 cognitively unimpaired, middle-aged, Black Americans (N = 29, F/M = 17/12) and Non-Hispanic White (N = 47, F/M = 27/20) individuals. We compared cerebrospinal fluid phosphorylated tau141 and amyloid beta (Aβ)42 to fMRI default mode network (DMN) subnetwork connectivity, WMH volumes, and hippocampal volumes.

RESULTS

Results revealed a significant race × Aβ42 interaction in Black Americans: lower Aβ42 was associated with reduced DMN connectivity and increased WMH volumes regions but not in non-Hispanic White individuals.

DISCUSSION

Our findings suggest that precuneus DMN connectivity and temporal WMHs may be linked to Alzheimer's disease risk pathology during middle age, particularly in Black Americans.

HIGHLIGHTS

Cerebrospinal fluid (CSF) amyloid beta (Aβ)42 relates to precuneus functional connectivity in Black, but not White, Americans. Higher white matter hyperintensity volume relates to lower CSF Aβ42 in Black Americans. Precuneus may be a hub for early Alzheimer's disease pathology changes detected by functional connectivity.

Default mode network dynamics: An integrated neurocircuitry perspective on social dysfunction in human brain disorders

Our intricate social brain is implicated in a range of brain disorders, where social dysfunction emerges as a common neuropsychiatric feature cutting across diagnostic boundaries. Understanding the neurocircuitry underlying social dysfunction and exploring avenues for its restoration could present a transformative and transdiagnostic approach to overcoming therapeutic challenges in these disorders. The brain's default mode network (DMN) plays a crucial role in social functioning and is implicated in various neuropsychiatric conditions. By thoroughly examining the current understanding of DMN functionality, we propose that the DMN integrates diverse social processes, and disruptions in brain communication at regional and network levels due to disease hinder the seamless integration of these social functionalities. Consequently, this leads to an altered balance between self-referential and attentional processes, alongside a compromised ability to adapt to social contexts and anticipate future social interactions. Looking ahead, we explore how adopting an integrated neurocircuitry perspective on social dysfunction could pave the way for innovative therapeutic approaches to address brain disorders.

Individual large-scale functional network mapping for major depressive disorder with electroconvulsive therapy

Personalized functional connectivity mapping has been demonstrated to be promising in identifying underlying neurophysiological basis for brain disorders and treatment effects. Electroconvulsive therapy (ECT) has been proved to be an effective treatment for major depressive disorder (MDD) while its active mechanisms remain unclear. Here, 46 MDD patients before and after ECT as well as 46 demographically matched healthy controls (HC) underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans. A spatially regularized form of non-negative matrix factorization (NMF) was used to accurately identify functional networks (FNs) in individuals to map individual-level static and dynamic functional network connectivity (FNC) to reveal the underlying neurophysiological basis of therepetical effects of ECT for MDD. Moreover, these static and dynamic FNCs were used as features to predict the clinical treatment outcomes for MDD patients. We found that ECT could modulate both static and dynamic large-scale FNCs at individual level in MDD patients, and dynamic FNCs were closely associated with depression and anxiety symptoms. Importantly, we found that individual FNCs, particularly the individual dynamic FNCs could better predict the treatment outcomes of ECT suggesting that dynamic functional connectivity analysis may be better to link brain functional characteristics with clinical symptoms and treatment outcomes. Taken together, our findings provide new evidence for the active mechanisms and biomarkers for ECT to improve diagnostic accuracy and to guide individual treatment selection for MDD patients.

Neural correlates of approach-avoidance behavior in healthy subjects: Effects of low-frequency repetitive transcranial magnetic stimulation (rTMS) over the right dorsolateral prefrontal cortex

The dorsolateral prefrontal cortex (dlPFC) is implicated in top-down regulation of emotion, but the detailed network mechanisms require further elucidation. To investigate network-level functions of the dlPFC in emotion regulation, this study measured changes in task-based activation, resting-state and task-based functional connectivity (FC) patterns following suppression of dlPFC excitability by 1-Hz repetitive transcranial magnetic stimulation (rTMS). In a sham-controlled within-subject design, 1-Hz active or sham rTMS was applied to the right dlPFC of 19 healthy volunteers during two separate counterbalanced sessions. Following active and sham rTMS, functional magnetic resonance imaging (fMRI) was conducted in the resting state (rs-fMRI) and during approach-avoidance task responses to pictures with positive and negative emotional content (task-based fMRI). Activation and generalized psychophysiological interaction analyses were performed on task-based fMRI, and seed-based FC analysis was applied to rs-fMRI data. Task-based fMRI revealed greater and more lateralized activation in the right hemisphere during negative picture responses compared to positive picture responses. After active rTMS, greater activation was observed in the left middle prefrontal cortex compared to sham rTMS. Further, rTMS reduced response times and error rates in approach to positive pictures compared to negative pictures. Significant FC changes due to rTMS were observed predominantly in the frontoparietal network (FPN) and visual network (VN) during the task, and in the default mode network (DMN) and VN at rest. Suppression of right dlPFC activity by 1-Hz rTMS alters large-scale neural networks and modulates emotion, supporting potential applications for the treatment of mood disorders.

Social dysfunction relates to shifts within socioaffective brain systems among Schizophrenia and Alzheimer's disease patients

Social dysfunction represents one of the most common signs of neuropsychiatric disorders, such as Schizophrenia (SZ) and Alzheimer's disease (AD). Perturbed socioaffective neural processing is crucially implicated in SZ/AD and generally linked to social dysfunction. Yet, transdiagnostic properties of social dysfunction and its neurobiological underpinnings remain unknown. As part of the European PRISM project, we examined whether social dysfunction maps onto shifts within socioaffective brain systems across SZ and AD patients. We probed coupling of social dysfunction with socioaffective neural processing, as indexed by an implicit facial emotional processing fMRI task, across SZ (N = 46), AD (N = 40) and two age-matched healthy control (HC) groups (N = 26 HC-younger and N = 27 HC-older). Behavioural (i.e., social withdrawal, interpersonal dysfunction, diminished prosocial or recreational activity) and subjective (i.e., feelings of loneliness) aspects of social dysfunction were assessed using the Social Functioning Scale and De Jong-Gierveld loneliness questionnaire, respectively. Across SZ/AD/HC participants, more severe behavioural social dysfunction related to hyperactivity within fronto-parieto-limbic brain systems in response to sad emotions (P = 0.0078), along with hypoactivity of these brain systems in response to happy emotions (P = 0.0418). Such relationships were not found for subjective experiences of social dysfunction. These effects were independent of diagnosis, and not confounded by clinical and sociodemographic factors. In conclusion, behavioural aspects of social dysfunction across SZ/AD/HC participants are associated with shifts within fronto-parieto-limbic brain systems. These findings pinpoint altered socioaffective neural processing as a putative marker for social dysfunction, and could aid personalized care initiatives grounded in social behaviour.

Quantification of Glutathione and Its Associated Spontaneous Neuronal Activity in Major Depressive Disorder and Obsessive-Compulsive Disorder

BACKGROUND

Glutathione (GSH) is a crucial antioxidant in the human brain. Although proton magnetic resonance spectroscopy using the Mescher-Garwood point-resolved spectroscopy sequence is highly recommended, limited literature has measured cortical GSH using this method in major psychiatric disorders.

METHODS

By combining magnetic resonance spectroscopy and resting-state functional magnetic resonance imaging, we quantified brain GSH and glutamate in the medial prefrontal cortex and precuneus and explored relationships between GSH levels and intrinsic neuronal activity as well as clinical symptoms among healthy control (HC) participants (n = 30), people with major depressive disorder (MDD) (n = 28), and people with obsessive-compulsive disorder (OCD) (n = 28).

RESULTS

GSH concentrations were lower in the medial prefrontal cortex and precuneus in both the MDD and OCD groups than in the HC group. In the HC group, positive correlations were noted between GSH and glutamate levels and between GSH and fractional amplitude of low-frequency fluctuations in both regions. However, while these correlations were absent in both patient groups, there was a weak positive correlation between glutamate and fractional amplitude of low-frequency fluctuations. Moreover, GSH levels were negatively correlated with depressive and compulsive symptoms in MDD and OCD, respectively.

CONCLUSIONS

These findings suggest that reduced GSH levels and an imbalance between GSH and glutamate could increase oxidative stress and alter neurotransmitter signaling, thereby leading to disruptions in GSH-related neurochemical-neuronal coupling and psychopathologies across MDD and OCD. Understanding these mechanisms could provide valuable insights into the processes that underlie these disorders and potentially become a springboard for future directions and advancing our knowledge of their neurobiological foundations.

Differential increase of hippocampal subfield volume after socio-affective mental training relates to reductions in diurnal cortisol

The hippocampus is a central modulator of the HPA-axis, impacting the regulation of stress on brain structure, function, and behavior. The current study assessed whether three different types of 3 months mental Training Modules geared towards nurturing (a) attention-based mindfulness, (b) socio-affective, or (c) socio-cognitive skills may impact hippocampal organization by reducing stress. We evaluated mental training-induced changes in hippocampal subfield volume and intrinsic functional connectivity, by combining longitudinal structural and resting-state fMRI connectivity analysis in 332 healthy adults. We related these changes to changes in diurnal and chronic cortisol levels. We observed increases in bilateral cornu ammonis volume (CA1-3) following the 3 months compassion-based module targeting socio-affective skills (Affect module), as compared to socio-cognitive skills (Perspective module) or a waitlist cohort with no training intervention. Structural changes were paralleled by relative increases in functional connectivity of CA1-3 when fostering socio-affective as compared to socio-cognitive skills. Furthermore, training-induced changes in CA1-3 structure and function consistently correlated with reductions in cortisol output. Notably, using a multivariate approach, we found that other subfields that did not show group-level changes also contributed to changes in cortisol levels. Overall, we provide a link between a socio-emotional behavioural intervention, changes in hippocampal subfield structure and function, and reductions in cortisol in healthy adults.

Consistency and stability of individualized cortical functional networks parcellation at 3.0 T and 5.0 T MRI

Background

Individualized cortical functional networks parcellation has been reported as highly reproducible at 3.0 T. However, in view of the complexity of cortical networks and the greatly increased sensitivity provided by ultra-high field 5.0 T MRI, the parcellation consistency between different magnetic fields is unclear.

Purpose

To explore the consistency and stability of individualized cortical functional networks parcellation at 3.0 T and 5.0 T MRI based on spatial and functional connectivity analysis.

Materials and methods

Thirty healthy young participants were enrolled. Each subject underwent resting-state fMRI at both 3.0 T and 5.0 T in a random order in less than 48 h. The individualized cortical functional networks was parcellated for each subject using a previously proposed iteration algorithm. Dice coefficient was used to evaluate the spatial consistency of parcellated networks between 3.0 T and 5.0 T. Functional connectivity (FC) consistency was evaluated using the Euclidian distance and Graph-theory metrics.

Results

A functional cortical atlas consisting of 18 networks was individually parcellated at 3.0 T and 5.0 T. The spatial consistency of these networks at 3.0 T and 5.0 T for the same subject was significantly higher than that of inter-individuals. The FC between the 18 networks acquired at 3.0 T and 5.0 T were highly consistent for the same subject. Positive cross-subject correlations in Graph-theory metrics were found between 3.0 T and 5.0 T.

Conclusion

Individualized cortical functional networks at 3.0 T and 5.0 T showed consistent and stable parcellation results both spatially and functionally. The 5.0 T MR provides finer functional sub-network characteristics than that of 3.0 T.

Preventive effect of one-session brief focused attention meditation on state fatigue: Resting state functional magnetic resonance imaging study

INTRODUCTION

The extended practice of meditation may reduce the influence of state fatigue by changing neurocognitive processing. However, little is known about the preventive effects of one-session brief focused attention meditation (FAM) on state fatigue in healthy participants or its potential neural mechanisms. This study examined the preventive effects of one-session brief FAM on state fatigue and its neural correlates using resting-state functional MRI (rsfMRI) measurements.

METHODS

We randomly divided 56 meditation-naïve participants into FAM and control groups. After the first rsfMRI scan, each group performed a 10-minute each condition while wearing a functional near-infrared spectroscopy (fNIRS) device for assessing brain activity. Subsequently, following a second rsfMRI scan, the participants completed a fatigue-inducing task (a Go/NoGo task) for 60 min. We evaluated the temporal changes in the Go/NoGo task performance of participants as an indicator of state fatigue. We then calculated changes in the resting-state functional connectivity (rsFC) of the rsfMRI from before to after each condition and compared them between groups. We also evaluated neural correlates between the changes in rsFC and state fatigue.

RESULTS AND DISCUSSION

The fNIRS measurements indicated differences in brain activity during each condition between the FAM and control groups, showing decreased medial prefrontal cortex activity and decreased functional connectivity between the medial prefrontal cortex and middle frontal gyrus. The control group exhibited a decrement in Go/NoGo task performance over time, whereas the FAM group did not. These results, thus, suggested that FAM could prevent state fatigue. Compared with the control group, the rsFC analysis revealed a significant increase in the connectivity between the left dorsomedial prefrontal cortex and right superior parietal lobule in the FAM group, suggesting a modification of attention regulation by cognitive effort. In the control group, increased connectivity was observed between the bilateral posterior cingulate cortex and left inferior occipital gyrus, which might be associated with poor attention regulation and reduced higher-order cognitive function. Additionally, the change in the rsFC of the control group was related to state fatigue.

CONCLUSION

Our findings suggested that one session of 10-minute FAM could prevent behavioral state fatigue by employing cognitive effort to modify attention regulation as well as suppressing poor attention regulation and reduced higher-order cognitive function.

Sleep defined by arousal threshold reveals decreases in corticocortical functional correlations independently from the conventional sleep stages

Sleep research and sleep medicine have benefited from the use of polysomnography but have also suffered from an overreliance on the conventional, polysomnography-defined sleep stages. For example, reports of sleep-specific brain activity patterns have, with few exceptions, been constrained by assessing brain function as it relates to the conventional sleep stages. This limits the variety of sleep states and underlying activity patterns that one can discover. If undiscovered brain activity patterns exist during sleep, then removing the constraint of a stage-specific analysis may uncover them. The current study used all-night functional magnetic resonance imaging sleep data and defined sleep behaviorally with auditory arousal threshold (AAT) to begin to search for new brain states. It was hypothesized that, during sleep compared to wakefulness, corticocortical functional correlations would decrease. Functional correlation values calculated in a 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. The hypothesis was supported using both correlation matrices of brain networks and single seed-region analyses showing whole-brain maps. This represents a novel approach to studying the neuroanatomical correlates of sleep with high spatial resolution by defining sleep in a way that was independent from the conventional sleep stages. This work provides initial evidence to justify searching for sleep stages that are more neuroanatomically localized and unrelated to the conventional sleep stages.

Neural signatures of default mode network subsystems in first-episode, drug-naive patients with major depressive disorder after 6-week thought induction psychotherapy treatment

Evidence indicates that the default mode network (DMN) plays a crucial role in the neuropathology of major depressive disorder (MDD). However, the neural signatures of DMN subsystems in MDD after low resistance Thought Induction Psychotherapy (TIP) remain incompletely understood. We collected functional magnetic resonance imaging data from 20 first-episode, drug-naive MDD and 20 healthy controls (HCs). The DMN was segmented into three subsystems and seed-based functional connectivity (FC) was computed. After 6-week treatment, the significantly reduced FCs with the medial temporal lobe memory subsystem in MDD at baseline were enhanced and were comparable to that in HCs. Changed Hamilton Depression Rating Scale scores were significantly related with changed FC between the posterior cingulate cortex (PCC) and the right precuneus (PCUN). Further, changed serotonin 5-hydroxytryptamine levels were significantly correlated with changed FCs between the PCC and the left PCUN, between the posterior inferior parietal lobule and the left inferior temporal gyrus, and between the retrosplenial cortex and the right inferior frontal gyrus, opercular part. Finally, the support vector machine obtained an accuracy of 67.5% to distinguish between MDD at baseline and HCs. These findings may deepen our understanding of the neural basis of the effects of TIP on DMN subsystems in MDD.

Disparity in temporal and spatial relationships between resting-state electrophysiological and fMRI signals

Resting-state brain networks (RSNs) have been widely applied in health and disease, but the interpretation of RSNs in terms of the underlying neural activity is unclear. To address this fundamental question, we conducted simultaneous recordings of whole-brain resting-state functional magnetic resonance imaging (rsfMRI) and electrophysiology signals in two separate brain regions of rats. Our data reveal that for both recording sites, spatial maps derived from band-specific local field potential (LFP) power can account for up to 90% of the spatial variability in RSNs derived from rsfMRI signals. Surprisingly, the time series of LFP band power can only explain to a maximum of 35% of the temporal variance of the local rsfMRI time course from the same site. In addition, regressing out time series of LFP power from rsfMRI signals has minimal impact on the spatial patterns of rsfMRI-based RSNs. This disparity in the spatial and temporal relationships between resting-state electrophysiology and rsfMRI signals suggests that electrophysiological activity alone does not fully explain the effects observed in the rsfMRI signal, implying the existence of an rsfMRI component contributed by 'electrophysiology-invisible' signals. These findings offer a novel perspective on our understanding of RSN interpretation.

Precision mapping of the default network reveals common and distinct (inter) activity for autobiographical memory and theory of mind

The default network is widely implicated as a common neural substrate for self-generated thought, such as remembering one's past (autobiographical memory) and imagining the thoughts and feelings of others (theory of mind). Findings that the default network comprises subnetworks of regions, some commonly and some distinctly involved across processes, suggest that one's own experiences inform their understanding of others. With the advent of precision functional MRI (fMRI) methods, however, it is unclear if this shared substrate is observed instead due to traditional group analysis methods. We investigated this possibility using a novel combination of methodological strategies. Twenty-three participants underwent multi-echo resting-state and task fMRI. We used their resting-state scans to conduct cortical parcellation sensitive to individual variation while preserving our ability to conduct group analysis. Using multivariate analyses, we assessed the functional activation and connectivity profiles of default network regions while participants engaged in autobiographical memory, theory of mind, or a sensorimotor control condition. Across the default network, we observed stronger activity associated with both autobiographical memory and theory of mind compared to the control condition. Nonetheless, we also observed that some regions showed preferential activity to either experimental condition, in line with past work. The connectivity results similarly indicated shared and distinct functional profiles. Our results support that autobiographical memory and theory of mind, two theoretically important and widely studied domains of social cognition, evoke common and distinct aspects of the default network even when ensuring high fidelity to individual-specific characteristics.NEW & NOTEWORTHY We used cutting-edge precision functional MRI (fMRI) methods such as multi-echo fMRI acquisition and denoising, a robust experimental paradigm, and individualized cortical parcellation across 23 participants to provide evidence that remembering one's past experiences and imagining the thoughts and feelings of others share a common neural substrate. Evidence from activation and connectivity analyses indicate overlapping and distinct functional profiles of these widely studied episodic and social processes.

Abnormal large-scale brain functional network dynamics in social anxiety disorder

AIMS

Although static abnormalities of functional brain networks have been observed in patients with social anxiety disorder (SAD), the brain connectome dynamics at the macroscale network level remain obscure. We therefore used a multivariate data-driven method to search for dynamic functional network connectivity (dFNC) alterations in SAD.

METHODS

We conducted spatial independent component analysis, and used a sliding-window approach with a k-means clustering algorithm, to characterize the recurring states of brain resting-state networks; then state transition metrics and FNC strength in the different states were compared between SAD patients and healthy controls (HC), and the relationship to SAD clinical characteristics was explored.

RESULTS

Four distinct recurring states were identified. Compared with HC, SAD patients demonstrated higher fractional windows and mean dwelling time in the highest-frequency State 3, representing "widely weaker" FNC, but lower in States 2 and 4, representing "locally stronger" and "widely stronger" FNC, respectively. In State 1, representing "widely moderate" FNC, SAD patients showed decreased FNC mainly between the default mode network and the attention and perceptual networks. Some aberrant dFNC signatures correlated with illness duration.

CONCLUSION

These aberrant patterns of brain functional synchronization dynamics among large-scale resting-state networks may provide new insights into the neuro-functional underpinnings of SAD.

Neuroticism and openness exhibit an anti-correlation pattern to dissociable default mode network: using resting connectivity and structural equation modeling analysis

The default mode network (DMN) can be subdivided into ventral and dorsal subsystems, which serve affective cognition and mental sense construction, respectively. An internally dissociated pattern of anti-correlations was observed between these two subsystems. Although numerous studies on neuroticism and openness have demonstrated the neurological functions of the DMN, little is known about whether different subsystems and hubs regions within the network are engaged in different functions in response to the two traits. We recruited 223 healthy volunteers in this study and collected their resting-state functional magnetic resonance imaging (fMRI) and NEO Five-Factor Inventory scores. We used independent component analysis (ICA) to obtain the DMN, before further decomposing it into the ventral and dorsal subsystems. Then, the network coherence of hubs regions within subsystems was extracted to construct two structural equation models (SEM) to explore the relationship between neuroticism and openness traits and DMN. We observed that the ventral DMN could significantly predict positive openness and negative neuroticism. The dorsal DMN was diametrically opposed. Additionally, the medial prefrontal cortex (mPFC) and middle temporal gyrus (MTG), both of which are core hubs of the subnetworks within the DMN, are significantly positively correlated with neuroticism and openness. These findings may point to a biological basis that neuroticism and openness are engaged in opposite mechanisms and support the hypothesis about the functional dissociation of the DMN.

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.

Contrasting topologies of synchronous and asynchronous functional brain networks

We generated asynchronous functional networks (aFNs) using a novel method called optimal causation entropy (oCSE) and compared aFN topology to the correlation-based synchronous functional networks (sFNs) which are commonly used in network neuroscience studies. Functional magnetic resonance imaging (fMRI) time series from 212 participants of the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) study were used to generate aFNs and sFNs. As a demonstration of how aFNs and sFNs can be used in tandem, we used multivariate mixed effects models to determine whether age interacted with node efficiency to influence connection probabilities in the two networks. After adjusting for differences in network density, aFNs had higher global efficiency but lower local efficiency than the sFNs. In the aFNs, nodes with the highest outgoing global efficiency tended to be in the brainstem and orbitofrontal cortex. aFN nodes with the highest incoming global efficiency tended to be members of the Default Mode Network (DMN) in sFNs. Age interacted with node global efficiency in aFNs and node local efficiency in sFNs to influence connection probability. We conclude that the sFN and aFN both offer information about functional brain connectivity which the other type of network does not.