Atypical Interpersonal Problem-Solving and Resting-state Functional Connectivity in Adolescents with Maltreatment Experience

BACKGROUND

Childhood maltreatment is associated with altered neurocognitive functioning, which is thought to reflect, in part, adaptation to early adverse environmental experiences. However, we continue to lack a precise mechanistic understanding linking atypical neurocognitive processing with social functioning and psychiatric outcomes following early adversity.

OBJECTIVE

The present work investigated interpersonal problem-solving, resting-state functional connectivity (rsFC), and mental health symptoms in adolescents with documented maltreatment experience and explored whether altered neural function contributes in part to poorer social functioning.

METHODS

Forty adolescents (aged 12-17) with documented experiences of abuse or neglect and a carefully matched group of 42 non-maltreated peers participated in this study that measured task-based interpersonal problem-solving skills and rsFC.

RESULTS

Adolescents with maltreatment experience showed poorer interpersonal problem-solving performance, which partly accounted for their elevated mental health symptoms. Resting-state seed-based analyses revealed that adolescents with maltreatment experience showed a significant increase in rsFC between medial Default Mode Network (DMN) hubs, the medial prefrontal cortex (mPFC), with a posterior cluster, including the posterior cingulate cortex (PCC), precuneus (PCu), retrosplenial cortex (RSC), and lingual gyrus (LG). Moderation analyses revealed that maltreatment-related increased DMN rsFC partly accounted for poorer performance in interpersonal problem-solving.

CONCLUSION

Poorer interpersonal problem-solving, partly accounted for by atypical coupling between DMN medial hubs, was associated with maltreatment exposure. Interventions tailored to enhance interpersonal problem-solving represents a promising avenue to promote resilience and reduce the likelihood of mental health disorder following maltreatment experience.

The reciprocal relationship between openness and creativity: from neurobiology to multicultural environments

The desire for novelty and variety in experiences, which may manifest in an inclination to engage with individuals from a diverse range of cultural backgrounds, collectively constitutes the personality dimension known as "Openness to Experience." Empirical research has identified a positive correlation between trait openness and various expressions of creativity, such as divergent ideation, innovative problem-solving strategies, and cumulative creative accomplishments. This nexus between openness to interpersonal diversity, as an aspect of the larger personality trait of openness, and creativity has precipitated considerable scholarly interest across the disciplines of personality, social and organizational psychology, and neuroscientific investigation. In this paper, we review the neurobehavioral properties, including the cognitive processes and neural mechanisms, that connect these two constructs. Further, we explore how culture influences levels of openness and creativity in individuals and consider how creativity predisposes individuals toward openness to a plethora of experiences, including those occurring in culturally diverse contexts. This reciprocal entanglement of creativity and openness has been shown to foster a reduction in biases, augment conflict resolution capabilities, and generally yield superior outcomes in multicultural environments.

Task-based attentional and default mode connectivity associated with science and math anxiety profiles among university physics students

PURPOSE

Attentional control theory (ACT) posits that elevated anxiety increases the probability of re-allocating cognitive resources needed to complete a task to processing anxiety-related stimuli. This process impairs processing efficiency and can lead to reduced performance effectiveness. Science, technology, engineering, and math (STEM) students frequently experience anxiety about their coursework, which can interfere with learning and performance and negatively impact student retention and graduation rates. The objective of this study was to extend the ACT framework to investigate the neurobiological associations between science and math anxiety and cognitive performance among 123 physics undergraduate students.

PROCEDURES

Latent profile analysis (LPA) identified four profiles of science and math anxiety among STEM students, including two profiles that represented the majority of the sample (Low Science and Math Anxiety; 59.3% and High Math Anxiety; 21.9%) and two additional profiles that were not well represented (High Science and Math Anxiety; 6.5% and High Science Anxiety; 4.1%). Students underwent a functional magnetic resonance imaging (fMRI) session in which they performed two tasks involving physics cognition: the Force Concept Inventory (FCI) task and the Physics Knowledge (PK) task.

FINDINGS

No significant differences were observed in FCI or PK task performance between High Math Anxiety and Low Science and Math Anxiety students. During the three phases of the FCI task, we found no significant brain connectivity differences during scenario and question presentation, yet we observed significant differences during answer selection within and between the dorsal attention network (DAN), ventral attention network (VAN), and default mode network (DMN). Further, we found significant group differences during the PK task were limited to the DAN, including DAN-VAN and within-DAN connectivity.

CONCLUSIONS

These results highlight the different cognitive processes required for physics conceptual reasoning compared to physics knowledge retrieval, provide new insight into the underlying brain dynamics associated with anxiety and physics cognition, and confirm the relevance of ACT theory for science and math anxiety.

Altered metabolic-functional coupling in the epileptogenic network could predict surgical outcomes of mesial temporal lobe epilepsy

Objective

To investigate the relationship between glucose metabolism and functional activity in the epileptogenic network of patients with mesial temporal lobe epilepsy (MTLE) and to determine whether this relationship is associated with surgical outcomes.

Methods

¹⁸F-FDG PET and resting-state functional MRI (rs-fMRI) scans were performed on a hybrid PET/MR scanner in 38 MTLE patients with hippocampal sclerosis (MR-HS), 35 MR-negative patients and 34 healthy controls (HC). Glucose metabolism was measured using ¹⁸F-FDG PET standardized uptake value ratio (SUVR) relative to cerebellum; Functional activity was obtained by fractional amplitude of low-frequency fluctuation (fALFF). The betweenness centrality (BC) of metabolic covariance network and functional network were calculated using graph theoretical analysis. Differences in SUVR, fALFF, BC and the spatial voxel-wise SUVR-fALFF couplings of the epileptogenic network, consisting of default mode network (DMN) and thalamus, were evaluated by Mann-Whitney U test (using the false discovery rate [FDR] for multiple comparison correction). The top ten SUVR-fALFF couplings were selected by Fisher score to predict surgical outcomes using logistic regression model.

Results

The results showed decreased SUVR-fALFF coupling in the bilateral middle frontal gyrus (P_FDR = 0.0230, P_FDR = 0.0296) in MR-HS patients compared to healthy controls. Coupling in the ipsilateral hippocampus was marginally increased (P_FDR = 0.0802) in MR-HS patients along with decreased BC of metabolic covariance network and functional network (P_FDR = 0.0152; P_FDR = 0.0429). With Fisher score ranking, the top ten SUVR-fALFF couplings in regions from DMN and thalamic subnuclei could predict surgical outcomes with the best performance being a combination of ten SUVR-fALFF couplings with an AUC of 0.914.

Conclusion

These findings suggest that the altered neuroenergetic coupling in the epileptogenic network is associated with surgical outcomes of MTLE patients, which may provide insight into their pathogenesis and help with preoperative evaluation.

Topological abnormality of structural covariance network in MRI-negative frontal lobe epilepsy

Background

Frontal lobe epilepsy (FLE) is the second most common type of focal epilepsy, however, imaging studies of FLE have been far less than Temporal lobe epilepsy (TLE) and the structural findings were not consistent in previous literature.

Object

Investigate the changes in cortical thickness in patients with FLE and the alteration of the structural covariance networks (SCNs) of cortical thickness with graph-theory.

Method

Thirty patients with FLE (18 males/12 females; 28.33 ± 11.81 years) and 27 demographically matched controls (15 males/12 females; 29.22 ± 9.73 years) were included in this study with high-resolution structural brain MRI scans. The cortical thickness was calculated, and structural covariance network (SCN) of cortical thickness were reconstructed using 68 × 68 matrix and analyzed with graph-theory approach.

Result

Cortical thickness was not significantly different between two groups, but path length and node betweenness were significantly increased in patients with FLE, and the regional network alterations were significantly changed in right precentral gyrus and right temporal pole (FDR corrected, p < 0.05). Comparing to HC group, network hubs were decreased and shifted away from frontal lobe.

Conclusion

The topological properties of cortical thickness covariance network were significantly altered in patients with FLE, even without obvious surface-based morphological damage. Graph-theory based SCN analysis may provide sensitive neuroanatomical biomarkers for FLE.

Decreased functional connectivity is associated with increased levels of Cerebral Spinal Fluid soluble-PDGFRβ, a marker of blood brain barrier breakdown, in older adults

Resting-state functional connectivity (FC) is suggested to be cross-sectionally associated with both vascular burden and Alzheimer's disease (AD) pathology. For instance, studies in pre-clinical AD subjects have shown increases of cerebral spinal fluid soluble platelet-derived growth factor receptor-β (CSF sPDGFRβ, a marker of BBB breakdown) but have not demonstrated if this vascular impairment affects neuronal dysfunction. It's possible that increased levels of sPDGFRβ in the CSF may correlate with impaired FC in metabolically demanding brain regions (i.e. Default Mode Network, DMN). Our study aimed to investigate the relationship between these two markers in older individuals that were cognitively normal and had cognitive impairment. Eighty-nine older adults without dementia from the University of Southern California were selected from a larger cohort. Region of interest (ROI) to ROI analyses were conducted using DMN seed regions. Linear regression models measured significant associations between BOLD FC strength among seed-target regions and sPDGFRβ values, while covarying for age and sex. Comparison of a composite ROI created by averaging FC values between seed and all target regions among cognitively normal and impaired individuals was also examined. Using CSF sPDGFRβ as a biomarker of BBB breakdown, we report that increased breakdown correlated with decreased functional connectivity in DMN areas, specifically the PCC while the hippocampus exhibited an interaction effect using CDR score. We conclude that BBB breakdown as measured by CSF sPDGFRβ affects neural networks resulting in decreased functional connections that leads to cognitive dysfunction.

Distinct but cooperating brain networks supporting semantic cognition

Semantic cognition is a complex multifaceted brain function involving multiple processes including sensory, semantic, and domain-general cognitive systems. However, it remains unclear how these systems cooperate with each other to achieve effective semantic cognition. Here, we used independent component analysis (ICA) to investigate the functional brain networks that support semantic cognition. We used a semantic judgment task and a pattern-matching control task, each with 2 levels of difficulty, to disentangle task-specific networks from domain-general networks. ICA revealed 2 task-specific networks (the left-lateralized semantic network [SN] and a bilateral, extended semantic network [ESN]) and domain-general networks including the frontoparietal network (FPN) and default mode network (DMN). SN was coupled with the ESN and FPN but decoupled from the DMN, whereas the ESN was synchronized with the FPN alone and did not show a decoupling with the DMN. The degree of decoupling between the SN and DMN was associated with semantic task performance, with the strongest decoupling for the poorest performing participants. Our findings suggest that human higher cognition is achieved by the multiple brain networks, serving distinct and shared cognitive functions depending on task demands, and that the neural dynamics between these networks may be crucial for efficient semantic cognition.

The role of the salience network in cognitive and affective deficits

Analysis and interpretation of studies on cognitive and affective dysregulation often draw upon the network paradigm, especially the Triple Network Model, which consists of the default mode network (DMN), the frontoparietal network (FPN), and the salience network (SN). DMN activity is primarily dominant during cognitive leisure and self-monitoring processes. The FPN peaks during task involvement and cognitive exertion. Meanwhile, the SN serves as a dynamic "switch" between the DMN and FPN, in line with salience and cognitive demand. In the cognitive and affective domains, dysfunctions involving SN activity are connected to a broad spectrum of deficits and maladaptive behavioral patterns in a variety of clinical disorders, such as depression, insomnia, narcissism, PTSD (in the case of SN hyperactivity), chronic pain, and anxiety, high degrees of neuroticism, schizophrenia, epilepsy, autism, and neurodegenerative illnesses, bipolar disorder (in the case of SN hypoactivity). We discuss behavioral and neurological data from various research domains and present an integrated perspective indicating that these conditions can be associated with a widespread disruption in predictive coding at multiple hierarchical levels. We delineate the fundamental ideas of the brain network paradigm and contrast them with the conventional modular method in the first section of this article. Following this, we outline the interaction model of the key functional brain networks and highlight recent studies coupling SN-related dysfunctions with cognitive and affective impairments.

A neurocognitive account of attentional control theory: how does trait anxiety affect the brain's attentional networks?

Attentional control theory (ACT) was proposed to account for trait anxiety's effects on cognitive performance. According to ACT, impaired processing efficiency in high anxiety is mediated through inefficient executive processes that are needed for effective attentional control. Here we review the central assumptions and predictions of ACT within the context of more recent empirical evidence from neuroimaging studies. We then attempt to provide an account of ACT within a framework of the relevant cognitive processes and their associated neural mechanisms and networks, particularly the fronto-parietal, cingular-opercula, and default mode networks. Future research directions, including whether a neuroscience-informed model of ACT can provide a platform for novel neurocognitive intervention for anxiety, are also discussed.

Dual-targeted repetitive transcranial magnetic stimulation modulates brain functional network connectivity to improve cognition in mild cognitive impairment patients

Background: Mild cognitive impairment (MCI) is a condition between normal aging and dementia; nearly 10-15% of MCI patients develop dementia annually. There are no effective interventions for MCI progression. Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive brain stimulation technique that has attempted to improve the overall cognitive function of MCI patients. However, it does not affect episodic memory improvement. Methods: In this study, we engaged 15 clinically diagnosed MCI patients and normal controls to explore the effect of dual-targeted rTMS on progressing cognitive function, particularly episodic memory in MCI patients. Resting-state EEG recordings and neuropsychological assessments were conducted before and after the intervention. EEG features were extracted using an adaptive algorithm to calculate functional connectivity alterations in relevant brain regions and the mechanisms of altered brain functional networks in response to dual-target rTMS. Results: The study revealed that the functional brain connectivity between the right posterior cingulate gyrus (PCC) and the right dorsal caudate nucleus (DC) was significantly reduced in MCI patients compared to normal controls (p < 0.001). Dual-target rTMS increased the strength of the reduced functional connectivity (p < 0.001), which was related to cognitive enhancement (p < 0.05). Conclusion: This study provides a new stimulation protocol for rTMS intervention. Improving the functional connectivity of the right PCC to the right DC is a possible mechanism by which rTMS improves overall cognitive and memory function in MCI patients.

DLPFC stimulation alters large-scale brain networks connectivity during a drug cue reactivity task: A tDCS-fMRI study

Transcranial direct current stimulation (tDCS) is a promising intervention for reducing craving/consumption in individuals with substance use disorders. However, its exact mechanism of action has not yet been well explored. We aimed to examine the network-based effects of tDCS while people with methamphetamine use disorders (MUDs) were exposed to drug cues. In a randomized, double-blind sham-controlled trial with a crossover design, 15 participants with MUDs were recruited to receive 20 min of active/sham tDCS with an anode/cathode over F4/F3. MRI data, including structural and task-based functional MRI during a standard drug cue-reactivity task, were collected immediately before and after stimulation sessions. Craving scores were also recorded before and after MRI scans. Individualized head models were generated to determine brain regions with strong electric fields (EFs). Using atlas-based parcellation of head models, averaged EFs were extracted from the main nodes of three large-scale networks that showed abnormalities in MUDs; executive control (ECN), default mode (DMN), and ventral attention (VAN) networks. Main nodes with high EF intensity were used as seed regions for task-based functional connectivity (FC) [using generalized psychophysiological interaction (gPPI)] and activity [using a general linear model (GLM)] calculations. Subjective craving showed a significant reduction in immediate craving after active (-15.42 ± 5.42) compared to sham (-1 ± 2.63). In seed-to-whole brain results, the PFC node in ECN showed an enhanced PPI connectivity with precuneus and visual cortex; the cluster center in MNI (6, -84, -12); the PFC node in DMN showed a decreased PPI connectivity with contralateral parietal cortex;(-48, -60, 46). ROI-to-ROI results showed increased PPI connectivity within/between ECN-VAN while connectivity between ECN-DMN decreased. In line with connectivity, functional activity in the right PFC node in DMN decreased after tDCS while activity in PFC nodes of ECN/VAN increased. EF calculations in PFC nodes revealed that EF in DMN was outward, while the direction of EFs was inward in ECN/VAN. This study provides new insight into neural circuitry underlying MUDs that can be modulated by tDCS at the network level and specifically suggests that bilateral tDCS increases cortical excitability in ECN and VAN, while it has opposite effects on DMN that may be related to the direction of EFs.

Extracting default mode network based on graph neural network for resting state fMRI study

Functional magnetic resonance imaging (fMRI)-based study of functional connections in the brain has been highlighted by numerous human and animal studies recently, which have provided significant information to explain a wide range of pathological conditions and behavioral characteristics. In this paper, we propose the use of a graph neural network, a deep learning technique called graphSAGE, to investigate resting state fMRI (rs-fMRI) and extract the default mode network (DMN). Comparing typical methods such as seed-based correlation, independent component analysis, and dictionary learning, real data experiment results showed that the graphSAGE is more robust, reliable, and defines a clearer region of interests. In addition, graphSAGE requires fewer and more relaxed assumptions, and considers the single subject analysis and group subjects analysis simultaneously.

Altered intrinsic default mode network functional connectivity in patients with remitted geriatric depression and amnestic mild cognitive impairment

OBJECTIVES

Patients with geriatric depression exhibit a spectrum of symptoms ranging from mild to severe cognitive impairment which could potentially lead to the development of Alzheimer's disease (AD). The aim of the study is to assess the alterations of the default mode network (DMN) in remitted geriatric depression (RGD) patients and whether it could serve as an underlying neuropathological mechanism associated with the risk of progression of AD.

DESIGN

Cross-sectional study.

PARTICIPANTS

A total of 154 participants, comprising 66 RGD subjects (which included 27 patients with comorbid amnestic mild cognitive impairment [aMCI] and 39 without aMCI [RGD]), 45 aMCI subjects without a history of depression (aMCI), and 43 matched healthy comparisons (HC), were recruited.

MEASUREMENTS

All participants completed neuropsychological tests and underwent resting-state functional magnetic resonance imaging (fMRI). Posterior cingulate cortex (PCC)-seeded DMN functional connectivity (FC) along with cognitive function were compared among the four groups, and correlation analyses were conducted.

RESULTS

In contrast to HC, RGD, aMCI, and RGD-aMCI subjects showed significant impairment across all domains of cognitive functions except for attention. Furthermore, compared with HC, there was a similar and significant decrease in PCC-seed FC in the bilateral medial superior frontal gyrus (M-SFG) in the RGD, aMCI, and RGD-aMCI groups.

CONCLUSIONS

The aberrations in rsFC of the DMN were associated with cognitive deficits in RGD patients and might potentially reflect an underlying neuropathological mechanism for the increased risk of developing AD. Therefore, altered connectivity in the DMN could serve as a potential neural marker for the conversion of geriatric depression to AD.

Ventral Attention Network Correlates With High Traits of Emotion Dysregulation in Community Women - A Resting-State EEG Study

In recent years, many studies have focused on resting-state brain activity, and especially on functional connectivity (FC), an approach that typically describes the statistical interdependence of activity in distant brain regions through specific networks. Our aim was to study the neurophysiological correlates of emotion dysregulation. Therefore, we expected that both the Default Mode Network (DMN), and the Ventral Attention Network (VAN) would have been involved. Indeed, the latter plays a role in the automatic orienting of attention towards biologically salient stimuli and includes key regions for emotion control and modulation. Starting from a community sample of 422 female students, we selected 25 women with high traits of emotion dysregulation (HD group) and 25 with low traits (LD group). They underwent a 64-channel EEG recording during a five-minute resting state with eyes open. Seed-based FC was computed on the EEG Alpha band (8-13 Hz) as a control band, and on EEG Gamma power (30-50 Hz) as the relevant measure. The power within each network and inter-network connectivity (Inter-NC) was also calculated. Analysis of the EEG Gamma band revealed, in the HD group, higher levels of Inter-NC between the VAN and all other resting-state networks as compared with the LD group, while no differences emerged in the Alpha band. Concerning correlations, Alpha power in the VAN was negatively correlated in the HD group with affective lability (ALS-18 questionnaire), both for total score (ρ = -0.52, p FDR < 0.01) and the Depression/Elation subscale) ρ = -0.45, p FDR < 0.05). Consistent with this, in the Gamma band, a positive correlation was found between VAN spectral power and the Depression/Elation subscale of ALS-18, again in the HD group only (ρ = 0.47, p FDR < 0.05). In conclusion, both resting state FC and network power in the VAN were found to be related to high emotion dysregulation, even in our non-clinical sample with high traits. Emotion dysregulation was characterized, in the EEG gamma band, by a VAN strongly connected to all other networks, a result that points, in women prone to emotion dysregulation, to a strong automatic orienting of attention towards their internal state, bodily sensations, and emotionally intense related thoughts.

Spindle-Shaped Neurons in the Human Posteromedial (Precuneus) Cortex

The human posteromedial cortex (PMC), which includes the precuneus (PC), represents a multimodal brain area implicated in emotion, conscious awareness, spatial cognition, and social behavior. Here, we describe the presence of Nissl-stained elongated spindle-shaped neurons (suggestive of von Economo neurons, VENs) in the cortical layer V of the anterior and central PC of adult humans. The adapted "single-section" Golgi method for postmortem tissue was used to study these neurons close to pyramidal ones in layer V until merging with layer VI polymorphic cells. From three-dimensional (3D) reconstructed images, we describe the cell body, two main longitudinally oriented ascending and descending dendrites as well as the occurrence of spines from proximal to distal segments. The primary dendritic shafts give rise to thin collateral branches with a radial orientation, and pleomorphic spines were observed with a sparse to moderate density along the dendritic length. Other spindle-shaped cells were observed with straight dendritic shafts and rare branches or with an axon emerging from the soma. We discuss the morphology of these cells and those considered VENs in cortical areas forming integrated brain networks for higher-order activities. The presence of spindle-shaped neurons and the current discussion on the morphology of putative VENs address the need for an in-depth neurochemical and transcriptomic characterization of the PC cytoarchitecture. These findings would include these spindle-shaped cells in the synaptic and information processing by the default mode network and for general intelligence in healthy individuals and in neuropsychiatric disorders involving the PC in the context of the PMC functioning.

Resting-State Brain Variability in Youth With Attention-Deficit/Hyperactivity Disorder

In this study, we sought to determine the nature of the abnormality in resting-state default mode network (DMN) activation and explore its correlation with functional connectivity in attention-deficit/hyperactivity disorder (ADHD). We obtained resting-state functional magnetic resonance images of youth with ADHD and typically developing counterparts from the publicly available ADHD-200 database. We used data from Peking University (232 scans) and New York University (172 scans); the scan repetition time was 2 s for both data collection sites. We applied generalized estimating equations to estimate the variability of the averaged blood-oxygen-level-dependent (BOLD) time series extracted from the DMN at rest. We performed network-based statistics to determine the association between the observed differences in BOLD signal variability and altered functional connectivity. We analyzed data from 105 youth with ADHD (age: mean 12.17, standard deviation 2.31, median 12.25; 15.2% female, 84.8% male) and 140 typically developing youth (age: mean 11.99, standard deviation 2.28, median 11.85; 47.1% female, 52.9% male), who aged 7-17 years. The imaging data were cross-sectionally collected for each participant at one time point. We observed a greater number of significant BOLD signal changes and higher-order polynomial significant associations in youth with ADHD. Moreover, there were significant between-group differences in BOLD signal change after the first 140 s, which coincided with decreased resting-state functional connectivity within the DMN in youth with ADHD. Increased variability of neural signaling was intermittently observed in the brains of youth with ADHD at rest, thereby indicating their default mode state was more unstable than that of typically developing youth.

Aberrant Amplitude of Low-Frequency Fluctuation and Degree Centrality within the Default Mode Network in Patients with Vascular Mild Cognitive Impairment

This study aimed to investigate whole-brain spontaneous activities changes in patients with vascular mild cognitive impairment (VaMCI), and to evaluate the relationships between these brain alterations and their neuropsychological assessments. Thirty-one patients with VaMCI and thirty-one healthy controls (HCs) underwent structural MRI and resting-state functional MRI (rs-fMRI) and neuropsychological assessments. The functional alterations were determined by the amplitude of low-frequency fluctuation (ALFF) and degree centrality (DC). The gray matter volume (GMV) changes were analyzed using voxel-based morphometry (VBM). Linear regression analysis was used to evaluate the relationships between the structural and functional changes of brain regions and neuropsychological assessments. The VaMCI group had significantly lower scores in the Montreal Cognitive Assessment (MoCA), and higher scores on the Hamilton Anxiety Rating Scale (HAMA) and Hamilton Depression Rating Scale (HAMD). Compared to the HCs, the VaMCI group exhibited GM atrophy in the right precentral gyrus (PreCG) and right inferior temporal gyrus (ITG). VaMCI patients further exhibited significantly decreased brain activity within the default mode network (DMN), including the bilateral precuneus (PCu), angular gyrus (AG), and medial frontal gyrus (medFG). Linear regression analysis revealed that the decreased ALFF was independently associated with lower MoCA scores, and the GM atrophy was independently associated with higher HAMD scores. The current finding suggested that aberrant spontaneous brain activity in the DMN might subserve as a potential biomarker of VaMCI, which may highlight the underlying mechanism of cognitive decline in cerebral small vessel disease.

fMRI Evidence for Default Mode Network Deactivation Associated with Rapid Eye Movements in Sleep

System-specific brain responses—time-locked to rapid eye movements (REMs) in sleep—are characteristically widespread, with robust and clear activation in the primary visual cortex and other structures involved in multisensory integration. This pattern suggests that REMs underwrite hierarchical processing of visual information in a time-locked manner, where REMs index the generation and scanning of virtual-world models, through multisensory integration in dreaming—as in awake states. Default mode network (DMN) activity increases during rest and reduces during various tasks including visual perception. The implicit anticorrelation between the DMN and task-positive network (TPN)—that persists in REM sleep—prompted us to focus on DMN responses to temporally-precise REM events. We timed REMs during sleep from the video recordings and quantified the neural correlates of REMs—using functional MRI (fMRI)—in 24 independent studies of 11 healthy participants. A reanalysis of these data revealed that the cortical areas exempt from widespread REM-locked brain activation were restricted to the DMN. Furthermore, our analysis revealed a modest temporally-precise REM-locked decrease—phasic deactivation—in key DMN nodes, in a subset of independent studies. These results are consistent with hierarchical predictive coding; namely, permissive deactivation of DMN at the top of the hierarchy (leading to the widespread cortical activation at lower levels; especially the primary visual cortex). Additional findings indicate REM-locked cerebral vasodilation and suggest putative mechanisms for dream forgetting.

[Effect of acupuncture on default mode network in patients with migraine based on functional Magnetic Resonance Imaging: a preliminary study]

OBJECTIVE

To investigate the effect of acupuncture on default mode network (DMN) in migraine patients without aura based on functional Magnetic Resonance Imaging (fMRI).

METHODS

Fifteen patients with migraine were included and treated with acupuncture based on "root-knot" theory (Zuqiaoyin [GB 44] for shaoyang headache, Lidui [ST 45] for yangming headache, Zhiyin [BL 67] for taiyang headache, and ashi point), once every other day, three times a week for 4 weeks. The patients received fMRI scanning before and after acupuncture treatment, the effect of acupuncture on DMN in patients with migraine was observed; the frequency of migraine attack, visual analogue scale (VAS) score and the using of analgesic medication before and after treatment were recorded to evaluate the curative effect of acupuncture; the migraine-specific quality of life questionnaire (MSQ), self-rating anxiety scale (SAS) and self-rating depression scale (SDS) were used to evaluate the improvements of quality of life and emotional state.

RESULTS

Compared before acupuncture, the functional connections of left parahippocampal cortex (PHC) and anterior medial prefrontal cortex (aMPFC), dorsal medial prefrontal cortex (dMPFC) and lateral temporal cortex (LTC) in DMN after acupuncture were weakened (P<0.05), and the functional connections of bilateral posterior cingulate cortex (PCC) and dMPFC were weakened (P<0.05). Compared before treatment, the frequency of migraine attack, VAS, SAS and SDS scores after treatment were decreased (P<0.05), and MSQ score was increased (P<0.05).

CONCLUSION

Acupuncture shows good clinical efficacy for migraine without aura, and could adjust the functional connection of DMN.

Regional and remote connectivity patterns in focal extratemporal lobe epilepsy

Background

Focal epilepsy accounts for most epilepsy cases, and frontal lobe epilepsy (FLE) accounts for the largest proportion of cases of extratemporal epilepsy syndrome. The epileptogenic zone is usually not easy to locate, contributing to a lack of imaging studies. The objective of this study was to evaluate functional connectivity patterns to explore the underlying pathological mechanisms of this disorder.

Methods

Forty-three patients with focal extratemporal epilepsy [mean age ± standard deviation (SD): 29.51±8.04 years, 19 males] and the same number of healthy controls (mean age ± SD: 29.56±8.02 years, 19 males) were recruited to undergo functional magnetic resonance imaging. Mean regional homogeneity (ReHo) was measured, and regions showing significant alterations in ReHo in patients were identified to examine functional connectivity (FC). In particular, FC within the default mode network (DMN) in patients was analyzed.

Results

Patients with extratemporal lobe epilepsy showed significantly higher ReHo in the bilateral precentral gyrus, and lower ReHo in frontal-cerebellum regions than healthy controls [P<0.05, Gaussian random field (GRF)-corrected]. FC analysis based on regions of interest showed significantly higher connectivity in the frontoparietal-insula region and lowered FC in the frontal-cerebellum regions (P<0.05, GRF-corrected). Altered FC within DMN was also demonstrated (P<0.05, GRF-corrected).

Conclusions

Analyses of ReHo and FC based on regions of interest suggest epilepsy-related neural networks are located mainly in frontal regions in extratemporal lobe epilepsy. These findings reveal disruptions of interactions and connectivity of large-scale neural networks and frontotemporal-cerebellar regions, suggesting connectivity-based pathophysiology.

Analysis of Default Mode Network in Social Anxiety Disorder: EEG Resting-State Effective Connectivity Study

Recent brain imaging findings by using different methods (e.g., fMRI and PET) have suggested that social anxiety disorder (SAD) is correlated with alterations in regional or network-level brain function. However, due to many limitations associated with these methods, such as poor temporal resolution and limited number of samples per second, neuroscientists could not quantify the fast dynamic connectivity of causal information networks in SAD. In this study, SAD-related changes in brain connections within the default mode network (DMN) were investigated using eight electroencephalographic (EEG) regions of interest. Partial directed coherence (PDC) was used to assess the causal influences of DMN regions on each other and indicate the changes in the DMN effective network related to SAD severity. The DMN is a large-scale brain network basically composed of the mesial prefrontal cortex (mPFC), posterior cingulate cortex (PCC)/precuneus, and lateral parietal cortex (LPC). The EEG data were collected from 88 subjects (22 control, 22 mild, 22 moderate, 22 severe) and used to estimate the effective connectivity between DMN regions at different frequency bands: delta (1-3 Hz), theta (4-8 Hz), alpha (8-12 Hz), low beta (13-21 Hz), and high beta (22-30 Hz). Among the healthy control (HC) and the three considered levels of severity of SAD, the results indicated a higher level of causal interactions for the mild and moderate SAD groups than for the severe and HC groups. Between the control and the severe SAD groups, the results indicated a higher level of causal connections for the control throughout all the DMN regions. We found significant increases in the mean PDC in the delta (p = 0.009) and alpha (p = 0.001) bands between the SAD groups. Among the DMN regions, the precuneus exhibited a higher level of causal influence than other regions. Therefore, it was suggested to be a major source hub that contributes to the mental exploration and emotional content of SAD. In contrast to the severe group, HC exhibited higher resting-state connectivity at the mPFC, providing evidence for mPFC dysfunction in the severe SAD group. Furthermore, the total Social Interaction Anxiety Scale (SIAS) was positively correlated with the mean values of the PDC of the severe SAD group, r (22) = 0.576, p = 0.006 and negatively correlated with those of the HC group, r (22) = -0.689, p = 0.001. The reported results may facilitate greater comprehension of the underlying potential SAD neural biomarkers and can be used to characterize possible targets for further medication.

The emergent relationship between temporoparietal junction and anosognosia in Alzheimer's disease

Anosognosia and impairment of insight are characteristic features of Alzheimer's disease (AD), which can lead to delays in appropriate medical care and significant family discord. The default mode network (DMN), a distributed but highly connected network of brain regions more active during rest than during task, is integrally involved in awareness. DMN dysfunction is common in AD, and disrupted communication between memory-related and self-related DMN networks is associated with anosognosia in AD patients. In addition, the temporoparietal junction (TPJ) is a key region of the "social brain" and also contributes to representations of the self. The exact classification of the TPJ within the DMN is unclear, though connections between the TPJ and DMN have been highlighted in multiple avenues of research. Here we discuss the relationship between the TPJ, DMN, and AD, as well as the potential involvement of the TPJ in anosognosia in AD. We review past and present findings to raise attention to the TPJ, with a specific emphasis on neuroimaging technologies which suggest a pivotal role of the TPJ within large-scale brain networks linked to anosognosia in AD.

Alteration of spatial patterns at the network-level in facial synkinesis: an independent component and connectome analysis

Background

The treatment of post-facial palsy synkinesis (PFPS) remains inadequate. Previous studies have confirmed that brain plasticity is involved in the process of functional restoration. Isolated activation has been well studied, however, the brain works as an integrity of several isolated regions. This study aimed to assess the alteration of the brain network topology with overall and local characteristics of information dissemination. Understanding the neural mechanisms of PFPS could help to improve therapy options and prognosis.

Methods

Patients with facial synkinesis and healthy controls (HCs) were estimated using functional magnetic resonance imaging (fMRI) of resting-state. Subsequently, an independent component analysis (ICA) was used to extract four subnets from the whole brain. Then we used the measurements of graph theory and calculated in the whole-brain network and each sub-network.

Results

We found no significant difference between the patient group and the HCs on the whole-brain scale. Then we identified four subnetworks from the resting-state data. In the sub-network property analysis, patients' locally distributed properties in the sensorimotor network (SMN) and ventral default mode network (vDMN) were reduced. It revealed that γ (10,000 permutations, P=0.048) and S (10,000 permutations, P=0.022) within the SMN progressively decreased in patients with PFPS. For the analysis of vDMN, significant differences were found in γ (10,000 permutations, P=0.019), Elocal (10,000 permutations, P=0.008), and β (10,000 permutations, P=0.011) between the groups.

Conclusions

Our results demonstrated a reduction in local network processing efficiency in patients with PFPS. Therefore, we speculate that decreased characteristics in the intra-vDMN and intra-SMN, rather than the whole-brain network, may serve distinct symptoms such as facial nerve damage or more synkinetic movements. This finding of the alteration of network properties is a small step forward to help uncover the underlying mechanism.

Spinal Manipulative Therapy Alters Brain Activity in Patients With Chronic Low Back Pain: A Longitudinal Brain fMRI Study

Background: Spinal manipulative therapy (SMT) helps to reduce chronic low back pain (cLBP). However, the underlying mechanism of pain relief and the neurological response to SMT remains unclear. We utilized brain functional magnetic resonance imaging (fMRI) upon the application of a real-time spot pressure mechanical stimulus to assess the effects of SMT on patients with cLBP.

Methods: Patients with cLBP (Group 1, n = 14) and age-matched healthy controls without cLBP (Group 2, n = 20) were prospectively enrolled. Brain fMRI was performed for Group 1 at three time points: before SMT (TP1), after the first SMT session (TP2), and after the sixth SMT session (TP3). The healthy controls (Group 2) did not receive SMT and underwent only one fMRI scan. During fMRI scanning, a real-time spot pressure mechanical stimulus was applied to the low back area of all participants. Participants in Group 1 completed clinical questionnaires assessing pain and quality of life using a visual analog scale (VAS) and the Chinese Short Form Oswestry Disability Index (C-SFODI), respectively.

Results: Before SMT (TP1), there were no significant differences in brain activity between Group 1 and Group 2. After the first SMT session (TP2), Group 1 showed significantly greater brain activity in the right parahippocampal gyrus, right dorsolateral prefrontal cortex, and left precuneus compared to Group 2 (P < 0.05). After the sixth SMT session (TP3), Group 1 showed significantly greater brain activity in the posterior cingulate gyrus and right inferior frontal gyrus compared to Group 2 (P < 0.05). After both the first and sixth SMT sessions (TP2 and TP3), Group 1 had significantly lower VAS pain scores and C-SFODI scores than at TP1 (P < 0.001).

Conclusion: We observed alterations in brain activity in regions of the default mode network in patients with cLBP after SMT. These findings suggest the potential utility of the default mode network as a neuroimaging biomarker for pain management in patients with cLBP.

Clinical Trial Registration:Chinese Clinical Trial Registry, identifier ChiCTR1800015620.

Impact of self-designed Ningxin Anshen Decoction on the resting-state network functional connectivity in patients with mild to moderate generalized anxiety disorders

BACKGROUND

Generalized anxiety disorder (GAD) is a persistent chronic excessive anxiety that is hard to control. Our previous study indicated that self-designed Ningxin Anshen Formula (NXAS) was effective to treat mild to moderate GAD patients. This study is a randomized controlled clinical trial and aimed to investigate the imapct of self-designed NXAS on the resting-state functional connectivity (rsFC) in patients with mild to moderate GAD and explore the potential mechanisms.

METHODS

A total of 61 patients diagnosed with mild to moderate GAD were recruited and divided into two groups randomly: NXAS group (n=31) and placebo group (n=30). Before and after treatment, the rsFC was examined by resting-state functional MRI (rs-fMRI), the anxiety was assessed with HAMA, and the independent component analysis (ICA) was used to analyze the resting-state functional connectivity (rsFC). The correlation between HAMA score and abnormal rsFC was further evaluated.

RESULTS

The default mode network (DMN) showed evident rsFC interaction in the PCUN in both groups before and after therapy. The salience network (SN) showed obvious rsFC interaction in the bilateral gyrus frontalis inferiors and bilateral gyri temporalis superiors before and after therapy. In the NXAS group, the rsFC interction reduced significantly in the left gyrus frontalis inferior, but remained unchanged in the right gyrus frontalis inferior and bilateral gyri temporalis superiors after therapy. In the control group, the rsFC interaction increased dramatically after treatment. In addition, the abnormal rsFC had no relationship with HAMA score.

CONCLUSIONS

The self-designed NXAS can increase the rsFC in the PUCN on DMN and reduce rsFC in the orbIFG.L on SN to exert anti-anxiety effect.

Altruistic Punishment and Impulsivity in Parkinson's Disease: A Social Neuroscience Perspective

Non-motor symptoms of Parkinson's disease (PD) are of increasing interest in clinical and psychological research. Disinhibition-the inability to inhibit inappropriate behavior-leads to social and emotional impairments, including impulsive behavior and disregard for social conventions and decision-making behavior. In recent years, the latter has been investigated using economic exchanges during social interactions. Altruistic punishment-to punish someone who violates group norms even if it foresees a personal cost-is one of the most useful and fruitful paradigms; it allows to maintain a cooperation system within social groups. Alterations of this cognitive ability negatively impact the quality of life of the individual and social stability. Social neuroscience has suggested association between impulsive behaviors and altruistic punishment. Neuroimaging research aimed at exploring functional networks and intrinsic functional connectivity went in this direction. To date, little is known about these issues in neurodegenerative diseases such as PD. Dopamine replacement treatment and dopamine-agonists have been associated with impulse-control disorder and impulsive-compulsive behavior able to affect social decision-making. Frontal-executive dysfunction determines an alteration of social functioning through a mechanism of subversion of online action-monitoring, which associates disinhibition with volition. Genetic polymorphisms, alterations of the nigro-striatal substance, and impairment in the medial prefrontal cortex and in the Default mode network (DMN) seem to be able to explain these mechanisms. This theoretical perspective article aims to present these topics in order to encourage an interdisciplinary discussion capable of generating new research and developing rehabilitative intervention to improve social decision-making in PD patients.

Random Forest Classification of Alcohol Use Disorder Using EEG Source Functional Connectivity, Neuropsychological Functioning, and Impulsivity Measures

: Individuals with alcohol use disorder (AUD) manifest a variety of impairments that can be attributed to alterations in specific brain networks. The current study aims to identify features of EEG-based functional connectivity, neuropsychological performance, and impulsivity that can classify individuals with AUD (N = 30) from unaffected controls (CTL, N = 30) using random forest classification. The features included were: (i) EEG source functional connectivity (FC) of the default mode network (DMN) derived using eLORETA algorithm, (ii) neuropsychological scores from the Tower of London test (TOLT) and the visual span test (VST), and (iii) impulsivity factors from the Barratt impulsiveness scale (BIS). The random forest model achieved a classification accuracy of 80% and identified 29 FC connections (among 66 connections per frequency band), 3 neuropsychological variables from VST (total number of correctly performed trials in forward and backward sequences and average time for correct trials in forward sequence) and all four impulsivity scores (motor, non-planning, attentional, and total) as significantly contributing to classifying individuals as either AUD or CTL. Although there was a significant age difference between the groups, most of the top variables that contributed to the classification were not significantly correlated with age. The AUD group showed a predominant pattern of hyperconnectivity among 25 of 29 significant connections, indicating aberrant network functioning during resting state suggestive of neural hyperexcitability and impulsivity. Further, parahippocampal hyperconnectivity with other DMN regions was identified as a major hub region dysregulated in AUD (13 connections overall), possibly due to neural damage from chronic drinking, which may give rise to cognitive impairments, including memory deficits and blackouts. Furthermore, hypoconnectivity observed in four connections (prefrontal nodes connecting posterior right-hemispheric regions) may indicate a weaker or fractured prefrontal connectivity with other regions, which may be related to impaired higher cognitive functions. The AUD group also showed poorer memory performance on the VST task and increased impulsivity in all factors compared to controls. Features from all three domains had significant associations with one another. These results indicate that dysregulated neural connectivity across the DMN regions, especially relating to hyperconnected parahippocampal hub as well as hypoconnected prefrontal hub, may potentially represent neurophysiological biomarkers of AUD, while poor visual memory performance and heightened impulsivity may serve as cognitive-behavioral indices of AUD.

Random Forest Classification of Alcohol Use Disorder Using fMRI Functional Connectivity, Neuropsychological Functioning, and Impulsivity Measures

Individuals with alcohol use disorder (AUD) are known to manifest a variety of neurocognitive impairments that can be attributed to alterations in specific brain networks. The current study aims to identify specific features of brain connectivity, neuropsychological performance, and impulsivity traits that can classify adult males with AUD (n = 30) from healthy controls (CTL, n = 30) using the Random Forest (RF) classification method. The predictor variables were: (i) fMRI-based within-network functional connectivity (FC) of the Default Mode Network (DMN), (ii) neuropsychological scores from the Tower of London Test (TOLT), and the Visual Span Test (VST), and (iii) impulsivity factors from the Barratt Impulsiveness Scale (BIS). The RF model, with a classification accuracy of 76.67%, identified fourteen DMN connections, two neuropsychological variables (memory span and total correct scores of the forward condition of the VST), and all impulsivity factors as significantly important for classifying participants into either the AUD or CTL group. Specifically, the AUD group manifested hyperconnectivity across the bilateral anterior cingulate cortex and the prefrontal cortex as well as between the bilateral posterior cingulate cortex and the left inferior parietal lobule, while showing hypoconnectivity in long-range anterior-posterior and interhemispheric long-range connections. Individuals with AUD also showed poorer memory performance and increased impulsivity compared to CTL individuals. Furthermore, there were significant associations among FC, impulsivity, neuropsychological performance, and AUD status. These results confirm the previous findings that alterations in specific brain networks coupled with poor neuropsychological functioning and heightened impulsivity may characterize individuals with AUD, who can be efficiently identified using classification algorithms such as Random Forest.

Triple Network Model Dynamically Revisited: Lower Salience Network State Switching in Pre-psychosis

Emerging evidence has attributed altered network coordination between the default mode, central executive, and salience networks (DMN/CEN/SAL) to disturbances seen in schizophrenia, but little is known for at-risk psychosis stages. Moreover, pinpointing impairments in specific network-to-network interactions, although essential to resolve possibly distinct harbingers of conversion to clinically diagnosed schizophrenia, remains particularly challenging. We addressed this by a dynamic approach to functional connectivity, where right anterior insula brain interactions were examined through co-activation pattern (CAP) analysis. We utilized resting-state fMRI in 19 subjects suffering from subthreshold delusions and hallucinations (UHR), 28 at-risk for psychosis with basic symptoms describing only self-experienced subclinical disturbances (BS), and 29 healthy controls (CTR) matched for age, gender, handedness, and intelligence. We extracted the most recurring CAPs, compared their relative occurrence and average dwell time to probe their temporal expression, and quantified occurrence balance to assess the putative loss of competing relationships. Our findings substantiate the pivotal role of the right anterior insula in governing CEN-to-DMN transitions, which appear dysfunctional prior to the onset of psychosis, especially when first attenuated psychotic symptoms occur. In UHR subjects, it is longer active in concert with the DMN and there is a loss of competition between a SAL/DMN state, and a state with insula/CEN activation paralleled by DMN deactivation. These features suggest that abnormal network switching disrupts one's capacity to distinguish between the internal world and external environment, which is accompanied by inflexibility and an excessive awareness to internal processes reflected by prolonged expression of the right anterior insula-default mode co-activation pattern.

Default Mode Network Structural Integrity and Cerebellar Connectivity Predict Information Processing Speed Deficit in Multiple Sclerosis

Cognitive impairment affects about 50% of multiple sclerosis (MS) patients, but the mechanisms underlying this remain unclear. The default mode network (DMN) has been linked with cognition, but in MS its role is still poorly understood. Moreover, within an extended DMN network including the cerebellum (CBL-DMN), the contribution of cortico-cerebellar connectivity to MS cognitive performance remains unexplored. The present study investigated associations of DMN and CBL-DMN structural connectivity with cognitive processing speed in MS, in both cognitively impaired (CIMS) and cognitively preserved (CPMS) MS patients. 68 MS patients and 22 healthy controls (HCs) completed a symbol digit modalities test (SDMT) and had 3T brain magnetic resonance imaging (MRI) scans that included a diffusion weighted imaging protocol. DMN and CBL-DMN tracts were reconstructed with probabilistic tractography. These networks (DMN and CBL-DMN) and the cortico-cerebellar tracts alone were modeled using a graph theoretical approach with fractional anisotropy (FA) as the weighting factor. Brain parenchymal fraction (BPF) was also calculated. In CIMS SDMT scores strongly correlated with the FA-weighted global efficiency (GE) of the network [GE(CBL-DMN): ρ = 0.87, R² = 0.76, p < 0.001; GE(DMN): ρ = 0.82, R² = 0.67, p < 0.001; GE(CBL): ρ = 0.80, R² = 0.64, p < 0.001]. In CPMS the correlation between these measures was significantly lower [GE(CBL-DMN): ρ = 0.51, R² = 0.26, p < 0.001; GE(DMN): ρ = 0.48, R² = 0.23, p = 0.001; GE(CBL): ρ = 0.52, R² = 0.27, p < 0.001] and SDMT scores correlated most with BPF (ρ = 0.57, R² = 0.33, p < 0.001). In a multivariable regression model where SDMT was the independent variable, FA-weighted GE was the only significant explanatory variable in CIMS, while in CPMS BPF and expanded disability status scale were significant. No significant correlation was found in HC between SDMT scores, MRI or network measures. DMN structural GE is related to cognitive performance in MS, and results of CBL-DMN suggest that the cerebellum structural connectivity to the DMN plays an important role in information processing speed decline.

The Positive Brain - Resting State Functional Connectivity in Highly Vital and Flourishing Individuals

The World Health Organization has defined health as “complete physical, mental and social well-being and not merely the absence of disease or infirmity” (World Health Organization, 1948). An increasing number of studies have therefore started to investigate “the good life.” However, the underlying variation in brain activity has rarely been examined. The goal of this study was to assess differences in resting state functional connectivity (RSFC) between regular healthy individuals and healthy individuals with a high occurrence of flourishing and subjective vitality. Together, flourishing, a broad measure of psycho-social functioning and subjective vitality, an organismic marker of subjective well-being comprise the phenomenological opposite of a major depressive disorder. Out of a group of 43 participants, 20 high-flourishing (highFl) and 18 high-vital (highSV) individuals underwent a 7-min resting state period, where cortical activity in posterior brain areas was assessed using functional near-infrared spectroscopy (fNIRS). Network-based statistics (NBS) of FC yielded significantly different FC patterns for the highFl and highSV individuals compared to their healthy comparison group. The networks converged at areas of the posterior default mode network and differed in hub nodes in the left middle temporal/fusiform gyrus (flourishing) and the left primary/secondary somatosensory cortex (subjective vitality). The attained networks are discussed with regard to recent neuroscientific findings for other well-being measures and potential mechanisms of action based on social information processing and body-related self-perception.

Within-Network Connectivity in the Salience Network After Attention Bias Modification Training in Residual Depression: Report From a Preregistered Clinical Trial

Alterations in resting state networks (RSNs) are associated with emotional- and attentional control difficulties in depressed individuals. Attentional bias modification (ABM) training may lead to more adaptive emotional processing in depression, but little is known about the neural underpinnings associated with ABM. In the current study a sample of 134 previously depressed individuals were randomized into 14 days of computerized ABM- or a closely matched placebo training regime followed by a resting state magnetic resonance imaging (MRI) scan. Using independent component analysis (ICA) we examined within-network connectivity in three major RSN's, the default mode network (DMN), the salience network (SN) and the central executive network (CEN) after 2 weeks of ABM training. We found a significant difference between the training groups within the SN, but no difference within the DMN or CEN. Moreover, a significant symptom improvement was observed in the ABM group after training. Clinical Trial Registration: www.ClinicalTrials.gov, identifier NCT02931487.

Behavioral and Resting State Functional Connectivity Effects of High Frequency rTMS on Disorders of Consciousness: A Sham-Controlled Study

Objectives: A combined approach of behavioral characteristics and network properties was applied to explore the effect of repetitive transcranial magnetic stimulation (rTMS) on disorders of consciousness (DOC) and to observe changes in brain network connections before and after the stimulation.

Methods: A total of 7 DOC patients and 11 healthy controls were enrolled. The study was designed as a randomized, sham-controlled study. All DOC patients were given 20 Hz rTMS real and sham stimuli to the left M1 region, with each stimulus lasting for 5 consecutive working days and the interval between two stimuli being 1 week. Coma Recovery Scale-Revised (CRS-R) and resting state functional MRI data before and after stimuli were collected. The functional connection (FC) of the default mode network and the frontoparietal network were chosen as the central target to compare differences in network connections between the DOC group and the normal control group. For DOC patients, changes in behavior and brain function before and after real and sham stimuli were also assessed as a group and individually.

Results: (1). The overall analyses showed no significant changes of CRS-R scores or brain FC following real or sham rTMS stimuli in the DOC patients. However, real rTMS stimuli tended to enhance the FC of nodes in left lateral parietal cortex (LPC), left inferior temporal cortex (ITC) and right dorsolateral prefrontal cortex (DLPFC). (2). The individual analyses showed one minimally conscious state (MCS) patient presented with a obviously increased CRS-R score following real rTMS stimuli, and a visibly enhanced connectivity was observed in the nodes of left LPC, left ITC and right DLPFC of this patient.

Conclusion: Our findings did not provide sufficient evidence of therapeutic effect of 20 Hz rTMS over the left M1 in DOC. However, MCS patients shortly after brain injury may possibly benefit from rTMS. Reconstruction of the left LPC, the left ITC and the right DLPFC may be the brain networking foundation of improvements in consciousness from rTMS.

Alterations of the default mode network and cognitive impairment in patients with unilateral chronic tinnitus

Background

Previous studies have demonstrated that cognitive impairment is linked with neurophysiological alterations in chronic tinnitus. This study aimed to investigate the intrinsic functional connectivity (FC) pattern within the default mode network (DMN) and its associations with cognitive impairment in tinnitus patients using a resting-state functional magnetic resonance imaging (rs-fMRI).

Methods

Thirty-five chronic unilateral tinnitus patients, and 50 healthy controls were recruited for rsfMRI scanning. Both groups were age, gender and education level well-matched. The posterior cingulate cortex (PCC) was chosen as the region of interest (ROI) for detecting the FC changes, and determining if these abnormalities were related to a specific cognitive performance and tinnitus characteristic.

Results

Relative to the healthy controls, tinnitus patients showed increased FC between the PCC and the right medial prefrontal cortex (mPFC). Moreover, the enhanced FC between the PCC and right mPFC was correlated with the poorer TMT-B scores (r=0.474, P=0.008). These correlations were adjusted by age, gender, education level, GM volume, and mean hearing thresholds. The enhanced FC was not correlated with other tinnitus characteristics or cognitive performances.

Conclusions

The enhanced FC pattern of the PCC that is correlated with cognitive impairment in chronic tinnitus patients, especially the executive dysfunction. Enhanced connectivity pattern within the DMN may play a crucial role in neurophysiological mechanism in tinnitus patients with cognitive dysfunction.

Altered Functional Connectivity in Resting State Networks in Tourette's Disorder

Introduction: Brain regions are anatomically and functionally interconnected in order to facilitate important functions like cognition and movement. It remains incompletely understood how brain connectivity contributes to the pathophysiology of Tourette's disorder (TD). By using resting-state functional MRI, we aimed to identify alterations in the default mode network (DMN), frontal-parietal network (FPN), sensori-motor network (SMN), and salience network (SN) in TD compared with healthy control (HC) subjects. Method: In 23 adult TD patients and 22 HC, 3T-MRI resting-state scans were obtained. Independent component analysis was performed comparing TD and HC to investigate connectivity patterns within and between resting-state networks. Results: TD patients showed higher involvement of the dorsal medial prefrontal cortex in the connectivity of the DMN and less involvement of the inferior parietal cortex in the connectivity of the FPN when compared to HC. Moreover, TD patients showed a stronger coupling between DMN and left FPN than HC. Finally, in TD patients, functional connectivity within DMN correlated negatively with tic severity. Conclusion: We tentatively interpret the increased functional connectivity within DMN in TD patients as compensatory to the lower functional connectivity within left FPN. The stronger coupling between DMN and left FPN, together with the finding that higher DMN intrinsic connectivity is associated with lower tic severity would indicate that DMN is recruited to exert motor inhibition.

Differences in Cortical Structure and Functional MRI Connectivity in High Functioning Autism

Autism spectrum disorders (ASD) represent a complex group of neurodevelopmental conditions characterized by deficits in communication and social behaviors. We examined the functional connectivity (FC) of the default mode network (DMN) and its relation to multimodal morphometry to investigate superregional, system-level alterations in a group of 22 adolescents and young adults with high-functioning autism compared to age-, and intelligence quotient-matched 29 healthy controls. The main findings were that ASD patients had gray matter (GM) reduction, decreased cortical thickness and larger cortical surface areas in several brain regions, including the cingulate, temporal lobes, and amygdala, as well as increased gyrification in regions associated with encoding visual memories and areas of the sensorimotor component of the DMN, more pronounced in the left hemisphere. Moreover, patients with ASD had decreased connectivity between the posterior cingulate cortex, and areas of the executive control component of the DMN and increased FC between the anteromedial prefrontal cortex and areas of the sensorimotor component of the DMN. Reduced cortical thickness in the right inferior frontal lobe correlated with higher social impairment according to the scores of the Autism Diagnostic Interview-Revised (ADI-R). Reduced cortical thickness in left frontal regions, as well as an increased cortical thickness in the right temporal pole and posterior cingulate, were associated with worse scores on the communication domain of the ADI-R. We found no association between scores on the restrictive and repetitive behaviors domain of ADI-R with structural measures or FC. The combination of these structural and connectivity abnormalities may help to explain some of the core behaviors in high-functioning ASD and need to be investigated further.

Neuropsychodynamic Approach to Depression: Integrating Resting State Dysfunctions of the Brain and Disturbed Self-Related Processes

A mechanism-based approach was developed focusing on the psychodynamic, psychological and neuronal mechanisms in healthy and depressed persons. In this integrative concept of depression, the self is a core dimension in depression. It is attributed to negative emotions (e.g., failure, guilt). The increased inward focus in depression is connected with a decreased environmental focus. The development of neuropsychodynamic hypotheses of the altered self-reference is based on the investigation of the emotional-cognitive interaction in depressed patients. It may be hypothesized that the increased negative self-attributions—as typical characteristics of an increased self-focus in depression—may result from altered neuronal activity in subcortical-cortical midline structures in the brain, especially from hyperactivity in the cortical-subcortical midline regions and hypoactivity in the lateral regions. The increased resting state activity in depression is especially associated with an increased resting state activity in the default mode network (DMN) and a dysbalance between DMN and executive network (EN) activity. Possible therapeutic consequences of the neuropsychodynamic approach to depression involve the necessary emotional attunement in psychotherapy of depressed patients and the adequate timing of therapeutic interventions. The hypotheses which have been developed in the context of the neuropsychodynamic model of depression may be used for more specific psychotherapeutic interventions, aiming at specific mechanisms of compensation and defence, which are related to the increased resting state activity and the disturbed resting state-stimulus-interaction.

Mapping the Neural Dynamics of Korean-English Bilinguals With Medium Proficiency During Auditory Word Processing

Bilingualism is a worldwide phenomenon and provides an opportunity to understand how the brain represents language processing. Although many studies have investigated the neural mechanism of bilingualism, it still remain unclear how brain systems are involved in the second language processing. Here, we examined the neural dynamics of bilinguals with medium proficiency during auditory word processing. Korean–English (K–E) bilinguals were recruited for the study (L1: Korean and L2: English). They performed a word comprehension task on phonological and semantic aspects by hearing words. We compared their task performance, task-induced regional activity, and functional connectivity (FC) between L1 and L2 processing. Brain activation analyses revealed that L2 evoked more widespread and stronger activation in brain regions involved in auditory word processing and the increased regional activity in L2 was prominent during phonological processing. Moreover, L2 evoked up-regulation during semantic processing was associated with L2 proficiency. FC analyses demonstrated that the intra-network connectivity showed stronger in the language network (LN), dorsal attention network (DAN), and default mode network (DMN) in L2 than L1. For the L2 phonological processing, the increased FC within the DAN was positively correlated with individuals’ L2 proficiency. Also, L2 semantic processing induced the enhanced internetwork connectivity between the LN and DMN. Our findings suggest that L2 processing in K–E bilinguals induces dynamic changes in the brain at a regional and network-level and FC analysis can disentangle the different networks involvement in L2 auditory word processing according to two key features: phonology and semantics.

Age-Dependent Effects of Catechol-O-Methyltransferase (COMT) Gene Val158Met Polymorphism on Language Function in Developing Children

The genetic basis controlling language development remains elusive. Previous studies of the catechol-O-methyltransferase (COMT) Val¹⁵⁸Met genotype and cognition have focused on prefrontally guided executive functions involving dopamine. However, COMT may further influence posterior cortical regions implicated in language perception. We investigated whether COMT influences language ability and cortical language processing involving the posterior language regions in 246 children aged 6–10 years. We assessed language ability using a language test and cortical responses recorded during language processing using a word repetition task and functional near-infrared spectroscopy. The COMT genotype had significant effects on language performance and processing. Importantly, Met carriers outperformed Val homozygotes in language ability during the early elementary school years (6–8 years), whereas Val homozygotes exhibited significant language development during the later elementary school years. Both genotype groups exhibited equal language performance at approximately 10 years of age. Val homozygotes exhibited significantly less cortical activation compared with Met carriers during word processing, particularly at older ages. These findings regarding dopamine transmission efficacy may be explained by a hypothetical inverted U-shaped curve. Our findings indicate that the effects of the COMT genotype on language ability and cortical language processing may change in a narrow age window of 6–10 years.

Why and How. The Future of the Central Questions of Consciousness

In this review, we deal with two central questions of consciousness how and why, and we outline their possible future development. The question how refers to the empirical endeavor to reveal the neural correlates and mechanisms that form consciousness. On the other hand, the question why generally refers to the “hard problem” of consciousness, which claims that empirical science will always fail to provide a satisfactory answer to the question why is there conscious experience at all. Unfortunately, the hard problem of consciousness will probably never completely disappear because it will always have its most committed supporters. However, there is a good chance that its weight and importance will be highly reduced by empirically tackling consciousness in the near future. We expect that future empirical endeavor of consciousness will be based on a unifying brain theory and will answer the question as to what is the function of conscious experience, which will in turn replace the implications of the hard problem. The candidate of such a unifying brain theory is predictive coding, which will have to explain both perceptual consciousness and conscious mind-wandering in order to become the truly unifying theory of brain functioning.

Adaptive testing for multiple traits in a proportional odds model with applications to detect SNP-brain network associations

There has been increasing interest in developing more powerful and flexible statistical tests to detect genetic associations with multiple traits, as arising from neuroimaging genetic studies. Most of existing methods treat a single trait or multiple traits as response while treating an SNP as a predictor coded under an additive inheritance mode. In this paper, we follow an earlier approach in treating an SNP as an ordinal response while treating traits as predictors in a proportional odds model (POM). In this way, it is not only easier to handle mixed types of traits, e.g., some quantitative and some binary, but it is also potentially more robust to the commonly adopted additive inheritance mode. More importantly, we develop an adaptive test in a POM so that it can maintain high power across many possible situations. Compared to the existing methods treating multiple traits as responses, e.g., in a generalized estimating equation (GEE) approach, the proposed method can be applied to a high dimensional setting where the number of phenotypes (p) can be larger than the sample size (n), in addition to a usual small P setting. The promising performance of the proposed method was demonstrated with applications to the Alzheimer's Disease Neuroimaging Initiative (ADNI) data, in which either structural MRI driven phenotypes or resting-state functional MRI (rs-fMRI) derived brain functional connectivity measures were used as phenotypes. The applications led to the identification of several top SNPs of biological interest. Furthermore, simulation studies showed competitive performance of the new method, especially for p>n.

Prefrontal Function Engaging in External-Focused Attention in 5- to 6-Month-Old Infants: A Suggestion for Default Mode Network

The present study used functional near-infrared spectroscopy (fNIRS) to measure 5- to 6-month-old infants' hemodynamic response in the prefrontal cortex (PFC) to visual stimuli differing in saliency and social value. Nineteen Japanese 5- to 6-month-old infants watched video clips of Peek-a-Boo (social signal) performed by an anime character (AC) or a human, and hand movements without social signal performed by an AC. The PFC activity of infants was measured by 22-channel fNIRS, while behaviors including looking time were recorded simultaneously. NIRS data showed that infants' hemodynamic responses in the PFC generally decreased due to these stimuli, and the decrease was most prominent in the frontopolar (FP), covering medial PFC (MPFC), when infants were viewing Peek-a-Boo performed by an AC. Moreover, the decrease was more pronounced in the dorsolateral PFC (DLPFC) when infants were viewing Peek-a-Boo performed by an AC than by a human. Accordingly, behavioral data revealed significantly longer looking times when Peek-a-Boo was performed by an AC than by a human. No significant difference between Peek-a-Boo and non-Peek-a-Boo conditions was observed in either measure. These findings indicate that infants at this age may prefer stimuli with more salient features, which may be more effective in attracting their attentions. In conjunction with our previous findings on responses to self-name calling in infants of similar age, we hypothesize that the dynamic function of the MPFC and its vicinity (as part of default mode network (DMN): enhanced by self-focused stimuli, attenuated by externally focused stimuli), which is consistently observed in adults, may have already emerged in 5- to 6-month-old infants.

Default mode network deactivation during odor-visual association

Default mode network (DMN) deactivation has been shown to be functionally relevant for goal-directed cognition. In this study, the DMN's role during olfactory processing was investigated using two complementary functional magnetic resonance imaging (fMRI) paradigms with identical timing, visual-cue stimulation, and response monitoring protocols. Twenty-nine healthy, non-smoking, right-handed adults (mean age = 26 ± 4 years, 16 females) completed an odor-visual association fMRI paradigm that had two alternating odor + visual and visual-only trial conditions. During odor + visual trials, a visual cue was presented simultaneously with an odor, while during visual-only trial conditions the same visual cue was presented alone. Eighteen of the twenty-nine participants (mean age = 27.0 ± 6.0 years, 11 females) also took part in a control no-odor fMRI paradigm that consisted of a visual-only trial condition which was identical to the visual-only trials in the odor-visual association paradigm. Independent Component Analysis (ICA), extended unified structural equation modeling (euSEM), and psychophysiological interaction (PPI) were used to investigate the interplay between the DMN and olfactory network. In the odor-visual association paradigm, DMN deactivation was evoked by both the odor + visual and visual-only trial conditions. In contrast, the visual-only trials in the no-odor paradigm did not evoke consistent DMN deactivation. In the odor-visual association paradigm, the euSEM and PPI analyses identified a directed connectivity between the DMN and olfactory network which was significantly different between odor + visual and visual-only trial conditions. The results support a strong interaction between the DMN and olfactory network and highlights the DMN's role in task-evoked brain activity and behavioral responses during olfactory processing. Hum Brain Mapp 38:1125-1139, 2017. © 2016 Wiley Periodicals, Inc.

Noise Reduction in Arterial Spin Labeling Based Functional Connectivity Using Nuisance Variables

Arterial Spin Labeling (ASL) perfusion image series have recently been utilized for functional connectivity (FC) analysis in healthy volunteers and children with autism spectrum disorders (ASD). Noise reduction by using nuisance variables has been shown to be necessary to minimize potential confounding effects of head motion and physiological signals on BOLD based FC analysis. The purpose of the present study is to systematically evaluate the effectiveness of different noise reduction strategies (NRS) using nuisance variables to improve perfusion based FC analysis in two cohorts of healthy adults using state of the art 3D background-suppressed (BS) GRASE pseudo-continuous ASL (pCASL) and dual-echo 2D-EPI pCASL sequences. Five different NRS were performed in healthy volunteers to compare their performance. We then compared seed-based FC analysis using 3D BS GRASE pCASL in a cohort of 12 children with ASD (3f/9m, age 12.8 ± 1.3 years) and 13 typically developing (TD) children (1f/12m; age 13.9 ± 3 years) in conjunction with NRS. Regression of different combinations of nuisance variables affected FC analysis from a seed in the posterior cingulate cortex (PCC) to other areas of the default mode network (DMN) in both BOLD and pCASL data sets. Consistent with existing literature on BOLD-FC, we observed improved spatial specificity after physiological noise reduction and improved long-range connectivity using head movement related regressors. Furthermore, 3D BS GRASE pCASL shows much higher temporal SNR compared to dual-echo 2D-EPI pCASL and similar effects of noise reduction as those observed for BOLD. Seed-based FC analysis using 3D BS GRASE pCASL in children with ASD and TD children showed that noise reduction including physiological and motion related signals as nuisance variables is crucial for identifying altered long-range connectivity from PCC to frontal brain areas associated with ASD. This is the first study that systematically evaluated the effects of different NRS on ASL based FC analysis. 3D BS GRASE pCASL is the preferred ASL sequence for FC analysis due to its superior temporal SNR. Removing physiological noise and motion parameters is critical for detecting altered FC in neurodevelopmental disorders such as ASD.

Progressive Bidirectional Age-Related Changes in Default Mode Network Effective Connectivity across Six Decades

The default mode network (DMN) is a set of regions that is tonically engaged during the resting state and exhibits task-related deactivation that is readily reproducible across a wide range of paradigms and modalities. The DMN has been implicated in numerous disorders of cognition and, in particular, in disorders exhibiting age-related cognitive decline. Despite these observations, investigations of the DMN in normal aging are scant. Here, we used blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) acquired during rest to investigate age-related changes in functional connectivity of the DMN in 120 healthy normal volunteers comprising six, 20-subject, decade cohorts (from 20–29 to 70–79). Structural equation modeling (SEM) was used to assess age-related changes in inter-regional connectivity within the DMN. SEM was applied both using a previously published, meta-analytically derived, node-and-edge model, and using exploratory modeling searching for connections that optimized model fit improvement. Although the two models were highly similar (only 3 of 13 paths differed), the sample demonstrated significantly better fit with the exploratory model. For this reason, the exploratory model was used to assess age-related changes across the decade cohorts. Progressive, highly significant changes in path weights were found in 8 (of 13) paths: four rising, and four falling (most changes were significant by the third or fourth decade). In all cases, rising paths and falling paths projected in pairs onto the same nodes, suggesting compensatory increases associated with age-related decreases. This study demonstrates that age-related changes in DMN physiology (inter-regional connectivity) are bidirectional, progressive, of early onset and part of normal aging.

Effective Connectivity within the Default Mode Network: Dynamic Causal Modeling of Resting-State fMRI Data

The Default Mode Network (DMN) is a brain system that mediates internal modes of cognitive activity, showing higher neural activation when one is at rest. Nowadays, there is a lot of interest in assessing functional interactions between its key regions, but in the majority of studies only association of Blood-oxygen-level dependent (BOLD) activation patterns is measured, so it is impossible to identify causal influences. There are some studies of causal interactions (i.e., effective connectivity), however often with inconsistent results. The aim of the current work is to find a stable pattern of connectivity between four DMN key regions: the medial prefrontal cortex (mPFC), the posterior cingulate cortex (PCC), left and right intraparietal cortex (LIPC and RIPC). For this purpose functional magnetic resonance imaging (fMRI) data from 30 healthy subjects (1000 time points from each one) was acquired and spectral dynamic causal modeling (DCM) on a resting-state fMRI data was performed. The endogenous brain fluctuations were explicitly modeled by Discrete Cosine Set at the low frequency band of 0.0078–0.1 Hz. The best model at the group level is the one where connections from both bilateral IPC to mPFC and PCC are significant and symmetrical in strength (p < 0.05). Connections between mPFC and PCC are bidirectional, significant in the group and weaker than connections originating from bilateral IPC. In general, all connections from LIPC/RIPC to other DMN regions are much stronger. One can assume that these regions have a driving role within the DMN. Our results replicate some data from earlier works on effective connectivity within the DMN as well as provide new insights on internal DMN relationships and brain’s functioning at resting state.