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

BACKGROUND

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

AIM

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

METHODS

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

RESULTS

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

CONCLUSION

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

Sex heterogeneity of dynamic brain activity and functional connectivity in autism spectrum disorder

Sex heterogeneity has been frequently reported in autism spectrum disorders (ASD) and has been linked to static differences in brain function. However, given the complexity of ASD and diagnosis-by-sex interactions, dynamic characteristics of brain activity and functional connectivity may provide important information for distinguishing ASD phenotypes between females and males. The aim of this study was to explore sex heterogeneity of functional networks in the ASD brain from a dynamic perspective. Resting-state functional magnetic resonance imaging data from the Autism Brain Imaging Data Exchange database were analyzed in 128 ASD subjects (64 males/64 females) and 128 typically developing control (TC) subjects (64 males/64 females). A sliding-window approach was adopted for the estimation of dynamic amplitude of low-frequency fluctuation (dALFF) and dynamic functional connectivity (dFC) to characterize time-varying brain activity and functional connectivity respectively. We then examined the sex-related changes in ASD using two-way analysis of variance. Significant diagnosis-by-sex interaction effects were identified in the left anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC) and left precuneus in the dALFF analysis. Furthermore, there were significant diagnosis-by-sex interaction effects of dFC variance between the left ACC/mPFC and right ACC, left postcentral gyrus, left precuneus, right middle temporal gyrus and left inferior frontal gyrus, triangular part. These findings reveal the sex heterogeneity in brain activity and functional connectivity in ASD from a dynamic perspective, and provide new evidence for further exploring sex heterogeneity in ASD.

Specific static and dynamic functional network connectivity changes in thyroid-associated ophthalmopathy and it predictive values using machine learning

Background

Thyroid-associated ophthalmopathy (TAO) is a prevalent autoimmune disease characterized by ocular symptoms like eyelid retraction and exophthalmos. Prior neuroimaging studies have revealed structural and functional brain abnormalities in TAO patients, along with central nervous system symptoms such as cognitive deficits. Nonetheless, the changes in the static and dynamic functional network connectivity of the brain in TAO patients are currently unknown. This study delved into the modifications in static functional network connectivity (sFNC) and dynamic functional network connectivity (dFNC) among thyroid-associated ophthalmopathy patients using independent component analysis (ICA).

Methods

Thirty-two patients diagnosed with thyroid-associated ophthalmopathy and 30 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning. ICA method was utilized to extract the sFNC and dFNC changes of both groups.

Results

In comparison to the HC group, the TAO group exhibited significantly increased intra-network functional connectivity (FC) in the right inferior temporal gyrus of the executive control network (ECN) and the visual network (VN), along with significantly decreased intra-network FC in the dorsal attentional network (DAN), the default mode network (DMN), and the left middle cingulum of the ECN. On the other hand, FNC analysis revealed substantially reduced connectivity intra- VN and inter- cerebellum network (CN) and high-level cognitive networks (DAN, DMN, and ECN) in the TAO group compared to the HC group. Regarding dFNC, TAO patients displayed abnormal connectivity across all five states, characterized by notably reduced intra-VN connectivity and CN connectivity with high-level cognitive networks (DAN, DMN, and ECN), alongside compensatory increased connectivity between DMN and low-level perceptual networks (VN and basal ganglia network). No significant differences were observed between the two groups for the three dynamic temporal metrics. Furthermore, excluding the classification outcomes of FC within VN (with an accuracy of 51.61% and area under the curve of 0.35208), the FC-based support vector machine (SVM) model demonstrated improved performance in distinguishing between TAO and HC, achieving accuracies ranging from 69.35 to 77.42% and areas under the curve from 0.68229 to 0.81667. The FNC-based SVM classification yielded an accuracy of 61.29% and an area under the curve of 0.57292.

Conclusion

In summary, our study revealed that significant alterations in the visual network and high-level cognitive networks. These discoveries contribute to our understanding of the neural mechanisms in individuals with TAO, offering a valuable target for exploring future central nervous system changes in thyroid-associated eye diseases.

Functional network reorganization after endovascular thrombectomy in patients with anterior circulation stroke

BACKGROUND

Endovascular thrombectomy has been confirmed to be an effective therapy for acute ischemic stroke (AIS). However, how functional brain networks reorganize after restoration of blood supply in AIS patients, and whether the degree of reperfusion associates with functional network changes remains unclear.

METHODS

Resting-state fMRI data were collected from 43 AIS patients with anterior circulation occlusion after thrombectomy and 37 healthy controls (HCs). Both static and dynamic functional connectivity (FC) within four advanced functional networks including dorsal attention network (DAN), ventral attention network (VAN), executive control network (ECN) and default mode network (DMN), were calculated and compared between post-thrombectomy patients and HCs, and between two subgroups of post-thrombectomy patients with different reperfusion conditions.

RESULTS

As compared to HCs, patients showed significant differences in static FC of four functional networks, and in dynamic FC of DAN, ECN and DMN. Furthermore, patients with better reperfusion conditions exhibited increased static FC with precuneus, and altered dynamic FC within precuneus. Moreover, these alterations were associated with clinical assessments of stroke severity and functional recovery in post-thrombectomy patients.

CONCLUSIONS

Collectively, these findings may provide the potential imaging markers for assessment of thrombectomy efficacy and help establish the specific rehabilitation treatments for post-thrombectomy patients.

Left superior parietal lobe mediates the link between spontaneous mind-wandering tendency and task-switching performance

While increasing studies have documented the link between mind wandering and task switching, less is known about which brain regions mediate this relationship. Using the MPI-Leipzig Mind-Brain-Body dataset (N = 173), we investigated the association between trait-level tendencies of mind wandering, task-switching performance, structural connectivity, and resting-state functional connectivity. At the behavioral level, we found that higher spontaneous mind-wandering trait scores were associated with shorter reaction times on both repeat and switch trials. The whole brain cortical thickness analysis revealed a strong mediating role of the left superior parietal lobe, which is part of the dorsal attention network, in the link between spontaneous mind-wandering tendency and task-switching performance. The resting-state functional connectivity analysis further demonstrated that this association was partly mediated by the negative dorsal attention network-default mode network functional connectivity. No significant mediating effects were found for deliberate mind-wandering tendency. Overall, the findings highlight the pivotal role of the left superior parietal lobe in activating new mental set during mind-wandering and task-switching processes, providing another evidence in favor of a role for switching in mind wandering.

Association Between Negative Affect and Perceived Mortality Threat During the COVID-19 Pandemic: The Role of Brain Activity and Connectivity

The prevalence of the novel coronavirus (COVID-19) has been considered a major threat to physical and mental health around the world, causing great pressure and mortality threat to most people. The current study aimed to investigate the neurological markers underlying the relationship between perceived mortality threat (PMT) and negative affect (NA). We examined whether the regional amplitude of low-frequency fluctuations (ALFF) and resting-state functional connectivity (RSFC) before the COVID-19 outbreak (October 2019 to December 2019, wave 1) were predictive for NA and PMT during the mid-term of the COVID-19 pandemic (February 22 to 28, 2020, wave 2) among 603 young adults (age range 17-22, 70.8% females). Results indicated that PMT was associated with spontaneous activity in several regions (e.g., inferior temporal gyrus, medial occipital gyrus, medial frontal gyrus, angular gyrus, and cerebellum) and their RSFC with the distributed regions of the default mode network and cognitive control network. Furthermore, longitudinal mediation models showed that ALFF in the cerebellum, medial occipital gyrus, medial frontal gyrus, and angular gyrus (wave 1) predicted PMT (wave 2) through NA (wave 2). These findings revealed functional neural markers of PMT and suggest candidate mechanisms for explaining the complex relationship between NA and mental/neural processing related to PMT in the circumstance of a major crisis.

Design and application of a multimodality-compatible 1Tx/6Rx RF coil for monkey brain MRI at 7T

OBJECTIVE

Blood-oxygen-level-dependent functional MRI allows to investigte neural activities and connectivity. While the non-human primate plays an essential role in neuroscience research, multimodal methods combining functional MRI with other neuroimaging and neuromodulation enable us to understand the brain network at multiple scales.

APPROACH

In this study, a tight-fitting helmet-shape receive array with a single transmit loop for anesthetized macaque brain MRI at 7T was fabricated with four openings constructed in the coil housing to accommodate multimodal devices, and the coil performance was quantitatively evaluated and compared to a commercial knee coil. In addition, experiments over three macaques with infrared neural stimulation (INS), focused ultrasound stimulation (FUS), and transcranial direct current stimulation (tDCS) were conducted.

MAIN RESULTS

The RF coil showed higher transmit efficiency, comparable homogeneity, improved SNR and enlarged signal coverage over the macaque brain. Infrared neural stimulation was applied to the amygdala in deep brain region, and activations in stimulation sites and connected sites were detected, with the connectivity consistent with anatomical information. Focused ultrasound stimulation was applied to the left visual cortex, and activations were acquired along the ultrasound traveling path, with all time course curves consistent with pre-designed paradigms. The existence of transcranial direct current stimulation electrodes brought no interference to the RF system, as evidenced through high-resolution MPRAGE structure images.

SIGNIFICANCE

This pilot study reveals the feasibility for brain investigation at multiple spatiotemporal scales, which may advance our understanding in dynamic brain networks.

Noncoding transcripts are linked to brain resting-state activity in non-human primates

Brain-derived transcriptomes are known to correlate with resting-state brain activity in humans. Whether this association holds in nonhuman primates remains uncertain. Here, we search for such molecular correlates by integrating 757 transcriptomes derived from 100 macaque cortical regions with resting-state activity in separate conspecifics. We observe that 150 noncoding genes explain variations in resting-state activity at a comparable level with protein-coding genes. In-depth analysis of these noncoding genes reveals that they are connected to the function of nonneuronal cells such as oligodendrocytes. Co-expression network analysis finds that the modules of noncoding genes are linked to both autism and schizophrenia risk genes. Moreover, genes associated with resting-state noncoding genes are highly enriched in human resting-state functional genes and memory-effect genes, and their links with resting-state functional magnetic resonance imaging (fMRI) signals are altered in the brains of patients with autism. Our results highlight the potential for noncoding RNAs to explain resting-state activity in the nonhuman primate brain.

Resting-State Functional Connectivity Characteristics of Resilience to Traumatic Stress in Dutch Police Officers

Background

Insights into the neurobiological basis of resilience can have important implications for the prevention and treatment of stress-related disorders, especially in populations that are subjected to high-stress environments. Evaluating large-scale resting-state networks (RSNs) can provide information regarding resilient specific brain function which may be useful in understanding resilience. This study aimed to explore functional connectivity patterns specific for (high) resilience in Dutch policemen after exposure to multiple work-related traumatic events. We investigated resting-state functional connectivity (RSFC) of the salience network (SN), limbic network, and the default-mode network (DMN).

Methods

Resting-state functional MRI scans were obtained from trauma-exposed executive personnel of the Dutch police force and non-trauma-exposed recruits from the police academy. Participants were divided into three groups: a resilient group (n = 31; trauma exposure; no psychopathology), a vulnerable group (n = 32; trauma exposure, psychopathology), and a control group (n = 19; no trauma exposure, no psychopathology). RSFC of the three networks of interest was compared between these groups, using an independent component analysis and a dual regression approach.

Results

We found decreased resilience-specific positive RSFC of the salience network with several prefrontal regions. The DMN and limbic network RFSC did not show resilience-specific patterns.

Conclusion

This study shows a differential RSFC specific for resilient police officers. This differential RSFC may be related to a greater capacity for internal-focused thought and interoceptive awareness, allowing more effective higher-order responses to stress in highly resilient individuals.

Tasks activating the default mode network map multiple functional systems

Recent developments in network neuroscience suggest reconsidering what we thought we knew about the default mode network (DMN). Although this network has always been seen as unitary and associated with the resting state, a new deconstructive line of research is pointing out that the DMN could be divided into multiple subsystems supporting different functions. By now, it is well known that the DMN is not only deactivated by tasks, but also involved in affective, mnestic, and social paradigms, among others. Nonetheless, it is starting to become clear that the array of activities in which it is involved, might also be extended to more extrinsic functions. The present meta-analytic study is meant to push this boundary a bit further. The BrainMap database was searched for all experimental paradigms activating the DMN, and their activation likelihood estimation maps were then computed. An additional map of task-induced deactivations was also created. A multidimensional scaling indicated that such maps could be arranged along an anatomo-psychological gradient, which goes from midline core activations, associated with the most internal functions, to that of lateral cortices, involved in more external tasks. Further multivariate investigations suggested that such extrinsic mode is especially related to reward, semantic, and emotional functions. However, an important finding was that the various activation maps were often different from the canonical representation of the resting-state DMN, sometimes overlapping with it only in some peripheral nodes, and including external regions such as the insula. Altogether, our findings suggest that the intrinsic-extrinsic opposition may be better understood in the form of a continuous scale, rather than a dichotomy.

Aberrant static and dynamic functional network connectivity in heart failure with preserved ejection fraction

Aims

Heart failure may lead to brain functional alterations related to cognitive impairment. This study aimed to detect alterations of static functional network connectivity (FNC) and dynamic FNC in heart failure with preserved ejection fraction (HFpEF) and to estimate the association between the altered FNC and clinical features related to HFpEF.

Methods and results

The clinical and resting‐state functional magnetic resonance imaging (fMRI) data of HFpEF patients (n = 35) and healthy controls (HCs) (n = 35) were acquired at baseline. Resting‐state networks (RSNs) were established based on independent component analysis (ICA) and FNC analyses were performed. The associations between the FNC abnormalities and clinical features related to HFpEF were analysed. Compared with HCs, HFpEF patients showed decreased functional connectivity within the default mode network, left frontoparietal network, and right frontoparietal network and increased functional connectivity within the right frontoparietal network and visual network. Negative correlations were observed between decreased dynamic FNC and the left ventricular end‐diastolic diameter (LVDd) (r = −0.435, P = 0.015) as well as the left ventricular end‐systolic diameter (LVDs) (r = −0.443, P = 0.013).

Conclusions

The FNC disruption and altered temporal properties of functional dynamics in HFpEF patients may reflect the neural mechanisms of brain injury after HFpEF, which may deepen our understanding of the disease.

Mechanisms of Repetitive Transcranial Magnetic Stimulation on Post-stroke Depression: A Resting-State Functional Magnetic Resonance Imaging Study

We aimed to identify neural mechanisms underlying clinical response to repetitive transcranial magnetic stimulation (rTMS) in post-stroke depression (PSD) by the Resting-state functional magnetic resonance imaging (rs-fMRI). Thirty-two depressed patients after ischemic stroke were randomized in a 1:1 ratio to receive 20 min of 5 Hz rTMS or sham over left dorsolateral prefrontal cortex (DLPFC) in addition to routine supportive treatments. The clinical outcome was measured by the 17-item Hamilton Depression Rating Scale (HDRS-17), while the imaging results were acquired from rs-fMRI, including regional homogeneity (ReHo), fractional amplitude of low-frequency fluctuation (fALFF) and seed-based dynamic functional connection (dFC). HRSD-17 scores were improved in the two groups after treatment (P < 0.01), while greater mood improvement was observed in the rTMS group (P < 0.05). Compared with the sham group, the rTMS group demonstrated regions with higher ReHo and fALFF values locating mainly in the left hemisphere and highly consistent with the default mode network (DMN) (p < 0.05). Using the medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC) as seeds, significant difference between the two groups in dFC within the DMN was found after treatment, including 10 connections with increased connectivity strength and 2 connections with reduced connectivity strength. The ReHo, fALFF and dFC values within DMN in the rTMS group were negatively correlated with the HDRS scores after treatment (P < 0.05). Our results indicated reductions in depressive symptoms following rTMS in PSD are associated with functional alterations of different depression-related areas within the DMN.

Source space reduction for eLORETA

Objective.We introduce Sparse exact low resolution electromagnetic tomography (eLORETA), a novel method for estimating a nonparametric solution to the source localization problem. Its goal is to generate a sparser solution compared to other source localization methods including eLORETA while benefitting from the latter's superior source localization accuracy.Approach.Sparse eLORETA starts by reducing the source space of the Lead Field Matrix using structured sparse Bayesian learning from which a Reduced Lead Field Matrix is constructed, which is used as input to eLORETA.Main results.With Sparse eLORETA, source sparsity can be traded against signal fidelity; the proposed optimum is shown to yield a much sparser solution than eLORETA's with only a slight loss in signal fidelity.Significance.When pursuing a data-driven approach, for cases where it is difficult to choose specific regions of interest, or when subsequently a connectivity analysis is performed, source space reduction could prove beneficial.

Reduced functional network connectivity is associated with upper limb dysfunction in acute ischemic brainstem stroke

This study aimed to detect alterations in intra- and inter-network functional connectivity (FC) of multiple networks in acute brainstem ischemic stroke patients, and the relationship between FC and movement assessment scores to assess their ability to predict upper extremity motor impairment. Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from acute brainstem ischemic stroke patients (n = 50) and healthy controls (HCs) (n = 45). Resting-state networks (RSNs) were established based on independent component analysis (ICA) and the functional network connectivity (FNC) analysis was performed. Subsequently, correlation analysis was subsequently used to explore the relationship between FNC abnormalities and upper extremity motor impairment. Altered FC within default mode network (DMN), executive control network (ECN), the salience network (SN), auditory network (AN), and cerebellum network (CN) were found in the acute brainstem ischemic stroke group relative to HCs. Moreover, different patterns of altered network interactions were found between the patients and HCs, including the SN-CN, SN-AN, and ECN-DMN connections. Correlations between functional disconnection and upper limb dysfunction measurements in acute brainstem ischemic stroke patients were also found. This study intimated that widespread FNC impairment and altered integration existed in brainstem ischemic stroke at acute stage, suggesting that FNC disruption may be applied for early diagnosis and prediction of upper limb dysfunction in acute brainstem ischemic stroke.

Anger Experience and Anger Expression Through Drawing in Schizophrenia: An fNIRS Study

Differences in emotion experience and emotion expression between patients with schizophrenia and the healthy population have long been the focus of research and clinical attention. However, few empirical studies have addressed this topic using art-making as a tool of emotion expression. This study explores the differences in brain mechanism during the process of expressing anger between patients with schizophrenia and healthy participants using pictographic psychological techniques. We used functional near-infrared spectroscopy to fully detect changes in frontal cortex activity among participants in two groups-schizophrenia and healthy-during the process of experiencing and expressing anger. The results showed that there were no differences in the experience of anger between the two groups. In the process of anger expression, the dorsolateral prefrontal cortex, frontal pole, and other regions showed significant negative activation among patients with schizophrenia, which was significantly different from that of the healthy group. There were significant differences between patients with schizophrenia and the healthy group in the drawing features, drawing contents, and the ability to describe the contents of their drawings. Moreover, the effect size of the latter was greater than those of the former two. In terms of emotion expression, the drawing data and brain activation data were significantly correlated in each group; however, the correlation patterns differed between groups.

A reachable probability approach for the analysis of spatio-temporal dynamics in the human functional network

The dynamic architecture of the human brain has been consistently observed. However, there is still limited modeling work to elucidate how neuronal circuits are hierarchically and flexibly organized in functional systems. Here we proposed a reachable probability approach based on non-homogeneous Markov chains, to characterize all possible connectivity flows and the hierarchical structure of brain functional systems at the dynamic level. We proved at the theoretical level the convergence of the functional brain network system, and demonstrated that this approach is able to detect network steady states across connectivity structure, particularly in areas of the default mode network. We further explored the dynamically hierarchical functional organization centered at the primary sensory cortices. We observed smaller optimal reachable steps to their local functional regions, and differentiated patterns in larger optimal reachable steps for primary perceptual modalities. The reachable paths with the largest and second largest transition probabilities between primary sensory seeds via multisensory integration regions were also tracked to explore the flexibility and plasticity of the multisensory integration. The present work provides a novel approach to depict both the stable and flexible hierarchical connectivity organization of the human brain.

Sex difference in neural responses to gaming cues in Internet gaming disorder: Implications for why males are more vulnerable to cue-induced cravings than females

BACKGROUND

Although drug addiction studies have shown that females are more likely to become addicted and sensitive to drug cues, this feature seems reversed in Internet gaming disorder (IGD), of which males are more likely to be sufferers. Given the prevalence of IGD in the male population, the current study was set to examine the potential effect of sex on IGD's craving using a cue reactivity task.

METHODS

Sixty-five (32 males) IGD subjects underwent fMRI scanning during exposure to visual gaming cues and neutral cues. Brain responses to gaming cues relative to neutral cues were examined within two groups separately. In addition, Granger causal analysis (GCA) was conducted to investigate how the effective connectivity patterns were altered in male and female IGD subjects.

RESULTS

When facing gaming cues, lower regions of brain activation were observed in males compared to females, including the left anterior cingulate cortex (ACC), the superior frontal gyrus and the posterior cingulate cortex (PCC); GCA results, using the PCC as the ROI, showed higher middle temporal gyrus-PCC-right ACC/parahippocampal gyrus effective connectivity in males as compared with females, when exposed to gaming cues.

CONCLUSION

The results indicate that gaming cues could more severely disturb male IGD subjects' inhibition control function over game-elicited cravings compared to females, which might make it hard for males to control their game cravings and stop their gaming behaviors. This conclusion is valuable in understanding why males are more vulnerable to IGD than females.

Default mode network activity in depression subtypes

Depression continues to carry a major disease burden worldwide, with limitations on the success of traditional pharmacological or psychological treatments. Recent approaches have therefore focused upon the neurobiological underpinnings of depression, and on the "individualization" of depression symptom profiles. One such model of depression has divided the standard diagnostic criteria into four "depression subtypes", with neurological and behavioral pathways. At the same time, attention has been focused upon the region of the brain known as the "default mode network" (DMN) and its role in attention and problem-solving. However, to date, no review has been published of the links between the DMN and the four subtypes of depression. By searching the literature studies from the last 20 years, 62 relevant papers were identified, and their findings are described for the association they demonstrate between aspects of the DMN and the four depression subtypes. It is apparent from this review that there are potential positive clinical and therapeutic outcomes from focusing upon DMN activation and connectivity, via psychological therapies, transcranial magnetic stimulation, and some emerging pharmacological models.

Cross-species functional alignment reveals evolutionary hierarchy within the connectome

Evolution provides an important window into how cortical organization shapes function and vice versa. The complex mosaic of changes in brain morphology and functional organization that have shaped the mammalian cortex during evolution, complicates attempts to chart cortical differences across species. It limits our ability to fully appreciate how evolution has shaped our brain, especially in systems associated with unique human cognitive capabilities that lack anatomical homologues in other species. Here, we develop a function-based method for cross-species alignment that enables the quantification of homologous regions between humans and rhesus macaques, even when their location is decoupled from anatomical landmarks. Critically, we find cross-species similarity in functional organization reflects a gradient of evolutionary change that decreases from unimodal systems and culminates with the most pronounced changes in posterior regions of the default mode network (angular gyrus, posterior cingulate and middle temporal cortices). Our findings suggest that the establishment of the default mode network, as the apex of a cognitive hierarchy, has changed in a complex manner during human evolution - even within subnetworks.

Fine-Grained Topography and Modularity of the Macaque Frontal Pole Cortex Revealed by Anatomical Connectivity Profiles

The frontal pole cortex (FPC) plays key roles in various higher-order functions and is highly developed in non-human primates. An essential missing piece of information is the detailed anatomical connections for finer parcellation of the macaque FPC than provided by the previous tracer results. This is important for understanding the functional architecture of the cerebral cortex. Here, combining cross-validation and principal component analysis, we formed a tractography-based parcellation scheme that applied a machine learning algorithm to divide the macaque FPC (2 males and 6 females) into eight subareas using high-resolution diffusion magnetic resonance imaging with the 9.4T Bruker system, and then revealed their subregional connections. Furthermore, we applied improved hierarchical clustering to the obtained parcels to probe the modular structure of the subregions, and found that the dorsolateral FPC, which contains an extension to the medial FPC, was mainly connected to regions of the default-mode network. The ventral FPC was mainly involved in the social-interaction network and the dorsal FPC in the metacognitive network. These results enhance our understanding of the anatomy and circuitry of the macaque brain, and contribute to FPC-related clinical research.

Social interaction networks in the primate brain

Primate brains have evolved to understand and engage with their social world. Much about the structure of this world can be gleaned from social interactions. Circuits for the analysis of and participation in social interactions have now been mapped. Increased knowledge about their functional specializations and relative spatial locations promises to greatly improve the understanding of the functional organization of the primate social brain. Detailed electrophysiology, as in the case of the face-processing network, of local operations and functional interactions between areas is necessary to uncover neural mechanisms and computation principles of social cognition. New naturalistic behavioral paradigms, behavioral tracking, and new analytical approaches for parallel non-stationary data will be important components toward a neuroscientific theory of primates' interactive minds.

Changes in Brain Function Networks in Patients With Amnestic Mild Cognitive Impairment: A Resting-State fMRI Study

Patients with amnestic mild cognitive impairment (aMCI) are at high risk of developing dementia. This study used resting-state functional magnetic resonance imaging (rs-fMRI) and an independent component analysis (ICA) approach to explore changes in functional connectivity (FC) in the default mode network (DMN), executive control network (ECN), and salience network (SN). Thirty patients with aMCI and 30 healthy controls (HCs) were enrolled. All the participants underwent an rs-fMRI scan. The brain FC in DMN, ECN, and SN was calculated using the ICA approach. We found that the FC of brain regions in DMN decreased significantly and that of brain regions in ECN increased, which was in accordance with the findings of previous studies on Alzheimer's disease (AD) and aMCI. We also found that the FC of brain regions in SN increased, which was different from the findings of previous studies on AD. The increase in FC in brain regions in SN might result from different pathophysiological states in AD and aMCI, indicating that a decrease in FC in SN does not occur in a person with aMCI. These results are consistent with those of previous studies using the voxel-mirrored homotopic connectivity approach and seed-based correlation analysis. We therefore considered that the decrease in FC in DMN and the increase in FC in ECN and SN might be peculiar patterns observed on the rs-fMRI of a person with aMCI. These findings may contribute to the development of imaging biomarkers for the diagnosis of aMCI.

Frequency-dependent functional connectivity in resting state networks

Functional magnetic resonance imaging studies have documented the resting human brain to be functionally organized in multiple large‐scale networks, called resting‐state networks (RSNs). Other brain imaging techniques, such as electroencephalography (EEG) and magnetoencephalography (MEG), have been used for investigating the electrophysiological basis of RSNs. To date, it is largely unclear how neural oscillations measured with EEG and MEG are related to functional connectivity in the resting state. In addition, it remains to be elucidated whether and how the observed neural oscillations are related to the spatial distribution of the network nodes over the cortex. To address these questions, we examined frequency‐dependent functional connectivity between the main nodes of several RSNs, spanning large part of the cortex. We estimated connectivity using band‐limited power correlations from high‐density EEG data collected in healthy participants. We observed that functional interactions within RSNs are characterized by a specific combination of neuronal oscillations in the alpha (8–13 Hz), beta (13–30 Hz), and gamma (30–80 Hz) bands, which highly depend on the position of the network nodes. This finding may contribute to a better understanding of the mechanisms through which neural oscillations support functional connectivity in the brain.

Disrupted Brain Structural Connectivity Network in Subcortical Ischemic Vascular Cognitive Impairment With No Dementia

The alteration of the functional topological organization in subcortical ischemic vascular cognitive impairment with no dementia (SIVCIND) patients has been illuminated by previous neuroimaging studies. However, in regard to the changes in the structural connectivity of brain networks, little has been reported. In this study, a total of 27 subjects, consisting of 13 SIVCIND patients, and 14 normal controls, were recruited. Each of the structural connectivity networks was constructed by diffusion tensor tractography. Subsequently, graph theory, and network-based statistics (NBS) were employed to analyze the whole-brain mean factional anisotropy matrix. After removing the factor of age, gender, and duration of formal education, the clustering coefficients (C_p) and global efficiency (E_glob) were significantly decreased and the mean path length (L_p) was significantly increased in SIVCIND patients compared with normal controls. Using the combination of four network topological parameters as the classification feature, a classification accuracy of 78% was obtained by leave-one-out cross-validation for all subjects with a sensitivity of 69% and a specificity of 86%. Moreover, we also found decreased structural connections in the SIVCIND patients, which mainly concerned fronto-occipital, fronto-subcortical, and tempo-occipital connections (NBS corrected, p < 0.01). Additionally, significantly altered nodal centralities were found in several brain regions of the SIVCIND patients, mainly located in the prefrontal, subcortical, and temporal cortices. These results suggest that cognitive impairment in SIVCIND patients is associated with disrupted topological organization and provide structural evidence for developing reliable biomarkers related to cognitive decline in SIVCIND.

Different Patterns of Functional Connectivity Alterations Within the Default-Mode Network and Sensorimotor Network in Basal Ganglia and Pontine Stroke

Background

The aim of this study was to investigate whether patients with basal ganglia stroke and patients with pontine stroke have different types of functional connectivity (FC) alterations in the early chronic phase.

Material/Methods

We included 14 patients with pontine stroke, 17 patients with basal ganglia stroke, and 20 well-matched healthy controls (HCs). All of them underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning. The independent component analysis (ICA) approach was applied to extract information regarding the default-mode network (DMN), including anterior DMN (aDMN) and posterior DMN (pDMN) components and the sensorimotor network (SMN).

Results

Compared with HCs, patients with basal ganglia stroke exhibited significantly reduced FC in the left precuneus of the pDMN, right supplementary motor area (SMA), and right superior frontal gyrus (SFG) of the SMN. Additionally, FC in the left medial prefrontal gyrus (MFG) of the aDMN, right precuneus and right posterior cingulate cortex (PCC) of the pDMN, and left middle cingulate gyrus (mid-CC) of the SMN decreased in patients with pontine stroke.

Conclusions

The different patterns of FC damage in patients with basal ganglia stroke and patients with pontine stroke in the early chronic phase may provide a new method for investigating lesion-induced network plasticity.

Disrupted resting-state brain functional network in methamphetamine abusers: A brain source space study by EEG

This study aimed to examine the effects of chronic methamphetamine use on the topological organization of whole-brain functional connectivity network (FCN) by reconstruction of neural-activity time series at resting-state. The EEG of 36 individuals with methamphetamine use disorder (IWMUD) and 24 normal controls (NCs) were recorded, pre-processed and source-reconstructed using standardized low-resolution tomography (sLORETA). The brain FCNs of participants were constructed and between-group differences in network topological properties were investigated using graph theoretical analysis. IWMUD showed decreased characteristic path length, increased clustering coefficient and small-world index at delta and gamma frequency bands compared to NCs. Moreover, abnormal changes in inter-regional connectivity and network hubs were observed in all the frequency bands. The results suggest that the IWMUD and NCs have distinct FCNs at all the frequency bands, particularly at the delta and gamma bands, in which deviated small-world brain topology was found in IWMUD.

Cardiorespiratory fitness predicts effective connectivity between the hippocampus and default mode network nodes in young adults

Rodent and human studies examining the relationship between aerobic exercise, brain structure, and brain function indicate that the hippocampus (HC), a brain region critical for episodic memory, demonstrates striking plasticity in response to exercise. Beyond the hippocampal memory system, human studies also indicate that aerobic exercise and cardiorespiratory fitness (CRF) are associated with individual differences in large-scale brain networks responsible for broad cognitive domains. Examining network activity in large-scale resting-state brain networks may provide a link connecting the observed relationships between aerobic exercise, hippocampal plasticity, and cognitive enhancement within broad cognitive domains. Previously, CRF has been associated with increased functional connectivity of the default mode network (DMN), specifically in older adults. However, how CRF relates to the magnitude and directionality of connectivity, or effective connectivity, between the HC and other DMN nodes remains unknown. We used resting-state fMRI and conditional Granger causality analysis (CGCA) to test the hypothesis that CRF positively predicts effective connectivity between the HC and other DMN nodes in healthy young adults. Twenty-six participants (ages 18-35 years) underwent a treadmill test to determine CRF by estimating its primary determinant, maximal oxygen uptake (V^. O_2max ), and a 10-min resting-state fMRI scan to examine DMN effective connectivity. We identified the DMN using group independent component analysis and examined effective connectivity between nodes using CGCA. Linear regression analyses demonstrated that CRF significantly predicts causal influence from the HC to the ventromedial prefrontal cortex, posterior cingulate cortex, and lateral temporal cortex and to the HC from the dorsomedial prefrontal cortex. The observed relationship between CRF and hippocampal effective connectivity provides a link between the rodent literature, which demonstrates a relationship between aerobic exercise and hippocampal plasticity, and the human literature, which demonstrates a relationship between aerobic exercise and CRF and the enhancement of broad cognitive domains including, but not limited to, memory.

Network-based Responses to the Psychomotor Vigilance Task during Lapses in Adolescents after Short and Extended Sleep

Neuroimaging studies of the Psychomotor Vigilance Task (PVT) have revealed brain regions involved in attention lapses in sleep-deprived and well-rested adults. Those studies have focused on individual brain regions, rather than integrated brain networks, and have overlooked adolescence, a period of ongoing brain development and endemic short sleep. This study used functional MRI (fMRI) and a contemporary analytic approach to assess time-resolved peri-stimulus response of key brain networks when adolescents complete the PVT, and test for differences across attentive versus inattentive periods and after short sleep versus well-rested states. Healthy 14–17-year-olds underwent a within-subjects randomized protocol including 5-night spans of extended versus short sleep. PVT was performed during fMRI the morning after each sleep condition. Event-related independent component analysis (eICA) identified coactivating functional networks and corresponding time courses. Analysis of salient time course characteristics tested the effects of sleep condition, lapses, and their interaction. Seven eICA networks were identified supporting attention, executive control, motor, visual, and default-mode functions. Attention lapses, after either sleep manipulation, were accompanied by broadly increased response magnitudes post-stimulus and delayed peak responses in some networks. Well-circumscribed networks respond during the PVT in adolescents, with timing and intensity impacted by attentional lapses regardless of experimentally shortened or extended sleep.

Mapping Internet gaming disorder using effective connectivity: A spectral dynamic causal modeling study

OBJECTS

Understanding the neural basis underlying Internet gaming disorder (IGD) is essential for the diagnosis and treatment of this type of behavioural addiction. Aberrant resting-state functional connectivity (rsFC) of the default mode network (DMN) has been reported in individuals with IGD. Since rsFC is not a directional analysis, the effective connectivity within the DMN in IGD remains unclear. Here, we employed spectral dynamic causal modeling (spDCM) to explore this issue.

METHODS

Resting state fMRI data were collected from 64 IGD (age: 22.6 ± 2.2) and 63 well-matched recreational Internet game users (RGU, age: 23.1 ± 2.5). Voxel-based mean time series data extracted from the 4 brain regions within the DMN (medial prefrontal cortex, mPFC; posterior cingulate cortex, PCC; bilateral inferior parietal lobule, left IPL/right IPL) of two groups during the resting state were used for the spDCM analysis.

RESULTS

Compared with RGU, IGD showed reduced effective connectivity from the mPFC to the PCC and from the left IPL to the mPFC, with reduced self-connection in the PCC and the left IPL.

CONCLUSIONS

The spDCM could distinguish the changes in the functional architecture between two groups more precisely than rsFC. Our findings suggest that the decreased excitatory connectivity from the mPFC to the PCC may be a crucial biomarker for IGD. Future brain-based intervention should pay attention to dysregulation in the IPL-mPFC-PCC circuits.

Difference in regional neural fluctuations and functional connectivity in Crohn's disease: a resting-state functional MRI study

Patients with Crohn's disease (CD) are shown to have abnormal changes in brain structures. This study aimed to further investigate whether these patients have abnormal brain activities and network connectivity. Sixty patients with CD and 40 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (fMRI) scans. Amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity (FC) were used to assess differences in spontaneous regional brain activity and functional connectivity. Compared to the HCs, patients with CD showed significantly higher ALFF values in hippocampus and parahippocampus (HIPP/paraHIPP), anterior cingulate cortex, insula, superior frontal cortex and precuneus. The ALFF values were significantly lower in secondary somatosensory cortex (S2), precentral gyrus, and medial prefrontal cortex. Functional connectivities between left HIPP and left inferior temporal cortex, and right middle cingulate cortex, HIPP, and fusiform area were significantly lower. The functional connectivities between right HIPP and right inferior orbitofrontal cortex and left HIPP were also significantly lower. Patients with CD showed higher or lower spontaneous activity in multiple brain regions. Altered activities in these brain regions may collectively reflect abnormal function and regulation of visceral pain and sensation, external environmental monitoring, and cognitive processing in these patients. Lower functional connectivity of the hippocampus-limbic system was observed in these patients. These findings may provide more information to elucidate the neurobiological mechanisms of the disease.

A systematic review of neuroimaging in delirium: predictors, correlates and consequences

OBJECTIVE

Neuroimaging advances our understanding of delirium pathophysiology and its consequences. A previous systematic review identified 12 studies (total participants N = 764, delirium cases N = 194; years 1989-2007) and found associations with white matter hyperintensities (WMH) and cerebral atrophy. Our objectives were to perform an updated systematic review of neuroimaging studies in delirium published since January 2006 and summarise the available literature on predictors, correlates or outcomes.

METHODS

Studies were identified by keyword and MeSH-based electronic searches of EMBASE, MEDLINE and PsycINFO combining terms for neuroimaging, brain structure and delirium. We included neuroimaging studies of delirium in adults using validated delirium assessment methods.

RESULTS

Thirty-two studies (total N = 3187, delirium N = 1086) met the inclusion criteria. Imaging included magnetic resonance imaging (MRI; N = 9), computed tomography (N = 4), diffusion tensor imaging (N = 3), transcranial Doppler (N = 5), near infrared spectroscopy (N = 5), functional-MRI (N = 2), single photon emission computed tomography (N = 1), proton MRI spectroscopy (N = 1), arterial spin-labelling MRI (N = 1) and 2-¹³ fluoro-2-deoxyglucose positron emission tomography (N = 1). Despite heterogeneity in study design, delirium was associated with WMH, lower brain volume, atrophy, dysconnectivity, impaired cerebral autoregulation, reduced blood flow and cerebral oxygenation and glucose hypometabolism. There was evidence of long-term brain changes following intensive care unit delirium.

CONCLUSIONS

Neuroimaging is now used more widely in delirium research due to advances in technology. However, imaging delirious patients presents challenges leading to methodological limitations and restricted generalisability. The findings that atrophy and WMH burden predict delirium replicates findings from the original review, while advanced techniques have identified other substrates and mechanisms that warrant further investigation.

Partially impaired functional connectivity states between right anterior insula and default mode network in autism spectrum disorder

Time-invariant resting-state functional connectivity studies have illuminated the crucial role of the right anterior insula (rAI) in prominent social impairments of autism spectrum disorder (ASD). However, a recent dynamic connectivity study demonstrated that rather than being stationary, functional connectivity patterns of the rAI vary significantly across time. The present study aimed to explore the differences in functional connectivity in dynamic states of the rAI between individuals with ASD and typically developing controls (TD). Resting-state functional magnetic resonance imaging data obtained from a publicly available database were analyzed in 209 individuals with ASD and 298 demographically matched controls. A k-means clustering algorithm was utilized to obtain five dynamic states of functional connectivity of the rAI. The temporal properties, frequency properties, and meta-analytic decoding were first identified in TD group to obtain the characteristics of each rAI dynamic state. Multivariate analysis of variance was then performed to compare the functional connectivity patterns of the rAI between ASD and TD groups in obtained states. Significantly impaired connectivity was observed in ASD in the ventral medial prefrontal cortex and posterior cingulate cortex, which are two critical hubs of the default mode network (DMN). States in which ASD showed decreased connectivity between the rAI and these regions were those more relevant to socio-cognitive processing. From a dynamic perspective, these findings demonstrate partially impaired resting-state functional connectivity patterns between the rAI and DMN across states in ASD, and provide novel insights into the neural mechanisms underlying social impairments in individuals with ASD.

Neurogenetic profiles delineate large-scale connectivity dynamics of the human brain

Experimental and modeling work of neural activity has described recurrent and attractor dynamic patterns in cerebral microcircuits. However, it is still poorly understood whether similar dynamic principles exist or can be generalizable to the large-scale level. Here, we applied dynamic graph theory-based analyses to evaluate the dynamic streams of whole-brain functional connectivity over time across cognitive states. Dynamic connectivity in local networks is located in attentional areas during tasks and primary sensory areas during rest states, and dynamic connectivity in distributed networks converges in the default mode network (DMN) in both task and rest states. Importantly, we find that distinctive dynamic connectivity patterns are spatially associated with Allen Human Brain Atlas genetic transcription levels of synaptic long-term potentiation and long-term depression-related genes. Our findings support the neurobiological basis of large-scale attractor-like dynamics in the heteromodal cortex within the DMN, irrespective of cognitive state.

Principal States of Dynamic Functional Connectivity Reveal the Link Between Resting-State and Task-State Brain: An fMRI Study

Task-related reorganization of functional connectivity (FC) has been widely investigated. Under classic static FC analysis, brain networks under task and rest have been demonstrated a general similarity. However, brain activity and cognitive process are believed to be dynamic and adaptive. Since static FC inherently ignores the distinct temporal patterns between rest and task, dynamic FC may be more a suitable technique to characterize the brain’s dynamic and adaptive activities. In this study, we adopted [Formula: see text]-means clustering to investigate task-related spatiotemporal reorganization of dynamic brain networks and hypothesized that dynamic FC would be able to reveal the link between resting-state and task-state brain organization, including broadly similar spatial patterns but distinct temporal patterns. In order to test this hypothesis, this study examined the dynamic FC in default-mode network (DMN) and motor-related network (MN) using Blood-Oxygenation-Level-Dependent (BOLD)-fMRI data from 26 healthy subjects during rest (REST) and a hand closing-and-opening (HCO) task. Two principal FC states in REST and one principal FC state in HCO were identified. The first principal FC state in REST was found similar to that in HCO, which appeared to represent intrinsic network architecture and validated the broadly similar spatial patterns between REST and HCO. However, the second FC principal state in REST with much shorter “dwell time” implied the transient functional relationship between DMN and MN during REST. In addition, a more frequent shifting between two principal FC states indicated that brain network dynamically maintained a “default mode” in the motor system during REST, whereas the presence of a single principal FC state and reduced FC variability implied a more temporally stable connectivity during HCO, validating the distinct temporal patterns between REST and HCO. Our results further demonstrated that dynamic FC analysis could offer unique insights in understanding how the brain reorganizes itself during rest and task states, and the ways in which the brain adaptively responds to the cognitive requirements of tasks.

Decreased functional connectivity within the default-mode network in acute brainstem ischemic stroke

PURPOSE

Ischemic stroke within the brainstem is associated with an increased risk of cognitive dysfunction. This study aimed to explore the integrity of a default-mode network (DMN) and its relationship with clinical variables in patients with acute ischemic brainstem stroke using an independent component analysis (ICA) approach.

MATERIALS AND METHODS

Twenty-one patients with acute ischemic brainstem stroke and 25 well-matched healthy subjects were enrolled in this study and underwent resting-state functional magnetic resonance imaging. The ICA was adopted to extract the DMN, including its anterior and posterior components. Pearson correlation analyses were performed to investigate the relationship between DMN connectivity and clinical variables.

RESULTS

Compared with healthy controls, patients with acute ischemic stroke showed significantly decreased functional connectivity in the right medial prefrontal cortex (mPFC) and right precuneus within the anterior and posterior DMN, respectively. After correcting for age, sex, and education, hypoconnectivity in the right mPFC and right precuneus was negatively correlated with higher homocysteine in patients with stroke (r = -0.592, p = 0.010 and r = -0.491, p = 0.039, respectively).

CONCLUSION

The finding of decreased functional connectivity within the DMN of patients with acute brainstem stroke provides novel insight into the neural mechanisms that underlie cognitive impairment following ischemic insult to this brain region.

Relationship Between Alpha Rhythm and the Default Mode Network: An EEG-fMRI Study

PURPOSE

Reports of the relationship between the default mode network (DMN) and alpha power are conflicting. Our goal was to assess this relationship by analyzing concurrently obtained EEG/functional MRI data using hypothesis-independent methods.

METHODS

We collected functional MRI and EEG data during eyes-closed rest in 20 participants aged 19 to 37 (10 females) and performed independent component analysis on the functional MRI data and a Hamming-windowed fast Fourier transform on the EEG data. We correlated functional MRI fluctuations in the DMN with alpha power.

RESULTS

Of the six independent components found to have significant relationships with alpha, four contained DMN-associated regions: One independent component was positively correlated with alpha power, whereas all others were negatively correlated. Furthermore, two independent components with opposite relationships with alpha had overlapping voxels in the medial prefrontal cortex and posterior cingulate cortex, suggesting that subpopulations of neurons within these classic nodes within the DMN may have different relationships to alpha power.

CONCLUSIONS

Different parts of the DMN exhibit divergent relationships to alpha power. Our results highlight the relationship between DMN activity and alpha power, indicating that networks, such as the DMN, may have subcomponents that exhibit different behaviors.

The cholinergic contribution to the resting-state functional network in non-demented Parkinson's disease

The cholinergic system arising from the basal forebrain plays an important role in cognitive performance in Parkinson's disease (PD). Here, we analyzed cholinergic status-dependent cortical and subcortical resting-state functional connectivity in PD. A total of 61 drug-naïve PD patients were divided into tertiles based on normalized substantia innominata (SI) volumes. We compared the resting-state network from seed region of interest in the caudate, posterior cingulate cortex (PCC), and SI between the lowest (PD-L) and highest tertile (PD-H) groups. Correlation analysis of the functional networks was also performed in all subjects. The functional network analysis showed that PD-L subjects displayed decreased striato-cortical functional connectivity compared with PD-H subjects. Selecting the PCC as a seed, the PD-L patients displayed decreased functional connectivity compared to PD-H patients. Meanwhile, PD-L subjects had significantly increased cortical functional connectivity with the SI compared with PD-H subjects. Correlation analysis revealed that SI volume had a positive correlation with functional connectivity from the right caudate and PCC. The present study demonstrated that PD patients exhibited unique functional connectivity from the caudate and the PCC that may be closely associated with cholinergic status, suggesting an important role for the cholinergic system in PD-associated cognition.

Neuroendocrine Abnormalities Following Traumatic Brain Injury: An Important Contributor to Neuropsychiatric Sequelae

Neuropsychiatric symptoms following traumatic brain injury (TBI) are common and contribute negatively to TBI outcomes by reducing overall quality of life. The development of neurobehavioral sequelae, such as concentration deficits, depression, anxiety, fatigue, and loss of emotional well-being has historically been attributed to an ambiguous "post-concussive syndrome," considered secondary to frank structural injury and axonal damage. However, recent research suggests that neuroendocrine dysfunction, specifically hypopituitarism, plays an important role in the etiology of these symptoms. This post-head trauma hypopituitarism (PHTH) has been shown in the past two decades to be a clinically prevalent phenomenon, and given the parallels between neuropsychiatric symptoms associated with non-TBI-induced hypopituitarism and those following TBI, it is now acknowledged that PHTH is likely a substantial contributor to these impairments. The current paper seeks to provide an overview of hypothesized pathophysiological mechanisms underlying neuroendocrine abnormalities after TBI, and to emphasize the significance of this phenomenon in the development of the neurobehavioral problems frequently seen after head trauma.

Cerebellar Neural Circuits Involving Executive Control Network Predict Response to Group Cognitive Behavior Therapy in Social Anxiety Disorder

Some intrinsic connectivity networks including the default mode network (DMN) and executive control network (ECN) may underlie social anxiety disorder (SAD). Although the cerebellum has been implicated in the pathophysiology of SAD and several networks relevant to higher-order cognition, it remains unknown whether cerebellar areas involved in DMN and ECN exhibit altered resting-state functional connectivity (rsFC) with cortical networks in SAD. Forty-six patients with SAD and 64 healthy controls (HC) were included and submitted to the baseline resting-state functional magnetic resonance imaging (fMRI). Seventeen SAD patients who completed post-treatment clinical assessments were included after group cognitive behavior therapy (CBT). RsFC of three cerebellar subregions in both groups was assessed respectively in a voxel-wise way, and these rsFC maps were compared by two-sample t tests between groups. Whole-brain voxel-wise regression was performed to examine whether cerebellar connectivity networks can predict response to CBT. Lower rsFC circuits of cerebellar subregions compared with HC at baseline (p < 0.05, corrected by false discovery rate) were revealed. The left Crus I rsFC with dorsal medial prefrontal cortex was negatively correlated with symptom severity. The clinical assessments in SAD patients were significantly decreased after CBT. Higher pretreatment cerebellar rsFC with angular gyrus and dorsal lateral frontal cortex corresponded with greater symptom improvement following CBT. Cerebellar rsFC circuits involving DMN and ECN are possible neuropathologic mechanisms of SAD. Stronger pretreatment cerebellar rsFC circuits involving ECN suggest potential neural markers to predict CBT response.

Neural correlates of novelty and appropriateness processing in externally induced constraint relaxation

Novelty and appropriateness are considered the two fundamental features of creative thinking, including insight problem solving, which can be performed through chunk decomposition and constraint relaxation. Based on a previous study that separated the neural bases of novelty and appropriateness in chunk decomposition, in this study, we used event-related functional magnetic resonance imaging (fMRI) to further dissociate these mechanisms in constraint relaxation. Participants were guided to mentally represent the method of problem solving according to the externally provided solutions that were elaborately prepared in advance and systematically varied in their novelty and appropriateness for the given problem situation. The results showed that novelty processing was completed by the temporoparietal junction (TPJ) and regions in the executive system (dorsolateral prefrontal cortex [DLPFC]), whereas appropriateness processing was completed by the TPJ and regions in the episodic memory (hippocampus), emotion (amygdala), and reward systems (orbitofrontal cortex [OFC]). These results likely indicate that appropriateness processing can result in a more memorable and richer experience than novelty processing in constraint relaxation. The shared and distinct neural mechanisms of the features of novelty and appropriateness in constraint relaxation are discussed, enriching the representation of the change theory of insight.

Pre-treatment Resting-State Functional MR Imaging Predicts the Long-Term Clinical Outcome After Short-Term Paroxtine Treatment in Post-traumatic Stress Disorder

Background: The chronic phase of post-traumatic stress disorder (PTSD) and the limited effectiveness of existing treatments creates the need for the development of potential biomarkers to predict response to antidepressant medication at an early stage. However, findings at present focus on acute therapeutic effect without following-up the long-term clinical outcome of PTSD. So far, studies predicting the long-term clinical outcome of short-term treatment based on both pre-treatment and post-treatment functional MRI in PTSD remains limited. Methods: Twenty-two PTSD patients were scanned using resting-state functional MRI (rs-fMRI) before and after 12 weeks of treatment with paroxetine. Twenty patients were followed up using the same psychopathological assessments 2 years after they underwent the second MRI scan. Based on clinical outcome, the follow-up patients were divided into those with remitted PTSD or persistent PTSD. Amplitude of low-frequency fluctuations (ALFF) and degree centrality (DC) derived from pre-treatment and post-treatment rs-fMRI were used as classification features in a support vector machine (SVM) classifier. Results: Prediction of long-term clinical outcome by combined ALFF and DC features derived from pre-treatment rs-fMRI yielded an accuracy rate of 72.5% (p < 0.005). The most informative voxels for outcome prediction were mainly located in the precuneus, superior temporal area, insula, dorsal medial prefrontal cortex, frontal orbital cortex, supplementary motor area, lingual gyrus, and cerebellum. Long-term outcome could not be successfully classified by post-treatment imaging features with accuracy rates <50%. Conclusions: Combined information from ALFF and DC from rs-fMRI data before treatment could predict the long-term clinical outcome of PTSD, which is critical for defining potential biomarkers to customize PTSD treatment and improve the prognosis.

Threat Response System: Parallel Brain Processes in Pain vis-à-vis Fear and Anxiety

Pain is essential for avoidance of tissue damage and for promotion of healing. Notwithstanding the survival value, pain brings about emotional suffering reflected in fear and anxiety, which in turn augment pain thus giving rise to a self-sustaining feedforward loop. Given such reciprocal relationships, the present article uses neuroscientific conceptualizations of fear and anxiety as a theoretical framework for hitherto insufficiently understood pathophysiological mechanisms underlying chronic pain. To that end, searches of PubMed-indexed journals were performed using the following Medical Subject Headings' terms: pain and nociception plus amygdala, anxiety, cognitive, fear, sensory, and unconscious. Recursive sets of scientific and clinical evidence extracted from this literature review were summarized within the following key areas: (1) parallelism between acute pain and fear and between chronic pain and anxiety; (2) all are related to the evasion of sensory-perceived threats and are subserved by subcortical circuits mediating automatic threat-induced physiologic responses and defensive actions in conjunction with higher order corticolimbic networks (e.g., thalamocortical, thalamo-striato-cortical and amygdalo-cortical) generating conscious representations and valuation-based adaptive behaviors; (3) some instances of chronic pain and anxiety conditions are driven by the failure to diminish or block respective nociceptive information or unconscious treats from reaching conscious awareness; and (4) the neural correlates of pain-related conscious states and cognitions may become autonomous (i.e., dissociated) from the subcortical activity/function leading to the eventual chronicity. Identifying relative contributions of the diverse neuroanatomical sources, thus, offers prospects for the development of novel preventive, diagnostic, and therapeutic strategies in chronic pain patients.

Attention Shifts Recruit the Monkey Default Mode Network

A unifying function associated with the default mode network (DMN), which is more active during rest than under active task conditions, has been difficult to define. The DMN is activated during monitoring the external world for unexpected events, as a sentinel, and when humans are engaged in high-level internally focused tasks. The existence of DMN correlates in other species, such as mice, challenge the idea that internally focused, high-level cognitive operations, such as introspection, autobiographical memory retrieval, planning the future, and predicting someone else's thoughts, are evolutionarily preserved defining properties of the DMN. A recent human study demonstrated that demanding cognitive shifts could recruit the DMN, yet it is unknown whether this holds for nonhuman species. Therefore, we tested whether large changes in cognitive context would recruit DMN regions in female and male nonhuman primates. Such changes were measured as displacements of spatial attentional weights based on internal rules of relevance (spatial shifts) compared with maintaining attentional weights at the same location (stay events). Using fMRI in macaques, we detected that a cortical network, activated during shifts, largely overlapped with the DMN. Moreover, fMRI time courses sampled from independently defined DMN foci showed significant shift selectivity during the demanding attention task. Finally, functional clustering based on independent resting state data revealed that DMN and shift regions clustered conjointly, whereas regions activated during the stay events clustered apart. We therefore propose that cognitive shifting in primates generally recruits DMN regions. This might explain a breakdown of the DMN in many neurological diseases characterized by declined cognitive flexibility.SIGNIFICANCE STATEMENT Activation of the human default mode network (DMN) can be measured with fMRI when subjects shift thoughts between high-level internally directed cognitive states, when thinking about the self, the perspective of others, when imagining future and past events, and during mind wandering. Furthermore, the DMN is activated as a sentinel, monitoring the environment for unexpected events. Arguably, these cognitive processes have in common fast and substantial changes in cognitive context. As DMN activity has also been reported in nonhuman species, we tested whether shifts in spatial attention activated the monkey DMN. Core monkey DMN and shift-selective regions shared several functional properties, indicating that cognitive shifting, in general, might constitute one of the evolutionarily preserved functions of the DMN.

Relationships between short and fast brain timescales

Brain electric activity exhibits two important features: oscillations with different timescales, characterized by diverse functional and psychological outcomes, and a temporal power law distribution. In order to further investigate the relationships between low- and high- frequency spikes in the brain, we used a variant of the Borsuk-Ulam theorem which states that, when we assess the nervous activity as embedded in a sphere equipped with a fractal dimension, we achieve two antipodal points with similar features (the slow and fast, scale-free oscillations). We demonstrate that slow and fast nervous oscillations mirror each other over time via a sinusoid relationship and provide, through the Bloch theorem from solid-state physics, the possible equation which links the two timescale activities. We show that, based on topological findings, nervous activities occurring in micro-levels are projected to single activities at meso- and macro-levels. This means that brain functions assessed at the higher scale of the whole brain necessarily display a counterpart in the lower ones, and vice versa. Our topological approach makes it possible to assess brain functions both based on entropy, and in the general terms of particle trajectories taking place on donut-like manifolds. Condensed brain activities might give rise to ideas and concepts by combination of different functional and anatomical levels. Furthermore, cognitive phenomena, as well as social activity can be described by the laws of quantum mechanics; memories and decisions exhibit holographic organization. In physics, the term duality refers to a case where two seemingly different systems turn out to be equivalent. This topological duality holds for all the types of spatio-temporal brain activities, independent of their inter- and intra-level relationships, strength, magnitude and boundaries, allowing us to connect the physiological manifestations of consciousness to the electric activities of the brain.

Effect of Electro-Acupuncture and Moxibustion on Brain Connectivity in Patients with Crohn's Disease: A Resting-State fMRI Study

Acupuncture and moxibustion have been shown to be effective in treating Crohn’s disease (CD), but their therapeutic mechanisms remain unclear. Here we compared brain responses to either electro-acupuncture or moxibustion treatment in CD patients experiencing remission. A total of 65 patients were randomly divided into an electro-acupuncture group (n = 32) or a moxibustion group (n = 33), and treated for 12 weeks. Eighteen patients in the electro-acupuncture group and 20 patients in the moxibustion group underwent resting-state functional magnetic resonance imaging at baseline and after treatment. Seed-based analysis was used to compare the resting-state functional connectivity (rsFC) between bilateral hippocampus and other brain regions before and after the treatments, as well as between the two groups. The CD activity index (CDAI) and inflammatory bowel disease questionnaire (IBDQ) were used to evaluate disease severity and patient quality of life. Electro-acupuncture and moxibustion both significantly reduced CDAI values and increased IBDQ scores. In the electro-acupuncture group, the rsFC values between bilateral hippocampus and anterior middle cingulate cortex (MCC) and insula were significantly increased, and the changes were negatively correlated with the CDAI scores. In the moxibustion group, the rsFC values between bilateral hippocampus and precuneus as well as inferior parietal lobe (IPC) were significantly elevated, and the changes were negatively correlated with the CDAI scores. We conclude that the therapeutic effects of electro-acupuncture and moxibustion on CD may involve the differently modulating brain homeostatic afferent processing network and default mode network (DMN), respectively.

Atypical neuronal activation during a spatial working memory task in 13-year-old very preterm children

Children born very preterm (VP; <32 weeks' gestational age) are at risk for unfavorable outcomes in several cognitive domains, including spatial working memory (WM). The underlying neural basis of these cognitive impairments is poorly understood. We investigated differences in neuronal activation during spatial WM using a backward span (BS) task relative to a control (C) task in 45 VP children and 19 term-born controls aged 13 years. VP children showed significantly more activation in the bilateral superior frontal gyrus and significantly less activation in the left parahippocampal gyrus compared with controls. We further explored the distinct contributions of maintenance and manipulation processes of WM using forward span (FS)>C and BS > FS, respectively. There were no significant group differences in neuronal activation for FS > C. However, BS > FS revealed that VP children had significantly greater activation in the left middle frontal gyrus, in the left superior parietal gyrus and right cerebellar tonsil, and significantly less activation in the right precentral and postcentral gyrus and left insula compared with controls. Taken together these results suggest that VP children at 13 years of age show an atypical neuronal activation during spatial WM, specifically related to manipulation of spatial information in WM. It is unclear whether these findings reflect delayed maturation and/or recruitment of alternative neuronal networks as a result of neuroplasticity. Hum Brain Mapp 38:6172-6184, 2017. © 2017 Wiley Periodicals, Inc.

Decreased variability of dynamic phase synchronization in brain networks during hand movement

Dynamic functional connectivity analysis, a rapidly growing method, has been demonstrated to provide new spatiotemporal information about how brain motor network would reorganize from rest to motor tasks. Phase synchronization analysis, which has been widely applied in EEG-based FC analysis, is a promising alternative method in dynamic FC analysis. In this study, fMRI data were recorded from 28 healthy volunteers when they are resting and performing hand closing and opening (HCO) task. Dynamic FC was estimated by phase synchronization analysis. In addition, functional connectivity variability (FCV) was compared between rest and HCO to investigate the modulation induced by motor task on dynamics of motor-related FC and network. Results showed that the FCVs in network-of-interest, including default-mode network and motor network, decreased during HCO comparing with rest. Our results demonstrated that the unconstrained mental activities, which resulted in high FCV during rest, would focus on motor execution during HCO and thus led to decreased FCV during HCO.

An emergent functional parcellation of the temporal cortex

The temporal lobe has been associated with various cognitive functions which include memory, auditory cognition and semantics. However, at a higher level of conceptualisation, all of the functions associated with the temporal lobe can be considered as lying along one major axis; from modality-specific to modality-general processing. This paper used a spectral reordering technique on resting-state and task-based functional data to extract the major organisational axis of the temporal lobe in a bottom-up, data-driven fashion. Independent parcellations were performed on resting-state scans from 71 participants and active semantic task scans from 23 participants acquired using dual echo gradient echo planar imaging in order to preserve signal in inferior temporal cortex. The resulting organisational axis was consistent (over dataset and hemisphere) and progressed from superior temporal gyrus and posterior inferior temporal cortex to ventrolateral anterior temporal cortex. A hard parcellation separated a posterior (superior temporal and posterior fusiform and inferior temporal gyri) and an anterior cluster (ventrolateral anterior temporal lobe). The functional connectivity of the hard clusters supported the hypothesis that the connectivity gradient separated modality-specific and modality-general regions. This hypothesis was then directly tested by performing a VOI analysis upon an independent semantic task-based data set including auditory and visually presented stimuli. This confirmed that the ventrolateral anterior aspects of the temporal lobe are associated with modality-general processes whilst posterior and superior aspects are specific to certain modalities, with the posterior inferior subregions involved in visual processes and superior regions involved in audition.