Chronnectomic patterns and neural flexibility underlie executive function

Dynamic properties in functional connectivity changes and striatal dopamine deficiency in Parkinson's disease

Recent studies in Parkinson's disease (PD) patients reported disruptions in dynamic functional connectivity (dFC, i.e., a characterization of spontaneous fluctuations in functional connectivity over time). Here, we assessed whether the integrity of striatal dopamine terminals directly modulates dFC metrics in two separate PD cohorts, indexing dopamine-related changes in large-scale brain network dynamics and its implications in clinical features. We pooled data from two disease-control cohorts reflecting early PD. From the Parkinson's Progression Marker Initiative (PPMI) cohort, resting-state functional magnetic resonance imaging (rsfMRI) and dopamine transporter (DaT) single-photon emission computed tomography (SPECT) were available for 63 PD patients and 16 age- and sex-matched healthy controls. From the clinical research group 219 (KFO) cohort, rsfMRI imaging was available for 52 PD patients and 17 age- and sex-matched healthy controls. A subset of 41 PD patients and 13 healthy control subjects additionally underwent 18F-DOPA-positron emission tomography (PET) imaging. The striatal synthesis capacity of 18F-DOPA PET and dopamine terminal quantity of DaT SPECT images were extracted for the putamen and the caudate. After rsfMRI pre-processing, an independent component analysis was performed on both cohorts simultaneously. Based on the derived components, an individual sliding window approach (44 s window) and a subsequent k-means clustering were conducted separately for each cohort to derive dFC states (reemerging intra- and interindividual connectivity patterns). From these states, we derived temporal metrics, such as average dwell time per state, state attendance, and number of transitions and compared them between groups and cohorts. Further, we correlated these with the respective measures for local dopaminergic impairment and clinical severity. The cohorts did not differ regarding age and sex. Between cohorts, PD groups differed regarding disease duration, education, cognitive scores and L-dopa equivalent daily dose. In both cohorts, the dFC analysis resulted in three distinct states, varying in connectivity patterns and strength. In the PPMI cohort, PD patients showed a lower state attendance for the globally integrated (GI) state and a lower number of transitions than controls. Significantly, worse motor scores (Unified Parkinson's Disease Rating Scale Part III) and dopaminergic impairment in the putamen and the caudate were associated with low average dwell time in the GI state and a low total number of transitions. These results were not observed in the KFO cohort: No group differences in dFC measures or associations between dFC variables and dopamine synthesis capacity were observed. Notably, worse motor performance was associated with a low number of bidirectional transitions between the GI and the lesser connected (LC) state across the PD groups of both cohorts. Hence, in early PD, relative preservation of motor performance may be linked to a more dynamic engagement of an interconnected brain state. Specifically, those large-scale network dynamics seem to relate to striatal dopamine availability. Notably, most of these results were obtained only for one cohort, suggesting that dFC is impacted by certain cohort features like educational level, or disease severity. As we could not pinpoint these features with the data at hand, we suspect that other, in our case untracked, demographical features drive connectivity dynamics in PD. PRACTITIONER POINTS: Exploring dopamine's role in brain network dynamics in two Parkinson's disease (PD) cohorts, we unraveled PD-specific changes in dynamic functional connectivity. Results in the Parkinson's Progression Marker Initiative (PPMI) and the KFO cohort suggest motor performance may be linked to a more dynamic engagement and disengagement of an interconnected brain state. Results only in the PPMI cohort suggest striatal dopamine availability influences large-scale network dynamics that are relevant in motor control.

Investigating the relationship between resting-state EEG microstates and executive functions: A null finding

Recent advances in cognitive neurosciences suggest that intrinsic brain networks dynamics are associated with cognitive functioning. Despite this emerging perspective, limited research exists to validate this hypothesis. This Registered Report aimed to specifically test the relationship between intrinsic brain spatio-temporal dynamics and executive functions. Resting-state EEG microstates were used to assess brain spatio-temporal dynamics, while a comprehensive battery of nine cognitive function tasks was employed to evaluate executive functions in 140 participants. We hypothesized that microstates (class C and D) metrics would correlate with an executive functions composite score. Contrary to expectations, our hypotheses were not supported by the data. We however observed a small, non-significant trend with a negative correlation between microstate D occurrences and executive functions scores (r = -.18, 95% CI [-.33, -.01]) which however did not meet the adjusted threshold for significance. In light of the inconclusive or minor effect sizes observed, the assertion that intrinsic brain networks dynamics - as measured by resting-state EEG microstate metrics - are a reliable signature of executive functioning remains unsupported.

Alterations in Dynamic Functional Connectivity in Patients with Cerebral Small Vessel Disease

Cerebral small vessel disease (CSVD) is a common disease that seriously endangers people's health, and is easily overlooked by both patients and clinicians due to its near-silent onset. Dynamic functional connectivity (DFC) is a new concept focusing on the dynamic features and patterns of brain networks that represents a powerful tool for gaining novel insight into neurological diseases. To assess alterations in DFC in CSVD patients, and the correlation of DFC with cognitive function. We enrolled 35 CSVD patients and 31 normal control subjects (NC). Resting-state functional MRI (rs-fMRI) with a sliding-window approach and k-means clustering based on independent component analysis (ICA) was used to evaluate DFC. The temporal properties of fractional windows and the mean dwell time in each state, as well as the number of transitions between each pair of DFC states, were calculated. Additionally, we assessed the functional connectivity (FC) strength of the dynamic states and the associations of altered neuroimaging measures with cognitive performance. A dynamic analysis of all included subjects suggested four distinct functional connectivity states. Compared with the NC group, the CSVD group had more fractional windows and longer mean dwell times in state 4 characterized by sparse FC both inter-network and intra-networks. Additionally, the CSVD group had a reduced number of windows and shorter mean dwell times compared to the NC group in state 3 characterized by highly positive FC between the somatomotor and visual networks, and negative FC in the basal ganglia and somatomotor and visual networks. The number of transitions between state 2 and state 3 and between state 3 and state 4 was significantly reduced in the CSVD group compared to the NC group. Moreover, there was a significant difference in the FC strength between the two groups, and the altered temporal properties of DFC were significantly related to cognitive performance. Our study indicated that CSVD is characterized by altered temporal properties in DFC that may be sensitive neuroimaging biomarkers for early disease identification. Further study of DFC alterations could help us to better understand the progressive dysfunction of networks in CSVD patients.

Abnormal dynamic functional connectivity in young nondisabling intracerebral hemorrhage patients

OBJECTIVE

Previous resting-state functional magnetic resonance imaging studies on intracerebral hemorrhage patients have focused more on the static characteristics of brain activity, while the time-varying effects during scanning have received less attention. Therefore, the current study aimed to explore the dynamic functional network connectivity changes of intracerebral hemorrhage patients.

METHODS

Using independent component analysis, the sliding window approach, and the k-means clustering analysis method, different dynamic functional network connectivity states were detected from resting-state functional magnetic resonance imaging data of 37 intracerebral hemorrhage patients and 44 healthy controls. The inter-group differences in dynamic functional network connectivity patterns and temporal properties were investigated, followed by correlation analyses between clinical scales and abnormal functional indexes.

RESULTS

Ten resting-state networks were identified, and the dynamic functional network connectivity matrices were clustered into four different states. The transition numbers were decreased in the intracerebral hemorrhage patients compared with healthy controls, which was associated with trail making test scores in patients. The cerebellar network and executive control network connectivity in State 1 was reduced in patients, and this abnormal dynamic functional connectivity was positively correlated with the animal fluency test scores of patients.

INTERPRETATION

The current study demonstrated the characteristics of dynamic functional network connectivity in intracerebral hemorrhage patients and revealed that abnormal temporal properties and functional connectivity may be related to the performance of different cognitive domains after ictus. These results may provide new insights into exploring the neurocognitive mechanisms of intracerebral hemorrhage.

Dynamic Dysregulation of the Triple Network of the Brain in Mild Traumatic Brain Injury and Its Relationship With Cognitive Performance

A triple network model consisting of a default network, a salience network, and a central executive network has recently been used to understand connectivity patterns in cognitively normal versus dysfunctional brains. This study aimed to explore changes in the dynamic connectivity of triplet network in mild traumatic brain injury (mTBI) and its relationship to cognitive performance. In this work, we acquired resting-state functional magnetic resonance imaging (fMRI) data from 30 mTBI patients and 30 healthy controls (HCs). Independent component analysis, sliding time window correlation, and k-means clustering were applied to resting-state fMRI data. Further, we analyzed the relationship between changes in dynamic functional connectivity (FC) parameters and clinical variables in mTBI patients. The results showed that the dynamic functional connectivity of the brain triple network was clustered into five states. Compared with HC, mTBI patients spent longer in state 1, which is characterized by weakened dorsal default mode network (DMN) and anterior salience network (SN) connectivity, and state 3, which is characterized by a positive correlation between DMN and SN internal connectivity. Mild TBI patients had fewer metastases in different states than HC patients. In addition, the mean residence time in state 1 correlated with Montreal Cognitive Assessment scores in mTBI patients; the number of transitions between states correlated with Glasgow Coma Score in mTBI patients. Taken together, our findings suggest that the dynamic properties of FC in the triple network of mTBI patients are abnormal, and provide a new perspective on the pathophysiological mechanism of cognitive impairment from the perspective of dynamic FC.

The brain entropy dynamics in resting state

As a novel measure for irregularity and complexity of the spontaneous fluctuations of brain activities, brain entropy (BEN) has attracted much attention in resting-state functional magnetic resonance imaging (rs-fMRI) studies during the last decade. Previous studies have shown its associations with cognitive and mental functions. While most previous research assumes BEN is approximately stationary during scan sessions, the brain, even at its resting state, is a highly dynamic system. Such dynamics could be characterized by a series of reoccurring whole-brain patterns related to cognitive and mental processes. The present study aims to explore the time-varying feature of BEN and its potential links with general cognitive ability. We adopted a sliding window approach to derive the dynamical brain entropy (dBEN) of the whole-brain functional networks from the HCP (Human Connectome Project) rs-fMRI dataset that includes 812 young healthy adults. The dBEN was further clustered into 4 reoccurring BEN states by the k-means clustering method. The fraction window (FW) and mean dwell time (MDT) of one BEN state, characterized by the extremely low overall BEN, were found to be negatively correlated with general cognitive abilities (i.e., cognitive flexibility, inhibitory control, and processing speed). Another BEN state, characterized by intermediate overall BEN and low within-state BEN located in DMN, ECN, and part of SAN, its FW, and MDT were positively correlated with the above cognitive abilities. The results of our study advance our understanding of the underlying mechanism of BEN dynamics and provide a potential framework for future investigations in clinical populations.

Split-half reliability estimates of an online card sorting task in a community sample of young and elderly adults

Executive function is vital for normal social, cognitive, and motor functions. Executive function decline due to aging increases the risk of disability and falls in older adults, which has become an urgent public health issue. Fast and convenient neuropsychological tools are thus needed to identify high-risk groups as early as possible to conduct a timely intervention. Card sorting tasks, such as Wisconsin Card Sorting Task (WCST) and its variants, are popular tools for measuring executive function. This study investigated the reliability of an open-source, self-administered, online, short-version card sorting task with a sample of young (n = 107, 65 females, age: M = 30.1 years, SD = 5.5 years) and elderly Chinese (n = 113, 53 females, age: M = 64.0 years, SD = 6.7 years). We developed an automated scoring and visualization procedure following the recent recommendations on scoring perseverative responses to make the results comparable to the standardized WCST. Reliability estimates of commonly used measures were calculated using the split-half method. All task indices' reliabilities were reasonably good in both old and young groups except for "failure-to-maintain-set." Elderly Chinese adults showed compromised task performance on all measures compared with the young Chinese adults at the group level. The R script of automated scoring and estimation of reliability is publicly available.

Resting state network connectivity is associated with cognitive flexibility performance in youth in the Adolescent Brain Cognitive Development Study

Cognitive flexibility is an executive functioning skill that develops in childhood, and when impaired, has transdiagnostic implications for psychiatric disorders. To identify how intrinsic neural architecture at rest is linked to cognitive flexibility performance, we used the data-driven method of independent component analysis (ICA) to investigate resting state networks (RSNs) and their whole-brain connectivity associated with levels of cognitive flexibility performance in children. We hypothesized differences by cognitive flexibility performance in RSN connectivity strength in cortico-striatal circuitry, which would manifest via the executive control network, right and left frontoparietal networks (FPN), salience network, default mode network (DMN), and basal ganglia network. We selected participants from the Adolescent Brain Cognitive Development (ABCD) Study who scored at the 25th, ("CF-Low"), 50th ("CF-Average"), or 75th percentiles ("CF-High") on a cognitive flexibility task, were early to middle puberty, and did not exhibit significant psychopathology (n = 967, 47.9% female; ages 9-10). We conducted whole-brain ICA, identifying 14 well-characterized RSNs. Groups differed in connectivity strength in the right FPN, anterior DMN, and posterior DMN. Planned comparisons indicated CF-High had stronger connectivity between right FPN and supplementary motor/anterior cingulate than CF-Low. CF-High had more anti-correlated connectivity between anterior DMN and precuneus than CF-Average. CF-Low had stronger connectivity between posterior DMN and supplementary motor/anterior cingulate than CF-Average. Post-hoc correlations with reaction time by trial type demonstrated significant associations with connectivity. In sum, our results suggest childhood cognitive flexibility performance is associated with DMN and FPN connectivity strength at rest, and that there may be optimal levels of connectivity associated with task performance that vary by network.

Abnormal dynamic functional connectivity of hippocampal subregions associated with working memory impairment in melancholic depression

BACKGROUND

Previous studies have demonstrated structural and functional changes of the hippocampus in patients with major depressive disorder (MDD). However, no studies have analyzed the dynamic functional connectivity (dFC) of hippocampal subregions in melancholic MDD. We aimed to reveal the patterns for dFC variability in hippocampus subregions - including the bilateral rostral and caudal areas and its associations with cognitive impairment in melancholic MDD.

METHODS

Forty-two treatment-naive MDD patients with melancholic features and 55 demographically matched healthy controls were included. The sliding-window analysis was used to evaluate whole-brain dFC for each hippocampal subregions seed. We assessed between-group differences in the dFC variability values of each hippocampal subregion in the whole brain and cognitive performance on the MATRICS Consensus Cognitive Battery (MCCB). Finally, association analysis was conducted to investigate their relationships.

RESULTS

Patients with melancholic MDD showed decreased dFC variability between the left rostral hippocampus and left anterior lobe of cerebellum compared with healthy controls (voxel p < 0.005, cluster p < 0.0125, GRF corrected), and poorer cognitive scores in working memory, verbal learning, visual learning, and social cognition (all p < 0.05). Association analysis showed that working memory was positively correlated with the dFC variability values of the left rostral hippocampus-left anterior lobe of the cerebellum (r = 0.338, p = 0.029) in melancholic MDD.

CONCLUSIONS

These findings confirmed the distinct dynamic functional pathway of hippocampal subregions in patients with melancholic MDD, and suggested that the dysfunction of hippocampus-cerebellum connectivity may be underlying the neural substrate of working memory impairment in melancholic MDD.

Vigilance associates with the low-dimensional structure of fMRI data

The human brain exhibits rich dynamics that reflect ongoing functional states. Patterns in fMRI data, detected in a data-driven manner, have uncovered recurring configurations that relate to individual and group differences in behavioral, cognitive, and clinical traits. However, resolving the neural and physiological processes that underlie such measurements is challenging, particularly without external measurements of brain state. A growing body of work points to underlying changes in vigilance as one driver of time-windowed fMRI connectivity states, calculated on the order of tens of seconds. Here we examine the degree to which the low-dimensional spatial structure of instantaneous fMRI activity is associated with vigilance levels, by testing whether vigilance-state detection can be carried out in an unsupervised manner based on individual BOLD time frames. To investigate this question, we first reduce the spatial dimensionality of fMRI data, and apply Gaussian Mixture Modeling to cluster the resulting low-dimensional data without any a priori vigilance information. Our analysis includes long-duration task and resting-state scans that are conducive to shifts in vigilance. We observe a close alignment between low-dimensional fMRI states (data-driven clusters) and measurements of vigilance derived from concurrent electroencephalography (EEG) and behavior. Whole-brain coactivation analysis revealed cortical anti-correlation patterns that resided primarily during higher behavioral- and EEG-defined levels of vigilance, while cortical activity was more often spatially uniform in states corresponding to lower vigilance. Overall, these findings indicate that vigilance states may be detected in the low-dimensional structure of fMRI data, even within individual time frames.

A method for reconstruction of interpretable brain networks from transient synchronization in resting-state BOLD fluctuations

Resting-state (rs) fMRI has been widely used to examine brain-wide large-scale spatiotemporal architectures, known as resting-state networks (RSNs). Recent studies have focused on the temporally evolving characteristics of RSNs, but it is unclear what temporal characteristics are reflected in the networks. To address this issue, we devised a novel method for voxel-based visualization of spatiotemporal characteristics of rs-fMRI with a time scale of tens of seconds. We first extracted clusters of dominant activity-patterns using a region-of-interest approach and then used these temporal patterns of the clusters to obtain voxel-based activation patterns related to the clusters. We found that activation patterns related to the clusters temporally evolved with a characteristic temporal structure and showed mutual temporal alternations over minutes. The voxel-based representation allowed the decoding of activation patterns of the clusters in rs-fMRI using a meta-analysis of functional activations. The activation patterns of the clusters were correlated with behavioral measures. Taken together, our analysis highlights a novel approach to examine brain activity dynamics during rest.

Effects of neuromodulation on cognitive and emotional responses to psychosocial stressors in healthy humans

Physiological and psychological stressors can exert wide-ranging effects on the human brain and behavior. Research has improved understanding of how the sympatho-adreno-medullary (SAM) and hypothalamic-pituitary-adrenocortical (HPA) axes respond to stressors and the differential responses that occur depending on stressor type. Although the physiological function of SAM and HPA responses is to promote survival and safety, exaggerated psychobiological reactivity can occur in psychiatric disorders. Exaggerated reactivity may occur more for certain types of stressors, specifically, psychosocial stressors. Understanding stressor effects and how the body regulates these responses can provide insight into ways that psychobiological reactivity can be modulated. Non-invasive neuromodulation is one way that responding to stressors may be altered; research into these interventions may provide further insights into the brain circuits that modulate stress reactivity. This review focuses on the effects of acute psychosocial stressors and how neuromodulation might be effective in altering stress reactivity. Although considerable research into stress interventions focuses on treating pathology, it is imperative to first understand these mechanisms in non-clinical populations; therefore, this review will emphasize populations with no known pathology and consider how these results may translate to those with psychiatric pathologies.

Time varying dynamics of hallucinations in clinical and non-clinical voice-hearers

Auditory verbal hallucinations (AVH) are frequently associated with psychotic disorders, yet also occur in non-clinical voice-hearers. AVH in this group are similar to those within clinical voice-hearers in terms of several phenomenological aspects, but non-clinical voice-hearers report to have more control over their AVH and attribute less emotional valence to them. These dissimilarities may stem from differences on the neurobiological level, as it is still under debate whether the mechanisms involved in AVH are the same in clinical and non-clinical voice-hearers. In this study, 21 clinical and 21 non-clinical voice-hearers indicated the onset and offsets of AVH during an fMRI scan. Using a method called leading eigenvector dynamics analysis (LEiDA), we examined time-varying dynamics of functional connectivity involved in AVH with a sub-second temporal resolution. We assessed differences between groups, and between hallucination and rest periods in dwell time, switching frequency, probability of occurrence, and transition probabilities of nine recurrent states of functional connectivity with a permutation ANOVA. Deviations in dwell times, switching frequencies, and switch probabilities in the hallucination period indicated more erratic dynamics during this condition regardless of their clinical status. Post-hoc analyses of the dwell times exhibited the most distinct differences between the rest and hallucination condition for the non-clinical sample, suggesting stronger differences between the two conditions in this group. Overall, these findings suggest that the neurobiological mechanisms involved in AVH are similar in clinical and non-clinical individuals.

Inter-individual differences in baseline dynamic functional connectivity are linked to cognitive aftereffects of tDCS

Transcranial direct current stimulation (tDCS) has the potential to modulate cognitive training in healthy aging; however, results from various studies have been inconsistent. We hypothesized that inter-individual differences in baseline brain state may contribute to the varied results. We aimed to explore whether baseline resting-state dynamic functional connectivity (rs-dFC) and/or conventional resting-state static functional connectivity (rs-sFC) may be related to the magnitude of cognitive aftereffects of tDCS. To achieve this aim, we used data from our double-blind randomized sham-controlled cross-over tDCS trial in 25 healthy seniors in which bifrontal tDCS combined with cognitive training had induced significant behavioral aftereffects. We performed a backward regression analysis including rs-sFC/rs-dFC measures to explain the variability in the magnitude of tDCS-induced improvements in visual object-matching task (VOMT) accuracy. Rs-dFC analysis revealed four rs-dFC states. The occurrence rate of a rs-dFC state 4, characterized by a high correlation between the left fronto-parietal control network and the language network, was significantly associated with tDCS-induced VOMT accuracy changes. The rs-sFC measure was not significantly associated with the cognitive outcome. We show that flexibility of the brain state representing readiness for top-down control of object identification implicated in the studied task is linked to the tDCS-enhanced task accuracy.

Altered neural flexibility in children with attention-deficit/hyperactivity disorder

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders of childhood, and is often characterized by altered executive functioning. Executive function has been found to be supported by flexibility in dynamic brain reconfiguration. Thus, we applied multilayer community detection to resting-state fMRI data in 180 children with ADHD and 180 typically developing children (TDC) to identify alterations in dynamic brain reconfiguration in children with ADHD. We specifically evaluated MR derived neural flexibility, which is thought to underlie cognitive flexibility, or the ability to selectively switch between mental processes. Significantly decreased neural flexibility was observed in the ADHD group at both the whole brain (raw p = 0.0005) and sub-network levels (p < 0.05, FDR corrected), particularly for the default mode network, attention-related networks, executive function-related networks, and primary networks. Furthermore, the subjects with ADHD who received medication exhibited significantly increased neural flexibility (p = 0.025, FDR corrected) when compared to subjects with ADHD who were medication naïve, and their neural flexibility was not statistically different from the TDC group (p = 0.74, FDR corrected). Finally, regional neural flexibility was capable of differentiating ADHD from TDC (Accuracy: 77% for tenfold cross-validation, 74.46% for independent test) and of predicting ADHD severity using clinical measures of symptom severity (R2: 0.2794 for tenfold cross-validation, 0.156 for independent test). In conclusion, the present study found that neural flexibility is altered in children with ADHD and demonstrated the potential clinical utility of neural flexibility to identify children with ADHD, as well as to monitor treatment responses and disease severity.

Understanding cognitive control in aging: A brain network perspective

Cognitive control decline is a major manifestation of brain aging that severely impairs the goal-directed abilities of older adults. Magnetic resonance imaging evidence suggests that cognitive control during aging is associated with altered activation in a range of brain regions, including the frontal, parietal, and occipital lobes. However, focusing on specific regions, while ignoring the structural and functional connectivity between regions, may impede an integrated understanding of cognitive control decline in older adults. Here, we discuss the role of aging-related changes in functional segregation, integration, and antagonism among large-scale networks. We highlight that disrupted spontaneous network organization, impaired information co-processing, and enhanced endogenous interference promote cognitive control declines during aging. Additionally, in older adults, severe damage to structural network can weaken functional connectivity and subsequently trigger cognitive control decline, whereas a relatively intact structural network ensures the compensation of functional connectivity to mitigate cognitive control impairment. Thus, we propose that age-related changes in functional networks may be influenced by structural networks in cognitive control in aging (CCA). This review provided an integrative framework to understand the cognitive control decline in aging by viewing the brain as a multimodal networked system.

Altered stability of brain functional architecture after sleep deprivation: A resting-state functional magnetic resonance imaging study

Background and aims

Resting-state functional magnetic resonance imaging (fMRI) studies using static and dynamic functional connectivity (FC) approaches have revealed brain dysfunction resulting from sleep deprivation (SD). The effects of SD on the stability of brain functional architecture remain unclear. This study investigated the functional stability (FS) changes induced by SD and its association with neurocognitive alterations.

Materials and methods

In this study, we recruited 24 healthy women. All participants underwent two sessions of resting-state fMRI scanning and neurocognitive assessment. The assessments included the Digit Symbol Test, Digit Span Test, Trail-Making Test (TMT), and Complex Figure Test (CFT). Participants completed one session under rested wakefulness (RW) and one session after SD for 24 h. To estimate dynamic FC, we used the sliding window approach; and then, to characterize the FS of each voxel, we measured dynamic FC concordance over time. We used a paired t-test to identify differences in FS between RW and SD. To examine the relationship between these changes in FS and alterations in neurocognitive performance, we conducted Spearman’s correlation analyses.

Results

SD affected the performance of the Digit Symbol Test, Digit Span Test, and CFT. Compared with RW, subjects with SD exhibited decreased FS in the bilateral anterior and posterior cingulate gyrus and medial frontal gyrus, right superior frontal gyrus, and cerebellum posterior lobe, while they exhibited increased FS in the bilateral precentral/postcentral gyrus and supplementary motor area, right parahippocampal gyrus and fusiform gyrus, left inferior occipital gyrus, and bilateral cerebellum anterior lobe. After SD, FS changes in the right parahippocampal gyrus and fusiform gyrus were correlated with altered performance in the Digit Symbol Test and CFT.

Conclusion

Our findings showed that the stability of the brain’s functional architecture could be altered by SD. This stability alteration may correspond to multiple neurocognitive domain changes.

Dynamic trajectories of connectome state transitions are heritable

The brain’s functional connectome is dynamic, constantly reconfiguring in an individual-specific manner. However, which characteristics of such reconfigurations are subject to genetic effects, and to what extent, is largely unknown. Here, we identified heritable dynamic features, quantified their heritability, and determined their association with cognitive phenotypes. In resting-state fMRI, we obtained multivariate features, each describing a temporal or spatial characteristic of connectome dynamics jointly over a set of connectome states. We found strong evidence for heritability of temporal features, particularly, Fractional Occupancy (FO) and Transition Probability (TP), representing the duration spent in each connectivity configuration and the frequency of shifting between configurations, respectively. These effects were robust against methodological choices of number of states and global signal regression. Genetic effects explained a substantial proportion of phenotypic variance of these features (h² = 0.39, 95% CI = [.24,.54] for FO; h² = 0. 43, 95% CI = [.29,.57] for TP). Moreover, these temporal phenotypes were associated with cognitive performance. Contrarily, we found no robust evidence for heritability of spatial features of the dynamic states (i.e., states’ Modularity and connectivity pattern). Genetic effects may therefore primarily contribute to how the connectome transitions across states, rather than the precise spatial instantiation of the states in individuals. In sum, genetic effects impact the dynamic trajectory of state transitions (captured by FO and TP), and such temporal features may act as endophenotypes for cognitive abilities.

Altered Temporal Variations of Functional Connectivity Associated With Surgical Outcomes in Drug-Resistant Temporal Lobe Epilepsy

Background

Currently, more than one-third of patients with drug-resistant temporal lobe epilepsy (TLE) continue to develop seizures after resection surgery. Dynamic functional network connectivity (DFNC) analyses, capturing temporal properties of functional connectivity during MRI acquisition, may help us identify unfavorable surgical outcomes. The purpose of this work was to explore the association of DFNC variations of preoperative resting-state MRI and surgical outcomes in patients with drug-resistant TLE.

Methods

We evaluated 61 patients with TLE matched for age and gender with 51 healthy controls (HC). Patients with TLE were classified as seizure-free (n = 39) and not seizure-free (n = 16) based on the Engel surgical outcome scale. Six patients were unable to confirm the postoperative status and were not included in the subgroup analysis. The DFNC was calculated using group spatial independent component analysis and the sliding window approach.

Results

Dynamic functional network connectivity analyses suggested two distinct connectivity “States.” The dynamic connectivity state of patients with TLE was different from HC. TLE subgroup analyses showed not seizure-free (NSF) patients spent significantly more time in State II compared to seizure-free (SF) patients and HC. Further, the number of transitions from State II to State I was significantly lower in NSF patients. SF patients had compensatory enhancement of DFNC strengths between default and dorsal attention network, as well as within the default network. While reduced DFNC strengths of within-network and inter-network were both observed in NSF patients, patients with abnormally temporal properties and more extension DFNC strength alterations were less likely to receive seizure freedom.

Conclusions

Our study indicates that DFNC could offer a better understanding of dynamic neural impairment mechanisms of drug-resistant TLE functional network, epileptic brain network reorganization, and provide an additional preoperative evaluation support for surgical treatment of drug-resistant TLE.

Altered brain structural and functional connectivity in schizotypy

BACKGROUND

Schizotypy refers to schizophrenia-like traits below the clinical threshold in the general population. The pathological development of schizophrenia has been postulated to evolve from the initial coexistence of 'brain disconnection' and 'brain connectivity compensation' to 'brain connectivity decompensation'.

METHODS

In this study, we examined the brain connectivity changes associated with schizotypy by combining brain white matter structural connectivity, static and dynamic functional connectivity analysis of diffusion tensor imaging data and resting-state functional magnetic resonance imaging data. A total of 87 participants with a high level of schizotypal traits and 122 control participants completed the experiment. Group differences in whole-brain white matter structural connectivity probability, static mean functional connectivity strength, dynamic functional connectivity variability and stability among 264 brain sub-regions of interests were investigated.

RESULTS

We found that individuals with high schizotypy exhibited increased structural connectivity probability within the task control network and within the default mode network; increased variability and decreased stability of functional connectivity within the default mode network and between the auditory network and the subcortical network; and decreased static mean functional connectivity strength mainly associated with the sensorimotor network, the default mode network and the task control network.

CONCLUSIONS

These findings highlight the specific changes in brain connectivity associated with schizotypy and indicate that both decompensatory and compensatory changes in structural connectivity within the default mode network and the task control network in the context of whole-brain functional disconnection may be an important neurobiological correlate in individuals with high schizotypy.

Dynamic Alterations in Functional Connectivity Density in Amyotrophic Lateral Sclerosis: A Resting-State Functional Magnetic Resonance Imaging Study

Background and Aims

Current knowledge on the temporal dynamics of the brain functional organization in amyotrophic lateral sclerosis (ALS) is limited. This is the first study on alterations in the patterns of dynamic functional connection density (dFCD) involving ALS.

Methods

We obtained resting-state functional magnetic resonance imaging (fMRI) data from 50 individuals diagnosed with ALS and 55 healthy controls (HCs). We calculated the functional connectivity (FC) between a given voxel and all other voxels within the entire brain and yield the functional connection density (FCD) value per voxel. dFCD was assessed by sliding window correlation method. In addition, the standard deviation (SD) of dFCD across the windows was computed voxel-wisely to measure dFCD variability. The difference in dFCD variability between the two groups was compared using a two-sample t-test following a voxel-wise manner. The receiver operating characteristic (ROC) curve was used to assess the between-group recognition performance of the dFCD variability index.

Results

The dFCD variability was significantly reduced in the bilateral precentral and postcentral gyrus compared with the HC group, whereas a marked increase was observed in the left middle frontal gyrus of ALS patients. dFCD variability exhibited moderate potential (areas under ROC curve = 0.753–0.837, all P < 0.001) in distinguishing two groups.

Conclusion

ALS patients exhibit aberrant dynamic property in brain functional architecture. The dFCD evaluation improves our understanding of the pathological mechanisms underlying ALS and may assist in its diagnosis.

Increased Excursions to Functional Networks in Schizophrenia in the Absence of Task

Schizophrenia is a chronic psychotic disorder characterized by the disruption of thought processes, perception, cognition, and behaviors, for which there is still a lack of objective and quantitative biomarkers in brain activity. Using functional magnetic resonance imaging (fMRI) data from an open-source database, this study investigated differences between the dynamic exploration of resting-state networks in 71 schizophrenia patients and 74 healthy controls. Focusing on recurrent states of phase coherence in fMRI signals, brain activity was examined for intergroup differences through the lens of dynamical systems theory. Results showed reduced fractional occupancy and dwell time of a globally synchronized state in schizophrenia. Conversely, patients exhibited increased fractional occupancy, dwell time and limiting probability of being in states during which canonical functional networks—i.e., Limbic, Dorsal Attention and Somatomotor—synchronized in anti-phase with respect to the rest of the brain. In terms of state-to-state transitions, patients exhibited increased probability of switching to Limbic, Somatomotor and Visual networks, and reduced probability of remaining in states related to the Default Mode network, the Orbitofrontal network and the globally synchronized state. All results revealed medium to large effect sizes. Combined, these findings expose pronounced differences in the temporal expression of resting-state networks in schizophrenia patients, which may relate to the pathophysiology of this disorder. Overall, these results reinforce the utility of dynamical systems theory to extend current knowledge regarding disrupted brain dynamics in psychiatric disorders.

Abnormal regional spontaneous brain activities in white matter in patients with autism spectrum disorder

Previous studies have demonstrated patients with autism spectrum disorder (ASD) are accompanied by alterations of spontaneous brain activity in gray matter. However, whether the alterations of spontaneous brain activity exist in white matter remains largely unclear. In this study, 88 ASD patients and 87 typical controls (TCs) were included and regional homogeneity (ReHo) was calculated to characterize spontaneous brain activity in white matter. Voxel-wise two-sample t-tests were performed to investigate ReHo alterations, and cluster-level analyses were conducted to examine structural-functional coupling changes. Compared with TCs, the ASD group showed significantly decreased ReHo in the left superior corona radiata and left posterior limb of internal capsule, and decreased ReHo in the left anterior corona radiata with a trend level of significance. In addition, significantly weaker structural-functional coupling was observed in the left superior corona radiata and left posterior limb of internal capsule in ASD patients. Taken together, these findings highlighted abnormalities of white matter's regional spontaneous brain activity in ASD, which may provide new insights into the pathophysiological mechanisms of this disorder.

Sleep Quality Modulates the Association between Dynamic Functional Network Connectivity and Cognitive Function in Healthy Older Adults

Aging is associated with changes in sleep, brain activity, and cognitive function, as well as the association among these factors; however, the precise nature of these changes has not been elucidated. This study systematically investigated the modulatory effect of sleep on the relationship between brain functional network connectivity (FNC) and cognitive function in older adults. In total, 107 community-dwelling healthy older adults were recruited and assigned into poor sleep and good sleep groups based on the Pittsburgh Sleep Quality Index. The static functional network connectivity (sFNC), the temporal variability of dynamic FNC (dFNC) from variance (dFNC-var), and the dFNC from clustering state (dFNC-state) were calculated. Corresponding cognition-predictive models were constructed for each sleep group. dFNC but not sFNC, was able to significantly predict the cognitive function in older adults. Specifically, sleep played a modulatory role in the association between dFNC and cognitive function, with sleep-specific variations at both microscopic (i.e., specific edges) and macroscopic levels (i.e., specific states) of dFNC.

Altered Dynamic Functional Connectivity in Subcortical Ischemic Vascular Disease With Cognitive Impairment

Subcortical ischemic vascular disease (SIVD) can cause cognitive impairment and affect the static functional connectivity of resting functional magnetic resonance imaging (fMRI). Numerous previous studies have demonstrated that functional connectivities (FCs) fluctuate dynamically over time. However, little is known about the impact of cognitive impairment on brain dynamic functional connectivity (DFC) in SIVD patients with MCI. In the present study, the DFC analysis method was applied to the resting functional magnetic resonance imaging (fMRI) data of 37 SIVD controls (SIVD-Control) without cognitive impairment, 34 SIVD patients with amnestic MCI (SIVD-aMCI) and 30 SIVD patients with nonamnestic MCI (SIVD-naMCI). The results indicated that the cognitive impairment of SIVD mainly reduced the mean dwell time of State 3 with overall strong positive connections. The reduction degree of SIVD-aMCI was larger than that of SIVD-naMCI. The memory/execution function impairment of SIVD also changed the relationship between the mean dwell time of State 3 and the behavioral performance of the memory/execution task from significant to non-significant correlation. Moreover, SIVD-aMCI showed significantly lower system segregation of FC states than SIVD-Control and SIVD-naMCI. The system segregation of State 5 with overall weak connections was significantly positive correlated with the memory performance. The results may suggest that the mean dwell time of State 3 and the system segregation of State 5 may be used as important neural measures of cognitive impairments of SIVD.

Validating dynamicity in resting state fMRI with activation-informed temporal segmentation

Confirming the presence (or absence) of dynamic functional connectivity (dFC) states during rest is an important open question in the field of cognitive neuroscience. The prevailing dFC framework aims to identify dynamics directly from connectivity estimates with a sliding window approach, however this method suffers from several drawbacks including sensitivity to window size and poor test-retest reliability. We hypothesize that time-varying changes in functional connectivity are mirrored by significant temporal changes in functional activation, and that this coupling can be leveraged to study dFC without the need for a predefined sliding window. Here, we introduce a data-driven dFC framework, which involves informed segmentation of fMRI time series at candidate FC state transition points estimated from changes in whole-brain functional activation, rather than a fixed-length sliding window. We show our approach reliably identifies true cognitive state change points when applied on block-design working memory task data and outperforms the standard sliding window approach in both accuracy and computational efficiency in this context. When applied to data from four resting state fMRI scanning sessions, our method consistently recovers five reliable FC states, and subject-specific features derived from these states show significant correlation with behavioral phenotypes of interest (cognitive ability, personality). Overall, these results suggest abrupt whole-brain changes in activation can be used as a marker for changes in connectivity states and provides new evidence for the existence of time-varying FC in rest.

Pathologically reduced neural flexibility recovers during psychotherapy of OCD patients

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Psychiatric impairment is associated with decreased neural flexibility.

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Psychotherapy was able to increase the neural flexibility of the patients.

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Psychotherapy should increase adaptivity of cognitive-emotional-behavioral patterns.

Flexibility is a key feature of psychological health, allowing the individual to dynamically adapt to changing environmental demands, which is impaired in many psychiatric disorders like obsessive–compulsive disorder (OCD). Adequately responding to varying demands requires the brain to switch between different patterns of neural activity, which are represented by different brain network configurations (functional connectivity patterns). Here, we operationalize neural flexibility as the dissimilarity between consecutive connectivity matrices of brain regions (jump length). In total, 132 fMRI scans were obtained from 17 patients that were scanned four to five times during inpatient psychotherapy, and from 17 controls that were scanned at comparable time intervals. Significant negative correlations were found between the jump lengths and the symptom severity scores of OCD, depression, anxiety, and stress, suggesting that high symptom severity corresponds to inflexible brain functioning. Further analyses revealed that impaired reconfiguration (pattern stability) of the brain seems to be more related to general psychiatric impairment rather than to specific symptoms, e.g., of OCD or depression. Importantly, the group × time interaction of a repeated measures ANOVA was significant, as well as the post-hoc paired t-tests of the patients (first vs. last scan). The results suggest that psychotherapy is able to significantly increase the neural flexibility of patients. We conclude that psychiatric symptoms like anxiety, stress, depression, and OCD are associated with an impaired adaptivity of the brain. In general, our results add to the growing evidence that dynamic functional connectivity captures meaningful properties of brain functioning.

Brain Dynamics Underlying Cognitive Flexibility Across the Lifespan

The neural mechanisms contributing to flexible cognition and behavior and how they change with development and aging are incompletely understood. The current study explored intrinsic brain dynamics across the lifespan using resting-state fMRI data (n = 601, 6-85 years) and examined the interactions between age and brain dynamics among three neurocognitive networks (midcingulo-insular network, M-CIN; medial frontoparietal network, M-FPN; and lateral frontoparietal network, L-FPN) in relation to behavioral measures of cognitive flexibility. Hierarchical multiple regression analysis revealed brain dynamics among a brain state characterized by co-activation of the L-FPN and M-FPN, and brain state transitions, moderated the relationship between quadratic effects of age and cognitive flexibility as measured by scores on the Delis-Kaplan Executive Function System (D-KEFS) test. Furthermore, simple slope analyses of significant interactions revealed children and older adults were more likely to exhibit brain dynamic patterns associated with poorer cognitive flexibility compared with younger adults. Our findings link changes in cognitive flexibility observed with age with the underlying brain dynamics supporting these changes. Preventative and intervention measures should prioritize targeting these networks with cognitive flexibility training to promote optimal outcomes across the lifespan.

Functional Connectivity Within the Fronto-Parietal Network Predicts Complex Task Performance: A fNIRS Study

Performance in complex tasks is essential for many high risk operators. The achievement of such tasks is supported by high-level cognitive functions arguably involving functional activity and connectivity in a large ensemble of brain areas that form the fronto-parietal network. Here we aimed at determining whether the functional connectivity at rest within this network could predict performance in a complex task: the Space Fortress video game. Functional Near Infrared Spectroscopy (fNIRS) data from 32 participants were recorded during a Resting-State period, the completion of a simple version of Space Fortress (monotask) and the original version (multitask). The intrinsic functional connectivity within the fronto-parietal network (i.e., during the Resting-State) was a significant predictor of performance at Space Fortress multitask but not at its monotask version. The same pattern was observed for the functional connectivity during the task. Our overall results suggest that Resting-State functional connectivity within the fronto-parietal network could be used as an intrinsic brain marker for performance prediction of a complex task achievement, but not for simple task performance.

Dynamic functional connectivity profile of the salience network across the life span

The insular cortex and anterior cingulate cortex together comprise the salience or midcingulo-insular network, involved in detecting salient events and initiating control signals to mediate brain network dynamics. The extent to which functional coupling between the salience network and the rest of the brain undergoes changes due to development and aging is at present largely unexplored. Here, we examine dynamic functional connectivity (dFC) of the salience network in a large life span sample (n = 601; 6-85 years old). A sliding-window analysis and k-means clustering revealed five states of dFC formed with the salience network, characterized by either widespread asynchrony or different patterns of synchrony between the salience network and other brain regions. We determined the frequency, dwell time, total transitions, and specific state-to-state transitions for each state and subject, regressing the metrics with subjects' age to identify life span trends. A dynamic state characterized by low connectivity between the salience network and the rest of the brain had a strong positive quadratic relationship between age and both frequency and dwell time. Additional frequency, dwell time, total transitions, and state-to-state transition trends were observed with other salience network states. Our results highlight the metastable dynamics of the salience network and its role in the maturation of brain regions critical for cognition.

Sex-related differences in brain dynamism at rest as neural correlates of positive and negative valence system constructs

Clinical anxiety and depression are the most prevalent mental illnesses, likely representing maladaptive expressions of negative valence systems concerned with conditioned responses to fear, threat, loss, and frustrative nonreward. These conditions exhibit similar, striking sex/gender-related differences in onset, incidence, and severity for which the neural correlates are not yet established. In alarge sample of neurotypical young adults, we demonstrate that intrinsic brain dynamism metrics derived from sex-sensitive models of whole-brain network function are significantly associated with valence system traits. Surprisingly, we found that greater brain dynamism is strongly positively correlated to anxiety and depression traits in males, but almost wholly decoupled from traits for important cognitive control and reappraisal strategies associated with positive valence. Conversely, intrinsic brain dynamism is strongly positively coupled to drive, novelty-seeking and self-control in females with only rare or non-significant directional negative correlation with anxiety and depression traits. Our results suggest that the dynamic neural correlates of traits for valence, anxiety and depression are significantly different in males/men and females/women. These findings may relate to the known sex/gender-related differences in cognitive reappraisal of emotional experiences and clinical presentations of anxiety and depression, with potential relevance to gold standard therapies based on enhancing cognitive control strategies.

Brain state-dependent dynamic functional connectivity patterns in attention-deficit/hyperactivity disorder

Attention-deficit/hyperactivity disorder (ADHD) patients have presented aberrant static brain networks, however identifying ADHD patients based on dynamic information in brain networks is not fully clear. Data were obtained from 32 boys with ADHD and 52 sex- and age-matched typically developing controls; a sliding-window method was used to assess dynamic functional connectivity (dFC), and two reoccurring dFC states (the hot and cool states) were then identified using a k-means clustering method. The results showed that ADHD patients had significant changes in occurrence, transitions times and dFC strength of the cingulo-opercular network (CON) and sensorimotor network (SMN) in the cool state. The severity of ADHD symptoms showed significant correlations with the regional amplitude of dFC fluctuations in the ventral medial prefrontal cortex (vmPFC), anterior medial prefrontal cortex (amPFC) and precuneus. These findings could provide insights on the state-dependent dynamic changes in large-scale brain connectivity and network configurations in ADHD.

Atypical core-periphery brain dynamics in autism

The intrinsic function of the human brain is dynamic, giving rise to numerous behavioral subtypes that fluctuate distinctively at multiple timescales. One of the key dynamical processes that takes place in the brain is the interaction between core-periphery brain regions, which undergoes constant fluctuations associated with developmental time frames. Core-periphery dynamical changes associated with macroscale brain network dynamics span multiple timescales and may lead to atypical behavior and clinical symptoms. For example, recent evidence suggests that brain regions with shorter intrinsic timescales are located at the periphery of brain networks (e.g., sensorimotor hand, face areas) and are implicated in perception and movement. On the contrary, brain regions with longer timescales are core hub regions. These hubs are important for regulating interactions between the brain and the body during self-related cognition and emotion. In this review, we summarize a large body of converging evidence derived from time-resolved fMRI studies in autism to characterize atypical core-periphery brain dynamics and how they relate to core and contextual sensory and cognitive profiles.

Cognitive and behavioral profiles of pediatric surgical candidates with frontal and temporal lobe epilepsy

BACKGROUND

We aimed to prospectively analyze memory and executive and social cognitive functioning in patients with drug-resistant frontal lobe epilepsy (FLE) and temporal lobe epilepsy (TLE) with focal lesions and isolate the impact of intellectual ability on specific deficits.

METHODS

A neuropsychological evaluation was performed in 23 children with FLE, 22 children with TLE, and 36 healthy pediatric controls (HCs). Patients in the epilepsy groups had a range of lesions, including low-grade epilepsy-associated tumors (LEAT), focal cortical dysplasia (FCD) type II, and mesial temporal sclerosis (MS).

RESULTS

There were no significant differences between children with FLE and TLE regarding memory, executive, or social cognitive functioning. General Ability Index (GAI) was a predictor of memory, executive function, and social cognition scores and was influenced by age at onset, duration of epilepsy, and number of antiepileptic drugs (AEDs) prescribed at the time of assessment. Working Memory Index scores of patients with TLE, which measure verbal mnesic processing, were significantly lower than those of HCs and patients with TLE. The greatest differences in both clinical groups compared to HCs were recorded in cognitive executive functions, and patients with FLE had lower scores in this domain. Regarding behavioral executive functions, patients with TLE presented impaired emotional control and impulse inhibition and patients with FLE exhibited decreased flexibility.

CONCLUSION

Consistent with previous research, our findings provide further detailed evidence of small differences in cognitive performance among children with FLE and TLE. These differences emerge on analysis of the factors with which deficits are associated.

Whole-Brain Functional Dynamics Track Depressive Symptom Severity

Depressive symptoms are reported by 20% of the population and are related to altered functional integrity of large-scale brain networks. The link between moment-to-moment brain function and depressive symptomatology, and the implications of these relationships for clinical and community populations alike, remain understudied. The present study examined relationships between functional brain dynamics and subclinical-to-mild depressive symptomatology in a large community sample of adults with and without psychiatric diagnoses. This study used data made available through the Enhanced Nathan Kline Institute-Rockland Sample; 445 participants between 18 and 65 years of age completed a 10-min resting-state functional MRI scan. Coactivation pattern analysis was used to examine the dimensional relationship between depressive symptoms and whole-brain states. Elevated levels of depressive symptoms were associated with increased frequency and dwell time of the default mode network, a brain network associated with self-referential thought, evaluative judgment, and social cognition. Furthermore, increased depressive symptom severity was associated with less frequent occurrences of a hybrid brain network implicated in cognitive control and goal-directed behavior, which may impair the inhibition of negative thinking patterns in depressed individuals. These findings demonstrate how temporally dynamic techniques offer novel insights into time-varying neural processes underlying subclinical and clinically meaningful depressive symptomatology.

Task-generic and task-specific connectivity modulations in the ADHD brain: an integrated analysis across multiple tasks

Attention-deficit/hyperactivity disorder (ADHD) is associated with altered functioning in multiple cognitive domains and neural networks. This paper offers an overarching biological perspective across these. We applied a novel strategy that extracts functional connectivity modulations in the brain across one (P_single), two (P_mix) or three (P_all) cognitive tasks and compared the pattern of modulations between participants with ADHD (n-89), unaffected siblings (n = 93) and controls (n = 84; total N = 266; age range = 8-27 years). Participants with ADHD had significantly fewer P_all connections (modulated regardless of task), but significantly more task-specific (P_single) connectivity modulations than the other groups. The amplitude of these P_single modulations was significantly higher in ADHD. Unaffected siblings showed a similar degree of P_all connectivity modulation as controls but a similar degree of P_single connectivity modulation as ADHD probands. P_all connections were strongly reproducible at the individual level in controls, but showed marked heterogeneity in both participants with ADHD and unaffected siblings. The pattern of reduced task-generic and increased task-specific connectivity modulations in ADHD may be interpreted as reflecting a less efficient functional brain architecture due to a reduction in the ability to generalise processing pathways across multiple cognitive domains. The higher amplitude of unique task-specific connectivity modulations in ADHD may index a more "effortful" coping strategy. Unaffected siblings displayed a task connectivity profile in between that of controls and ADHD probands, supporting an endophenotype view. Our approach provides a new perspective on the core neural underpinnings of ADHD.

Dynamic Changes in Functional Network Connectivity Involving Amyotrophic Lateral Sclerosis and Its Correlation With Disease Severity

BACKGROUND

Aberrant static functional connectivity (FC) has been well demonstrated in amyotrophic lateral sclerosis (ALS); however, ALS-related alterations in FC dynamic properties remain unclear, although dynamic FC analyses contribute to uncover mechanisms underlying neurodegenerative disorders.

PURPOSE

To explore dynamic functional network connectivity (dFNC) in ALS and its correlation with disease severity.

STUDY TYPE

Prospective.

SUBJECTS

Thirty-two ALS patients and 45 healthy controls.

FIELD STRENGTH/SEQUENCE

Multiband resting-state functional images using gradient echo echo-planar imaging and T1-weighted images were acquired at 3.0 T.

ASSESSMENT

Disease severity was evaluated with the revised ALS Functional Rating Scale (ALSFRS-R) and patients were stratified according to diagnostic category. Independent component analysis was conducted to identify the components of seven intrinsic brain networks (ie, visual/sensorimotor (SMN)/auditory/cognitive-control (CCN)/default-mode (DMN)/subcortical/cerebellar networks). A sliding-window correlation approach was used to compute dFNC. FNC states were determined by k-mean clustering, and state-specific FNC and dynamic indices (fraction time/mean dwell time/transition number) were calculated.

STATISTICAL TESTS

Two-sample t test used for comparisons on dynamic measures and Spearman's correlation analysis.

RESULTS

ALS patients showed increased FNC between DMN-SMN in state 1 and between CCN-SMN in state 4. Patients remained in state 2 (showing the weakest FNC) for a significantly longer time (mean dwell time: 49.8 ± 40.1 vs. 93.6 ± 126.3; P < 0.05) and remained in state 1 (showing a relatively strong FNC) for a shorter time (fraction time: 0.27 ± 0.25 vs. 0.13 ± 0.20; P < 0.05). ALS patients exhibited less temporal variability in their FNC (transition number: 10.2 ± 4.4 vs. 7.8 ± 3.8; P < 0.05). A significant correlation was observed between ALSFRS-R and mean dwell time in state 2 (r = -0.414, P < 0.05) and transition number (r = 0.452, P < 0.05). No significant between-subgroup difference in dFNC properties was found (all P > 0.05).

DATA CONCLUSION

Our findings suggest aberrant dFNC properties in ALS, which is associated with disease severity.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 3.

Brain Mechanisms Supporting Flexible Cognition and Behavior in Adolescents With Autism Spectrum Disorder

Cognitive flexibility enables appropriate responses to a changing environment and is associated with positive life outcomes. Adolescence, with its increased focus on transitioning to independent living, presents particular challenges for youths with autism spectrum disorder (ASD) who often struggle to behave in a flexible way when faced with challenges. This review focuses on brain mechanisms underlying the development of flexible cognition during adolescence and how these neural systems are affected in ASD. Neuroimaging studies of task switching and set-shifting provide evidence for atypical lateral frontoparietal and midcingulo-insular network activation during cognitive flexibility task performance in individuals with ASD. Recent work also examines how intrinsic brain network dynamics support flexible cognition. These dynamic functional connectivity studies provide evidence for alterations in the number of transitions between brain states, as well as hypervariability of functional connections in adolescents with ASD. Future directions for the field include addressing issues related to measurement of cognitive flexibility using a combination of metrics with ecological and construct validity. Heterogeneity of executive function ability in ASD must also be parsed to determine which individuals will benefit most from targeted training to improve flexibility. The influence of pubertal hormones on brain network development and cognitive maturation in adolescents with ASD is another area requiring further exploration. Finally, the intriguing possibility that bilingualism might be associated with preserved cognitive flexibility in ASD should be further examined. Addressing these open questions will be critical for future translational neuroscience investigations of cognitive and behavioral flexibility in adolescents with ASD.

Static and dynamic functional connectivity supports the configuration of brain networks associated with creative cognition

Creative cognition is recognized to involve the integration of multiple spontaneous cognitive processes and is manifested as complex networks within and between the distributed brain regions. We propose that the processing of creative cognition involves the static and dynamic re-configuration of brain networks associated with complex cognitive processes. We applied the sliding-window approach followed by a community detection algorithm and novel measures of network flexibility on the blood-oxygen level dependent (BOLD) signal of 8 major functional brain networks to reveal static and dynamic alterations in the network reconfiguration during creative cognition using functional magnetic resonance imaging (fMRI). Our results demonstrate the temporal connectivity of the dynamic large-scale creative networks between default mode network (DMN), salience network, and cerebellar network during creative cognition, and advance our understanding of the network neuroscience of creative cognition.

Cognitive and behavioural flexibility: neural mechanisms and clinical considerations

Cognitive and behavioural flexibility permit the appropriate adjustment of thoughts and behaviours in response to changing environmental demands. Brain mechanisms enabling flexibility have been examined using non-invasive neuroimaging and behavioural approaches in humans alongside pharmacological and lesion studies in animals. This work has identified large-scale functional brain networks encompassing lateral and orbital frontoparietal, midcingulo-insular and frontostriatal regions that support flexibility across the lifespan. Flexibility can be compromised in early-life neurodevelopmental disorders, clinical conditions that emerge during adolescence and late-life dementias. We critically evaluate evidence for the enhancement of flexibility through cognitive training, physical activity and bilingual experience.

Individualizing Representational Similarity Analysis

Representational similarity analysis (RSA) is a popular multivariate analysis technique in cognitive neuroscience that uses functional neuroimaging to investigate the informational content encoded in brain activity. As RSA is increasingly being used to investigate more clinically-geared questions, the focus of such translational studies turns toward the importance of individual differences and their optimization within the experimental design. In this perspective, we focus on two design aspects: applying individual vs. averaged behavioral dissimilarity matrices to multiple participants' neuroimaging data and ensuring the congruency between tasks when measuring behavioral and neural representational spaces. Incorporating these methods permits the detection of individual differences in representational spaces and yields a better-defined transfer of information from representational spaces onto multivoxel patterns. Such design adaptations are prerequisites for optimal translation of RSA to the field of precision psychiatry.

An imbalance between functional segregation and integration in patients with pontine stroke: A dynamic functional network connectivity study

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Pontine stroke patients show abnormal time-varying brain activity.

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Pontine stroke patients exist aberrant functional segregation and integration.

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The alterations of dFNC may lead to a poor functional recovery after stroke.

Background

Previous studies on brain functional connectivity have revealed the neural physiopathology in patients with pontine stroke (PS). However, those studies focused only on the static features of intrinsic fluctuations, rather than on the time-varying effects throughout the entire scan. In the present study, we sought to explore the underlying mechanism of PS using the dynamic functional network connectivity (dFNC) method.

Methods

Resting-state functional magnetic resonance imaging (fMRI) data were collected from 58 patients with PS and 52 healthy controls (HC). Independent component analysis (ICA), the sliding window method, and k-means clustering analysis were performed to extract different functional networks, to calculate dFNC matrices, and to estimate distinct dynamic connectivity states. Additionally, temporal features were compared between the two groups in each state to explore the brain’s preference for different dynamic connectivity states in PS, and global and local efficiency were compared among states to explore the differences of topologic organization across different dFNC states. The correlations between clinical scales and the temporal features that differed between the two groups also were calculated.

Results

The dFNC analyses suggested four recurring states; in two of these states, the PS group showed a different duration from that of the HC group. Patients with PS spent significantly more time in a sparsely connected state (State 1), which was characterized by relatively low levels of connectivity within and between all brain networks. In contrast, patients with PS spent significantly less time in a highly segregated state (State 2), which was characterized by high levels of positive connectivities within primary perceptional domains and within higher cognitive control domains, and by high levels of negative inter-functional connectivities (inter-FCs) among primary perceptional and higher cognitive control domains. Additionally, the dwell time in State 2 was positively correlated with HC group’s long-term memory scores in the Rey Auditory Verbal Learning Test (RAVLT-L), whereas there was no correlation between the State-2 dwell time and RAVLT-L scores in the PS group. Furthermore, the sparsely connected state and the highly segregated state mentioned above had the highest global efficiency and the highest local efficiency among the four states, respectively.

Conclusions

In summary, we observed a preference in the aberrant brain for dynamic connectivity states with different network topologic organization in patients with PS, indicating abnormal functional segregation and integration of the whole brain and confirming the imperfection of functional network connectivity in patients with PS. These findings provide new evidence for the dynamic neural mechanisms underlying clinical symptoms in patients with PS.

Atypical Functional Covariance Connectivity Between Gray and White Matter in Children With Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder with atypical gray matter (GM) and white matter (WM) functional developmental course. However, the functional co-developmental pattern between GM and WM in ASD is unclear. Here, we utilized a functional covariance connectivity method to explore the concordance pattern between GM and WM function in individuals with ASD. A multi-center resting-state fMRI dataset composed of 105 male children with ASD and 102 well-matched healthy controls (HCs) from six sites of the ABIDE dataset was utilized. GM and WM ALFF maps were calculated for each subject. Voxel by voxel functional covariance connectivity of the ALFF values across subjects was calculated between GM and WM for children with ASD and HCs. A Z-test combining FDR multi-comparison correction was then employed to determine whether the functional covariance is significantly different between the two groups. A "bundling" strategy was utilized to ensure that the GM/WM clusters showing atypical functional covariance were larger than 5 voxels. Finally, canonical correlation analysis was conducted to explore whether the atypical GM/WM functional covariance is related to ASD symptoms. Results showed atypical functional covariance connections between specific GM and WM regions, whereas the ALFF values of these regions indicated no significant difference between the two groups. Canonical correlation analysis revealed a significant relationship between the atypical functional covariance and stereotyped behaviors of ASD. The results indicated an altered functional co-developmental pattern between WM and GM in ASD. LAY SUMMARY: White matter (WM) and gray matter (GM) are two major human brain organs supporting brain function. WM and GM functions show a specific co-developmental pattern in typical developed individuals. This study showed that this GM/WM co-developmental pattern was altered in children with ASD, while this altered GM/WM co-developmental pattern was related to stereotyped behaviors. These findings may help understand the GM/WM functional development of ASD.

Neural correlates of future weight loss reveal a possible role for brain-gastric interactions

Lifestyle dietary interventions are an essential practice in treating obesity, hence neural factors that may assist in predicting individual treatment success are of great significance. Here, in a prospective, open-label, three arms study, we examined the correlation between brain resting-state functional connectivity measured at baseline and weight loss following 6 months of lifestyle intervention in 92 overweight participants. We report a robust subnetwork composed mainly of sensory and motor cortical regions, whose edges correlated with future weight loss. This effect was found regardless of intervention group. Importantly, this main finding was further corroborated using a stringent connectivity-based prediction model assessed with cross-validation thus attesting to its robustness. The engagement of senso-motor regions in this subnetwork is consistent with the over-sensitivity to food cues theory of weight regulation. Finally, we tested an additional hypothesis regarding the role of brain-gastric interaction in this subnetwork, considering recent findings of a cortical network synchronized with gastric activity. Accordingly, we found a significant spatial overlap with the subnetwork reported in the present study. Moreover, power in the gastric basal electric frequency within our reported subnetwork negatively correlated with future weight loss. This finding was specific to the weight loss related subnetwork and to the gastric basal frequency. These findings should be further corroborated by combining direct recordings of gastric activity in future studies. Taken together, these intriguing results may have important implications for our understanding of the etiology of obesity and the mechanism of response to dietary intervention.

Incentive-driven decision-making networks in de novo and drug-treated Parkinson's disease patients with impulsive-compulsive behaviors: A systematic review of neuroimaging studies

BACKGROUND

In Parkinson's disease (PD), impulsive-compulsive behaviors (ICBs) may develop as side-effect of dopaminergic medications. Abnormal incentive-driven decision-making, which is supported by the cognitive control and motivation interaction, may represent an ICBs signature. This systematic review explored whether structural and/or functional brain differences between PD patients with vs without ICBs encompass incentive-driven decision-making networks.

METHODS

Structural and functional neuroimaging studies comparing PD patients with and without ICBs, either de novo or medicated, were included.

RESULTS

Thirty articles were identified. No consistent evidence of structural alteration both in de novo and medicated PD patients were found. Differences in connectivity within the default mode, the salience and the central executive networks predate ICBs development and remain stable once ICBs are fully developed. Medicated PD patients with ICBs show increased metabolism and cerebral blood flow in orbitofrontal and cingulate cortices, ventral striatum, amygdala, insula, temporal and supramarginal gyri. Abnormal ventral striatum connectivity with anterior cingulate cortex and limbic structures was reported in PD patients with ICBs.

DISCUSSION

Functional brain signatures of ICBs in PD encompass areas involved in cognitive control and motivational encoding networks of the incentive-driven decision-making. Functional alterations predating ICBs may be related to abnormal synaptic plasticity in these networks.

Functional neural network configuration in late childhood varies by age and cognitive state

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fMRI data from 60 children aged 9–12 during resting and tasks involving decision making, visual perception, and working memory were examined.

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At rest, the child brain exhibited network organization similar to adults though the degree of similarity was age- and network-dependent.

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During tasks, brain network configurations showed task-induced and age-related changes in integration.

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Frontoparietal network showed flexible connectivity pattern across states while networks for sensory and motor processing remained stable.

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Findings demonstrate that network connectivity characteristics may serve as markers for neural and cognitive maturation.

Late childhood and early adolescence is characterized by substantial brain maturation which contributes to both adult-like and age-dependent resting-state network connectivity patterns. However, it remains unclear whether these functional network characteristics in children are subject to differential modulation by distinct cognitive demands as previously found in adults. We conducted network analyses on fMRI data from 60 children (aged 9–12) during resting and during three distinct tasks involving decision making, visual perception, and spatial working memory. Graph measures of network architecture, functional integration, and flexibility were calculated for each of the four states. During resting state, the children’s network architecture was similar to that in young adults (N = 60, aged 20–23) but the degree of similarity was age- and network-dependent. During the task states, the children's whole-brain network exhibited enhanced integration in response to increased cognitive demand. Additionally, the frontoparietal network showed flexibility in connectivity patterns across states while networks implicated in motor and visual processing remained relatively stable. Exploratory analyses suggest different relationships between behavioral performance and connectivity profiles for the working memory and perceptual tasks. Together, our findings demonstrate state- and age-dependent features in functional network connectivity during late childhood, potentially providing markers for brain and cognitive development.

Cognitive flexibility in critical CHD: a target for intervention

Most children born with even the most critical forms of CHD are now surviving well into adulthood. However, with increased survival has come increased recognition of the diverse neurobehavioural and psychosocial challenges these children experience. Among these challenges are deficits in executive function skills, including inhibitory control, working memory, and cognitive flexibility. Over the past several years, whereas inhibitory control and working memory deficits have garnered particular attention among clinicians and interventionists, relatively less attention has been paid to cognitive flexibility. This is unfortunate given both the high prevalence of cognitive flexibility deficits observed in children and adolescents with critical CHD, and also the far-reaching relevance of cognitive flexibility in helping individuals achieve optimal quality of life across the lifespan. This paper reviews the construct of cognitive flexibility, including its definition, development, measurement, and neuroanatomical basis, provides a summary of how cognitive flexibility is affected by CHD, and offers evidence-based recommendations to systematically support the development of cognitive flexibility within the context of CHD.