Dynamic Functional Connectivity Reveals Abnormal Variability and Hyper‐connected Pattern in Autism Spectrum Disorder

Dynamic Functional Connectivity Reveals Abnormal Variability in the Amygdala Subregions of Children With Attention-Deficit/Hyperactivity Disorder

Objective: This study investigates whether the dynamic functional connectivity (dFC) of the amygdala subregions is altered in children with attention-deficit/hyperactivity disorder (ADHD).

Methods: The dFC of the amygdala subregions was systematically calculated using a sliding time window method, for 75 children with ADHD and 20 healthy control (HC) children.

Results: Compared with the HC group, the right superficial amygdala exhibited significantly higher dFC with the right prefrontal cortex, the left precuneus, and the left post-central gyrus for children in the ADHD group. The dFC of the amygdala subregions showed a negative association with the cognitive functions of children in the ADHD group.

Conclusion: Functional connectivity of the amygdala subregions is more unstable among children with ADHD. In demonstrating an association between the stability of functional connectivity of the amygdala and cognitive functions, this study may contribute by providing a new direction for investigating the internal mechanism of ADHD.

Aberrant dynamic functional connectivity features within default mode network in patients with autism spectrum disorder: evidence from dynamical conditional correlation

Autism spectrum disorder (ASD) is characterized by aberrant functional connectivity (FC) within/between certain large-scale brain networks. Although relatively lower level of FC between default mode network (DMN) regions (i.e., DMN-FC) has been detected in many previous studies, they failed to capture the temporal dynamic features of DMN-FC and were limited by small sample size. Here, the dynamical conditional correlation, which could assess precise FC at each time point and has been proved to be a technique with high test-retest reliability, was applied to investigate the DMN-FC pattern of patients with ASD from the Autism Brain Imaging Data Exchange, which included functional and structural brain imaging data of more than 1000 participants. The data analysis here showed that compared to typical developing (TD) participants, patients with ASD exhibited significantly lower mean DMN-FC level across recording time, but significantly higher variance of DMN-FC level across recording time. Moreover, these alterations were significantly associated with symptom severity of patients, especially their impaired communication skills and repetitive behaviors. These results support the view that aberrant temporal dynamic of FC within DMN is an important neuropathological feature of ASD and is a potential biomarker for ASD diagnosis.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-021-09723-9.

Abnormal transitions of dynamic functional connectivity states in bipolar disorder: A whole-brain resting-state fMRI study

BACKGROUND

Dynamic functional connectivity (dFC) based on resting-state fMRI has attracted interest in the field of bipolar disorder (BD), because dFC can better capture the evolving processes of emotion and cognition, which are typically impaired in BD. However, previous dFC studies of BD have typically focused on specific seed brain regions or specific functional brain networks, and they have ignored global dynamic information interaction in the whole brain. This study is aimed to reveal aberrant and interpretable whole-brain dFC patterns of BD.

METHODS

The resting-state fMRI data collected from 35 euthymic BD patients and 30 healthy people. We developed a new dFC inference pipeline, including the sliding-window method, k-means clustering, a new permutation with zero-inflated Poisson regression method, and a similarity analysis for interpretable states, to examine the different patterns of dFC states between BD patients and healthy participants.

RESULTS

BD patients had significantly more frequent transitions between two specific dFC states, which were respectively close to high-level cognitive networks and low-level sensory networks, than healthy controls (p < 0.05, FDR).

LIMITATIONS

The size of samples and other BD types need to be expanded to validate the results of this study. Possible confounding effect of medication.

CONCLUSIONS

This study detected aberrant dFC pattern of BD, which indicated the increased lability of the processes of cognition and emotion in BD, and this finding could improve our understanding of the neuropathological mechanism of BD.

Functional Networks Abnormalities in Autism Spectrum Disorder: Age-Related Hypo and Hyper Connectivity

Autism spectrum disorder (ASD) is a developmental disorder characterized by defects in social interaction. The past functional connectivity studies using resting-state fMRI have found both patterns of hypo-connectivity and hyper-connectivity in ASD and proposed the age as an important factor on functional connectivity disorders. However, this influence is not clearly characterized yet. Previous studies have often examined the functional connectivity disorders in particular brain regions in an age group or a mixture of age groups. The present study compares whole-brain within-connectivity and between-connectivity between ASD individuals and typically developing (TD) controls in three age groups including children (< 11 years), adolescents (11-18 years), and adults (> 18 years), each comprising 21 ASD individuals and 21 TD controls. The age groups were matched for age, Full IQ, and gender. Independent component analysis and dual regression were used to investigate within-connectivity. The full and partial correlations between ICs were used to investigate between-connectivity. Examination of the within-connectivity showed hyper-connectivity, especially in cerebellum and brainstem in ASD children but both hyper/hypo connectivity in adolescents and ASD adults. In ASD children, difference in the between-connectivity among default mode network (DMN), salience-executive network and fronto-parietal network were observed. There was also a negative correlation between DMN and temporal network. Full correlation comparison between ASD adolescents and TD individuals showed significant differences between cerebellum and DMN. Our results supported just the hyper-connectivity in childhood, but both hypo and hyper-connectivity after childhood and hypothesized that abnormal resting connections in ASD exist in the regions of the brain known to be involved in social cognition.

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.

Atypical Inter-Network Deactivation Associated With the Posterior Default-Mode Network in Autism Spectrum Disorder

Previous studies have suggested that atypical deactivation of functional brain networks contributes to the complex cognitive and behavioral profile associated with autism spectrum disorder (ASD). However, these studies have not considered the temporal dynamics of deactivation mechanisms between the networks. In this study, we examined (a) mutual deactivation and (b) mutual activation-deactivation (i.e., anticorrelated) time-lag patterns between resting-state networks (RSNs) in young adults with ASD (n = 20) and controls (n = 20) by applying the recently defined dynamic lag analysis (DLA) method, which measures time-lag variations peak-by-peak between the networks. In order to achieve temporally accurate lag patterns, the brain imaging data was acquired with a fast functional magnetic resonance imaging (fMRI) sequence (TR = 100 ms). Group-level independent component analysis was used to identify 16 RSNs for the DLA. We found altered mutual deactivation timings in ASD in (a) three of the deactivated and (b) two of the transiently anticorrelated (activated-deactivated) RSN pairs, which survived the strict threshold for significance of surrogate data. Of the significant RSN pairs, 80% included the posterior default-mode network (DMN). We propose that temporally altered deactivation mechanisms, including timings and directionality, between the posterior DMN and RSNs mediating processing of socially relevant information may contribute to the ASD phenotype. LAY SUMMARY: To understand autistic traits on a neural level, we examined temporal fluctuations in information flow between brain regions in young adults with autism spectrum disorder (ASD) and controls. We used a fast neuroimaging procedure to investigate deactivation mechanisms between brain regions. We found that timings and directionality of communication between certain brain regions were temporally altered in ASD, suggesting atypical deactivation mechanisms associated with the posterior default-mode network.