Functional connectivity at rest is sensitive to individual differences in executive function: A network analysis

The multiverse of data preprocessing and analysis in graph-based fMRI: A systematic literature review of analytical choices fed into a decision support tool for informed analysis

The large number of different analytical choices used by researchers is partly responsible for the challenge of replication in neuroimaging studies. For an exhaustive robustness analysis, knowledge of the full space of analytical options is essential. We conducted a systematic literature review to identify the analytical decisions in functional neuroimaging data preprocessing and analysis in the emerging field of cognitive network neuroscience. We found 61 different steps, with 17 of them having debatable parameter choices. Scrubbing, global signal regression, and spatial smoothing are among the controversial steps. There is no standardized order in which different steps are applied, and the parameter settings within several steps vary widely across studies. By aggregating the pipelines across studies, we propose three taxonomic levels to categorize analytical choices: 1) inclusion or exclusion of specific steps, 2) parameter tuning within steps, and 3) distinct sequencing of steps. We have developed a decision support application with high educational value called METEOR to facilitate access to the data in order to design well-informed robustness (multiverse) analysis.

Atypical dynamic network reconfiguration and genetic mechanisms in patients with major depressive disorder

BACKGROUND

Brain dynamics underlie complex forms of flexible cognition or the ability to shift between different mental modes. However, the precise dynamic reconfiguration based on multi-layer network analysis and the genetic mechanisms of major depressive disorder (MDD) remains unclear.

METHODS

Resting-state functional magnetic resonance imaging (fMRI) data were acquired from the REST-meta-MDD consortium, including 555 patients with MDD and 536 healthy controls (HC). A time-varying multi-layer network was constructed, and dynamic modular characteristics were used to investigate the network reconfiguration. Additionally, partial least squares regression analysis was performed using transcriptional data provided by the Allen Human Brain Atlas (AHBA) to identify genes associated with atypical dynamic network reconfiguration in MDD.

RESULTS

In comparison to HC, patients with MDD exhibited lower global and local recruitment coefficients. The local reduction was particularly evident in the salience and subcortical networks. Spatial transcriptome correlation analysis revealed an association between gene expression profiles and atypical dynamic network reconfiguration observed in MDD. Further functional enrichment analyses indicated that positively weighted reconfiguration-related genes were primarily associated with metabolic and biosynthetic pathways. Additionally, negatively enriched genes were predominantly related to programmed cell death-related terms.

CONCLUSIONS

Our findings offer robust evidence of the atypical dynamic reconfiguration in patients with MDD from a novel perspective. These results offer valuable insights for further exploration into the mechanisms underlying MDD.

An executive-functions-based reading training enhances sensory-motor systems integration during reading fluency in children with dyslexia

The Simple View of Reading model suggests that intact language processing and word decoding lead to proficient reading comprehension, with recent studies pointing at executive functions as an important component contributing to reading proficiency. Here, we aimed to determine the underlying mechanism(s) for these changes. Participants include 120 8- to 12-year-old children (n = 55 with dyslexia, n = 65 typical readers) trained on an executive functions-based reading program, including pre/postfunctional MRI and behavioral data collection. Across groups, improved word reading was related to stronger functional connections within executive functions and sensory networks. In children with dyslexia, faster and more accurate word reading was related to stronger functional connections within and between sensory networks. These results suggest greater synchronization of brain systems after the intervention, consistent with the "neural noise" hypothesis in children with dyslexia and support the consideration of including executive functions as part of the Simple View of Reading model.

Neurodevelopmental Subtypes of Functional Brain Organization in the ABCD Study Using a Rigorous Analytic Framework

The current study demonstrates that an individual's resting-state functional connectivity (RSFC) is a dependable biomarker for identifying differential patterns of cognitive and emotional functioning during late childhood. Using baseline RSFC data from the Adolescent Brain Cognitive Development (ABCD) study, which includes children aged 9-11, we identified four distinct RSFC subtypes We introduce an integrated methodological pipeline for testing the reliability and importance of these subtypes. In the Identification phase, Leiden Community Detection defined RSFC subtypes, with their reproducibility confirmed through a split-sample technique in the Validation stage. The Evaluation phase showed that distinct cognitive and mental health profiles are associated with each subtype, with the Predictive phase indicating that subtypes better predict various cognitive and mental health characteristics than individual RSFC connections. The Replication stage employed bootstrapping and down-sampling methods to substantiate the reproducibility of these subtypes further. This work allows future explorations of developmental trajectories of these RSFC subtypes.

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.

Atrophy in behavioural variant frontotemporal dementia spans multiple large-scale prefrontal and temporal networks

The identification of a neurodegenerative disorder's distributed pattern of atrophy-or atrophy 'signature'-can lend insights into the cortical networks that degenerate in individuals with specific constellations of symptoms. In addition, this signature can be used as a biomarker to support early diagnoses and to potentially reveal pathological changes associated with said disorder. Here, we characterized the cortical atrophy signature of behavioural variant frontotemporal dementia (bvFTD). We used a data-driven approach to estimate cortical thickness using surface-based analyses in two independent, sporadic bvFTD samples (n = 30 and n = 71, total n = 101), using age- and gender-matched cognitively and behaviourally normal individuals. We found highly similar patterns of cortical atrophy across the two independent samples, supporting the reliability of our bvFTD signature. Next, we investigated whether our bvFTD signature targets specific large-scale cortical networks, as is the case for other neurodegenerative disorders. We specifically asked whether the bvFTD signature topographically overlaps with the salience network, as previous reports have suggested. We hypothesized that because phenotypic presentations of bvFTD are diverse, this would not be the case, and that the signature would cross canonical network boundaries. Consistent with our hypothesis, the bvFTD signature spanned rostral portions of multiple networks, including the default mode, limbic, frontoparietal control and salience networks. We then tested whether the signature comprised multiple anatomical subtypes, which themselves overlapped with specific networks. To explore this, we performed a hierarchical clustering analysis. This yielded three clusters, only one of which extensively overlapped with a canonical network (the limbic network). Taken together, these findings argue against the hypothesis that the salience network is preferentially affected in bvFTD, but rather suggest that-at least in patients who meet diagnostic criteria for the full-blown syndrome-neurodegeneration in bvFTD encompasses a distributed set of prefrontal, insular and anterior temporal nodes of multiple large-scale brain networks, in keeping with the phenotypic diversity of this disorder.

Functional network segregation is associated with higher functional connectivity in endurance runners

Neuroimaging studies have identified significant differences in brain structure, function, and connectivity between endurance runners and healthy controls. However, the topological organization of large-scale functional brain networks remains unexplored in endurance runners. Using resting-state functional magnetic resonance imaging data, this study examined the differences in the topological organization of functional networks between endurance runners (n = 22) and healthy controls (n = 20). Endurance runners had significantly higher clustering coefficients in the whole-brain functional network than healthy controls, but the two did not differ regarding the shortest path length or small-world index. Using network-based statistics, we identified one subnetwork in endurance runners with higher functional connectivity than healthy controls, and the mean functional connectivity of the subnetwork significantly correlated with the three aforementioned small-world parameters. In this subnetwork, the mean clustering coefficient of nodes associated with short-range connections was higher in endurance runners than in healthy controls, but the mean clustering coefficient of nodes associated with long-range connections did not differ between the two groups. In conclusion, using graph theoretical approaches, we revealed significant differences in the topological organization of the whole-brain functional network and functional connectivity between endurance runners and healthy controls. The relationship between these two features suggests that a more segregated network may arise from the optimization of the identified subnetwork in endurance runners. These findings are possibly the neural basis underlying the good performance of endurance runners in endurance running.

Role of the amygdala in disrupted integration and effective connectivity of cortico-subcortical networks in apathy

BACKGROUND

Apathy is a quantitative reduction in motivation and goal-directed behaviors, not only observed in neuropsychiatric disorders, but also present in healthy populations. Although brain abnormalities associated with apathy in clinical disorders have been studied, the organization of brain networks in healthy individuals has yet to be identified.

METHOD

We examined properties of intrinsic brain networks in healthy individuals with varied levels of apathy. By using functional magnetic resonance imaging in combination with graph theory analysis and dynamic causal modeling analysis, we tested communications among nodes and modules as well as effective connectivity among brain networks.

RESULTS

We found that the average participation coefficient of the subcortical network, especially the amygdala, was lower in individuals with high than low apathy. Importantly, we observed weaker effective connectivity fromthe hippocampus and parahippocampal gyrus to the amygdala, and from the amygdala to the parahippocampal gyrus and medial frontal cortex in individuals with apathy.

CONCLUSION

These findings suggest that individuals with high apathy exhibit aberrant communication within the cortical-to-subcortical network, characterized by differences in amygdala-related effective connectivity. Our work sheds light on the neural basis of apathy in subclinical populations and may have implications for understanding the development of clinical conditions that feature apathy.

Quantification of body ownership awareness induced by the visual movement illusion of the lower limbs: a study of electroencephalogram and surface electromyography

The visual movement illusion (VMI) is a subjective experience. This illusion is produced by watching the subject's motion video. At the same time, VMI evokes awareness of body ownership. We applied the power spectral density (PSD) matrix and the partial directed correlation (PDC) matrix to build the PPDC matrix for the γ₂ band (34-98.5 Hz), combining cerebral cortical and musculomotor cortical complexity and PPDC to quantify the degree of body ownership. Thirty-five healthy subjects were recruited to participate in this experiment. The subjects' electroencephalography (EEG) and surface electromyography (sEMG) data were recorded under resting conditions, observation conditions, illusion conditions, and actual seated front-kick movements. The results show the following: (1) VMI activates the cerebral cortex to some extent; (2) VMI enhances cortical muscle excitability in the rectus femoris and medial vastus muscles; (3) VMI induces a sense of body ownership; (4) the use of PPDC values, fuzzy entropy values of muscles, and fuzzy entropy values of the cerebral cortex can quantify whether VMI induces awareness of body ownership. These results illustrate that PPDC can be used as a biomarker to show that VMI affects changes in the cerebral cortex and as a quantitative tool to show whether body ownership awareness arises.

Multisensory integration and white matter pathology: Contributions to cognitive dysfunction

The ability to simultaneously process and integrate multiple sensory stimuli is paramount to effective daily function and essential for normal cognition. Multisensory management depends critically on the interplay between bottom-up and top-down processing of sensory information, with white matter (WM) tracts acting as the conduit between cortical and subcortical gray matter (GM) regions. White matter tracts and GM structures operate in concert to manage both multisensory signals and cognition. Altered sensory processing leads to difficulties in reweighting and modulating multisensory input during various routine environmental challenges, and thus contributes to cognitive dysfunction. To examine the specific role of WM in altered sensory processing and cognitive dysfunction, this review focuses on two neurologic disorders with diffuse WM pathology, multiple sclerosis and mild traumatic brain injury, in which persistently altered sensory processing and cognitive impairment are common. In these disorders, cognitive dysfunction in association with altered sensory processing may develop initially from slowed signaling in WM tracts and, in some cases, GM pathology secondary to WM disruption, but also because of interference with cognitive function by the added burden of managing concurrent multimodal primary sensory signals. These insights promise to inform research in the neuroimaging, clinical assessment, and treatment of WM disorders, and the investigation of WM-behavior relationships.

Functional reorganization of contralesional networks varies according to isocitrate dehydrogenase 1 mutation status in patients with left frontal lobe glioma

PURPOSE

The study aimed to assess how isocitrate dehydrogenase 1 (IDH1) mutation status in patients with glioma may alter functional connectivity (FC) in the default mode network (DMN) and fronto-parietal network (FPN).

METHODS

Using resting-state functional magnetic resonance imaging, a seed-based FC analysis was employed to investigate connectivity within and between networks in seventeen patients with IDH1-mutant glioma (IDH1-M), eleven patients with IDH1-wildtype glioma (IDH1-WT), and nineteen healthy controls (HC).

RESULTS

For FC within the DMN, compared to HC, both IDH1-M and IDH1-WT exhibited significantly increased FC between the posterior cingulate cortex (PCC) and the right retrosplenial cortex, right precuneus/cuneus, and right middle cingulate cortex and between the right lateral parietal cortex (LP_R) and the right middle temporal gyrus. For FC within the FPN, compared with HC, IDH1-M showed significantly greater FC between the right posterior parietal cortex (PPC_R) and the right inferior, right medial, and right middle frontal gyrus, and IDH1-WT showed significantly increased FC between the PPC_R and the right middle frontal gyrus. For FC between the DMN and FPN, relative to IDH1-WT and HC, IDH1-M exhibited significantly increased FC between the LP_R and the right superior frontal gyrus and between the PPC_R and the right precuneus/cuneus. In contrast, compared to IDH1-M and HC, IDH1-WT showed significantly reduced FC between the PPC_R and the right angular gyrus.

CONCLUSION

The preliminary findings revealed that there should be differences in the patterns of network reorganization between IDH1-M and IDH1-WT with different growth kinetics.

The longitudinal development of large-scale functional brain networks for arithmetic ability from childhood to adolescence

Arithmetic ability is an important high-level cognitive function that requires interaction among multiple brain regions. Previous studies on arithmetic development have focused on task-induced activation in isolated brain regions or functional connectivity among particular seed regions. However, it remains largely unknown whether and how functional connectivity among large-scale brain modules contributes to arithmetic development. In the present study, we used a longitudinal sample of task-based functional magnetic resonance imaging (fMRI) data comprising 63 typically developing children, with two testing points being about two years apart. With graph theory, we examined the longitudinal development of large-scale brain modules for a multiplication task in younger (mean age 9.88 at time 1) and older children (mean age 12.34 at time 1), respectively. The results showed that the default-mode (DMN) and frontal-parietal networks (FPN) became increasingly segregated over time. Specifically, intra-connectivity within the DMN and FPN increased significantly with age, and inter-connectivity between the DMN and visual network decreased significantly with age. Such developmental changes were mainly observed in the younger children, but not in the older children. Moreover, the change in network segregation of the DMN was positively correlated with longitudinal gain in arithmetic performance in the younger children, and individual difference in network segregation of the FPN was positively correlated with arithmetic performance at time 2 in the older children. Taken together, the present results highlight the development of the functional architecture in large-scale brain networks from childhood to adolescence, which may provide insights into potential neural mechanisms underlying arithmetic development.

Network controllability mediates the relationship between rigid structure and flexible dynamics

Precisely how the anatomical structure of the brain supports a wide range of complex functions remains a question of marked importance in both basic and clinical neuroscience. Progress has been hampered by the lack of theoretical frameworks explaining how a structural network of relatively rigid interareal connections can produce a diverse repertoire of functional neural dynamics. Here, we address this gap by positing that the brain's structural network architecture determines the set of accessible functional connectivity patterns according to predictions of network control theory. In a large developmental cohort of 823 youths aged 8 to 23 years, we found that the flexibility of a brain region's functional connectivity was positively correlated with the proportion of its structural links extending to different cognitive systems. Notably, this relationship was mediated by nodes' boundary controllability, suggesting that a region's strategic location on the boundaries of modules may underpin the capacity to integrate information across different cognitive processes. Broadly, our study provides a mechanistic framework that illustrates how temporal flexibility observed in functional networks may be mediated by the controllability of the underlying structural connectivity.

Resting-state dynamic functional connectivity predicts the psychosocial stress response

Acute stress triggers a complex cascade of psychological, physiological, and neural responses, which show large and enduring individual differences. Although previous studies have examined the relationship between the stress response and dynamic features of the brain's resting state, no study has used the brain's dynamic activity in the resting state to predict individual differences in the psychosocial stress response. In the current study, resting-state scans of forty-eight healthy participants were collected, and then their individual acute stress responses during the Montreal Imaging Stress Test (MIST) paradigm were recorded. Results defined a connectivity state (CS) characterized by positive correlations across the whole brain during resting-state that could negatively predict participants' feelings of social evaluative threat during stress tasks. Another CS characterized by negative correlations between the frontal-parietal network (FPN) and almost all other networks, except the dorsal attentional network (DAN), could predict participants' subjective stress, feelings of uncontrollability, and feelings of social evaluative threat. However, no CS could predict participants' salivary cortisol stress response. Overall, these results suggested that the brain state characterized as attentional regulation, linking self-control, and top-down regulation ability, could predict the psychosocial stress response. This study also developed an objective indicator for predicting human stress responses.

The role of prefrontal cortex in cognitive control and executive function

Concepts of cognitive control (CC) and executive function (EF) are defined in terms of their relationships with goal-directed behavior versus habits and controlled versus automatic processing, and related to the functions of the prefrontal cortex (PFC) and related regions and networks. A psychometric approach shows unity and diversity in CC constructs, with 3 components in the most commonly studied constructs: general or common CC and components specific to mental set shifting and working memory updating. These constructs are considered against the cellular and systems neurobiology of PFC and what is known of its functional neuroanatomical or network organization based on lesioning, neurochemical, and neuroimaging approaches across species. CC is also considered in the context of motivation, as "cool" and "hot" forms. Its Common CC component is shown to be distinct from general intelligence (g) and closely related to response inhibition. Impairments in CC are considered as possible causes of psychiatric symptoms and consequences of disorders. The relationships of CC with the general factor of psychopathology (p) and dimensional constructs such as impulsivity in large scale developmental and adult populations are considered, as well as implications for genetic studies and RDoC approaches to psychiatric classification.

Decreased modular segregation of the frontal-parietal network in major depressive disorder

Major depressive disorder (MDD) is a common psychiatric condition associated with aberrant large-scale distributed brain networks. However, it is unclear how the network dysfunction in MDD patients is characterized by imbalance or derangement of network modular segregation. Fifty-one MDD patients and forty-three matched healthy controls (HC) were recruited in the present study. We analyzed intrinsic brain activity derived from resting-state functional magnetic resonance imaging (R-fMRI) and then examined brain network segregation by computing the participation coefficient (PC). Further intra- and inter-modular connections analysis were preformed to explain atypical PC. Besides, we explored the potential relationship between the above graph theory measures and symptom severity in MDD. Lower modular segregation of the frontal-parietal network (FPN) was found in MDD compared with the HC group. The MDD group exhibited increased inter-module connections between the FPN and cingulo-opercular network (CON), between the FPN and cerebellum (Cere), between the CON and Cere. At the nodal level, the PC of the anterior prefrontal cortex, anterior cingulate cortex, inferior parietal lobule (IPL), and intraparietal sulcus showed larger in MDD. Additionally, the inter-module connections between the FPN and CON and the PC values of the IPL were negatively correlated with depression symptom in the MDD group. These findings might give evidence about abnormal FPN in MDD from the perspective of modular segregation in brain networks.

Topographical functional correlates of interindividual differences in executive functions in young healthy twins

Executive functions (EF) are a set of higher-order cognitive abilities that enable goal-directed behavior by controlling lower-level operations. In the brain, those functions have been traditionally associated with activity in the Frontoparietal Network, but recent neuroimaging studies have challenged this view in favor of more widespread cortical involvement. In the present study, we aimed to explore whether the network that serves as critical hubs at rest, which we term network reliance, differentiate individuals as a function of their level of EF. Furthermore, we investigated whether such differences are driven by genetic as compared to environmental factors. For this purpose, resting-state functional magnetic resonance imaging data and the behavioral testing of 453 twins from the Colorado Longitudinal Twins Study were analyzed. Separate indices of EF performance were obtained according to a bifactor unity/diversity model, distinguishing between three independent components representing: Common EF, Shifting-specific and Updating-specific abilities. Through an approach of step-wise in silico network lesioning of the individual functional connectome, we show that interindividual differences in EF are associated with different dependencies on neural networks at rest. Furthermore, these patterns show evidence of mild heritability. Such findings add knowledge to the understanding of brain states at rest and their connection with human behavior, and how they might be shaped by genetic influences.

Bilingual language entropy influences executive functions through functional connectivity and signal variability

How bilinguals' experience in managing multiple languages in different communicative contexts influences the cognitive and neural aspects of executive functions remains unclear. Therefore, we examined whether variations in language experience in young adult bilinguals were associated with data-driven brain functional network patterns (connectivity and signal variability) defined by performance during executive control tasks (Stroop and task-switching). Multiple aspects of language experience, such as the extent of balanced bilingualism in language proficiency and usage, and language diversity across social contexts (i.e., language entropy) were assessed. We found that greater language diversity, rather than balanced bilingualism per se, was related to higher brain network specialization and segregation concentrated on the default mode and executive control networks, and lower signal variability, a pattern linked to smaller RT-indices related to executive functioning of shifting, goal-maintenance, and conflict-monitoring. Our findings underscore the important role of language diversity in influencing bilinguals' neurocognitive characteristics of executive functioning.

Cortical Frontoparietal Network Dysfunction in CHMP2B-Frontotemporal Dementia

A rare cause of inherited frontotemporal dementia (FTD) is a mutation in the CHMP2B gene on chromosome 3 leading to the autosomal dominantly inherited FTD (CHMP2B-FTD). Since CHMP2B-FTD is clinically well-characterized, and patients show a distinct pattern of executive dysfunction, the condition offers possible insight in the early electroencephalographic (EEG) changes in the cortical networks. Specifically, EEG microstate analysis parses the EEG signals into topographies believed to represent discrete network activations. We investigated the EEG dynamics in patients with symptomatic CHMP2B-FTD (n = 5) as well as pre-symptomatic mutation carriers (n = 5) compared to non-carrier family members (n = 6). The data was parsed into four archetypal microstates and global power was calculated. A trend was found for lower occurrence in microstate D in CHMP2B-FTD (p-value = 0.177, F-value = 2.036). Patients with recent symptom onset (<1 year) showed an increased duration of microstate D, whereas patients who had been symptomatic for longer periods (>2 years) showed decreased duration. Patients with CHMP2B-FTD present with executive dysfunction, and microstate D has previously been shown to be associated with the fronto-parietal network. The biphasic pattern may represent the pathophysiological changes in brain dynamics during neurodegeneration, which may apply to other neurodegenerative diseases.

Brain parcellation selection: An overlooked decision point with meaningful effects on individual differences in resting-state functional connectivity

Over the past decade extensive research has examined the segregation of the human brain into large-scale functional networks. The resulting network maps, i.e. parcellations, are now commonly used for the a priori identification of functional networks. However, the use of these parcellations, particularly in developmental and clinical samples, hinges on four fundamental assumptions: (1) the various parcellations are equally able to recover the networks of interest; (2) adult-derived parcellations well represent the networks in children’s brains; (3) network properties, such as within-network connectivity, are reliably measured across parcellations; and (4) parcellation selection does not impact the results with regard to individual differences in given network properties. In the present study we examined these assumptions using eight common parcellation schemes in two independent developmental samples. We found that the parcellations are equally able to capture networks of interest in both children and adults. However, networks bearing the same name across parcellations (e.g., default network) do not produce reliable within-network measures of functional connectivity. Critically, parcellation selection significantly impacted the magnitude of associations of functional connectivity with age, poverty, and cognitive ability, producing meaningful differences in interpretation of individual differences in functional connectivity based on parcellation choice. Our findings suggest that work employing parcellations may benefit from the use of multiple schemes to confirm the robustness and generalizability of results. Furthermore, researchers looking to gain insight into functional networks may benefit from employing more nuanced network identification approaches such as using densely-sampled data to produce individual-derived network parcellations. A transition towards precision neuroscience will provide new avenues in the characterization of functional brain organization across development and within clinical populations.

Genetic and Environmental Influence on the Human Functional Connectome

Detailed mapping of genetic and environmental influences on the functional connectome is a crucial step toward developing intermediate phenotypes between genes and clinical diagnoses or cognitive abilities. We analyzed resting-state functional magnetic resonance imaging data from two adult twin samples (Nos = 446 and 371) to quantify genetic and environmental influence on all pairwise functional connections between 264 brain regions (~35 000 functional connections). Nonshared environmental influence was high across the whole connectome. Approximately 14-22% of connections had nominally significant genetic influence in each sample, 4.6% were significant in both samples, and 1-2% had heritability estimates greater than 30%. Evidence of shared environmental influence was weak. Genetic influences on connections were distinct from genetic influences on a global summary measure of the connectome, network-based estimates of connectivity, and movement during the resting-state scan, as revealed by a novel connectome-wide bivariate genetic modeling procedure. The brain's genetic organization is diverse and not as one would expect based solely on structure evident in nongenetically informative data or lower resolution data. As follow-up, we make novel classifications of functional connections and examine highly localized connections with particularly strong genetic influence. This high-resolution genetic taxonomy of brain connectivity will be useful in understanding genetic influences on brain disorders.

Individualized video recommendation modulates functional connectivity between large scale networks

With the emergence of AI‐powered recommender systems and their extensive use in the video streaming service, questions and concerns also arise. Why can recommended video content continuously capture users' attention? What is the impact of long‐term exposure to personalized video content on one's behaviors and brain functions? To address these questions, we designed an fMRI experiment presenting participants with personally recommended videos and generally recommended ones. To examine how large‐scale networks were modulated by personalized video content, graph theory analysis was applied to investigate the interaction between seven networks, including the ventral and dorsal attention networks (VAN, DAN), frontal–parietal network (FPN), salience network (SN), and three subnetworks of default mode network (dorsal medial prefrontal (dMPFC), Core, and medial temporal lobe (MTL)). Our results showed that viewing nonpersonalized video content mainly enhanced the connectivity in the DAN‐FPN‐Core pathway, whereas viewing personalized ones increased not only the connectivity in this pathway but also the DAN‐VAN‐dMPFC pathway. In addition, both personalized and nonpersonalized short videos decreased the couplings between SN and VAN as well as between two DMN subsystems, Core and MTL. Collectively, these findings uncovered distinct patterns of network interactions in response to short videos and provided insights into potential neural mechanisms by which human behaviors are biased by personally recommended content.

Functional connectivity evidence for state-independent executive function deficits in patients with major depressive disorder

BACKGROUND

Persistent neurocognitive deficits are often associated with poor outcomes of major depressive disorder (MDD). Executive dysfunction is the most common cognitive deficit in MDD. However, it remains unclear which subcomponent of executive dysfunction is state-independent with distinct neural substrates.

METHODS

A comprehensive neurocognitive test battery was used to assess four subcomponents of executive function (working memory, inhibition, shifting, and verbal fluency) in 95 MDD patients and 111 matched healthy controls (HCs). After 6 months of paroxetine treatment, 56 patients achieved clinical remission (rMDD) and completed the second-time neurocognitive test. Network-based statistics analysis was utilized to explore the changes in functional connectivity (FC).

RESULTS

Compared with the HCs, all the four subcomponents of MDD patients were significantly impaired. After treatment, there was a significant improvement in working memory, inhibition, and verbal fluency in the rMDD group. And shifting and verbal fluency of the rMDD group remained impaired compared with the HCs. Fifteen functional connections were interrupted in the MDD group, and 11 connections remained in a disrupted state after treatment. Importantly, verbal fluency was negatively correlated with the disrupted FC between the right dorsal prefrontal cortex and the left inferior parietal lobule in patients with MDD and remitted MDD.

LIMITATIONS

The correlation analysis of the association between cognitive impairment and connectivity alterations precluded us from making causal inferences.

CONCLUSIONS

Verbal fluency is the potential state-independent cognitive deficit with distinct neural basis in patients with MDD.

The effect of vascular health factors on white matter microstructure mediates age-related differences in executive function performance

Even within healthy aging, vascular risk factors can detrimentally influence cognition, with executive functions (EF) particularly vulnerable. Fronto-parietal white matter (WM) connectivity in part, supports EF and may be particularly sensitive to vascular risk. Here, we utilized structural equation modeling in 184 healthy adults (aged 20-94 years of age) to test the hypotheses that: 1) fronto-parietal WM microstructure mediates age effects on EF; 2) higher blood pressure (BP) and white matter hyperintensity (WMH) burden influences this association. All participants underwent comprehensive cognitive and neuropsychological testing including tests of processing speed, executive function (with a focus on tasks that require switching and inhibition) and completed an MRI scanning session that included FLAIR imaging for semi-automated quantification of white matter hyperintensity burden and diffusion-weighted imaging for tractography. Structural equation models were specified with age (as a continuous variable) and blood pressure predicting within-tract WMH burden and fractional anisotropy predicting executive function and processing speed. Results indicated that fronto-parietal white matter of the genu of the corpus collosum, superior longitudinal fasciculus, and the inferior frontal occipital fasciculus (but not cortico-spinal tract) mediated the association between age and EF. Additionally, increased systolic blood pressure and white matter hyperintensity burden within these white matter tracts contribute to worsening white matter health and are important factors underlying age-brain-behavior associations. These findings suggest that aging brings about increases in both BP and WMH burden, which may be involved in the degradation of white matter connectivity and in turn, negatively impact executive functions as we age.

Cortico-muscular functional network: an exploration of cortico-muscular coupling in hand movements

Objective. The main objective of this research was to study cortico-muscular, intra-cortical, and inter-muscular coupling. Herein, we established a cortico-muscular functional network (CMFN) to assess the network differences associated with making a fist, opening the hand, and wrist flexion.Approach. We used transfer entropy (TE) to calculate the causality between electroencephalographic and electromyographic data and established the TE connection matrix. We then applied graph theory to analyze the clustering coefficient, global efficiency, and small-world attributes of the CMFN. We also used Relief-F to extract the features of the TE connection matrix of the beta2 band for the different hand movements and observed high accuracy when this feature was used for action recognition.Main results. We found that the CMFN of the three actions in the beta band had small-world attributes, among which the beta2 band's small-world was stronger. Moreover, we found that the extracted features were mainly concentrated in the left frontal area, left motor area, occipital lobe, and related muscles, suggesting that the CMFN could be used to assess the coupling differences between the cortex and the muscles that are associated with different hand movements. Overall, our results showed that the beta2 (21-35 Hz) wave is the main information carrier between the cortex and the muscles, and the CMFN can be used in the beta2 band to assess cortico-muscular coupling.Significance. Our study preliminarily explored the CMFN associated with hand movements, providing additional insights regarding the transmission of information between the cortex and the muscles, thereby laying a foundation for future rehabilitation therapy targeting pathological cortical areas in stroke patients.

Altered resting-state networks may explain the executive impairment in young health immigrants into high-altitude area

Executive function is a complex involving multiple advanced brain functions like planning, working memory, mental flexibility and psychomotor. Previous researches indicated that executive function may be impaired after acute or chronic high-altitude exposure, while the underlying neurobiological mechanism has not been totally clarified. In the present study, based on 69 young healthy volunteers immigrating to high-altitude, Stroop test was utilized to identify the potential impairment of executive function after two-year high-altitude exposure while resting-state functional MRI (rs-fMRI) technology was employed to observe the alteration of resting-state networks. Stroop test indicated that the subjects experienced significantly lower accuracies and prolonged responding time after two-year exposure. Resting-state network analysis displayed a significantly decreased degree of co-activation within the left/right frontoparietal network, sensorimotor network, and auditory network after exposure. In the frontoparietal network, decreased co-activation intensity was found in left angular gyrus, while in the right frontoparietal network, decreased co-activation intensity was found in left precentral gyrus and postcentral gyrus. Similarly, as for sensorimotor and auditory network, left middle frontal gyrus and left superior temporal gyrus was identified to have decreased co-activation, respectively. Moreover, the responding delays in ST (part II) were negatively correlated with the signal intensity alteration of the right frontoparietal network. All these evidences indicated that the high-altitude exposure induced alteration in above resting state networks may be the functional basis of executive control impairment.

Development and validation of the Uniform Data Set (v3.0) executive function composite score (UDS3-EF)

INTRODUCTION

Cognitive composite scores offer a means of precisely measuring executive functioning (EF).

METHODS

We developed the Uniform Data Set v3.0 EF composite score (UDS3-EF) in 3507 controls from the National Alzheimer's Coordinating Center dataset using item-response theory and applied nonlinear and linear demographic adjustments. The UDS3-EF was validated with other neuropsychological tests and brain magnetic resonance imaging from independent research cohorts using linear models.

RESULTS

Final model fit was good-to-excellent: comparative fit index = 0.99; root mean squared error of approximation = 0.057. UDS3-EF scores differed across validation cohorts (controls > mild cognitive impairment > Alzheimer's disease-dementia ≈ behavioral variant frontotemporal dementia; P < 0.001). The UDS3-EF correlated most strongly with other EF tests (βs = 0.50 to 0.85, Ps < 0.001) and more with frontal, parietal, and temporal lobe gray matter volumes (βs = 0.18 to 0.33, Ps ≤ 0.004) than occipital gray matter (β = 0.12, P = 0.04). The total sample needed to detect a 40% reduction in UDS3-EF change (n = 286) was ≈40% of the next best measure (F-words; n = 714).

CONCLUSIONS

The UDS3-EF is well suited to quantify EF in research and clinical trials and offers psychometric and practical advantages over its component tests.

Gender-related differences in frontal-parietal modular segregation and altered effective connectivity in internet gaming disorder

BACKGROUND

Although previous studies have revealed gender-related differences in executive function in internet gaming disorder (IGD), neural mechanisms underlying these processes remain unclear, especially in terms of brain networks.

METHODS

Resting-state fMRI data were collected from 78 subjects with IGD (39 males, 20.8 ± 2.16 years old) and 72 with recreational game use (RGU) (39 males, 21.5 ± 2.56 years old). By utilizing graph theory, we calculated participation coefficients among brain network modules for all participants and analyzed the diagnostic-group-by-gender interactions. We further explored possible causal relationships between networks through spectral dynamic causal modeling (spDCM) to assess differences in between-network connections.

RESULTS

Compared to males with RGU, males with IGD demonstrated reduced modular segregation of the frontal-parietal network (FPN). Male IGD subjects also showed increased connections between the FPN and cingulo-opercular network (CON); however, these differences were not found in female subjects. Further spDCM analysis indicated that the causal influence from CON to FPN in male IGD subjects was enhanced relative to that of RGU males, while this influence was relatively reduced in females with IGD.

CONCLUSIONS

These results suggest poor modular segmentation of the FPN and abnormal FPN/CON connections in males with IGD, suggesting a mechanism for male vulnerability to IGD. An increased "bottom-up" effect from the CON to FPN in male IGD subjects could reflect dysfunction between the brain networks. Different mechanisms may underlie in IGD, suggesting that different interventions may be optimal in males and females with IGD.

The Impact of the BAILAMOS™ Dance Program on Brain Functional Connectivity and Cognition in Older Latino Adults: A Pilot Study

Dance is a culturally salient form of physical activity (PA) for older Latinos. Resting-state functional connectivity (FC) is a putative biomarker for age-related cognitive decline. We aimed to investigate the impact of the BAILAMOS™ dance program on FC in three brain functional networks (Default Mode [DMN], Frontoparietal [FPN], and Salience [SAL] networks), and cognition. Ten cognitively healthy older Latinos participated in the four-month BAILAMOS™ dance program. We assessed PA levels (self-reported and device-assessed) and estimated cardiorespiratory fitness, cognition, and resting-state FC via functional magnetic resonance imaging at baseline and post-intervention. We performed paired t-tests and Pearson correlations. Given the pilot nature of the study, significance levels were set at p < 0.05 and effect sizes are reported. We observed a significant increase in self-reported moderate leisure-time PA from pre- to post-intervention (t(9) = 3.16, p = 0.011, d = 0.66). FC within-FPN regions of interest (ROIs) significantly increased pre- to post-intervention (t(9) = 2.35, p = 0.043, d = 0.70). DMN ROIs showed an increase, with a moderate effect size, in the integration with other networks' ROIs (t(9) = 1.96, p = 0.081, d = 0.64) post-intervention. Increases in moderate leisure-time PA at post-intervention were associated with increases in the FC within-FPN (R = 0.79, p = 0.006). Our results suggest that dance might be a promising approach for improving age-related disruption of FC within- and between-networks commonly associated with cognitive decline.

Crosstalk between Depression and Dementia with Resting-State fMRI Studies and Its Relationship with Cognitive Functioning

Alzheimer’s disease (AD) is the most common type of dementia, and depression is a risk factor for developing AD. Epidemiological studies provide a clinical correlation between late-life depression (LLD) and AD. Depression patients generally remit with no residual symptoms, but LLD patients demonstrate residual cognitive impairment. Due to the lack of effective treatments, understanding how risk factors affect the course of AD is essential to manage AD. Advances in neuroimaging, including resting-state functional MRI (fMRI), have been used to address neural systems that contribute to clinical symptoms and functional changes across various psychiatric disorders. Resting-state fMRI studies have contributed to understanding each of the two diseases, but the link between LLD and AD has not been fully elucidated. This review focuses on three crucial and well-established networks in AD and LLD and discusses the impacts on cognitive decline, clinical symptoms, and prognosis. Three networks are the (1) default mode network, (2) executive control network, and (3) salience network. The multiple properties emphasized here, relevant for the hypothesis of the linkage between LLD and AD, will be further developed by ongoing future studies.

Fronto-cerebellar connectivity mediating cognitive processing speed

Processing speed is an important construct in understanding cognition. This study was aimed to control task specificity for understanding the neural mechanisms underlying cognitive processing speed. Forty young adult subjects performed attention tasks of two modalities (auditory and visual) and two levels of task rules (compatible and incompatible). Block-design fMRI captured BOLD signals during the tasks. Thirteen regions of interest were defined with reference to publicly available activation maps for processing speed tasks. Cognitive speed was derived from task reaction times, which yielded six sets of connectivity measures. Mixed-effect LASSO regression revealed six significant paths suggestive of a cerebello-frontal network predicting the cognitive speed. Among them, three are long range (two fronto-cerebellar, one cerebello-frontal), and three are short range (fronto-frontal, cerebello-cerebellar, and cerebello-thalamic). The long-range connections are likely to relate to cognitive control, and the short-range connections relate to rule-based stimulus-response processes. The revealed neural network suggests that automaticity, acting on the task rules and interplaying with effortful top-down attentional control, accounts for cognitive speed.

The role of cognitive reserve in the relationship between metabolic syndrome and cognitive functioning

Metabolic syndrome (MetS) is a cluster of vascular risk factors that can impact cognition. Cognitive reserve (CR), specifically early operators of reserve (e.g., education), have not been explored in the relationship between MetS and cognition. Adults 45-90 years old (n = 149) underwent neuropsychological testing and evaluation for MetS. Exploratory and confirmatory factor analyses defined neuropsychological domains and created a CR score based on early operators of CR. Regression analyses examined the association among MetS, CR, and neuropsychological performance. CFA revealed two neuropsychological factors: Episodic Memory and Executive Functioning. Controlling for age and physical ability, MetS and CR were significant predictors of the Factors. With CR in the model, MetS became a non-significant predictor of Executive Functioning; CR and physical ability were the most significant predictors. CR and MetS significantly predicted Episodic Memory . The results are discussed in the context of neuroprotective factors and cognitive aging.

Striatal-frontal network activation during voluntary task selection under conditions of monetary reward

During voluntary task selection, a number of internal and external biases may guide such a choice. However, it is not well understood how reward influences task selection when multiple options are possible. To address this issue, we examined brain activation in a voluntary task-switching paradigm while participants underwent fMRI (n = 19). To reinforce the overall goal to choose the tasks randomly, participants were told of a large bonus that they would receive at the end of the experiment for making random task choices. We also examined how occasional, random rewards influenced both task performance and brain activation. We hypothesized that these transient rewards would increase the value of the just-performed task, and therefore bias participants to choose to repeat the same task on the subsequent trial. Contrary to expectations, transient reward had no consistent behavioral effect on subsequent task choice. Nevertheless, the receipt of such rewards did influence activation in brain regions associated with reward processing as well as those associated with goal-directed control. In addition, reward on a prior trial was found to influence activation during task choice on a subsequent trial, with greater activation in a number of executive function regions compared with no-reward trials. We posit that both the random presentation of transient rewards and the overall task bonus for random task choices together reinforced the goal to choose the tasks randomly, which in turn influenced activation in both reward-related regions and those regions involved in abstract goal processing.

Relationships between multiple dimensions of executive functioning and resting-state networks in adults

The current study sought to examine the functional connectivity of resting state networks (RSNs) as they relate to the individual domains of executive functioning (EF). Based on the Unity and Diversity model (Miyake et al., 2000), EF performance was captured using a three-factor model proposed by Karr et al. (2018), which includes inhibition, shifting, and fluency. Publicly available data was used from the Nathan Kline Institute -Rockland project was used. Of the 722 participants who completed the Delis-Kaplan Executive Function System (D-KEFS), which was used to measure EF performance, 269 of these individuals completed resting state fMRI scans. First, a confirmatory factory analysis replicated Karr et al. (2018) revealing three components: inhibition, shifting and fluency. Next, RSNs were identified across the sample using an Independent Components Analysis (ICA) and was compared to previously established intrinsic connectivity networks (Laird et al., 2011). Finally, dual regression was used to analyze the relationships between the functional connectivity of RSNs and EF performance, which indicated that RSNs were differentially associated with inhibition and shifting. Better inhibition was related to increased connectivity between the left striatum and the attentional control network. Better shifting performance was related to increased connectivity between the pre- and postcentral gyri and the speech and sensorimotor network. These results highlight individual differences within these RSNs that are unique to the literature, as non-EF confounds are mitigated within the current measurements of EF performance.

Functional connectivity of the dorsolateral prefrontal cortex contributes to different components of executive functions

OBJECTIVE

The dorsolateral prefrontal cortex (DLPFC) orchestrates other brain regions and plays a vital role for "the most uniquely human" executive functions (EFs), which are divided into distinct components. Components of EFs have been localized to different brain regions and at the same time the DLPFC was found to be involved in a majority of EF components. The possible mechanism of the DLPFC's contribution to EF components might be found in DLPFC functional connectivity (FC): this FC of the DLPFC with other brain regions contributes to different EF components.

METHOD

To explore the DLPFC FC contribution to different EFs, we used an integrative approach involving analysis of fMRI and neuropsychological assessment of EFs. Fifty healthy adults (27 females and 23 males, mean age 34.5 ± 16.6 years) underwent neuropsychological assessment of EFs as well as task-based and resting-state fMRI. Task-based fMRI was applied as a functional localizer for individually defined DLPFC ROIs that were further used for the FC seed-based correlation analysis of the resting-state data. Then we looked for associations between individual scores of different EF components and the whole-brain resting-state FC of the DLPFC.

RESULTS

Resting-state correlates of DLPFC FC were revealed for three out of the seven EF components derived from an extensive neuropsychological assessment: inhibition, switching, and the verbal EF component.

CONCLUSIONS

Our study is the first to reveal the contribution of the DLPFC FC to several distinct EF components. The obtained results give insight into the brain mechanisms of EFs.

Influence of comorbid anxiety symptoms on cognitive deficits in patients with major depressive disorder

BACKGROUND

Major depressive disorder (MDD) patients with comorbid anxiety symptoms showed obvious cognitive deficits. However, it remains unclear whether comorbid anxiety symptoms will make a specific contribution to cognitive deficits in MDD.

METHODS

Executive function, processing speed, attention and memory were assessed in 162 MDD patients, and 142 healthy controls (HCs) by a comprehensive neuropsychological battery. 14-item Hamilton Anxiety Rating Scale (HAM-A) was used for anxiety symptoms and MDD patients with HAM-A total score >14 were classified into MDD with comorbid anxiety (MDDA) group. A multivariate analysis of covariance and regression models was conducted to evaluate the effects of anxiety symptoms on cognitive deficits.

RESULTS

There were no significantly differences in all 4 cognitive domains between MDD alone and MDDA patients (all p < 0.05). In MDDA subgroup, HAM-A total score contributed to executive function and memory (both p < 0.05), while HAM-A psychic symptoms contributed to all 4 domains (all p < 0.05). Moreover, after controlling for the severity of depression, either anxiety symptoms shown as HAMA total score or psychic anxiety symptoms only contributed significantly to the executive function performance.

LIMITATIONS

The cross-sectional design made it hard to acquire a cognitive performance trajectory accompanied by the fluctuations in anxiety symptoms.

CONCLUSION

Our findings suggest that there is no significant difference in cognitive performance between MDD alone and MDDA patients. However, comorbid anxiety, especially psychic anxiety may contribute to extensive cognitive deficits in MDDA patients. Notably, anxiety symptoms only independently triggered executive dysfunction when eliminating effect of the severity of depression.

Structural core of the executive control network: A high angular resolution diffusion MRI study

Executive function (EF) is a set of cognitive capabilities considered essential for successful daily living, and is negatively affected by ageing and neurodegenerative conditions. Underpinning EF performance are functional nodes in the executive control network (ECN), while the structural connectivity underlying this network is not well understood. In this paper, we evaluated the structural white matter tracts that interconnect the ECN and investigated their relationship to the EF performance. Using high‐angular resolution diffusion MRI data, we performed tractography analysis of structural connectivity in a cognitively normal cohort (n = 140), specifically targeting the connectivity between ECN nodes. Our data revealed the presence of a strongly‐connected “structural core” of the ECN comprising three components: interhemispheric frontal connections, a fronto‐parietal subnetwork and fronto‐striatal connections between right dorsolateral prefrontal cortex and right caudate. These pathways were strongly correlated with EF performance (p = .003). Post‐hoc analysis of subregions within the significant ECN connections showed that these effects were driven by a highly specific subset of interconnected cortical regions. The structural core subnetwork of the functional ECN may be an important feature crucial to a better future understanding of human cognition and behaviour.

Modular segregation of task-dependent brain networks contributes to the development of executive function in children

Executive function (EF) refers as to a set of high-level cognitive abilities that are critical to many aspects of daily life. Despite its importance in human daily life, the neural networks responsible for the development of EF in childhood are not well understood. The present study thus aimed to examine the development of task-dependent brain network organization and its relationship to age-related improvements in EF. To address this issue, we recruited eighty-eight Chinese children ranging in age from 7 to 12 years old, and collected their functional magnetic resonance imaging (fMRI) data when they performed an EF task. By utilizing graph theory, we found that the task-dependent brain network modules became increasingly segregated with age. Specifically, the intra-module connections within the default-mode network (DMN), frontal-parietal network (FPN) and sensorimotor network (SMN) increased significantly with age. In contrast, the inter-module connections of the visual network to both the FPN/SMN decreased significantly with age. Most importantly, modular segregation of the FPN significantly mediated the relationship between age and EF performance. These findings add to our growing understanding of how development changes in task-dependent brain network organization support vast behavioral improvements in EF observed during childhood.

White matter lesion loads associated with dynamic functional connectivity within attention network in patients with relapsing-remitting multiple sclerosis

Using time-variant of blood oxygenation level dependent (BOLD) signal to investigate the temporal changes in functional connectivity (FC) between key nodes may shed light on the dynamic characteristics of network. Twenty-two relapsing-remitting multiple sclerosis (RRMS) and 22 well-matched healthy control subjects (HCs) participated in this study. Previously validated key nodes of attention network seeds were defined as spherical regions of interests (ROIs); then, we captured the pattern of dFC using sliding window correlation of ROIs in the RRMS and HCs during rest. Furthermore, correlation analysis between altered dFC of paired-ROIs with clinical measures in RRMS were performed. Compared with the HCs, the RRMS showed: a certain specificity transient pattern of FC of attention network at time window levels, including decreased dFC within dorsal attention network [connections of left intraparietal sulcus (LIPS)-right intraparietal sulcus (RIPS), LIPS-right frontal eye field (RFEF) and left frontal eye field (LFEF)-RIPS] and ventral attention network [connection of right ventral frontal cortex (RVFC)-right temporal parietal junction (RTPJ)], increased dFC between dorsal and ventral attention network (connections of LIPS-RTPJ and LIPS-RVFC). Secondary analysis indicated that the dFC coefficients of the connections of LIPS-RIPS (r = -0.467, P = 0.023) and RVFC-RTPJ (r = -0.452, P = 0.043) were significant negative correlated with the total white matter lesion load. In conclusion, we found that the instantaneous configuration pattern of FC in attention network of RRMS are relate to lesions loads.

Disrupted topological organization of human brain connectome in diabetic retinopathy patients

OBJECTIVE

There is increasing neuroimaging evidence that type 2 diabetes patients with retinal microvascular complications show abnormal brain functional and structural architecture and are at an increased risk of cognitive decline and dementia. However, changes in the topological properties of the functional brain connectome in diabetic retinopathy (DR) patients remain unknown. The aim of this study was to explore the topological organization of the brain connectome in DR patients using graph theory approaches.

METHODS

Thirty-five DR patients (18 males and 17 females) and 38 healthy controls (HCs) (18 males and 20 females), matched for age, sex, and education, underwent resting-state magnetic resonance imaging scans. Graph theory analysis was performed to investigate the topological properties of brain functional connectome at both global and nodal levels.

RESULTS

Both DR and HC groups showed high-efficiency small-world network in their brain functional networks. Notably, the DR group showed reduction in the clustering coefficient (P=0.0572) and local efficiency (P=0.0151). Furthermore, the DR group showed reduced nodal centralities in the default-mode network (DMN) and increased nodal centralities in the visual network (VN) (P<0.01, Bonferroni-corrected). The DR group also showed abnormal functional connections among the VN, DMN, salience network (SN), and sensorimotor network (SMN). Altered network metrics and nodal centralities were significantly correlated with visual acuity and fasting blood glucose level in DR patients.

CONCLUSION

DR patients showed abnormal topological organization of the human brain connectome. Specifically, the DR group showed reduction in the clustering coefficient and local efficiency, relative to HC group. Abnormal nodal centralities and functional disconnections were mainly located in the DMN, VN, SN, and SMN in DR patients. Furthermore, the disrupted topological attributes showed correlations with clinical variables. These findings offer important insight into the neural mechanism of visual loss and cognitive deficits in DR patients.

Exploration of Major Cognitive Deficits in Medication-Free Patients With Major Depressive Disorder

Background: Major depressive disorder (MDD) is associated with a wide range of cognitive deficits. However, it remains unclear whether there will be a major cognitive deficit independently caused by depression at acute episodes of MDD. Method: A comprehensive neurocognitive test battery was used to assess the executive function, processing speed, attention, and memory in 162 MDD patients and 142 healthy controls (HCs). A multivariate analysis of variance, hierarchical regression analyses and general linear regression analyses were used to explore the possible major cognitive deficits and their predictor variables. Results: MDD patients showed extensive impairment in all four cognitive domains. Impairment of executive function and processing speed were found to persist even with other cognitive domains and clinical variables being accounted for. Executive function and processing speed were further predicted by total disease duration and depression severity, respectively. Conclusions: Executive function and processing speed may be two distinct major deficits at acute episodes of MDD. Furthermore, the executive function is likely originated from the cumulative effect of disease duration and processing speed is possibly derived from the temporary effect of current depressive episode.

Education, and the balance between dynamic and stationary functional connectivity jointly support executive functions in relapsing-remitting multiple sclerosis

Graphical network characteristics and nonstationary functional connectivity features, both derived from resting-state functional magnetic resonance imaging (rsfMRI) data, have been associated with cognitive performance in healthy subjects. How these features jointly relate to cognition in diseased states has not been investigated. In this study, 46 relapsing-remitting multiple sclerosis subjects underwent rsfMRI scans and a focused cognitive battery. With a sliding window approach, we examined six dynamic network features that indicated how connectivity changed over time as well as six measures derived from graph theory to reflect static network characteristics. Multiset canonical correlation analysis (MCCA) was then carried out to investigate the relations between dynamic network features, stationary network characteristics, cognitive testing, demographic, disease severity, and mood. Multiple sclerosis (MS) subjects demonstrated weaker connectivity strength, decreased network density, reduced global changes, but increased changes in interhemispheric connectivity compared to controls. The MCCA model determined that executive functions and processing speed ability measured by Wechsler Adult Intelligence Scale IV (WAIS-IV) Working Memory Index, WAIS-IV Processing Speed Index, and the Verbal Fluency Test were positively correlated with education, dynamic connectivity, and static connectivity strength; while poor task switching was correlated with disease severity, psychiatric comorbidities such as depression, anxiety, and fatigue, and static network density. Taken together, our results suggest that better executive functioning in MS requires maintenance of a continued coordination between stationary and dynamic functional connectivity as well as the support of education, and dynamic functional connectivity may provide an additional cognitive biomarker of disease severity in the MS population.

Clinical subcategorization of minimally conscious state according to resting functional connectivity

Patients in minimally conscious state (MCS) have been subcategorized in MCS plus and MCS minus, based on command-following, intelligible verbalization or intentional communication. We here aimed to better characterize the functional neuroanatomy of MCS based on this clinical subcategorization by means of resting state functional magnetic resonance imaging (fMRI). Resting state fMRI was acquired in 292 MCS patients and a seed-based analysis was conducted on a convenience sample of 10 MCS plus patients, 9 MCS minus patients and 35 healthy subjects. We investigated the left and right frontoparietal networks (FPN), auditory network, default mode network (DMN), thalamocortical connectivity and DMN between-network anticorrelations. We also employed an analysis based on regions of interest (ROI) to examine interhemispheric connectivity and investigated intergroup differences in gray/white matter volume by means of voxel-based morphometry. We found a higher connectivity in MCS plus as compared to MCS minus in the left FPN, specifically between the left dorso-lateral prefrontal cortex and left temporo-occipital fusiform cortex. No differences between patient groups were observed in the auditory network, right FPN, DMN, thalamocortical and interhemispheric connectivity, between-network anticorrelations and gray/white matter volume. Our preliminary group-level results suggest that the clinical subcategorization of MCS may involve functional connectivity differences in a language-related executive control network. MCS plus and minus patients are seemingly not differentiated by networks associated to auditory processing, perception of surroundings and internal awareness/self-mentation, nor by interhemispheric integration and structural brain damage.

The Relationship Between Resting State Network Connectivity and Individual Differences in Executive Functions

The brain is organized into a number of large networks based on shared function, for example, high-level cognitive functions (frontoparietal network), attentional capabilities (dorsal and ventral attention networks), and internal mentation (default network). The correlations of these networks during resting-state fMRI scans varies across individuals and is an indicator of individual differences in ability. Prior work shows higher cognitive functioning (as measured by working memory and attention tasks) is associated with stronger negative correlations between frontoparietal/attention and default networks, suggesting that increased ability may depend upon the diverging activation of networks with contrasting function. However, these prior studies lack specificity with regard to the higher-level cognitive functions involved, particularly with regards to separable components of executive function (EF). Here we decompose EF into three factors from the unity/diversity model of EFs: Common EF, Shifting-specific EF, and Updating-specific EF, measuring each via factor scores derived from a battery of behavioral tasks completed by 250 adult participants (age 28) at the time of a resting-state scan. We found the hypothesized segregated pattern only for Shifting-specific EF. Specifically, after accounting for one’s general EF ability (Common EF), individuals better able to fluidly switch between task sets have a stronger negative correlation between the ventral attention network and the default network. We also report non-predicted novel findings in that individuals with higher Shifting-specific abilities exhibited more positive connectivity between frontoparietal and visual networks, while those individuals with higher Common EF exhibited increased connectivity between sensory and default networks. Overall, these results reveal a new degree of specificity with regard to connectivity/EF relationships.