Involvement of the default mode network under varying levels of cognitive effort

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

BACKGROUND

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

AIM

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

METHODS

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

RESULTS

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

CONCLUSION

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

Association between clinical features and decreased degree centrality and variability in dynamic functional connectivity in the obsessive-compulsive disorder

Neuroimaging studies have indicated widespread brain structural and functional disruptions in patients with obsessive-compulsive disorder (OCD). However, the underlying mechanism of these changes remains unclear. A total of 45 patients with OCD and 42 healthy controls (HC) were enrolled. The study investigated local degree centrality (DC) abnormalities and employed abnormal regions of DC as seeds to investigate variability in dynamic functional connectivity (dFC) in the whole brain using a sliding window approach to analyze resting-state functional magnetic resonance imaging. The relationship between abnormal DC and dFC as well as the clinical features of OCD were examined using correlation analysis. Our findings suggested decreased DC in the bilateral thalamus, bilateral precuneus, and bilateral cuneus in OCD patients and a nominally negative correlation between the DC value in the thalamus and illness severity measured using the Yale-Brown Obsessive Compulsive Scale (Y-BOCS). In addition, seed-based dFC analysis showed that compared to measurements in the HC, the patients had decreased dFC variability between the left thalamus and the left cuneus and right lingual gyrus, and between the bilateral cuneus and bilateral postcentral gyrus, and a nominally positive correlation between the duration of illness and dFC variability between the left cuneus and left postcentral gyrus. These results indicated that OCD patients had decreased hub importance in the bilateral thalamus and cuneus throughout the entire brain. This reduction was associated with impaired coupling with dynamic function in the visual cortex and sensorimotor network and provided novel insights into the neurophysiological mechanisms underlying OCD.

Default mode network dynamics: An integrated neurocircuitry perspective on social dysfunction in human brain disorders

Our intricate social brain is implicated in a range of brain disorders, where social dysfunction emerges as a common neuropsychiatric feature cutting across diagnostic boundaries. Understanding the neurocircuitry underlying social dysfunction and exploring avenues for its restoration could present a transformative and transdiagnostic approach to overcoming therapeutic challenges in these disorders. The brain's default mode network (DMN) plays a crucial role in social functioning and is implicated in various neuropsychiatric conditions. By thoroughly examining the current understanding of DMN functionality, we propose that the DMN integrates diverse social processes, and disruptions in brain communication at regional and network levels due to disease hinder the seamless integration of these social functionalities. Consequently, this leads to an altered balance between self-referential and attentional processes, alongside a compromised ability to adapt to social contexts and anticipate future social interactions. Looking ahead, we explore how adopting an integrated neurocircuitry perspective on social dysfunction could pave the way for innovative therapeutic approaches to address brain disorders.

Brain activations elicited during task-switching generalize beyond the task: A partial least squares correlation approach to combine fMRI signals and cognition

An underlying hypothesis for broad transfer from cognitive training is that the regional brain signals engaged during the training task are related to the transfer tasks. However, it is unclear whether the brain activations elicited from a specific cognitive task can generalize to performance of other tasks, esp. in normal aging where cognitive training holds much promise. In this large dual-site functional magnetic resonance imaging (fMRI) study, we aimed to characterize the neurobehavioral correlates of task-switching in normal aging and examine whether the task-switching-related fMRI-blood-oxygen-level-dependent (BOLD) signals, engaged during varieties of cognitive control, generalize to other tasks of executive control and general cognition. We therefore used a hybrid blocked and event-related fMRI task-switching paradigm to investigate brain regions associated with multiple types of cognitive control on 129 non-demented older adults (65-85 years). This large dataset provided a unique opportunity for a data-driven partial least squares-correlation approach to investigate the generalizability of multiple fMRI-BOLD signals associated with task-switching costs to other tasks of executive control, general cognition, and demographic characteristics. While some fMRI signals generalized beyond the scanned task, others did not. Results indicate right middle frontal brain activation as detrimental to task-switching performance, whereas inferior frontal and caudate activations were related to faster processing speed during the fMRI task-switching, but activations of these regions did not predict performance on other tasks of executive control or general cognition. However, BOLD signals from the right lateral occipital cortex engaged during the fMRI task positively predicted performance on a working memory updating task, and BOLD signals from the left post-central gyrus that were disengaged during the fMRI task were related to slower processing speed in the task as well as to lower general cognition. Together, these results suggest generalizability of these BOLD signals beyond the scanned task. The findings also provided evidence for the general slowing hypothesis of aging as most variance in the data were explained by low processing speed and global low BOLD signal in older age. As processing speed shared variance with task-switching and other executive control tasks, it might be a possible basis of generalizability between these tasks. Additional results support the dedifferentiation hypothesis of brain aging, as right middle frontal activations predicted poorer task-switching performance. Overall, we observed that the BOLD signals related to the fMRI task not only generalize to the performance of other executive control tasks, but unique brain predictors of out-of-scanner performance can be identified.

Infraslow dynamic patterns in human cortical networks track a spectrum of external to internal attention

Early efforts to understand the human cerebral cortex focused on localization of function, assigning functional roles to specific brain regions. More recent evidence depicts the cortex as a dynamic system, organized into flexible networks with patterns of spatiotemporal activity corresponding to attentional demands. In functional MRI (fMRI), dynamic analysis of such spatiotemporal patterns is highly promising for providing non-invasive biomarkers of neurodegenerative diseases and neural disorders. However, there is no established neurotypical spectrum to interpret the burgeoning literature of dynamic functional connectivity from fMRI across attentional states. In the present study, we apply dynamic analysis of network-scale spatiotemporal patterns in a range of fMRI datasets across numerous tasks including a left-right moving dot task, visual working memory tasks, congruence tasks, multiple resting state datasets, mindfulness meditators, and subjects watching TV. We find that cortical networks show shifts in dynamic functional connectivity across a spectrum that tracks the level of external to internal attention demanded by these tasks. Dynamics of networks often grouped into a single task positive network show divergent responses along this axis of attention, consistent with evidence that definitions of a single task positive network are misleading. Additionally, somatosensory and visual networks exhibit strong phase shifting along this spectrum of attention. Results were robust on a group and individual level, further establishing network dynamics as a potential individual biomarker. To our knowledge, this represents the first study of its kind to generate a spectrum of dynamic network relationships across such an axis of attention.

Individual-level functional connectivity predicts cognitive control efficiency

Cognitive control (CC) is essential for problem-solving in everyday life, and CC-related deficits occur alongside costly and debilitating disorders. The tri-partite model suggests that CC comprises multiple behaviors, including switching, inhibiting, and updating. Activity within the fronto-parietal control network B (FPCN-B), the dorsal attention network (DAN), the cingulo-opercular network (CON), and the lateral default-mode network (L-DMN) is related to switching and inhibiting behaviors. However, our understanding of how these brain regions interact to bring about cognitive switching and inhibiting in individuals is unclear. In the current study, subjects performed two in-scanner tasks that required switching and inhibiting. We used support vector regression (SVR) models containing individually-estimated functional connectivity between the FPCN-B, DAN, CON and L-DMN to predict switching and inhibiting behaviors. We observed that: inter-network connectivity can predict inhibiting and switching behaviors in individuals, and the L-DMN plays a role in switching and inhibiting behaviors. Therefore, individually estimated inter-network connections are markers of CC behaviors, and CC behaviors may arise due to interactions between a set of networks.

Altered functional connectivity between cortical networks associated with inhibitory control in trauma-exposed females

Post-traumatic stress disorder (PTSD) is associated with impaired inhibitory control and alterations in large-scale brain network connectivity. However, few studies to date have examined the construct of inhibitory control as it relates to resting-state functional connectivity (rsFC) in a population with PTSD or trauma-exposure. The present study investigated the relationship between impaired inhibitory control and rsFC within the default mode network (DMN), central executive network (CEN), and salience network (SN) in a sample of females exposed to interpersonal trauma with and without PTSD (n = 67). Participants completed a classic Color-Word Stroop task as a measure of inhibitory control and two resting-state fMRI scans. We conducted voxelwise rsFC analyses with seed regions in the DMN, CEN, and SN and voxelwise linear regression analyses to examine the relationship between inhibitory control and rsFC of these networks across the sample. Better Stroop performance was negatively associated with total self-reported PTSD symptoms. An analysis of PTSD symptom clusters indicated that better Stroop performance was also associated with re-experiencing and hyperarousal symptoms, but not avoidance PTSD symptoms. Decreased coupling between the CEN and the DMN was associated with better inhibitory control in this sample of trauma-exposed females. These findings lend support to the hypothesis that efficient switching between these networks may contribute to better performance on cognitive and attentional tasks in trauma-exposed individuals.

Disrupted resting-sate brain network dynamics in children born extremely preterm

The developing brain has to adapt to environmental and intrinsic insults after extremely preterm (EPT) birth. Ongoing maturational processes maximize their fit to the environment and this can provide a substrate for neurodevelopmental failures. Resting-state functional magnetic resonance imaging was used to scan 33 children born EPT, at < 27 weeks of gestational age, and 26 full-term controls at 10 years of age. We studied the capability of a brain area to propagate neural information (intrinsic ignition) and its variability across time (node-metastability). This framework was computed for the dorsal attention network (DAN), frontoparietal, default-mode network (DMN), and the salience, limbic, visual, and somatosensory networks. The EPT group showed reduced intrinsic ignition in the DMN and DAN, compared with the controls, and reduced node-metastability in the DMN, DAN, and salience networks. Intrinsic ignition and node-metastability values correlated with cognitive performance at 12 years of age in both groups, but only survived in the term group after adjustment. Preterm birth disturbed the signatures of functional brain organization at rest in 3 core high-order networks: DMN, salience, and DAN. Identifying vulnerable resting-state networks after EPT birth may lead to interventions that aim to rebalance brain function.

The role of the salience network in cognitive and affective deficits

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

Perspectives before incremental trans-disciplinary cross-validation of clinical self-evaluation tools and functional MRI in psychiatry: 10 years later

Translational validity (or trans-disciplinary validity) is defined as one possible approach to achieving incremental validity by combining simultaneous clinical state-dependent measures and functional MRI data acquisition. It is designed under the assumption that the simultaneous administration of the two methods may produce a dataset with enhanced synchronization and concordance. Translational validation aims at "bridging" the explanatory gap by implementing validated psychometric tools clinically in the experimental settings of fMRI and then translating them back to clinical utility. Our studies may have identified common diagnostic task-specific denominators in terms of activations and network modulation. However, those common denominators need further investigation to determine whether they signify disease or syndrome-specific features (signatures), which, at the end of the day, raises one more question about the poverty of current conventional psychiatric classification criteria. We propose herewith a novel algorithm for translational validation based on our explorative findings. The algorithm itself includes pre-selection of a test based on its psychometric characteristics, adaptation to the functional MRI paradigm, exploration of the underpinning whole brain neural correlates in healthy controls as compared to a patient population with certain diagnoses, and finally, investigation of the differences between two or more diagnostic classes.