The modulation of brain network integration and arousal during exploration

Local effective connectivity changes after transcranial direct current stimulation in obsessive-compulsive disorder patients

AIM

This study investigates the effects of transcranial direct current stimulation (tDCS) on brain network connectivity in individuals with obsessive-compulsive disorder (OCD).

METHODS

In a randomized, double-blind, sham-controlled experimental design anodal tDCS (vs. sham) was applied in a total of 43 right-handed patients with OCD, targeting the right pre-supplementary motor area (pre-SMA). Cathodal reference electrode was put on the left pre-SMA. The current was set as 2 mA, with a stimulation duration of either 30 s (sham) or 1200 s. Concurrent resting-state functional MRI data were collected following tDCS (or sham) stimulation. We employed regression dynamic causal modelling (rDCM) to extract whole brain effective connectivity (EC) matrices subsequently analyzing these matrices through graph theory approaches to examine changes in brain activity across different network scales.

RESULTS

We found that tDCS compared to sham caused significant changes in local effective connectivity. Increased recruitment level was detectable in the sensorimotor network (SMN), indicating enhanced intra-network connectivity after active tDCS. Clustering coefficient and local efficiency were also found to be increased in the same area. No significant changes were detectable with regard to global network connectivity.

CONCLUSIONS

Current findings indicate that single-session tDCS can effectively alter local effective connectivities within the SMN in OCD patients. Given the relevance of the SMN and connected regions for the pathophysiology of OCD we believe that tDCS targeting these areas might constitute an effective intervention to normalize altered network connectivity in the disorder of OCD.

LIMITATION

We used a single tDCS session, which may not reflect long-term effects.

Meta-Analysis Reveals That Explore-Exploit Decisions are Dissociable by Activation in the Dorsal Lateral Prefrontal Cortex, Anterior Insula, and the Dorsal Anterior Cingulate Cortex

Explore-exploit research faces challenges in generalizability due to a limited theoretical basis for exploration and exploitation. Neuroimaging can help identify whether explore-exploit decisions involve an opponent processing system to address this issue. Thus, we conducted a coordinate-based meta-analysis (N=23 studies) finding activation in the dorsal lateral prefrontal cortex, anterior insula, and anterior cingulate cortex during exploration versus exploitation, which provides some evidence for opponent processing. However, the conjunction of explore-exploit decisions was associated with activation in the dorsal anterior cingulate cortex and dorsal medial prefrontal cortex, suggesting that these brain regions do not engage in opponent processing. Furthermore, exploratory analyses revealed heterogeneity in brain responses between task types during exploration and exploitation respectively. Coupled with results suggesting that activation during exploration and exploitation decisions is generally more similar than it is different suggests that there remain significant challenges in characterizing explore-exploit decision making. Nonetheless, dorsal lateral prefrontal cortex, anterior insula, and dorsal anterior cingulate cortex activation differentiate explore and exploit decisions and identifying these responses can aid in targeted interventions aimed at manipulating these decisions.

Meta-Analysis Reveals That Explore-Exploit Decisions Are Dissociable by Activation in the Dorsal Lateral Prefrontal Cortex, Anterior Insula, and Dorsal Anterior Cingulate Cortex

Explore-exploit research faces challenges in generalizability due to a limited theoretical basis for exploration and exploitation. Neuroimaging can help identify whether explore-exploit decisions involve an opponent processing system to address this issue. Thus, we conducted a coordinate-based meta-analysis (N = 23 studies) finding activation in the dorsal lateral prefrontal cortex, anterior insula, and dorsal anterior cingulate cortex during exploration versus exploitation, which provides some evidence for opponent processing. However, the conjunction of explore-exploit decisions was associated with activation in the anterior cingulate cortex and dorsal medial prefrontal cortex, suggesting that these brain regions do not engage in opponent processing. Furthermore, exploratory analyses revealed heterogeneity in brain responses between task types during exploration and exploitation respectively. Coupled with results suggesting that activation during exploration and exploitation decisions is generally more similar than it is different suggests that there remain significant challenges in characterizing explore-exploit decision-making. Nonetheless, dorsal lateral prefrontal cortex, anterior insula, and dorsal anterior cingulate cortex activation differentiate explore and exploit decisions, and identifying these responses can aid in targeted interventions aimed at manipulating these decisions.

Neural Dynamics During the Generation and Evaluation of Creative and Non-Creative Ideas

What are the neural dynamics that drive creative thinking? Recent studies have provided much insight into the neural mechanisms of creative thought. Specifically, the interaction between the executive control, default mode, and salience brain networks has been shown to be an important marker of individual differences in creative ability. However, how these different brain systems might be recruited dynamically during the two key components of the creative process-generation and evaluation of ideas-remains far from understood. In the current study we applied state-of-the-art network neuroscience methodologies to examine the neural dynamics related to the generation and evaluation of creative and non-creative ideas using a novel within-subjects design. Participants completed two functional magnetic resonance imaging sessions, taking place a week apart. In the first imaging session, participants generated either creative (alternative uses) or non-creative (common characteristics) responses to common objects. In the second imaging session, participants evaluated their own creative and non-creative responses to the same objects. Network neuroscience methods were applied to examine and directly compare reconfiguration, integration, and recruitment of brain networks during these four conditions. We found that generating creative ideas led to significantly higher network reconfiguration than generating non-creative ideas, whereas evaluating creative and non-creative ideas led to similar levels of network integration. Furthermore, we found that these differences were attributable to different dynamic patterns of neural activity across the executive control, default mode, and salience networks. This study is the first to show within-subject differences in neural dynamics related to generating and evaluating creative and non-creative ideas.

Pupillary response is associated with the reset and switching of functional brain networks during salience processing

The interface between processing internal goals and salient events in the environment involves various top-down processes. Previous studies have identified multiple brain areas for salience processing, including the salience network (SN), dorsal attention network, and the locus coeruleus-norepinephrine (LC-NE) system. However, interactions among these systems in salience processing remain unclear. Here, we simultaneously recorded pupillometry, EEG, and fMRI during an auditory oddball paradigm. The analyses of EEG and fMRI data uncovered spatiotemporally organized target-associated neural correlates. By modeling the target-modulated effective connectivity, we found that the target-evoked pupillary response is associated with the network directional couplings from late to early subsystems in the trial, as well as the network switching initiated by the SN. These findings indicate that the SN might cooperate with the pupil-indexed LC-NE system in the reset and switching of cortical networks, and shed light on their implications in various cognitive processes and neurological diseases.

Dynamic Functional Connectivity of Emotion Processing in Beta Band with Naturalistic Emotion Stimuli

While naturalistic stimuli, such as movies, better represent the complexity of the real world and are perhaps crucial to understanding the dynamics of emotion processing, there is limited research on emotions with naturalistic stimuli. There is a need to understand the temporal dynamics of emotion processing and their relationship to different dimensions of emotion experience. In addition, there is a need to understand the dynamics of functional connectivity underlying different emotional experiences that occur during or prior to such experiences. To address these questions, we recorded the EEG of participants and asked them to mark the temporal location of their emotional experience as they watched a video. We also obtained self-assessment ratings for emotional multimedia stimuli. We calculated dynamic functional the connectivity (DFC) patterns in all the frequency bands, including information about hubs in the network. The change in functional networks was quantified in terms of temporal variability, which was then used in regression analysis to evaluate whether temporal variability in DFC (tvDFC) could predict different dimensions of emotional experience. We observed that the connectivity patterns in the upper beta band could differentiate emotion categories better during or prior to the reported emotional experience. The temporal variability in functional connectivity dynamics is primarily related to emotional arousal followed by dominance. The hubs in the functional networks were found across the right frontal and bilateral parietal lobes, which have been reported to facilitate affect, interoception, action, and memory-related processing. Since our study was performed with naturalistic real-life resembling emotional videos, the study contributes significantly to understanding the dynamics of emotion processing. The results support constructivist theories of emotional experience and show that changes in dynamic functional connectivity can predict aspects of our emotional experience.

Diurnal variations of resting-state fMRI data: A graph-based analysis

Circadian rhythms (lasting approximately 24 h) control and entrain various physiological processes, ranging from neural activity and hormone secretion to sleep cycles and eating habits. Several studies have shown that time of day (TOD) is associated with human cognition and brain functions. In this study, utilizing a chronotype-based paradigm, we applied a graph theory approach on resting-state functional MRI (rs-fMRI) data to compare whole-brain functional network topology between morning and evening sessions and between morning-type (MT) and evening-type (ET) participants. Sixty-two individuals (31 MT and 31 ET) underwent two fMRI sessions, approximately 1 hour (morning) and 10 h (evening) after their wake-up time, according to their declared habitual sleep-wake pattern on a regular working day. In the global analysis, the findings revealed the effect of TOD on functional connectivity (FC) patterns, including increased small-worldness, assortativity, and synchronization across the day. However, we identified no significant differences based on chronotype categories. The study of the modular structure of the brain at mesoscale showed that functional networks tended to be more integrated with one another in the evening session than in the morning session. Local/regional changes were affected by both factors (i.e., TOD and chronotype), mostly in areas associated with somatomotor, attention, frontoparietal, and default networks. Furthermore, connectivity and hub analyses revealed that the somatomotor, ventral attention, and visual networks covered the most highly connected areas in the morning and evening sessions: the latter two were more active in the morning sessions, and the first was identified as being more active in the evening. Finally, we performed a correlation analysis to determine whether global and nodal measures were associated with subjective assessments across participants. Collectively, these findings contribute to an increased understanding of diurnal fluctuations in resting brain activity and highlight the role of TOD in future studies on brain function and the design of fMRI experiments.

Probabilistically Weighted Multilayer Networks disclose the link between default mode network instability and psychosis-like experiences in healthy adults

The brain is a complex system in which the functional interactions among its subunits vary over time. The trajectories of this dynamic variation contribute to inter-individual behavioral differences and psychopathologic phenotypes. Despite many methodological advancements, the study of dynamic brain networks still relies on biased assumptions in the temporal domain. The current paper has two goals. First, we present a novel method to study multilayer networks: by modelling intra-nodal connections in a probabilistic, biologically driven way, we introduce a temporal resolution of the multilayer network based on signal similarity across time series. This new method is tested on synthetic networks by varying the number of modules and the sources of noise in the simulation. Secondly, we implement these probabilistically weighted (PW) multilayer networks to study the association between network dynamics and subclinical, psychosis-relevant personality traits in healthy adults. We show that the PW method for multilayer networks outperforms the standard procedure in modular detection and is less affected by increasing noise levels. Additionally, the PW method highlighted associations between the temporal instability of default mode network connections and psychosis-like experiences in healthy adults. PW multilayer networks allow an unbiased study of dynamic brain functioning and its behavioral correlates.

Flexible brain transitions between hierarchical network segregation and integration associated with cognitive performance during a multisource interference task

Cognition involves locally segregated and globally integrated processing. This process is hierarchically organized and linked to evidence from hierarchical modules in brain networks. However, researchers have not clearly determined how flexible transitions between these hierarchical processes are associated with cognitive behavior. Here, we designed a multisource interference task (MSIT) and introduced the nested-spectral partition (NSP) method to detect hierarchical modules in brain functional networks. By defining hierarchical segregation and integration across multiple levels, we showed that the MSIT requires higher network segregation in the whole brain and most functional systems but generates higher integration in the control system. Meanwhile, brain networks have more flexible transitions between segregated and integrated configurations in the task state. Crucially, higher functional flexibility in the resting state, less flexibility in the task state and more efficient switching of the brain from resting to task states were associated with better task performance. Our hierarchical modular analysis was more effective at detecting alterations in functional organization and the phenotype of cognitive performance than graph-based network measures at a single level.