Flexible adjustment of the effective connectivity between the fronto-parietal and visual regions supports cognitive flexibility

Add, subtract and multiply: Meta-analyses of brain correlates of arithmetic operations in children and adults

Mathematical operations are cognitive actions we take to calculate relations among numbers. Arithmetic operations, addition, subtraction, multiplication, and division are elemental in education. Addition is the first one taught in school and is most popular in functional magnetic resonance imaging (fMRI) studies. Division, typically taught last is least studied with fMRI. fMRI meta-analyses show that arithmetic operations activate brain areas in parietal, cingulate and insular cortices for children and adults. Critically, no meta-analysis examines concordance across brain correlates of separate arithmetic operations in children and adults. We review and examine using quantitative meta-analyses data from fMRI articles that report brain coordinates separately for addition, subtraction, multiplication, and division in children and adults. Results show that arithmetic operations elicit common areas of concordance in fronto-parietal and cingulo-opercular networks in adults and children. Between operations differences are observed primarily for adults. Interestingly, higher within-group concordance, expressed in activation likelihood estimates, is found in brain areas associated with the cingulo-opercular network rather than the fronto-parietal network in children, areas also common between adults and children. Findings are discussed in relation to constructivist cognitive theory and practical directions for future research.

Cognitive flexibility moderates the relationship between openness-to-experience and perceptual reversals of Necker cube

It is not clear whether personality is related to basic perceptual processes at the level of automatic bottom-up processes or controlled top-down processes. Two experiments examined how personality influences perceptual dynamics, focusing on how cognitive flexibility moderates the relationship between personality and perceptual reversals of the Necker cube. The participants viewed stimuli either passively or with the intent to either hold or switch the orientation of the Necker cube. The influence of openness was predominantly evident in conditions necessitating intentional control over perceptual reversals. The link between openness and intentional perceptual reversals was always moderated by cognitive flexibility, which was measured in three different ways. No relationship was detected between personality traits and reversals in the passive viewing condition, suggesting that relatively spontaneous adaptation-inhibition processes may not be personality-dependent. Overall, our research sheds light on the nuanced influence of personality traits on perceptual experiences, mediated by cognitive flexibility.

How the intrinsic functional connectivity patterns of the semantic network support semantic processing

Semantic processing, a core of language comprehension, involves the activation of brain regions dispersed extensively across the frontal, temporal, and parietal cortices that compose the semantic network. To comprehend the functional structure of this semantic network and how it prepares for semantic processing, we investigated its intrinsic functional connectivity (FC) and the relation between this pattern and semantic processing ability in a large sample from the Human Connectome Project (HCP) dataset. We first defined a well-studied brain network for semantic processing, and then we characterized the within-network connectivity (WNC) and the between-network connectivity (BNC) within this network using a voxel-based global brain connectivity (GBC) method based on resting-state functional magnetic resonance imaging (fMRI). The results showed that 97.73% of the voxels in the semantic network displayed considerably greater WNC than BNC, demonstrating that the semantic network is a fairly encapsulated network. Moreover, multiple connector hubs in the semantic network were identified after applying the criterion of WNC > 1 SD above the mean WNC of the semantic network. More importantly, three of these connector hubs (i.e., the left anterior temporal lobe, angular gyrus, and orbital part of the inferior frontal gyrus) were reliably associated with semantic processing ability. Our findings suggest that the three identified regions use WNC as the central mechanism for supporting semantic processing and that task-independent spontaneous connectivity in the semantic network is essential for semantic processing.

Deep learning with explainability for characterizing age-related intrinsic differences in dynamic brain functional connectivity

Although many deep learning models-based medical applications are performance-driven, i.e., accuracy-oriented, their explainability is more critical. This is especially the case with neuroimaging, where we are often interested in identifying biomarkers underlying brain development or disorders. Herein we propose an explainable deep learning approach by elucidating the information transmission mechanism between two layers of a deep network with a joint feature selection strategy that considers several shallow-layer explainable machine learning models and sparse learning of the deep network. At the end, we apply and validate the proposed approach to the analysis of dynamic brain functional connectivity (FC) from fMRI in a brain development study. Our approach can identify the differences within and between functional brain networks over age during development. The results indicate that the brain network transits from undifferentiated structures to more specialized and organized ones, and the information processing ability becomes more efficient as age increases. In addition, we detect two developmental patterns in the brain network: the FCs in regions related to visual and sound processing and mental regulation become weakened, while those between regions corresponding to emotional processing and cognitive activities are enhanced.

Planning ahead: Predictable switching recruits task-active and resting-state networks

Switching is a difficult cognitive process characterised by costs in task performance; specifically, slowed responses and reduced accuracy. It is associated with the recruitment of a large coalition of task-positive regions including those referred to as the multiple demand cortex (MDC). The neural correlates of switching not only include the MDC, but occasionally the default mode network (DMN), a characteristically task-negative network. To unpick the role of the DMN during switching we collected fMRI data from 24 participants playing a switching paradigm that perturbed predictability (i.e., cognitive load) across three switch dimensions-sequential, perceptual, and spatial predictability. We computed the activity maps unique to switch vs. stay trials and all switch dimensions, then evaluated functional connectivity under these switch conditions by computing the pairwise mutual information functional connectivity (miFC) between regional timeseries. Switch trials exhibited an expected cost in reaction time while sequential predictability produced a significant benefit to task accuracy. Our results showed that switch trials recruited a broader activity map than stay trials, including regions of the DMN, the MDC, and task-positive networks such as visual, somatomotor, dorsal, salience/ventral attention networks. More sequentially predictable trials recruited increased activity in the somatomotor and salience/ventral attention networks. Notably, changes in sequential and perceptual predictability, but not spatial predictability, had significant effects on miFC. Increases in perceptual predictability related to decreased miFC between control, visual, somatomotor, and DMN regions, whereas increases in sequential predictability increased miFC between regions in the same networks, as well as regions within ventral attention/ salience, dorsal attention, limbic, and temporal parietal networks. These results provide novel clues as to how DMN may contribute to executive task performance. Specifically, the improved task performance, unique activity, and increased miFC associated with increased sequential predictability suggest that the DMN may coordinate more strongly with the MDC to generate a temporal schema of upcoming task events, which may attenuate switching costs.

The right inferior frontal gyrus as pivotal node and effective regulator of the basal ganglia-thalamocortical response inhibition circuit

Background

The involvement of specific basal ganglia-thalamocortical circuits in response inhibition has been extensively mapped in animal models. However, the pivotal nodes and directed causal regulation within this inhibitory circuit in humans remains controversial.

Objective

The main aim of the present study was to determine the causal information flow and critical nodes in the basal ganglia-thalamocortical inhibitory circuits and also to examine whether these are modulated by biological factors (i.e. sex) and behavioral performance.

Methods

Here, we capitalize on the recent progress in robust and biologically plausible directed causal modeling (DCM-PEB) and a large response inhibition dataset (n = 250) acquired with concomitant functional magnetic resonance imaging to determine key nodes, their causal regulation and modulation via biological variables (sex) and inhibitory performance in the inhibitory circuit encompassing the right inferior frontal gyrus (rIFG), caudate nucleus (rCau), globus pallidum (rGP), and thalamus (rThal).

Results

The entire neural circuit exhibited high intrinsic connectivity and response inhibition critically increased causal projections from the rIFG to both rCau and rThal. Direct comparison further demonstrated that response inhibition induced an increasing rIFG inflow and increased the causal regulation of this region over the rCau and rThal. In addition, sex and performance influenced the functional architecture of the regulatory circuits such that women displayed increased rThal self-inhibition and decreased rThal to GP modulation, while better inhibitory performance was associated with stronger rThal to rIFG communication. Furthermore, control analyses did not reveal a similar key communication in a left lateralized model.

Conclusions

Together, these findings indicate a pivotal role of the rIFG as input and causal regulator of subcortical response inhibition nodes.

Prefrontal activation in response to a plantar contact task under open and closed eye conditions in patients with cerebral infarction

Objective

This study investigates the effect of a bilateral (paralyzed side, healthy side) plantar contact task on dorsolateral prefrontal activation in patients recovering from cerebral infarction under open and closed eye conditions.

Methods

We selected 10 patients with cerebral infarction, admitted to the neurorehabilitation center of Beijing Rehabilitation Hospital, affiliated with Capital Medical University, from January 2019 to July 2020, who met our established criteria. Under open-eye and closed-eye conditions, the paralyzed and healthy sides performed the plantar contact tasks separately. The dorsolateral prefrontal region was monitored simultaneously with functional near-infrared spectroscopy (fNIRS), and activation was analyzed according to the curve-type changes of oxyhemoglobin and deoxyhemoglobin changes in the dorsolateral prefrontal cortex with 560 near-infrared monitoring channels.

Results

After stratifying the data based on the eyes-open and eyes-closed conditions, some degree of heterogeneity was observed between the layers. Under the eyes-closed condition, the Pearson χ2 was 0.142, with a p value of 0.706, indicating no significant impact of the eyes-closed condition on the activation of the dorsolateral prefrontal cortex during the plantar task, whether performed on the paralyzed or the healthy side.In contrast, the Pearson χ2 value was 15.15 for the eyes-open condition, with a p value of 0.002. This suggests that carrying out the plantar task, either on the paralyzed or the healthy side, with eyes open significantly influenced the activation of the dorsolateral prefrontal cortex. Furthermore, activation of the dorsolateral prefrontal cortex was 1.55 times higher when the task was executed with the paralyzed side compared to the healthy side. This implies that the paralyzed side was more likely to activate the dorsolateral prefrontal lobe when performing the plantar contact task under eyes-open conditions.

Conclusion

Observations via fNIRS revealed that the plantar contact task elicited dorsolateral prefrontal cortex activation. Moreover, the activation effect was intensified when performed on the paralyzed side under eyes-open conditions. Therapeutic methods that leverage these findings-namely cognitive-motor therapies that promote the recovery of motor functions by activating cognitive control brain regions via perception (information construction)-may hold promise.

Control dilemma: Evidence of the stability-flexibility trade-off

Cognitive control can be applied flexibly when task goals or environments change (i.e., cognitive flexibility), or stably to pursue a goal in the face of distraction (i.e., cognitive stability). Whether these seemingly contradictory characteristics have an inverse relationship has been controversial, as some studies have suggested a trade-off mechanism between cognitive flexibility and cognitive stability, while others have not found such reciprocal associations. This study investigated the possible antagonistic correlation between cognitive flexibility and stability using a novel version of the flexibility-stability paradigm and the classic cued task switching paradigm. In Experiment 1, we showed that cognitive flexibility was inversely correlated with cognitive stability, as increased distractor proportions were associated with decreased cognitive flexibility and greater cognitive stability. Moreover, cognitive flexibility and stability were regulated by a single control system instead of two independent control mechanisms, as the model selection results indicated that the reciprocally regulated model with one integration parameter outperformed all other models, and the model parameter was inversely linked to cognitive flexibility and stability. We found similar results using the classic cued task switching paradigm in Experiment 2. Therefore, a trade-off between cognitive flexibility and stability was observed from the paradigms used in this study.

Brain connectivity modulation by Bayesian surprise in relation to control demand drives cognitive flexibility via control engagement

Human control is characterized by its flexibility and adaptability in response to the conditional probability in the environment. Previous studies have revealed that efficient conflict control could be attained by predicting and adapting to the changing control demand. However, it is unclear whether cognitive flexibility could also be gained by predicting and adapting to the changing control demand. The present study aimed to explore this issue by combining the model-based analyses of behavioral and neuroimaging data with a probabilistic cued task switching paradigm. We demonstrated that the Bayesian surprise (i.e. unsigned precision-weighted prediction error [PE]) negatively modulated the connections among stimulus processing brain regions and control regions/networks. The effect of Bayesian surprise modulation on these connections guided control engagement as reflected by the control PE effect on behavior, which in turn facilitated cognitive flexibility. These results bridge a gap in the literature by illustrating the neural and behavioral effect of control demand prediction (or PE) on cognitive flexibility and offer novel insights into the source of switch cost and the mechanism of cognitive flexibility.

An explainable autoencoder with multi-paradigm fMRI fusion for identifying differences in dynamic functional connectivity during brain development

Multi-paradigm deep learning models show great potential for dynamic functional connectivity (dFC) analysis by integrating complementary information. However, many of them cannot use information from different paradigms effectively and have poor explainability, that is, the ability to identify significant features that contribute to decision making. In this paper, we propose a multi-paradigm fusion-based explainable deep sparse autoencoder (MF-EDSAE) to address these issues. Considering explainability, the MF-EDSAE is constructed based on a deep sparse autoencoder (DSAE). For integrating information effectively, the MF-EDASE contains the nonlinear fusion layer and multi-paradigm hypergraph regularization. We apply the model to the Philadelphia Neurodevelopmental Cohort and demonstrate it achieves better performance in detecting dynamic FC (dFC) that differ significantly during brain development than the single-paradigm DSAE. The experimental results show that children have more dispersive dFC patterns than adults. The function of the brain transits from undifferentiated systems to specialized networks during brain development. Meanwhile, adults have stronger connectivities between task-related functional networks for a given task than children. As the brain develops, the patterns of the global dFC change more quickly when stimulated by a task.

The identification of interacting brain networks during robot-assisted training with multimodal stimulation

Objective.Robot-assisted rehabilitation training is an effective way to assist rehabilitation therapy. So far, various robotic devices have been developed for automatic training of central nervous system following injury. Multimodal stimulation such as visual and auditory stimulus and even virtual reality technology were usually introduced in these robotic devices to improve the effect of rehabilitation training. This may need to be explained from a neurological perspective, but there are few relevant studies.Approach.In this study, ten participants performed right arm rehabilitation training tasks using an upper limb rehabilitation robotic device. The tasks were completed under four different feedback conditions including multiple combinations of visual and auditory components: auditory feedback; visual feedback; visual and auditory feedback (VAF); non-feedback. The functional near-infrared spectroscopy devices record blood oxygen signals in bilateral motor, visual and auditory areas. Using hemoglobin concentration as an indicator of cortical activation, the effective connectivity of these regions was then calculated through Granger causality.Main results.We found that overall stronger activation and effective connectivity between related brain regions were associated with VAF. When participants completed the training task without VAF, the trends in activation and connectivity were diminished.Significance.This study revealed cerebral cortex activation and interacting networks of brain regions in robot-assisted rehabilitation training with multimodal stimulation, which is expected to provide indicators for further evaluation of the effect of rehabilitation training, and promote further exploration of the interaction network in the brain during a variety of external stimuli, and to explore the best sensory combination.

Function without feeling: neural reactivity and intercommunication during flexible motor adjustments evoked by emotional and neutral stimuli

Motor conflicts arise when we need to quickly overwrite prepotent behavior. It has been proposed that affective stimuli modulate the neural processing of motor conflicts. However, previous studies have come to inconsistent conclusions regarding the neural impact of affective information on conflict processing. We employed functional magnetic resonance imaging during a Go/Change-Go task, where motor conflicts were either evoked by neutral or emotionally negative stimuli. Dynamic causal modeling was used to investigate how motor conflicts modulate the intercommunication between the anterior cingulate cortex (ACC) and the anterior insula (AI) as 2 central regions for cognitive control. Conflicts compared to standard actions were associated with increased BOLD activation in several brain areas, including the dorsal ACC and anterior insula. There were no differences in neural activity between emotional and non-emotional conflict stimuli. Conflicts compared to standard actions lowered neural self-inhibition of the ACC and AI and led to increased effective connectivity from the ACC to AI contralateral to the acting hand. Thus, our study indicates that neural conflict processing is primarily driven by the functional relevance of action-related stimuli, not their inherent affective meaning. Furthermore, it sheds light on the role of interconnectivity between ACC and AI for the implementation of flexible behavioral change.

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.

Understanding cognitive control in aging: A brain network perspective

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

The hidden community architecture of human brain networks

The organizational principles of the community architecture of human brain networks are still mostly unknown. Here, we found that brain networks have a moderate degree of community segregation but are specifically organized to achieve high community overlap while maintaining their segregated community structures. These properties are distinct from other real-world complex networks. Additionally, we found that human subjects with a higher degree of community overlap in their brain networks show greater dynamic reconfiguration and cognitive flexibility.

Reconfiguration of response rule is more difficult than that of task goal: Behavior and electrophysiological evidence

Previous studies have investigated the neural mechanisms underlying cognitive control by using the task-switching paradigm, but differentiation from response rule switching (RR-switch) remains poorly explored. In this study, a partial voluntary task-switching (VTS) paradigm was used to explore the electrophysiological differences between task switching (T-switch) and RR-switching. Participants were sequentially presented with Arabic numerals colored red or green. If the color in the current trial was the same as that in the previous trial, the participants had to perform the same task following the same response rule. Otherwise, they had to voluntarily switch tasks (e.g., from parity task to magnitude task) or switch response rules (e.g., from "pressing F for odd and J for even number' to 'pressing J for odd and F for even number"). The behavioral results indicated that RR-switch was infrequently selected, and the performance was less efficient than that of the T-switch. Event-related potential results showed that both T- and RR-switches elicited a larger switch-positivity in the P2 and P3 time windows than that in the repeat condition. Switch-positivity was larger for RR-switch than for T-switch over the frontal sites, suggesting that more attention and cognitive resources were required to update information for the RR-switch than for the T-switch. These findings suggest that in the VTS, the hierarchical relationship between task goals and response rules is relatively loose, resulting in the neural disassociation of task reconfiguration and response change.

Genetic Architecture Underlying Differential Resting-state Functional Connectivity of Subregions Within the Human Visual Cortex

The human visual cortex is a heterogeneous entity that has multiple subregions showing substantial variability in their functions and connections. We aimed to identify genes associated with resting-state functional connectivity (rsFC) of visual subregions using transcriptome-neuroimaging spatial correlations in discovery and validation datasets. Results showed that rsFC of eight visual subregions were associated with expression measures of eight gene sets, which were specifically expressed in brain tissue and showed the strongest correlations with visual behavioral processes. Moreover, there was a significant divergence in these gene sets and their functional features between medial and lateral visual subregions. Relative to those associated with lateral subregions, more genes associated with medial subregions were found to be enriched for neuropsychiatric diseases and more diverse biological functions and pathways, and to be specifically expressed in multiple types of neurons and immune cells and during the middle and late stages of cortical development. In addition to shared behavioral processes, lateral subregion associated genes were uniquely correlated with high-order cognition. These findings of commonalities and differences in the identified rsFC-related genes and their functional features across visual subregions may improve our understanding of the functional heterogeneity of the visual cortex from the perspective of underlying genetic architecture.

Effects of food stimuli on event-related potentials of restrained eating subgroups during task switching

Executive functions are thought to affect problematic eating behaviors in restrained eaters. While neurophysiological features of inhibitory control among restrained eaters in particular have been extensively investigated, considerably less is known about its influence on cognitive flexibility. The present study investigated the behavioral and neural correlates of food-related cognitive flexibility with event-related potentials (ERPs) associated in a task-switching paradigm among successful restrained eaters (SREs, n = 30) and unsuccessful restrained eaters (UREs, n = 32). Behavioral results revealed smaller switch reaction times among SREs than among UREs in both food-stimuli and neutral-stimuli tasks. ERP analyses indicated that neutral-switch trials, especially in UREs, displayed larger N2 amplitudes. In addition, SREs displayed larger P3 amplitudes in frontal, frontal-central, and central than UREs. P3 amplitude increased significantly during food-stimuli tasks compared to that during neutral-stimuli tasks. These results indicate that SREs possess better efficiency in enhanced cognitive transformation during the processing of target monitoring and conflict resolution. This is the first study to provide evidence for differences between SREs and UREs during task switching using ERP measures and reliance on different food-related processing strategies among SREs compared to UREs.

Altered patterns of brain dynamics linked with body mass index in youth with autism

Children with autism spectrum disorder (ASD) have higher rates of overweight and obesity (OWOB) compared with typically developing (TD) children. Brain functional connectivity differences have been shown in both ASD and OWOB. However, only one study to date has examined ASD and OWOB concurrently, so little is known regarding the neural mechanisms associated with the higher prevalence of OWOB and its behavioral impacts in ASD. We investigated co-activation patterns (CAPs) of brain regions identified by independent component analysis in 129 children and adolescents between 6 and 18 years of age (n = 68 ASD). We examined the interaction between body mass index (BMI) and diagnosis in predicting dynamic brain metrics (dwell time, DT; frequency of occurrence, and transitions between states) as well as dimensional brain-behavior relationships. The relationship between BMI and brain dynamics was moderated by diagnosis (ASD, TD), particularly among the frequency of CAP 4, characterized by co-activation of lateral frontoparietal, temporal, and frontal networks. This pattern was negatively associated with parent-reported inhibition skills. Children with ASD had shorter CAP 1, characterized by co-activation of the subcortical, temporal, sensorimotor, and frontal networks, and CAP 4 DTs compared with TD children. CAP 1 DT was negatively associated with cognitive flexibility, inhibition, social functioning, and BMI. Cognitive flexibility moderated the relationship between BMI and brain dynamics in the visual network. Our findings provide novel evidence of neural mechanisms associated with OWOB in children with ASD. Further, poorer cognitive flexibility may result in increased vulnerability for children with ASD and co-occurring OWOB. LAY SUMMARY: Obesity is a societal epidemic and is common in autism, however, little is known about the neural mechanisms associated with the higher rates of obesity in autism. Here, we find unique patterns of brain dynamics associated with obesity in autism that were not observed in typically developing children. Further, the relationship between body mass index and brain dynamics depended on cognitive flexibility. These findings suggest that individuals with autism may be more vulnerable to the effects of obesity on brain function. Autism Res 2021, 14: 873-886. © 2021 International Society for Autism Research, Wiley Periodicals LLC.