Cognitive ability is associated with changes in the functional organization of the cognitive control brain network

The effect of physical exercise on cognitive function in schizophrenia patients: A GRADE assessed systematic review and meta-analysis of controlled clinical trials

BACKGROUND

Physical exercise has demonstrated the potential to improve cognitive impairment in schizophrenia, although the results are limited. The objective of this meta-analysis is to synthesize the existing evidence on the impact of physical exercise on cognitive functions in schizophrenia.

METHODS

A systematic search of PubMed, Scopus, Web of Science, and Embase was conducted. The study included controlled clinical trials on patients with schizophrenia that received physical exercise as the intervention for improving cognition. A meta-analysis was conducted using a random-effects model, and the outcomes were reported using the standardized mean difference (SMD) and a 95 % confidence interval (95 % CI).

RESULTS

A total of 22 articles, including 1066 patients (565 in the intervention group and 501 in the control group), were included in the final analysis. Physical exercises significantly improved global cognition (SMD: 0.73, 95 % CI (0.46-1.00), P < 0.001), and aerobic exercise was found to have a more significant effect than resistance and mindfulness exercise (SMD: 0.76, 95 % CI (0.45-1.07), P < 0.001). The speed of processing [SMD: 0.88, 95 % CI (0.37-1.38), P = 0.001], attention [SMD: 0.61, 95 % CI (0.20-1.02), P = 0.004], and visual learning memory [SMD: 1.42, 95 % CI (0.14-2.71), P = 0.03] demonstrated significant improvement after physical exercise, while no significant effects were observed on working memory, verbal learning memory, reasoning and problem-solving, and social cognition.

CONCLUSIONS

Exercise can improve overall cognitive function in people with Schizophrenia. However, it is unclear whether this improvement is significant in specific cognitive domains.

The developmental trajectory of 1H-MRS brain metabolites from childhood to adulthood

Human brain development is ongoing throughout childhood, with for example, myelination of nerve fibers and refinement of synaptic connections continuing until early adulthood. 1H-Magnetic Resonance Spectroscopy (1H-MRS) can be used to quantify the concentrations of endogenous metabolites (e.g. glutamate and γ -aminobutyric acid (GABA)) in the human brain in vivo and so can provide valuable, tractable insight into the biochemical processes that support postnatal neurodevelopment. This can feasibly provide new insight into and aid the management of neurodevelopmental disorders by providing chemical markers of atypical development. This study aims to characterize the normative developmental trajectory of various brain metabolites, as measured by 1H-MRS from a midline posterior parietal voxel. We find significant non-linear trajectories for GABA+ (GABA plus macromolecules), Glx (glutamate + glutamine), total choline (tCho) and total creatine (tCr) concentrations. Glx and GABA+ concentrations steeply decrease across childhood, with more stable trajectories across early adulthood. tCr and tCho concentrations increase from childhood to early adulthood. Total N-acetyl aspartate (tNAA) and Myo-Inositol (mI) concentrations are relatively stable across development. Trajectories likely reflect fundamental neurodevelopmental processes (including local circuit refinement) which occur from childhood to early adulthood and can be associated with cognitive development; we find GABA+ concentrations significantly positively correlate with recognition memory scores.

The restoration ability of a short nap after sleep deprivation on the brain cognitive function: A dynamic functional connectivity analysis

AIMS

The brain function impairment induced by sleep deprivation (SD) is temporary and can be fully reversed with sufficient sleep. However, in many cases, long-duration recovery sleep is not feasible. Thus, this study aimed to investigate whether a short nap after SD is sufficient to restore brain function.

METHODS

The data of 38 subjects, including resting state functional magnetic resonance imaging data collected at three timepoints (before SD, after 30 h of SD, and after a short nap following SD) and psychomotor vigilance task (PVT) data, were collected. Dynamic functional connectivity (DFC) analysis was used to evaluate changes in brain states among three timepoints, and four DFC states were distinguished across the three timepoints.

RESULTS

Before SD, state 2 (a resting-like FC matrix) was dominant (48.26%). However, after 30 h SD, the proportion of state 2 dramatically decreased, and state 3 (still resting-like, but FCs were weakened) became dominant (40.92%). The increased proportion of state 3 positively correlated with a larger PVT "lapse" time. After a nap, the proportions of states 2 and 3 significantly increased and decreased, respectively, and the change in proportion of state 2 negatively correlated with the change in PVT "lapse" time.

CONCLUSIONS

Taken together, the results indicated that, after a nap, the cognitive function impairment caused by SD may be reversed to some extent. Additionally, DFC differed among timepoints, which was also associated with the extent of cognitive function impairment after SD (state 3) and the extent of recovery therefrom after a nap (state 2).

Brain functional characterization of response-code conflict in dual-tasking and its modulation by age

Crosstalk between conflicting response codes contributes to interference in dual-tasking, an effect exacerbated in advanced age. Here, we investigated (i) brain activity correlates of such response-code conflicts, (ii) activity modulations by individual dual-task performance and related cognitive abilities, (iii) task-modulated connectivity within the task network, and (iv) age-related differences in all these aspects. Young and older adults underwent fMRI while responding to the pitch of tones through spatially mapped speeded button presses with one or two hands concurrently. Using opposing stimulus-response mappings between hands, we induced conflict between simultaneously activated response codes. These response-code conflicts elicited activation in key regions of the multiple-demand network. While thalamic and parietal areas of the conflict-related network were modulated by attentional, working-memory and task-switching abilities, efficient conflict resolution in dual-tasking mainly relied on increasing supplementary motor activity. Older adults showed non-compensatory hyperactivity in left superior frontal gyrus, and higher right premotor activity was modulated by working-memory capacity. Finally, connectivity between premotor or parietal seed regions and the conflict-sensitive network was neither conflict-specific nor age-sensitive. Overall, resolving dual-task response-code conflict recruited substantial parts of the multiple-demand network, whose activity and coupling, however, were only little affected by individual differences in task performance or age.

Methylphenidate as a treatment option for substance use disorder: a transdiagnostic perspective

A transition in viewing mental disorders from conditions defined as a set of unique characteristics to one of the quantitative variations on a collection of dimensions allows overlap between disorders. The overlap can be utilized to extend to treatment approaches. Here, we consider the overlap between attention-deficit/hyperactivity disorder and substance use disorder to probe the suitability to use methylphenidate as a treatment for substance use disorder. Both disorders are characterized by maladaptive goal-directed behavior, impaired cognitive control, hyperactive phasic dopaminergic neurotransmission in the striatum, prefrontal hypoactivation, and reduced frontal cortex gray matter volume/density. In addition, methylphenidate has been shown to improve cognitive control and normalize associated brain activation in substance use disorder patients and clinical trials have found methylphenidate to improve clinical outcomes. Despite the theoretical basis and promising, but preliminary, outcomes, many questions remain unanswered. Most prominent is whether all patients who are addicted to different substances may equally profit from methylphenidate treatment.

Negative association between anterior insula activation and resilience during sustained attention: an fMRI twin study

BACKGROUND

While previous studies have suggested that higher levels of cognitive performance may be related to greater wellbeing and resilience, little is known about the associations between neural circuits engaged by cognitive tasks and wellbeing and resilience, and whether genetics or environment contribute to these associations.

METHODS

The current study consisted of 253 monozygotic and dizygotic adult twins, including a subsample of 187 early-life trauma-exposed twins, with functional Magnetic Resonance Imaging data from the TWIN-E study. Wellbeing was measured using the COMPAS-W Wellbeing Scale while resilience was defined as a higher level of positive adaptation (higher levels of wellbeing) in the presence of trauma exposure. We probed both sustained attention and working memory processes using a Continuous Performance Task in the scanner.

RESULTS

We found significant negative associations between resilience and activation in the bilateral anterior insula engaged during sustained attention. Multivariate twin modelling showed that the association between resilience and the left and right insula activation was mostly driven by common genetic factors, accounting for 71% and 87% of the total phenotypic correlation between these variables, respectively. There were no significant associations between wellbeing/resilience and neural activity engaged during working memory updating.

CONCLUSIONS

The findings suggest that greater resilience to trauma is associated with less activation of the anterior insula during a condition requiring sustained attention but not working memory updating. This possibly suggests a pattern of 'neural efficiency' (i.e. more efficient and/or attenuated activity) in people who may be more resilient to trauma.

Using Nonhuman Primate Models to Reverse-Engineer Prefrontal Circuit Failure Underlying Cognitive Deficits in Schizophrenia

In this chapter, I review studies in nonhuman primates that emulate the circuit failure in prefrontal cortex responsible for working memory and cognitive control deficits in schizophrenia. These studies have characterized how synaptic malfunction, typically induced by blockade of NMDAR, disrupts neural function and computation in prefrontal networks to explain errors in cognitive tasks that are seen in schizophrenia. This work is finding causal relationships between pathogenic events of relevance to schizophrenia at vastly different levels of scale, from synapses, to neurons, local, circuits, distributed networks, computation, and behavior. Pharmacological manipulation, the dominant approach in primate models, has limited construct validity for schizophrenia pathogenesis, as the disease results from a complex interplay between environmental, developmental, and genetic factors. Genetic manipulation replicating schizophrenia risk is more advanced in rodent models. Nonetheless, gene manipulation in nonhuman primates is rapidly advancing, and primate developmental models have been established. Integration of large scale neural recording, genetic manipulation, and computational modeling in nonhuman primates holds considerable potential to provide a crucial schizophrenia model moving forward. Data generated by this approach is likely to fill several crucial gaps in our understanding of the causal sequence leading to schizophrenia in humans. This causal chain presents a vexing problem largely because it requires understanding how events at very different levels of scale relate to one another, from genes to circuits to cognition to social interactions. Nonhuman primate models excel here. They optimally enable discovery of causal relationships across levels of scale in the brain that are relevant to cognitive deficits in schizophrenia. The mechanistic understanding of prefrontal circuit failure they promise to provide may point the way to more effective therapeutic interventions to restore function to prefrontal networks in the disease.

Employing Connectome-Based Models to Predict Working Memory in Multiple Sclerosis

Introduction: Individuals with multiple sclerosis (MS) are vulnerable to deficits in working memory (WM), but the search for neural correlates of WM within circumscribed areas has been inconclusive. Given the widespread neural alterations observed in MS, predictive modeling approaches that capitalize on whole-brain connectivity may better capture individual differences in WM. Materials and Methods: We applied connectome-based predictive modeling to functional magnetic resonance imaging data from WM tasks in two independent samples with relapsing-remitting MS. In the internal sample (n_internal = 36), cross-validation was used to train a model to predict accuracy on the Paced Visual Serial Addition Test from functional connectivity. We hypothesized that this MS-specific model would successfully predict performance on the N-back task in the validation cohort (n_validation = 36). In addition, we assessed the generalizability of existing WM networks derived in healthy young adults to these samples, and we explored anatomical differences between the healthy and MS networks. Results: We successfully derived an MS-specific predictive model of WM in the internal sample (full: r_s = 0.47, permuted p = 0.011), but the predictions were not significant in the validation cohort (r_s = -0.047; p = 0.78, mean squared error [MSE] = 0.006, R² = -2.21%). In contrast, the healthy networks successfully predicted WM in both MS samples (internal: r_s = 0.33 p = 0.049, MSE = 0.009, R² = 13.4%; validation cohort: r_s = 0.46, p = 0.005, MSE = 0.005, R² = 16.9%), demonstrating their translational potential. Discussion: Functional networks identified in a large sample of healthy individuals predicted significant variance in WM in MS. Networks derived in small samples of people with MS may have limited generalizability, potentially due to disease-related heterogeneity. The robustness of models derived in large clinical samples warrants further investigation. ClinicalTrials.gov ID: NCT03244696.

Influence of Cerebral Glucose Metabolism by Chronic Pain-Mediated Cognitive Impairment in Adolescent Rats

Chronic pain during adolescence can lead to mental health disorders in adulthood, but the underlying mechanism is still unclear. Furthermore, the homeostasis of cerebral glucose metabolism and neurotransmitter metabolic kinetics are closely associated with cognitive development and pain progression. The present study investigated changes in cognitive function and glucose metabolism in adult rats, which had experienced chronic pain during their adolescence. Here, spared nerve injury (SNI) surgery was conducted in 4-week-old male rats. Mechanical nociceptive reflex thresholds were analyzed, and SNI chronic pain (SNI-CP) animals were screened. Based on animal behavioral tests (open field, three-chambered social, novel object recognition and the Y maze), the SNI-CP animals showed learning and memory impairment and anxiety-like behaviors, compared to SNI no chronic pain (SNI-NCP) animals. The cerebral glucose metabolism in the prefrontal cortex and hippocampus of adult SNI-CP animals was decreased with positron emission tomography/computed tomography. GABA₂ and Glu₄ levels in the metabolic kinetics study were significantly decreased in the hippocampus, frontal cortex, and temporal cortex, and the expression of GLUT3 and GLUT4 was also significantly downregulated in the prefrontal cortex and hippocampus of adult rats in the SNI-CP group. These findings suggest that the rats which suffered chronic pain during adolescence have lower cerebral glucose metabolism in the cortex and hippocampus, which could be related to cognitive function during the development of the central nervous system.

Local Prefrontal Cortex TMS-Induced Reactivity Is Related to Working Memory and Reasoning in Middle-Aged Adults

Introduction

The prefrontal cortex (PFC) plays a crucial role in cognition, particularly in executive functions. Cortical reactivity measured with Transcranial Magnetic Stimulation combined with Electroencephalography (TMS-EEG) is altered in pathological conditions, and it may also be a marker of cognitive status in middle-aged adults. In this study, we investigated the associations between cognitive measures and TMS evoked EEG reactivity and explored whether the effects of this relationship were related to neurofilament light chain levels (NfL), a marker of neuroaxonal damage.

Methods

Fifty two healthy middle-aged adults (41–65 years) from the Barcelona Brain Health Initiative cohort underwent TMS-EEG, a comprehensive neuropsychological assessment, and a blood test for NfL levels. Global and Local Mean-Field Power (GMFP/LMFP), two measures of cortical reactivity, were quantified after left prefrontal cortex (L-PFC) stimulation, and cognition was set as the outcome of the regression analysis. The left inferior parietal lobe (L-IPL) was used as a control stimulation condition.

Results

Local reactivity was significantly associated with working memory and reasoning only after L-PFC stimulation. No associations were found between NfL and cognition. These specific associations were independent of the status of neuroaxonal damage indexed by the NfL biomarker and remained after adjusting for age, biological sex, and education.

Conclusion

Our results demonstrate that TMS evoked EEG reactivity at the L-PFC, but not the L-IPL, is related to the cognitive status of middle-aged individuals and independent of NfL levels, and may become a valuable biomarker of frontal lobe-associated cognitive function.

Computer Programming E-Learners' Personality Traits, Self-Reported Cognitive Abilities, and Learning Motivating Factors

Educational systems around the world encourage students to engage in programming activities, but programming learning is one of the most challenging learning tasks. Thus, it was significant to explore the factors related to programming learning. This study aimed to identify computer programming e-learners’ personality traits, self-reported cognitive abilities and learning motivating factors in comparison with other e-learners. We applied a learning motivating factors questionnaire, the Big Five Inventory—2, and the SRMCA instruments. The sample consisted of 444 e-learners, including 189 computer programming e-learners, the mean age was 25.19 years. It was found that computer programming e-learners demonstrated significantly lower scores of extraversion, and significantly lower scores of motivating factors of individual attitude and expectation, reward and recognition, and punishment. No significant differences were found in the scores of self-reported cognitive abilities between the groups. In the group of computer programming e-learners, extraversion was a significant predictor of individual attitude and expectation; conscientiousness and extraversion were significant predictors of challenging goals; extraversion and agreeableness were significant predictors of clear direction; open-mindedness was a significant predictor of a diminished motivating factor of punishment; negative emotionality was a significant predictor of social pressure and competition; comprehension-knowledge was a significant predictor of individual attitude and expectation; fluid reasoning and comprehension-knowledge were significant predictors of challenging goals; comprehension-knowledge was a significant predictor of clear direction; and visual processing was a significant predictor of social pressure and competition. The SEM analysis demonstrated that personality traits (namely, extraversion, conscientiousness, and reverted negative emotionality) statistically significantly predict learning motivating factors (namely, individual attitude and expectation, and clear direction), but the impact of self-reported cognitive abilities in the model was negligible in both groups of participants and non-participants of e-learning based computer programming courses; χ² (34) = 51.992, p = 0.025; CFI = 0.982; TLI = 0.970; NFI = 0.950; RMSEA = 0.051 [0.019–0.078]; SRMR = 0.038. However, as this study applied self-reported measures, we strongly suggest applying neurocognitive methods in future research.

Neural activity during response inhibition in mild traumatic brain injury and posttraumatic stress disorder

Mild traumatic brain injury (mTBI) is often characterized by deficits in response inhibition, which can contribute to marked social and occupational dysfunction. mTBI often occurs in the context of psychologically traumatic events. This can cause posttraumatic stress disorder (PTSD), which also impedes response inhibition. The overlap or distinction in these inhibitory deficits in mTBI and PTSD is unclear. This study aimed to assess behavioral, neurophysiological, and neuroimaging indices of response inhibition in mTBI by also assessing these parameters in healthy controls (HC) and PTSD participants. Participants with mTBI (without PTSD) (n = 46), PTSD (without mTBI) (n = 41), and HC (n = 40) were assessed during a response inhibition task (the Go/NoGo task) during neuropsychological testing and separate functional magnetic imaging and event-related potentials sessions. PTSD symptom severity was assessed with the Clinician-Administered PTSD Scale. Both mTBI and PTSD participants performed more omission errors on the Go/NoGo task and were associated with greater N2 amplitude, greater left inferior parietal activation and reduced connectivity of the left inferior parietal cluster and left angular gyrus compared to HC. There were no differences between mTBI and PTSD on any of these measures. These findings highlight that both mTBI and PTSD contribute to neural dysfunction during response inhibition, and arguably these occur due to distinct mechanisms. In the context of the common comorbidity between these two conditions, strategies to address response inhibition deficits in mTBI may need to consider causative factors underpinning neurological insult of mTBI and psychological effects associated with PTSD.

Neural activity during response inhibition associated with improvement of dysphoric symptoms of PTSD after trauma-focused psychotherapy-an EEG-fMRI study

Although trauma-focused cognitive behavioural therapy (TF-CBT) is the frontline treatment for posttraumatic stress disorder (PTSD), up to one half of patients do not respond optimally to this treatment. Inhibitory functions are important for successful management of PTSD, yet there is a dearth of knowledge regarding the extent to which neural mechanisms unpinning response inhibition are associated with TF-CBT response. Treatment-seeking PTSD patients (n = 40) were assessed during a response inhibition task (the Go/No-Go task) while undergoing functional magnetic imaging (fMRI) and event-related potentials (ERP) in separate sessions. PTSD symptom severity was assessed with the Clinician-Administered PTSD Scale, before undergoing nine sessions of TF-CBT. They were then reassessed post-treatment to estimate reduction in fear and dysphoric symptoms of PTSD. Although neural responses during the inhibitory task did not predict overall symptom change, reduced activation in the left precuneus and the right superior parietal cortex predicted greater improvement in dysphoric symptoms. ERP responses during response inhibition indicated that lower P3 peak latency predicted greater reduction of dysphoric symptoms. There were no significant predictors of changes of fear symptoms. These findings indicate that neural activity associated with response inhibition can act as a predictive biomarker of TF-CBT response for PTSD symptoms. This pattern of findings underscores the importance of delineating the role of biomarkers to predict remission of subtypes of PTSD.

EEG microstate features according to performance on a mental arithmetic task

In this study, we hypothesized that task performance could be evaluated applying EEG microstate to mental arithmetic task. This pilot study also aimed at evaluating the efficacy of microstates as novel features to discriminate task performance. Thirty-six subjects were divided into good and poor performers, depending on how well they performed the task. Microstate features were derived from EEG recordings during resting and task states. In the good performers, there was a decrease in type C and an increase in type D features during the task compared to the resting state. Mean duration and occurrence decreased and increased, respectively. In the poor performers, occurrence of type D feature, mean duration and occurrence showed greater changes. We investigated whether microstate features were suitable for task performance classification and eleven features including four archetypes were selected by recursive feature elimination (RFE). The model that implemented them showed the highest classification performance for differentiating between groups. Our pilot findings showed that the highest mean Area Under Curve (AUC) was 0.831. This study is the first to apply EEG microstate features to specific cognitive tasks in healthy subjects, suggesting that EEG microstate features can reflect task achievement.

Intrinsic functional connectivity of the default mode and cognitive control networks relate to change in behavioral performance over two years

Understanding how brain circuitry mediates cognitive control of behavior is crucial for understanding both mental health and disease. Cognitive control describes the group of behaviors that guide goal-directed action such as sustaining attention, processing information and inhibiting impulsive responses. We rely on these behaviors for daily social, occupational and emotional functioning. Two brain networks, the cognitive control network (CCN) and default mode network (DMN), are thought to cooperate in an inverse relationship to support these functions. However, we do not yet know how connectivity within and between these networks directly relates to healthy cognitive control behaviors, and whether these interactions change over time. Here, we employed a longitudinal design to investigate if change in intrinsic connectivity in these networks will correlate with change in a range of cognitive control functions. Over two years, 109 healthy individuals, aged eight to thirty-eight, were tested twice using fMRI to assess intrinsic functional connectivity of the CCN and DMN and a validated cognitive battery. We found that increased within-network connectivity through central and left DMN was associated with increased memory performance. Additionally, decreased connectivity between posterior parietal CCN and DMN nodes and decreased connectivity between left and right dorsolateral prefrontal nodes was associated with increased cognitive performance. These findings were age and gender controlled, suggesting that age-independent plastic change in intrinsic connectivity through these networks directly relate to changing behavior. This has implications for targeting intrinsic connectivity as a possible mechanism to improve cognitive function.

Effect of Process-Based Multi-Task Cognitive Training Program on Executive Function in Older Adults With Mild Cognitive Impairment: Study Rationale and Protocol Design for a Randomized Controlled Trial

INTRODUCTION

Recent research from both human and animal studies confirms that cognitive training gains a considerable effect on multiple cognitive domains in older adults with mild cognitive impairment. Previous studies have yet paid scant attention to executive function training. Little is known about whether this specific benefit translates to maintaining long-term effectiveness and transfer effects are. This study is designed as an effort to address this issue.

OBJECTIVE

The program aimed to evaluate the effect of process-based multi-task cognitive training on executive function and further explore its long-term effects and transfer effects in older adults with MCI. Furthermore, we will explore the neural correlates latent the changed performances underlying the cognitive intervention.

METHODS

This program is a single-blinded, randomized, prospective clinical trial to test the effect of process-based multi-task cognitive training in older adults with MCI. Ninety participants with MCI will be recruited and randomly assigned to the cognitive training group (n=45) and the wait-list control group (n=45). The cognitive training group will receive 10 weeks of process-based multi-task cognitive training and health education twice a week, at 40~60 min per session. While the wait-list control group will only receive 10 weeks of health education during the research period. The effect is measured using the executive function, neuropsychological assessment performance and related brain activity assessed with electroencephalogram parameters (slowness and complexity of the EEG) at baseline, after 10 weeks of training, and a 3-month follow-up.

RESULTS

The study is currently ongoing. Recruitment began in March 2019 and will conclude at the end of 2020. Effects of the process-based multi-task cognitive training on executive function in older adults with MCI will be described in intention-to-treat analysis and protocol set principle. We will also explore the potential long-term effects and transfer effects.

DISCUSSION

If a process-based multi-task cognitive training program results in positive changes to executive function in older adults with MCI, this might provide a viable and potential approach to delay the cognitive decline. Clinical Trial Registration: ChiCTR1900020585. Registered on January 09, 2019. http://www.chictr.org.cn/showproj.aspx?proj=34664.

Investigating the neural basis of cognitive control dysfunction in mood disorders

OBJECTIVES

Dysfunction of cognitive control is a feature of both bipolar disorder (BP) and major depression (MDD) and persists through to remission. However, it is unknown whether these disorders are characterized by common or distinct disruptions of cognitive control function and its neural basis. We investigated this gap in knowledge in asymptomatic BP and MDD participants, interpreted within a framework of normative function.

METHODS

Participants underwent fMRI scans engaging cognitive control through a working memory task and completed a cognitive battery evaluating performance across multiple subdomains of cognitive control, including attention, impulsivity, processing speed, executive function, and memory. Analysis was performed in two stages: (i) cognitive control-related brain activation and deactivation were correlated with cognitive control performance in 115 healthy controls (HCs), then, (ii) significantly correlated regions from (i) were compared between 25 asymptomatic BP, 25 remitted MDD, and with 25 different HCs, matched for age and gender.

RESULTS

Impulsivity and executive function performance were significantly worse in BP compared to both MDD and HCs. Both BP and MDD had significantly poorer memory performance compared to HCs. Greater deactivation of the medial prefrontal cortex (MPFC) during the fMRI task was associated with better executive function in healthy controls. Significantly less deactivation in this region was present in both BP and MDD compared to HCs.

CONCLUSIONS

Failure to deactivate the MPFC, a key region of the default mode network, during working memory processing is a shared neural feature present in both bipolar and major depression and could be a source of common cognitive dysfunction.

Neural oscillatory dynamics serving abstract reasoning reveal robust sex differences in typically-developing children and adolescents

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A cohort of 10–16 year-olds completed an abstract reasoning task during MEG.

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Performance on the abstract reasoning task correlated with fluid intelligence.

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The task was associated with increased cortical dynamics in frontoparietal areas.

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Youth showed sexually divergent patterns of distributed cortical activity with age.

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Specific frontoparietal activity differentially predicted aspects of task behavior.

Fluid intelligence, the ability to problem-solve in novel situations, is linked to higher-order cognitive abilities, and to academic achievement in youth. Previous research has demonstrated that fluid intelligence and the underlying neural circuitry continues to develop throughout adolescence. Neuroimaging studies have predominantly focused on identifying the spatial distribution of brain regions associated with fluid intelligence, with only a few studies examining the temporally-sensitive cortical oscillatory dynamics underlying reasoning abilities. The present study collected magnetoencephalography (MEG) during an abstract reasoning task to examine these spatiotemporal dynamics in a sample of 10-to-16 year-old youth. We found increased cortical activity across a distributed frontoparietal network. Specifically, our key results showed: (1) age was associated with increased theta activity in occipital and cerebellar regions, (2) robust sex differences were distributed across frontoparietal regions, and (3) that specific frontoparietal regions differentially predicted abstract reasoning performance among males versus females despite similar mean performance. Among males, increased theta activity mediated the relationship between age and faster reaction times; conversely, among females, decreased theta mediated the relationship between age and improved accuracy. These findings may suggest that males and females engage in distinct neurocognitive strategies across development to achieve similar behavioral outcomes during fluid reasoning tasks.

Cognitive ability is associated with changes in the functional organization of the cognitive control brain network

Cognitive control is one of the most important skills in day-to-day social and intellectual functioning but we are yet to understand the neural basis of the group of behaviors required to carry this out. Here, we probed changes over time in the brain network associated with cognitive control (the dorsolateral prefrontal cortex, the dorsal posterior parietal cortex, and the dorsal anterior cingulate cortex) using both behavioral assays and functional brain imaging during a selective working memory task in 69 healthy participants within the age range 18-38 years (mean: 25, SD: ±6), assessed twice, 2 years apart. We aimed to explore the relationship of changing network activation and connectivity with behavioral tasks associated with cognitive control in this otherwise neurodevelopmentally stable group. We found that increased connectivity between frontoparietal cognitive control network regions during the working memory task was associated with improved memory and executive functions over the 2-year period and that this association was not impacted by age, gender, or baseline performance. These results provide evidence that changes in the functional organization of the cognitive control brain network occur despite the absence of neurodevelopment, aging or targeted cognitive training effects, and could modulate cognitive performance in early to mid-adulthood. Understanding how and why this change is occurring could provide insights into the mechanisms through which cognitive control ability is cultivated over time. This could aid in the development of interventions in cases where cognitive control is impaired.

Functional connectivity of intrinsic cognitive networks during resting state and task performance in preadolescent children

Earlier studies on adults have shown that functional connectivity (FC) of brain networks can vary depending on the brain state and cognitive challenge. Network connectivity has been investigated quite extensively in children in resting state, much less during tasks and is largely unexplored between these brain states. Here we used functional magnetic resonance imaging and independent component analysis to investigate the functional architecture of large-scale brain networks in 16 children (aged 7–11 years, 11 males) and 16 young adults (aged 22–29 years, 10 males) during resting state and visual working memory tasks. We identified the major neurocognitive intrinsic connectivity networks (ICNs) in both groups. Children had stronger FC than adults within the cingulo-opercular network in resting state, during task performance, and after controlling for performance differences. During tasks, children had stronger FC than adults also within the default mode (DMN) and right frontoparietal (rFPN) networks, and between the anterior DMN and the frontopolar network, whereas adults had stronger coupling between the anterior DMN and rFPN. Furthermore, children compared to adults modulated the FC strength regarding the rFPN differently between the brain states. The FC within the anterior DMN correlated with age and performance in children so that the younger they were, the stronger was the FC, and the stronger the FC within this network, the slower they performed the tasks. The group differences in the network connectivity reported here, and the observed correlations with task performance, provide insight into the normative development of the preadolescent brain and link maturation of functional connectivity with improving cognitive performance.