Brain and cognitive reserve: Translation via network control theory

Cognition and Cognitive Reserve

Cognition is a mental process that provides the ability to think, know, and learn. Though cognitive skills are necessary to do daily tasks and activities, cognitive aging causes changes in various cognitive functions. Cognitive abilities that are preserved and strengthened by experience can be kept as a reserve and utilized when necessary. The concept of reserving cognition was found when people with Alzheimer's disease had differences in clinical manifestations and cognitive functions. The cognitive reserve builds resilience against cognitive decline and improves the quality of life. Also, several lines of studies have found that the plasticity between neurons has a significant impact on cognitive reserve and acts against cognitive decline. To extend the findings, the present study provides a comprehensive understanding of cognitive reserve and the variables that are involved in maintaining cognition. The study also considers reading as one of the cognitive proxies that develops and maintains cognitive reserve.

Reliability, validity, and responsiveness of the Arabic version of HIT-6 questionnaire in patients with migraine indicated for preventive therapy: A multi-center study

BACKGROUND

The Headache Impact Test (HIT-6) is an important patient-reported outcome measure (PROM) in migraine prevention trials.

OBJECTIVES

This study aimed to (i) assess the reliability and validity of the Arabic version of HIT-6 in Arabic-speaking patients experiencing migraine, and (ii) evaluate the responsiveness of HIT-6 following migraine preventive therapy.

METHODS

In this prospective study, patients with migraine (n = 145) were requested to fill out a headache diary, the Arabic version of HIT-6, and Migraine Disability Assessment Scale (MIDAS) at two time points (baseline and 3 months after initiation of prophylactic treatment). Some respondents (n = 73) were requested to fill out HIT-6 again 1 week from the baseline for test-retest reliability. The intensity of migraine headache attacks was evaluated using the Visual Analogue Scale (VAS). An anchor-based method was used to establish the minimal important change (MIC) value and responsiveness of HIT-6.

RESULTS

The total scores of HIT-6 were significantly correlated to a fair degree with MIDAS (r = 0.41), as well as VAS (r = 0.53), and monthly migraine days (r = 0.38) at the baseline while at the follow-up (after 3 months), the correlations were of moderate degree with MIDAS scores (r = 0.62) and monthly migraine days (r = 0.60; convergent validity). Reliability estimates of the Arabic HIT-6 were excellent (Cronbach's α = 0.91 at baseline and 0.89 at follow-up). The average measure interclass correlation coefficient (ICC) value for the test-retest reliability was 0.96 (95% confidence interval = 0.94-0.98, p < 0.001). The HIT-6 total score is sensitive to change, being significantly reduced after prophylactic treatment compared to before (effect size = 1.5, standardized response mean = 1.3). A reduction from baseline of 4.5 on HIT-6 showed the highest responsiveness to predict improvement with an area under the curve equal to 0.66, sensitivity of 80%, specificity of 45%, and significance at 0.021. Changes in the HIT-6 total score were positively correlated with changes in monthly migraine days (r = 0.40) and VAS scores (r = 0.69) but not with changes in the score of MIDAS (r = 0.07).

CONCLUSION

The Arabic version of HIT-6 is valid, reliable, and sensitive to detect clinical changes following migraine prophylactic treatment with a MIC of 4.5 points.

Disentangling sex-dependent effects of APOE on diverse trajectories of cognitive decline in Alzheimer's disease

Current diagnostic systems for Alzheimer's disease (AD) rely upon clinical signs and symptoms, despite the fact that the multiplicity of clinical symptoms renders various neuropsychological assessments inadequate to reflect the underlying pathophysiological mechanisms. Since putative neuroimaging biomarkers play a crucial role in understanding the etiology of AD, we sought to stratify the diverse relationships between AD biomarkers and cognitive decline in the aging population and uncover risk factors contributing to the diversities in AD. To do so, we capitalized on a large amount of neuroimaging data from the ADNI study to examine the inflection points along the dynamic relationship between cognitive decline trajectories and whole-brain neuroimaging biomarkers, using a state-of-the-art statistical model of change point detection. Our findings indicated that the temporal relationship between AD biomarkers and cognitive decline may differ depending on the synergistic effect of genetic risk and biological sex. Specifically, tauopathy-PET biomarkers exhibit a more dynamic and age-dependent association with Mini-Mental State Examination scores (p<0.05), with inflection points at 72, 78, and 83 years old, compared with amyloid-PET and neurodegeneration (cortical thickness from MRI) biomarkers. In the landscape of health disparities in AD, our analysis indicated that biological sex moderates the rate of cognitive decline associated with APOE4 genotype. Meanwhile, we found that higher education levels may moderate the effect of APOE4, acting as a marker of cognitive reserve.

Impaired Cortico-Thalamo-Cerebellar Integration Across Schizophrenia, Bipolar II, and Attention Deficit Hyperactivity Disorder Patients Suggests Potential Neural Signatures for Psychiatric Illness

Understanding aberrant functional changes between brain regions has shown promise for characterizing and differentiating the symptoms associated with progressive psychiatric disorders. The functional integration between the thalamus and cerebellum significantly influences learning and memory in cognition. Observed in schizophrenic patients, dysfunction within the corticalthalamocerebellar (CTC) circuitry is linked to challenges in prioritizing, processing, coordinating, and responding to information. This study explored whether abnormal CTC functional network connectivity patterns are present across schizophrenia (SCHZ) patients, bipolar II disorder (BIPOL) patients, and ADHD patients by examining both task- and task-free conditions compared to healthy volunteers (HC). Leveraging fMRI data from 135 participants (39 HC, 27 SCHZ patients, 38 BIPOL patients, and 31 ADHD patients), we analyzed functional network connectivity (FNC) patterns across 115 cortical, thalamic, subcortical, and cerebellar regions of interest (ROIs). Guiding our investigation: First, do the brain regions of the CTC circuit exhibit distinct abnormal patterns at rest in SCHZ, ADHD, and BIPOL? Second, do working memory tasks in these patients engage common regions of the circuit in similar or unique patterns? Consistent with previous findings, our observations revealed FNC patterns constrained in the cerebellar, thalamic, striatal, hippocampal, medial prefrontal and insular cortices across all three psychiatric cohorts when compared to controls in both task and task-free conditions. Post hoc analysis suggested a predominance in schizophrenia and ADHD patients during rest, while the task condition demonstrated effects across all three disorders. Factor-by-covariance GLM MANOVA further specified regions associated with clinical symptoms and trait assessments. Our study provides evidence suggesting that dysfunctional CTC circuitry in both task-free and task-free conditions may be an important broader neural signature of psychiatric illness.

Measures of cognitive reserve: An umbrella review

Objective: Recently, there has been a growing interest in operationalizing and measuring cognitive reserve (CR) for clinical and research purposes. This umbrella review aims to summarize the existing systematic and meta-analytic reviews about measures of CR. Method: A literature search was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and the guidelines of Aromataris et al. (2015) to identify the systematic reviews and meta-analysis involving the assessment of CR. The methodological quality of the papers included in this umbrella review was assessed with A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR-2) and Specialist Unit for Review Evidence (SURE). Results: Thirty-one reviews were identified, sixteen of which were systematic reviews, and fifteen were meta-analyses. Most of the reviews had a critically low quality, according to AMSTAR-2. The reviews included between two and 135 studies. Most of the papers focused on older adults, mainly those with dementia. CR was measured using one to six proxies, but most considered each proxy separately. The most assessed proxies of CR were education on its own, combined with occupation and/or engagement in activities or combined with parental education, bilingualism, and engagement in activities when four CR proxies were studied. Most of the studies included in higher quality reviews focused on three proxies, with education and engagement in activities being the most evaluated using CR questionnaires. Conclusion: Despite the growing interest in measuring CR, its operationalization did not improve since the last umbrella review in this field.

Brain and cognitive reserve mitigate balance dysfunction in multiple sclerosis

BACKGROUND

Approximately two-thirds of patients with multiple sclerosis (MS) complain different degrees of balance dysfunction, but some of them are able to withstand considerable disease burden without an overt balance impairment. Here, we tested the hypothesis that brain and cognitive reserve lessen the effect of MS-related tissue damage on balance control.

METHODS

We measured the postural sway of 148 patients and 74 sex- and age-matched healthy controls by force platform under different conditions reflecting diverse neuro-pathological substrates of balance dysfunction: eyes opened (EO), eyes closed (EC), and while performing the Stroop test, i.e., dual-task (DT). Lesion volumes on T2-hyperintense and T1-hypointense sequences, and normalized brain volume provided estimations of MS-related tissue damage in patients with MS. Hierarchical linear regressions explored the protective effect against the MS-related tissue damage of intracranial volume and educational attainment (proxies for brain and cognitive reserve, respectively) on balance.

RESULTS

Larger intracranial volume and high educational attainment mitigated the detrimental effect of MS-related tissue damage on postural sway under EO (adjusted-R2=0.20 and 0.27, respectively, p<0.01) and DT (adjusted-R2=0.22 and 0.30, respectively, p<0.06) conditions. Neither educational level nor brain size was associated with postural sway under EC condition.

CONCLUSION

Our findings suggest a protective role of brain and cognitive reserve even on balance, an outcome that relies on both motor control and higher order processing resources. The lack of a protective effect on postural sway under EC condition confirms that this latter outcome is closer associated with spinal cord rather than brain damage.

Impact of five floor coverings on the orthostatic balance of healthy subjects

Plantar skin sensitivity contributes to the regulation of postural control and, therefore, changing the characteristics of the plantar support surface can modify this control. This study aimed at assessing the impact of five different floor coverings on the orthostatic balance in 48 healthy subjects. Static posturography was performed with eyes open or closed on a platform in a control condition (no covering) and with five different covering surfaces: foam, silicone, ethyl vinyl acetate, and two textured mats with small (height 2 mm) or large pimples (7 mm). The average velocity of center of pressure (CoP) displacement was the primary endpoint measure and ten other posturographic variables were assessed. Comfort and pain produced by the covering were also scored. In eyes open condition, the average velocity of CoP displacement was increased when subjects stood on the foam mat, the silicone mat, and especially the textured mat with large pimples. Several other posturographic variables showed significant changes with different types of floor coverings with eyes open. These changes were not correlated to the comfort or pain scores associated with the different surfaces. In contrast, no difference was observed compared to the control condition (no covering) with eyes closed. This study shows that adding smooth or textured floor covering can alter balance in eyes open condition. In eyes closed condition, although more disturbing for balance, healthy subjects achieved better postural adaptation, probably by mobilizing more of their proprioceptive resources. This posturographic examination procedure could, therefore, be used to assess "proprioceptive reserve" capacities in clinical practice.

A pattern of cognitive resource disruptions in childhood psychopathology

The Hurst exponent (H) isolated in fractal analyses of neuroimaging time series is implicated broadly in cognition. Within this literature, H is associated with multiple mental disorders, suggesting that H is transdimensionally associated with psychopathology. Here, we unify these results and demonstrate a pattern of decreased H with increased general psychopathology and attention-deficit/hyperactivity factor scores during a working memory task in 1,839 children. This pattern predicts current and future cognitive performance in children and some psychopathology in 703 adults. This pattern also defines psychological and functional axes associating psychopathology with an imbalance in resource allocation between fronto-parietal and sensorimotor regions, driven by reduced resource allocation to fronto-parietal regions. This suggests the hypothesis that impaired working memory function in psychopathology follows from a reduced cognitive resource pool and a reduction in resources allocated to the task at hand.

Design and Harmonization Approach for the Multi-Institutional Neurocognitive Discovery Study (MINDS) of Adult Congenital Heart Disease (ACHD) Neuroimaging Ancillary Study: A Technical Note

Dramatic advances in the management of congenital heart disease (CHD) have improved survival to adulthood from less than 10% in the 1960s to over 90% in the current era, such that adult CHD (ACHD) patients now outnumber their pediatric counterparts. ACHD patients demonstrate domain-specific neurocognitive deficits associated with reduced quality of life that include deficits in educational attainment and social interaction. Our hypothesis is that ACHD patients exhibit vascular brain injury and structural/physiological brain alterations that are predictive of specific neurocognitive deficits modified by behavioral and environmental enrichment proxies of cognitive reserve (e.g., level of education and lifestyle/social habits). This technical note describes an ancillary study to the National Heart, Lung, and Blood Institute (NHLBI)-funded Pediatric Heart Network (PHN) "Multi-Institutional Neurocognitive Discovery Study (MINDS) in Adult Congenital Heart Disease (ACHD)". Leveraging clinical, neuropsychological, and biospecimen data from the parent study, our study will provide structural-physiological correlates of neurocognitive outcomes, representing the first multi-center neuroimaging initiative to be performed in ACHD patients. Limitations of the study include recruitment challenges inherent to an ancillary study, implantable cardiac devices, and harmonization of neuroimaging biomarkers. Results from this research will help shape the care of ACHD patients and further our understanding of the interplay between brain injury and cognitive reserve.

Cognitive reserve and other determinants of cognitive function in older adults: Insights from a community-based cross-sectional study

Background

India will be the home of 323 million elderly persons by 2050. This means a surge in the dependent population primarily due to age-related cognitive decline. Evidence suggests that life course factors may have a modulatory role on cognitive function. The present study explores such potential influence by investigating the effect of cognitive reserve (a latent construct using education and occupation) and physical, psychological, and social determinants on cognitive function in community dwelling elderly.

Methods

A community-based cross-sectional study was conducted in urban areas of West Bengal (India) among elderly aged ≥60 years. Data was collected by personal interviews for socio-demographic and medical profile. Cognitive function was assessed using Bangla Adaptation of Mini-Mental State Examination (BAMSE). Educational level and occupational complexity were used as proxy indicators for calculating cognitive reserve.

Results

Of the 370 elderlies interviewed (mean age = 68.9 years), cognitive function was abnormal in 13.5%. The cognitive function had a significant inverse relationship with depression symptoms, loneliness, hypertension, anemia, and basic activities of daily living. There was a significant difference in the cognitive reserve of the elderly with normal and abnormal cognitive function (mean 33.7 and 26.8, respectively). In the presence of covariates like sleep quality, depression, hypertension, and hemoglobin levels, the effect of age on cognitive function had a significant mediation influence of cognitive reserve - total effect = -0.2349; 95% CI = (-0.2972 to -0.1725) and direct effect = -0.2583; 95% CI = (-0.3172 to -0.1994).

Conclusion

The quantum of effect of the age on cognitive function decreases with good cognitive reserve as a cognitive reserve has a significant mediation effect on the relationship between age and cognitive function.

Computational modelling in disorders of consciousness: Closing the gap towards personalised models for restoring consciousness

Disorders of consciousness are complex conditions characterised by persistent loss of responsiveness due to brain injury. They present diagnostic challenges and limited options for treatment, and highlight the urgent need for a more thorough understanding of how human consciousness arises from coordinated neural activity. The increasing availability of multimodal neuroimaging data has given rise to a wide range of clinically- and scientifically-motivated modelling efforts, seeking to improve data-driven stratification of patients, to identify causal mechanisms for patient pathophysiology and loss of consciousness more broadly, and to develop simulations as a means of testing in silico potential treatment avenues to restore consciousness. As a dedicated Working Group of clinicians and neuroscientists of the international Curing Coma Campaign, here we provide our framework and vision to understand the diverse statistical and generative computational modelling approaches that are being employed in this fast-growing field. We identify the gaps that exist between the current state-of-the-art in statistical and biophysical computational modelling in human neuroscience, and the aspirational goal of a mature field of modelling disorders of consciousness; which might drive improved treatments and outcomes in the clinic. Finally, we make several recommendations for how the field as a whole can work together to address these challenges.

Noradrenergic and cholinergic systems take centre stage in neuropsychiatric diseases of ageing

Noradrenergic and cholinergic systems are among the most vulnerable brain systems in neuropsychiatric diseases of ageing, including Alzheimer's disease, Parkinson's disease, Lewy body dementia, and progressive supranuclear palsy. As these systems fail, they contribute directly to many of the characteristic cognitive and psychiatric symptoms. However, their contribution to symptoms is not sufficiently understood, and pharmacological interventions targeting noradrenergic and cholinergic systems have met with mixed success. Part of the challenge is the complex neurobiology of these systems, operating across multiple timescales, and with non-linear changes across the adult lifespan and disease course. We address these challenges in a detailed review of the noradrenergic and cholinergic systems, outlining their roles in cognition and behaviour, and how they influence neuropsychiatric symptoms in disease. By bridging across levels of analysis, we highlight opportunities for improving drug therapies and for pursuing personalised medicine strategies.

The oDGal Mouse: A Novel, Physiologically Relevant Rodent Model of Sporadic Alzheimer's Disease

Sporadic Alzheimer's disease (sAD) represents a serious and growing worldwide economic and healthcare burden. Almost 95% of current AD patients are associated with sAD as opposed to patients presenting with well-characterized genetic mutations that lead to AD predisposition, i.e., familial AD (fAD). Presently, the use of transgenic (Tg) animals overexpressing human versions of these causative fAD genes represents the dominant research model for AD therapeutic development. As significant differences in etiology exist between sAD and fAD, it is perhaps more appropriate to develop novel, more sAD-reminiscent experimental models that would expedite the discovery of effective therapies for the majority of AD patients. Here we present the oDGal mouse model, a novel model of sAD that displays a range of AD-like pathologies as well as multiple cognitive deficits reminiscent of AD symptomology. Hippocampal cognitive impairment and pathology were delayed with N-acetyl-cysteine (NaC) treatment, which strongly suggests that reactive oxygen species (ROS) are the drivers of downstream pathologies such as elevated amyloid beta and hyperphosphorylated tau. These features demonstrate a desired pathophenotype that distinguishes our model from current transgenic rodent AD models. A preclinical model that presents a phenotype of non-genetic AD-like pathologies and cognitive deficits would benefit the sAD field, particularly when translating therapeutics from the preclinical to the clinical phase.

Reduced emergent character of neural dynamics in patients with a disrupted connectome

High-level brain functions are widely believed to emerge from the orchestrated activity of multiple neural systems. However, lacking a formal definition and practical quantification of emergence for experimental data, neuroscientists have been unable to empirically test this long-standing conjecture. Here we investigate this fundamental question by leveraging a recently proposed framework known as "Integrated Information Decomposition," which establishes a principled information-theoretic approach to operationalise and quantify emergence in dynamical systems - including the human brain. By analysing functional MRI data, our results show that the emergent and hierarchical character of neural dynamics is significantly diminished in chronically unresponsive patients suffering from severe brain injury. At a functional level, we demonstrate that emergence capacity is positively correlated with the extent of hierarchical organisation in brain activity. Furthermore, by combining computational approaches from network control theory and whole-brain biophysical modelling, we show that the reduced capacity for emergent and hierarchical dynamics in severely brain-injured patients can be mechanistically explained by disruptions in the patients' structural connectome. Overall, our results suggest that chronic unresponsiveness resulting from severe brain injury may be related to structural impairment of the fundamental neural infrastructures required for brain dynamics to support emergence.

Turning Back the Clock: A Retrospective Single-Blind Study on Brain Age Change in Response to Nutraceuticals Supplementation vs. Lifestyle Modifications

BACKGROUND

There is a growing consensus that chronological age (CA) is not an accurate indicator of the aging process and that biological age (BA) instead is a better measure of an individual's risk of age-related outcomes and a more accurate predictor of mortality than actual CA. In this context, BA measures the "true" age, which is an integrated result of an individual's level of damage accumulation across all levels of biological organization, along with preserved resources. The BA is plastic and depends upon epigenetics. Brain state is an important factor contributing to health- and lifespan.

METHODS AND OBJECTIVE

Quantitative electroencephalography (qEEG)-derived brain BA (BBA) is a suitable and promising measure of brain aging. In the present study, we aimed to show that BBA can be decelerated or even reversed in humans (N = 89) by using customized programs of nutraceutical compounds or lifestyle changes (mean duration = 13 months).

RESULTS

We observed that BBA was younger than CA in both groups at the end of the intervention. Furthermore, the BBA of the participants in the nutraceuticals group was 2.83 years younger at the endpoint of the intervention compared with their BBA score at the beginning of the intervention, while the BBA of the participants in the lifestyle group was only 0.02 years younger at the end of the intervention. These results were accompanied by improvements in mental-physical health comorbidities in both groups. The pre-intervention BBA score and the sex of the participants were considered confounding factors and analyzed separately.

CONCLUSIONS

Overall, the obtained results support the feasibility of the goal of this study and also provide the first robust evidence that halting and reversal of brain aging are possible in humans within a reasonable (practical) timeframe of approximately one year.

Transitions between cognitive topographies: contributions of network structure, neuromodulation, and disease

Patterns of neural activity underlie human cognition. Transitions between these patterns are orchestrated by the brain's network architecture. What are the mechanisms linking network structure to cognitively relevant activation patterns? Here we implement principles of network control to investigate how the architecture of the human connectome shapes transitions between 123 experimentally defined cognitive activation maps (cognitive topographies) from the NeuroSynth meta-analytic engine. We also systematically incorporate neurotransmitter receptor density maps (18 receptors and transporters) and disease-related cortical abnormality maps (11 neurodegenerative, psychiatric and neurodevelopmental diseases; N = 17 000 patients, N = 22 000 controls). Integrating large-scale multimodal neuroimaging data from functional MRI, diffusion tractography, cortical morphometry, and positron emission tomography, we simulate how anatomically-guided transitions between cognitive states can be reshaped by pharmacological or pathological perturbation. Our results provide a comprehensive look-up table charting how brain network organisation and chemoarchitecture interact to manifest different cognitive topographies. This computational framework establishes a principled foundation for systematically identifying novel ways to promote selective transitions between desired cognitive topographies.

Predicting Antidepressant Treatment Response Using Functional Brain Controllability Analysis

Introduction: For decades, predicting response to the antidepressant medication has been a critical unmet need in depression treatment in clinic, and a technical challenge in depression research. Methods: In this study, a recently developed functional brain network controllability (fBNC) analysis approach was employed to identify the antidepressant treatment responders and nonresponders from depression patients at the pretreatment period. The fBNC, which captures the ability of brain regions to guide the brain's behavior from an initial state to a desired state with suitable choice of inputs, may provide valuable features for antidepressant response prediction. The performance of prediction was evaluated using resting-state functional magnetic resonance imaging data collected from a 6-week longitudinal clinical trial with escitalopram in treating unmedicated depression patients (n = 20). Treatment outcomes were assessed using the Hamilton Depression Rating Scale (HAMD) scores. Patients were considered as the treatment responders if their post-treatment HAMD scores were decreased by 50% or more at 6 weeks post-treatment. Results: Results showed significantly larger global average controllability and lower global modal controllability, greater regional average controllability, and smaller regional modal controllability of default mode network in treatment responders compared with the treatment nonresponders at the pretreatment period. By performing optimal control analysis, our results showed no significant difference of the neuromodulation effects between the treatment responders and nonresponders. Discussion: Our results suggest that the fBNC measures may be utilized as novel biomarkers to predict antidepressant response on depression and provide theoretical support to employ neuromodulation for treating antidepressant nonresponders. Impact statement In this study, by employing the novel functional brain controllability analysis on top of the brain connectivity network, we identified a set of biomarkers to identify the groups of depressive patients who responded to the antidepressant treatments from those who did not. We further provided the theoretical support to utilize neuromodulation for treating antidepressant nonresponders. These findings have clinical implications as accurate identification of antidepressant treatment response before starting the treatment may reduce patients' suffering and costs and increase the treatment outcomes by adjusting and personalizing the treatment protocol.

Age-related changes in network controllability are mitigated by redundancy in large-scale brain networks

The aging brain undergoes major changes in its topology. The mechanisms by which the brain mitigates age-associated changes in topology to maintain robust control of brain networks are unknown. Here we used diffusion MRI data from cognitively intact participants (n=480, ages 40-90) to study age-associated changes in the controllability of structural brain networks, features that could mitigate these changes, and the overall effect on cognitive function. We found age-associated declines in controllability in control hubs and large-scale networks, particularly within the and frontoparietal control and default mode networks. Redundancy, quantified via the assessment of multi-step paths within networks, mitigated the effects of changes in topology on network controllability. Lastly, network controllability, redundancy, and grey matter volume each played important complementary roles in cognitive function. In sum, our results highlight the importance of redundancy for robust control of brain networks and in cognitive function in healthy-aging.

Presurgical Executive Functioning in Low-Grade Glioma Patients Cannot Be Topographically Mapped

Executive dysfunctions have a high prevalence in low-grade glioma patients and may be the result of structural disconnections of particular subcortical tracts and/or networks. However, little research has focused on preoperative low-grade glioma patients. The frontotemporoparietal network has been closely linked to executive functions and is substantiated by the superior longitudinal fasciculus. The aim of this study was to investigate their role in executive functions in low-grade glioma patients. Patients from two neurological centers were included with IDH-mutated low-grade gliomas. The sets of preoperative predictors were (i) distance between the tumor and superior longitudinal fasciculus, (ii) structural integrity of the superior longitudinal fasciculus, (iii) overlap between tumor and cortical networks, and (iv) white matter disconnection of the same networks. Linear regression and random forest analyses were performed. The group of 156 patients demonstrated significantly lower performance than normative samples and had a higher prevalence of executive impairments. However, both regression and random forest analyses did not demonstrate significant results, meaning that neither structural, cortical network overlap, nor network disconnection predictors explained executive performance. Overall, our null results indicate that there is no straightforward topographical explanation of executive performance in low-grade glioma patients. We extensively discuss possible explanations, including plasticity-induced network-level equipotentiality. Finally, we stress the need for the development of novel methods to unveil the complex and interacting mechanisms that cause executive deficits in low-grade glioma patients.

Integrating media content analysis, reception analysis, and media effects studies

Every day, the world of media is at our fingertips, whether it is watching movies, listening to the radio, or browsing online media. On average, people spend over 8 h per day consuming messages from the mass media, amounting to a total lifetime dose of more than 20 years in which conceptual content stimulates our brains. Effects from this flood of information range from short-term attention bursts (e.g., by breaking news features or viral 'memes') to life-long memories (e.g., of one's favorite childhood movie), and from micro-level impacts on an individual's memory, attitudes, and behaviors to macro-level effects on nations or generations. The modern study of media's influence on society dates back to the 1940s. This body of mass communication scholarship has largely asked, "what is media's effect on the individual?" Around the time of the cognitive revolution, media psychologists began to ask, "what cognitive processes are involved in media processing?" More recently, neuroimaging researchers started using real-life media as stimuli to examine perception and cognition under more natural conditions. Such research asks: "what can media tell us about brain function?" With some exceptions, these bodies of scholarship often talk past each other. An integration offers new insights into the neurocognitive mechanisms through which media affect single individuals and entire audiences. However, this endeavor faces the same challenges as all interdisciplinary approaches: Researchers with different backgrounds have different levels of expertise, goals, and foci. For instance, neuroimaging researchers label media stimuli as "naturalistic" although they are in many ways rather artificial. Similarly, media experts are typically unfamiliar with the brain. Neither media creators nor neuroscientifically oriented researchers approach media effects from a social scientific perspective, which is the domain of yet another species. In this article, we provide an overview of approaches and traditions to studying media, and we review the emerging literature that aims to connect these streams. We introduce an organizing scheme that connects the causal paths from media content → brain responses → media effects and discuss network control theory as a promising framework to integrate media content, reception, and effects analyses.

Effect of methylphenidate on functional controllability: a preliminary study in medication-naïve children with ADHD

Methylphenidate (MPH) is the recommended first-line treatment for attention-deficit/hyperactivity disorder (ADHD). While MPH's mechanism of action as a dopamine and noradrenaline transporter blocker is well known, how this translates to ADHD-related symptom mitigation is still unclear. As functional connectivity is reliably altered in ADHD, with recent literature indicating dysfunctional connectivity dynamics as well, one possible mechanism is through altering brain network dynamics. In a double-blind, placebo-controlled MPH crossover trial, 19 medication-naïve children with ADHD underwent two functional MRI scanning sessions (one on MPH and one on placebo) that included a resting state scan and two inhibitory control tasks; 27 typically developing (TD) children completed the same protocol without medication. Network control theory, which quantifies how brain activity reacts to system inputs based on underlying connectivity, was used to assess differences in average and modal functional controllability during rest and both tasks between TD children and children with ADHD (on and off MPH) and between children with ADHD on and off MPH. Children with ADHD on placebo exhibited higher average controllability and lower modal controllability of attention, reward, and somatomotor networks than TD children. Children with ADHD on MPH were statistically indistinguishable from TD children on almost all controllability metrics. These findings suggest that MPH may stabilize functional network dynamics in children with ADHD, both reducing reactivity of brain organization and making it easier to achieve brain states necessary for cognitively demanding tasks.

Risk of Alzheimer's disease and related dementia by sex and race/ethnicity: The Multiethnic Cohort Study

INTRODUCTION

Data are limited for comparison of sex- and race/ethnicity-specific risks of Alzheimer's disease and related dementia (ADRD).

METHODS

In the population-based Multiethnic Cohort, we estimated the age-standardized diagnostic incidence rate (ASDIR) and relative risk of late-onset ADRD (n = 16,410) among 105,796 participants based on Medicare claims (1999-2014) by sex and race/ethnicity.

RESULTS

The ASDIR for ADRD was higher for women (17.0 per 1000 person-years) than for men (15.3) and varied across African Americans (22.9 in women, 21.5 in men), Native Hawaiians (19.3, 19.4), Latinos (16.8, 14.7), Whites (16.4, 15.5), Japanese Americans (14.8, 13.8), and Filipinos (12.5, 9.7). Similar risk patterns were observed for AD. Adjustment for education and cardiometabolic diseases attenuated the differences. Accounting for deaths from competing causes increased the sex difference, while reducing the racial/ethnic differences. Less racial/ethnic disparity was detected among apolipoprotein E (APOE) e4 carriers.

DISCUSSION

More research is needed to understand the sex and racial/ethnic differences in ADRD.

The network collapse in multiple sclerosis: An overview of novel concepts to address disease dynamics

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Multiple sclerosis (MS) can be considered as a network disorder.

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This review discusses network concepts in order to understand progression in MS.

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Damage is hypothesized to lead to a “network collapse” and clinical progression.

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New concepts are discussed that will likely influence the field in the near future.

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These include brain wiring, how regions communicate and robustness to damage.

Multiple sclerosis is a neuroinflammatory and neurodegenerative disorder of the central nervous system that can be considered a network disorder. In MS, lesional pathology continuously disconnects structural pathways in the brain, forming a disconnection syndrome. Complex functional network changes then occur that are poorly understood but closely follow clinical status. Studying these structural and functional network changes has been and remains crucial to further decipher complex symptoms like cognitive impairment and physical disability. Recent insights especially implicate the importance of monitoring network hubs in MS, like the thalamus and default-mode network which seem especially hit hard. Such network insights in MS have led to the hypothesis that as the network continues to become disconnected and dysfunctional, exceeding a certain threshold of network efficiency loss leads to a “network collapse”. After this collapse, crucial network hubs become rigid and overloaded, and at the same time a faster neurodegeneration and accelerated clinical (and cognitive) progression can be seen. As network neuroscience has evolved, the MS field can now move towards a clearer classification of the network collapse itself and specific milestone events leading up to it. Such an updated network-focused conceptual framework of MS could directly impact clinical decision making as well as the design of network-tailored rehabilitation strategies. This review therefore provides an overview of recent network concepts that have enhanced our understanding of clinical progression in MS, especially focusing on cognition, as well as new concepts that will likely move the field forward in the near future.

Prevention of delirium with agitation by yokukansan in older adults after cancer surgery

OBJECTIVE

Preventing postoperative delirium with agitation is vital in the older population. We examined the preventive effect of yokukansan on postoperative delirium with agitation in older adult patients undergoing highly invasive cancer resection.

METHODS

We performed a secondary per-protocol analysis of 149 patients' data from a previous clinical trial. Patients underwent scheduled yokukansan or placebo intervention 4-8 days presurgery and delirium assessment postoperatively. Delirium with agitation in patients aged ≥75 years was assessed using the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, and the Japanese version of the Delirium Rating Scale-Revised-98. We assessed odds ratios for yokukansan (TJ-54) compared with placebo for the manifestation of postoperative delirium with agitation across patients of all ages (n = 149) and those aged ≥65 years (n = 82) and ≥ 75 years (n = 21) using logistic regression.

RESULTS

Delirium with agitation manifested in 3/14 and 5/7 patients in the TJ-54 and placebo groups, respectively, among those aged ≥75 years. The odds ratio for yokukansan vs. placebo was 0.11 (95% confidence interval: 0.01-0.87). An age and TJ-54 interaction effect was detected in patients with delirium with agitation. No intergroup differences were observed in patients aged ≥65 years or across all ages for delirium with agitation.

CONCLUSIONS

This is the first study investigating the preventive effect of yokukansan on postoperative delirium with agitation in older adults. Yokukansan may alleviate workforce burdens in older adults caused by postoperative delirium with agitation following highly invasive cancer resection.

Personalizing repetitive transcranial magnetic stimulation for precision depression treatment based on functional brain network controllability and optimal control analysis

Brain neuromodulation effectively treats neurological diseases and psychiatric disorders such as Depression. However, due to patient heterogeneity, neuromodulation treatment outcomes are often highly variable, requiring patient-specific stimulation protocols throughout the recovery stages to optimize treatment outcomes. Therefore, it is critical to personalize neuromodulation protocol to optimize the patient-specific stimulation targets and parameters by accommodating inherent interpatient variability and intersession alteration during treatments. The study aims to develop a personalized repetitive transcranial magnetic stimulation (rTMS) protocol and evaluate its feasibility in optimizing the treatment efficiency using an existing dataset from an antidepressant experimental imaging study in depression. The personalization of the rTMS treatment protocol was achieved by personalizing both stimulation targets and parameters via a novel approach integrating the functional brain network controllability analysis and optimal control analysis. First, the functional brain network controllability analysis was performed to identify the optimal rTMS stimulation target from the effective connectivity network constructed from patient-specific resting-state functional magnetic resonance imaging data. The optimal control algorithm was then applied to optimize the rTMS stimulation parameters based on the optimized target. The performance of the proposed personalized rTMS technique was evaluated using datasets collected from a longitudinal antidepressant experimental imaging study in depression (n = 20). Simulation models demonstrated that the proposed personalized rTMS protocol outperformed the standard rTMS treatment by efficiently steering a depressive resting brain state to a healthy resting brain state, indicated by the significantly less control energy needed and higher model fitting accuracy achieved. The node with the maximum average controllability of each patient was designated as the optimal target region for the personalized rTMS protocol. Our results also demonstrated the theoretical feasibility of achieving comparable neuromodulation efficacy by stimulating a single node compared to stimulating multiple driver nodes. The findings support the feasibility of developing personalized neuromodulation protocols to more efficiently treat depression and other neurological diseases.

Through Thick and Thin: Baseline Cortical Volume and Thickness Predict Performance and Response to Transcranial Direct Current Stimulation in Primary Progressive Aphasia

Objectives

We hypothesized that measures of cortical thickness and volume in language areas would correlate with response to treatment with high-definition transcranial direct current stimulation (HD-tDCS) in persons with primary progressive aphasia (PPA).

Materials and Methods

In a blinded, within-group crossover study, PPA patients (N = 12) underwent a 2-week intervention HD-tDCS paired with constraint-induced language therapy (CILT). Multi-level linear regression (backward-fitted models) were performed to assess cortical measures as predictors of tDCS-induced naming improvements, measured by the Western Aphasia Battery-naming subtest, from baseline to immediately after and 6 weeks post-intervention.

Results

Greater baseline thickness of the pars opercularis significantly predicted naming gains (p = 0.03) immediately following intervention, while greater thickness of the middle temporal gyrus (MTG) and lower thickness of the superior temporal gyrus (STG) significantly predicted 6-week naming gains (p's < 0.02). Thickness did not predict naming gains in sham. Volume did not predict immediate gains for active stimulation. Greater volume of the pars triangularis and MTG, but lower STG volume significantly predicted 6-week naming gains in active stimulation. Greater pars orbitalis and MTG volume, and lower STG volume predicted immediate naming gains in sham (p's < 0.05). Volume did not predict 6-week naming gains in sham.

Conclusion

Cortical thickness and volume were predictive of tDCS-induced naming improvement in PPA patients. The finding that frontal thickness predicted immediate active tDCS-induced naming gains while temporal areas predicted naming changes at 6-week suggests that a broader network of regions may be important for long-term maintenance of treatment gains. The finding that volume predicted immediate naming performance in the sham condition may reflect the benefits of behavioral speech language therapy and neural correlates of its short-lived treatment gains. Collectively, thickness and volume were predictive of treatment gains in the active condition but not sham, suggesting that pairing HD-tDCS with CILT may be important for maintaining treatment effects.

Cognitive reserve: a multidimensional protective factor in Parkinson's disease related cognitive impairment

We explored the association between cognitive reserve (CR) and Parkinson' s disease (PD) related cognitive deterioration.Forty PD patients and 12 matched healthy controls (HC) were enrolled. The PD group was balanced for the presence/absence of cognitive impairment. All participants underwent MOCA. CR was measured by the Brief Intelligence Test, and a new comprehensive tool, named Cognitive Reserve Test (CoRe-T), including sections on leisure activities and creativity.Participants with higher CR obtained a better MOCA score irrespective of the group they belonged to. At the same time, irrespective of the CR level, the performance of the HC group was always better in comparison to the PD group. Within the PD group, a higher frequency of leisure activities was associated to be cognitively unimpaired, independently by the severity of motor symptoms and age.CR could help to cope with PD-related cognitive decline. Its multidimensional nature could have important applications in prevention and rehabilitation interventions.

Functional Brain Controllability Alterations in Stroke

Motor control deficits are very common in stroke survivors and often lead to disability. Current clinical measures for profiling motor control impairments are largely subjective and lack precise interpretation in a “control” perspective. This study aims to provide an accurate interpretation and assessment of the underlying “motor control” deficits caused by stroke, using a recently developed novel technique, i.e., the functional brain controllability analysis. The electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) were simultaneously recorded from 16 stroke patients and 11 healthy subjects during a hand-clenching task. A high spatiotemporal resolution fNIRS-informed EEG source imaging approach was then employed to estimate the cortical activity and construct the functional brain network. Subsequently, network control theory was applied to evaluate the modal controllability of some key motor regions, including primary motor cortex (M1), premotor cortex (PMC), and supplementary motor cortex (SMA), and also the executive control network (ECN). Results indicated that the modal controllability of ECN in stroke patients was significantly lower than healthy subjects (p = 0.03). Besides, the modal controllability of SMA in stroke patients was also significant smaller than healthy subjects (p = 0.02). Finally, the baseline modal controllability of M1 was found to be significantly correlated with the baseline FM-UL clinical scores (r = 0.58, p = 0.01). In conclusion, our results provide a new perspective to better understand the motor control deficits caused by stroke. We expect such an analytical methodology can be extended to investigate the other neurological or psychiatric diseases caused by cognitive control or motor control impairment.

Temporal exponential random graph models of longitudinal brain networks after stroke

Plasticity after stroke is a complex phenomenon. Functional reorganization occurs not only in the perilesional tissue but throughout the brain. However, the local connection mechanisms generating such global network changes remain largely unknown. To address this question, time must be considered as a formal variable of the problem rather than a simple repeated observation. Here, we hypothesized that the presence of temporal connection motifs, such as the formation of temporal triangles (T) and edges (E) over time, would explain large-scale brain reorganization after stroke. To test our hypothesis, we adopted a statistical framework based on temporal exponential random graph models (tERGMs), where the aforementioned temporal motifs were implemented as parameters and adapted to capture global network changes after stroke. We first validated the performance on synthetic time-varying networks as compared to standard static approaches. Then, using real functional brain networks, we showed that estimates of tERGM parameters were sufficient to reproduce brain network changes from 2 weeks to 1 year after stroke. These temporal connection signatures, reflecting within-hemisphere segregation (T) and between hemisphere integration (E), were associated with patients' future behaviour. In particular, interhemispheric temporal edges significantly correlated with the chronic language and visual outcome in subcortical and cortical stroke, respectively. Our results indicate the importance of time-varying connection properties when modelling dynamic complex systems and provide fresh insights into modelling of brain network mechanisms after stroke.

Characterizing Network Selectiveness to the Dynamic Spreading of Neuropathological Events in Alzheimer’s Disease

Background: Mounting evidence shows that the neuropathological burdens manifest preference in affecting brain regions during the dynamic progression of Alzheimer’s disease (AD). Since the distinct brain regions are physically wired by white matter fibers, it is reasonable to hypothesize the differential spreading pattern of neuropathological burdens may underlie the wiring topology, which can be characterized using neuroimaging and network science technologies. Objective: To study the dynamic spreading patterns of neuropathological events in AD. Methods: We first examine whether hub nodes with high connectivity in the brain network (assemble of white matter wirings) are susceptible to a higher level of pathological burdens than other regions that are less involved in the process of information exchange in the network. Moreover, we propose a novel linear mixed-effect model to characterize the multi-factorial spreading process of neuropathological burdens from hub nodes to non-hub nodes, where age, sex, and APOE4 indicators are considered as confounders. We apply our statistical model to the longitudinal neuroimaging data of amyloid-PET and tau-PET, respectively. Results: Our meta-data analysis results show that 1) AD differentially affects hub nodes with a significantly higher level of pathology, and 2) the longitudinal increase of neuropathological burdens on non-hub nodes is strongly correlated with the connectome distance to hub nodes rather than the spatial proximity. Conclusion: The spreading pathway of AD neuropathological burdens might start from hub regions and propagate through the white matter fibers in a prion-like manner.

Quantifying brain state transition cost via Schrödinger Bridge

Quantifying brain state transition cost is a fundamental problem in systems neuroscience. Previous studies utilized network control theory to measure the cost by considering a neural system as a deterministic dynamical system. However, this approach does not capture the stochasticity of neural systems, which is important for accurately quantifying brain state transition cost. Here, we propose a novel framework based on optimal control in stochastic systems. In our framework, we quantify the transition cost as the Kullback-Leibler divergence from an uncontrolled transition path to the optimally controlled path, which is known as Schrödinger Bridge. To test its utility, we applied this framework to functional magnetic resonance imaging data from the Human Connectome Project and computed the brain state transition cost in cognitive tasks. We demonstrate correspondence between brain state transition cost and the difficulty of tasks. The results suggest that our framework provides a general theoretical tool for investigating cognitive functions from the viewpoint of transition cost.

Social stress and risk of declining cognition: a longitudinal study of men and women in the United States

Limited research is available on the relationship between social stress and risk of declining cognition. We sought to examine whether social stress has adverse effects on risk of declining episodic memory and executive functioning in aging individuals. We used data from the MIDUS study, a national probability sample of non-institutionalized, English speaking respondents aged 25-74 living in the 48 contiguous states of the United States. The initial wave (1995) included 4963 non-institutionalized adults aged 32-84 (M = 55, SD = 12.4). We used an analytic sample from MIDUS-II (1996/1997) and MIDUS-III (2013) (n = 1821). The dependent variables are episodic memory and executive functioning, which were assessed with the Brief Test for Cognition (BTACT). The independent variables were social stress variables (subjective social status, family and marital stress, work stress and discrimination). To evaluate episodic memory and executive functioning changes over a time period of 10 years, we estimated adjusted linear regression models. Women report significantly lower subjective social status and more discrimination stress than men across all age groups. Controlling for education and income, age, and baseline episodic memory and executive functioning, lower subjective social status had additional adverse effects on declines in episodic memory in men and women. Marital risk had adverse effects on episodic memory in men but not in women. Daily discrimination had adverse effects on executive functioning on all individuals. Public health strategies should focus on reducing social stress in a socio-ecological perspective. Especially, subjective social status and discrimination stress might be a target for prevention efforts.

Proportional Changes in Cognitive Subdomains During Normal Brain Aging

Background: Neuroscience lacks a reliable method of screening the early stages of dementia. Objective: To improve the diagnostics of age-related cognitive functions by developing insight into the proportionality of age-related changes in cognitive subdomains. Materials and Methods: We composed a battery of psychophysiological tests and collected an open-access psychophysiological outcomes of brain atrophy (POBA) dataset by testing individuals without dementia. To extend the utility of machine learning (ML) classification in cognitive studies, we proposed estimates of the disproportional changes in cognitive functions: an index of simple reaction time to decision-making time (ISD), ISD with the accuracy performance (ISDA), and an index of performance in simple and complex visual-motor reaction with account for accuracy (ISCA). Studying the distribution of the values of the indices over age allowed us to verify whether diverse cognitive functions decline equally throughout life or there is a divergence in age-related cognitive changes. Results: Unsupervised ML clustering shows that the optimal number of homogeneous age groups is four. The sample is segregated into the following age-groups: Adolescents ∈ [0, 20), Young adults ∈ [20, 40), Midlife adults ∈ [40, 60) and Older adults ≥60 year of age. For ISD, ISDA, and ISCA values, only the median of the Adolescents group is different from that of the other three age-groups sharing a similar distribution pattern (p > 0.01). After neurodevelopment and maturation, the indices preserve almost constant values with a slight trend toward functional decline. The reaction to a moving object (RMO) test results (RMO_mean) follow another tendency. The Midlife adults group's median significantly differs from the remaining three age subsamples (p < 0.01). No general trend in age-related changes of this dependent variable is observed. For all the data (ISD, ISDA, ISCA, and RMO_mean), Levene's test reveals no significant changes of the variances in age-groups (p > 0.05). Homoscedasticity also supports our assumption about a linear dependency between the observed features and age. Conclusion: In healthy brain aging, there are proportional age-related changes in the time estimates of information processing speed and inhibitory control in task switching. Future studies should test patients with dementia to determine whether the changes of the aforementioned indicators follow different patterns.

Personality network neuroscience: Promises and challenges on the way toward a unifying framework of individual variability

We propose that the application of network theory to established psychological personality conceptions has great potential to advance a biologically plausible model of human personality. Stable behavioral tendencies are conceived as personality “traits.” Such traits demonstrate considerable variability between individuals, and extreme expressions represent risk factors for psychological disorders. Although the psychometric assessment of personality has more than hundred years tradition, it is not yet clear whether traits indeed represent “biophysical entities” with specific and dissociable neural substrates. For instance, it is an open question whether there exists a correspondence between the multilayer structure of psychometrically derived personality factors and the organizational properties of traitlike brain systems. After a short introduction into fundamental personality conceptions, this article will point out how network neuroscience can enhance our understanding about human personality. We will examine the importance of intrinsic (task-independent) brain connectivity networks and show means to link brain features to stable behavioral tendencies. Questions and challenges arising from each discipline itself and their combination are discussed and potential solutions are developed. We close by outlining future trends and by discussing how further developments of network neuroscience can be applied to personality research.

Global fractional anisotropy predicts transition to psychosis after 12 months in individuals at ultra-high risk for psychosis

OBJECTIVE

Psychosis spectrum disorders are associated with cerebral changes, but the prognostic value and clinical utility of these findings are unclear. Here, we applied a multivariate statistical model to examine the predictive accuracy of global white matter fractional anisotropy (FA) for transition to psychosis in individuals at ultra-high risk for psychosis (UHR).

METHODS

110 UHR individuals underwent 3 Tesla diffusion-weighted imaging and clinical assessments at baseline, and after 6 and 12 months. Using logistic regression, we examined the reliability of global FA at baseline as a predictor for psychosis transition after 12 months. We tested the predictive accuracy, sensitivity and specificity of global FA in a multivariate prediction model accounting for potential confounders to FA (head motion in scanner, age, gender, antipsychotic medication, parental socioeconomic status and activity level). In secondary analyses, we tested FA as a predictor of clinical symptoms and functional level using multivariate linear regression.

RESULTS

Ten UHR individuals had transitioned to psychosis after 12 months (9%). The model reliably predicted transition at 12 months (χ²  = 17.595, p = 0.040), accounted for 15-33% of the variance in transition outcome with a sensitivity of 0.70, a specificity of 0.88 and AUC of 0.87. Global FA predicted level of UHR symptoms (R²  = 0.055, F = 6.084, p = 0.016) and functional level (R²  = 0.040, F = 4.57, p = 0.036) at 6 months, but not at 12 months.

CONCLUSION

Global FA provided prognostic information on clinical outcome and symptom course of UHR individuals. Our findings suggest that the application of prediction models including neuroimaging data can inform clinical management on risk for psychosis transition.

Characterizing the Resilience Effect of Neurodegeneration for the Mechanistic Pathway of Alzheimer's Disease

BACKGROUND

With the rapid development of neurobiology and neuroimaging technologies, mounting evidence shows that Alzheimer's disease (AD) is caused by the build-up of two abnormal proteins, amyloid-β plaques (A) and neurofibrillary tangles (T). Over time, these AD-related neuropathological burdens begin to spread throughout the brain, which results in the characteristic progression of symptoms in AD.

OBJECTIVE

Although tremendous efforts have been made to link biological indicators to the progression of AD, limited attention has been paid to investigate the multi-factorial role of socioeconomic status (SES) in the prevalence or incidence of AD. There is high demand to explore the synergetic effect of sex and SES factors in moderating the neurodegeneration process caused by the accumulation of A and T biomarkers.

METHODS

We carry out a meta-data analysis on the longitudinal neuroimaging data, clinical outcomes, genotypes, and demographic data in Alzheimer's Disease Neuroimaging Initiative (ADNI) database (http://adni.loni.usc.edu).

RESULTS

Our major findings include 1) education and occupation show resilience effects at the angular gyrus, superior parietal lobule, lateral occipital-temporal sulcus, and posterior transverse collateral sulcus where we found significant slowdown of neurodegeneration due to higher education level or more advanced occupation rank; 2) A and T biomarkers manifest different spatial patterns of brain resilience; 3) BDNF (brain-derived neurotrophic factor) single nucleotide polymorphism (SNP) rs10835211 shows strong association to the identified resilience effect; 4) the identified resilience effect is associated with the clinical manifestation in memory, learning, and organization performance.

CONCLUSION

Several brain regions manifest resilience from SES to A and T biomarkers. BDNF SNPs have a potential association with the resilience effect from SES. In addition, cognitive measures of learning and memory demonstrate the resilience effect.

Common genetic variation is associated with longitudinal decline and network features in behavioral variant frontotemporal degeneration

The T allele in rs1768208 located in or near the myelin oligodendrocyte basic protein gene (MOBP) is a risk factor for frontotemporal degeneration pathology. We evaluated the hypothesis that the presence of a T allele in rs1768208 will be associated with rate of cognitive decline in behavioral variant frontotemporal degeneration (bvFTD) related to compromised frontal networks. We studied 81 individuals clinically diagnosed with bvFTD who were genotyped for rs1768208 and coded using a dominant model reflecting the presence (i.e., MOBP +) or absence (MOBP -) of the T risk allele. Linear mixed-effects models assessed the association of genotype on neuropsychological performance over time. Regression analyses examined differences in network structure by MOBP genotype. We found a genotype by time interaction for declining cognitive performance, whereby MOBP + individuals demonstrated faster rates of decline in executive function. The presence of a MOBP risk allele was associated with degradation of white matter network features in the frontal lobe. These findings suggest that individual genetic variation may contribute to heterogeneity in clinical progression.

Segregation of functional networks is associated with cognitive resilience in Alzheimer's disease

Cognitive resilience is an important modulating factor of cognitive decline in Alzheimer's disease, but the functional brain mechanisms that support cognitive resilience remain elusive. Given previous findings in normal ageing, we tested the hypothesis that higher segregation of the brain's connectome into distinct functional networks represents a functional mechanism underlying cognitive resilience in Alzheimer's disease. Using resting-state functional MRI, we assessed both resting-state functional MRI global system segregation, i.e. the balance of between-network to within-network connectivity, and the alternate index of modularity Q as predictors of cognitive resilience. We performed all analyses in two independent samples for validation: (i) 108 individuals with autosomal dominantly inherited Alzheimer's disease and 71 non-carrier controls; and (ii) 156 amyloid-PET-positive subjects across the spectrum of sporadic Alzheimer's disease and 184 amyloid-negative controls. In the autosomal dominant Alzheimer's disease sample, disease severity was assessed by estimated years from symptom onset. In the sporadic Alzheimer's sample, disease stage was assessed by temporal lobe tau-PET (i.e. composite across Braak stage I and III regions). In both samples, we tested whether the effect of disease severity on cognition was attenuated at higher levels of functional network segregation. For autosomal dominant Alzheimer's disease, we found higher functional MRI-assessed system segregation to be associated with an attenuated effect of estimated years from symptom onset on global cognition (P = 0.007). Similarly, for patients with sporadic Alzheimer's disease, higher functional MRI-assessed system segregation was associated with less decrement in global cognition (P = 0.001) and episodic memory (P = 0.004) per unit increase of temporal lobe tau-PET. Confirmatory analyses using the alternate index of modularity Q revealed consistent results. In conclusion, higher segregation of functional connections into distinct large-scale networks supports cognitive resilience in Alzheimer's disease.

Facial emotion mimicry in older adults with and without cognitive impairments due to Alzheimer's disease

Facial expression of humans is one of the main channels of everyday communication. The reported research work investigated communication regarding the pattern of emotional expression of healthy older adults and with mild cognitive impairments (MCI) or Alzheimer's disease (AD). It focuses on mimicking of displayed emotional facial expression on a sample of 25 older adults (healthy, MCI and AD patients). The adequacy of the patients' individual facial expressions in six basic emotions was measured with the Kinect 3D recording of the participants' facial expressions and compared to their own typical emotional facial expressions. The reactions were triggered by mimicking 49 still pictures of emotional facial expressions. No statistically significant differences in terms of frequency nor adequacy of emotional facial expression were reported in healthy and MCI groups. Unique patterns of emotional expressions have been observed in the AD group. Further investigating the pattern of older adults' facial expression may decrease the misunderstandings and increase the quality of life of the patients.

The missing role of gray matter in studying brain controllability

Brain controllability properties are normally derived from the white matter fiber tracts in which the neural substrate of the actual energy consumption, namely the gray matter, has been widely ignored. Here, we study the relationship between gray matter volume of regions across the whole cortex and their respective control properties derived from the structural architecture of the white matter fiber tracts. The data suggests that the ability of white fiber tracts to exhibit control at specific nodes not only depends on the connection strength of the structural connectome but additionally depends on gray matter volume at the host nodes. Our data indicate that connectivity strength and gray matter volume interact with respect to the brain’s control properties. Disentangling effects of the regional gray matter volume and connectivity strength, we found that frontal and sensory areas play crucial roles in controllability. Together these results suggest that structural and regional properties of the white matter and gray matter provide complementary information in studying the control properties of the intrinsic structural and functional architecture of the brain.

Network control theory suggests that the functions of large-scale brain circuits can be partially described with respect to the ability of brain regions to steer brain activity to different states. This ability, often quantified in terms of controllability metrics, has normally been derived from the structural architecture of the white matter fiber tracts. However, gray matter as the substrate that engenders much of the neural processes is widely ignored in this context. In the present work, we study the relationship between regional gray matter volume and control properties across the whole cortex and provide evidence that control properties not only depend on the connection strength of the structural connectome but also depend on sufficient gray matter volume at the host nodes.

Increased Within-Network Functional Connectivity May Predict NEDA Status in Fingolimod-Treated MS Patients

Only a few studies have evaluated the brain functional changes associated with disease-modifying therapies (DMTs) in multiple sclerosis (MS), though none used a composite measure of clinical and MRI outcomes to evaluate DMT-related brain functional connectivity (FC) measures predictive of short-term outcome. Therefore, we investigated the following: (1) baseline FC differences between patients who showed evidence of disease activity after a specific DMT and those who did not; (2) DMT-related effects on FC, and; (3) possible relationships between DMT-related FC changes and changes in performance. We used a previously analyzed dataset of 30 relapsing MS patients who underwent fingolimod treatment for 6 months and applied the “no evidence of disease activity” (NEDA-3) status as a clinical response indicator of treatment efficacy. Resting-state fMRI data were analyzed to obtain within- and between-network FC measures. After therapy, 14 patients achieved NEDA-3 status (hereinafter NEDA), while 16 did not (EDA). The two groups significantly differed at baseline, with the NEDA group having higher within-network FC in the anterior and posterior default mode, auditory, orbitofrontal, and right frontoparietal networks than the EDA. After therapy, NEDA showed significantly reduced within-network FC in the posterior default mode and left frontoparietal networks and increased between-network FC in the posterior default mode/orbitofrontal networks; they also showed PASAT improvement, which was correlated with greater within-network FC decrease in the posterior default mode network and with greater between-network FC increase. No significant longitudinal FC changes were found in the EDA. Taken together, these findings suggest that NEDA status after fingolimod is related to higher within-network FC at baseline and to a consistent functional reorganization after therapy.

Exercise Trials in Pediatric Brain Tumor: A Systematic Review of Randomized Studies

In pediatric brain tumor patients, treatment advances have increased survival rates to nearly 70%, while consequently shifting the burden of disease to long-term management. Exercise has demonstrated potential in improving multiple health impairments secondary to brain tumor treatment. However, these effects have not been consolidated through review. Therefore, we performed a systematic review of 6 health sciences databases (Medline, Embase, PsychINFO, CINAHL, SPORTDiscus, and Cochrane Central Database). Two reviewers screened studies against predefined inclusion criteria, namely that the study must: (i) be pediatric-specific; (ii) examine the effects of an exercise intervention; and (iii) employ a randomized or quasi-randomized trial design. The same 2 reviewers performed data extraction and analyses. From a pool of 4442, 5 articles-based on 2 independent trials-were included in our review (N=41). Exercise interventions were primarily aerobic, but included balance or muscle building components. Exercise had a positive effect on volumetric or diffusion-based neuroimaging outcomes, as well as motor performance and cardiorespiratory fitness. The effects of exercise on cognition remains unclear. Exercise did not worsen any of the outcomes studied. This review captures the state of the science, suggesting a potential role for exercise in children treated for brain tumor.

Cognitive/Functional Measures Predict Alzheimer's Disease, Dependent on Hippocampal Volume

OBJECTIVES

This study aimed to investigate the predictive value of cognitive/functional measures in combination with hippocampal volume (HCV) on the probability of conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD).

METHODS

The Rey Auditory Verbal Learning Test for immediate memory, Mini-Mental State Examination, a functional assessment for independent daily activities and Alzheimer's Disease Assessment Scale were used as cognitive/functional measures and HCV as neuroimaging measure. Logistic regression and Cox proportional hazard analyses were used to explore the measures' predictive values for AD conversion and time to conversion.

RESULTS

The probability of conversion from MCI to AD was associated with cognitive function, but this was moderated by HCV: higher at lower HCV and lower at higher HCV. General cognitive/functional measures were less predictive than immediate memory in predicting time to conversion to AD at small HCVs.

CONCLUSION

Effectiveness of cognitive measures and subtle functional abnormality in predicting conversion from MCI to AD is dependent on HCV, thus combined evaluation should be considered. A combination of HCV and immediate memory appear to perform best in predicting time to conversion.

Occupation-related effects on motor cortex thickness among older, cognitive healthy individuals

Both, decline of sensorimotor functions and cortical thickness are known processes in healthy aging. Physical activity has been suggested to enhance the execution of daily routine activities and to extend the time of functional independence in advanced age. We hypothesized that cortical thickness of motor areas in retired individuals could be related to physical demands of the profession carried out during working life. Depending on their former occupations, 69 cognitively healthy individuals (range 70–85 years) were divided into higher and lower physically complex occupations (HPCO n = 27 and LPCO n = 42) according to the international standard classification of occupations (ISCO-08). Participants underwent a high-resolution 3T T1-weighted MRI scan. Surface-based analysis revealed higher cortical thickness in the left precentral (P = 0.001) and postcentral gyrus (P < 0.001) and right postcentral gyrus (P = 0.001) for the HPCO relative to the LPCO group (corrected for multiple comparisons, sex, age and leisure activities in the past 20 years). Physical leisure activities associated with exertion were positively correlated with cortical thickness in the left pre- and postcentral gyrus (P = 0.037) of the LPCO group. Time since retirement was negatively associated with cortical thickness in the left postcentral gyrus (P = 0.004) of the HPCO group. Executing a higher physically complex occupation before retirement was related to relative higher cortical thickness in the primary motor and somatosensory cortex in later life, supporting the hypothesis that physical activity contributes to neural reserve in these regions. However, these benefits appear to vanish when physical activity is reduced due to retirement.

Learning dynamic graph embeddings for accurate detection of cognitive state changes in functional brain networks

Mounting evidence shows that brain functions and cognitive states are dynamically changing even in the resting state rather than remaining at a single constant state. Due to the relatively small changes in BOLD (blood-oxygen-level-dependent) signals across tasks, it is difficult to detect the change of cognitive status without requiring prior knowledge of the experimental design. To address this challenge, we present a dynamic graph learning approach to generate an ensemble of subject-specific dynamic graph embeddings, which allows us to use brain networks to disentangle cognitive events more accurately than using raw BOLD signals. The backbone of our method is essentially a representation learning process for projecting BOLD signals into a latent vertex-temporal domain with the greater biological underpinning of brain activities. Specifically, the learned representation domain is jointly formed by (1) a set of harmonic waves that govern the topology of whole-brain functional connectivities and (2) a set of Fourier bases that characterize the temporal dynamics of functional changes. In this regard our dynamic graph embeddings provide a new methodology to investigate how these self-organized functional fluctuation patterns oscillate along with the evolving cognitive status. We have evaluated our proposed method on both simulated data and working memory task-based fMRI datasets, where our dynamic graph embeddings achieve higher accuracy in detecting multiple cognitive states than other state-of-the-art methods.

The Contribution of Physical Exercise to Brain Resilience

Increasing attention has been given to understanding resilience to brain diseases, often described as brain or cognitive reserve. Among the protective factors for the development of resilience, physical activity/exercise has been considered to play an important role. Exercise is known to induce many positive effects on the brain. As such, exercise represents an important tool to influence neurodevelopment and shape the adult brain to react to life's challenges. Among many beneficial effects, exercise intervention has been associated with cognitive improvement and stress resilience in humans and animal models. Thus, a growing number of studies have demonstrated that exercise not only recovers or minimizes cognitive deficits by inducing better neuroplasticity and cognitive reserve but also counteracts brain pathology. This is evidenced before disease onset or after it has been established. In this review, we aimed to present encouraging data from current clinical and pre-clinical neuroscience research and discuss the possible biological mechanisms underlying the beneficial effects of physical exercise on resilience. We consider the implication of physical exercise for resilience from brain development to aging and for some neurological diseases. Overall, the literature indicates that brain/cognitive reserve built up by regular exercise in several stages of life, prepares the brain to be more resilient to cognitive impairment and consequently to brain pathology.

Appropriate time to apply control input to complex dynamical systems

Controlling a network structure has many potential applications many fields. In order to have an effective network control, not only finding good driver nodes is important, but also finding the optimal time to apply the external control signals to network nodes has a critical role. If applied in an appropriate time, one might be to control a network with a smaller control signals, and thus less energy. In this manuscript, we show that there is a relationship between the strength of the internal fluxes and the effectiveness of the external control signal. To be more effective, external control signals should be applied when the strength of the internal states is the smallest. We validate this claim on synthetic networks as well as a number of real networks. Our results may have important implications in systems medicine, in order to find the most appropriate time to inject drugs as a signal to control diseases.