Reduced default mode network effective connectivity in healthy aging is modulated by years of education.

Aging is a major risk factor for neurodegenerative diseases like dementia and Alzheimer's disease. Even in non-pathological aging, decline in cognitive functioning is observed in the majority of the elderly population, necessitating the importance of studying the processes involved in healthy aging in order to identify brain biomarkers that promote the conservation of functioning. The default mode network (DMN) has been of special interest to aging research due to its vulnerability to atrophy and functional decline over the course of aging. Prior work has focused almost exclusively on functional (i.e. undirected) connectivity, yet converging findings are scarce. Therefore, we set out to use spectral dynamic causal modeling to investigate changes in the effective (i.e. directed) connectivity within the DMN and to discover changes in information flow in a sample of cognitively normal adults spanning from 48 to 89 years (n = 63). Age was associated to reduced verbal memory performance. Modeling of effective connectivity revealed a pattern of age-related downregulation of posterior DMN regions driven by inhibitory connections from the hippocampus and middle temporal gyrus. Additionally, there was an observed decline in the hippocampus' susceptibility to network inputs with age, effectively disconnecting itself from other regions. The estimated effective connectivity parameters were robust and able to predict the age in out of sample estimates in a leave-one-out cross-validation. Attained education moderated the effects of aging, largely reversing the observed pattern of inhibitory connectivity. Thus, medial prefrontal cortex, hippocampus and posterior DMN regions formed an excitatory cycle of extrinsic connections related to the interaction of age and education. This suggests a compensatory role of years of education in effective connectivity, stressing a possible target for interventions. Our findings suggest a connection to the concept of cognitive reserve, which attributes a protective effect of educational level on cognitive decline in aging (Stern, 2009).

Communication, socialization, and ITC. The psychosocial construction of sustainability.

Over the past two decades, the facets related to environmental crises (in the plural) have grown increasingly intricate. What began as environmentalists' apprehension over nature degradation and the encouragement of citizen-driven initiatives has evolved. The current shift in emphasis and prevailing message strives to foster a culture where citizens refrain from independent initiatives. Instead, the directive is to heed the guidance of the knowledgeable (scientists, politicians, corporations, interest groups, etc.), as substantiated by our investigative findings, which align, in part, with existing literature. Conversely, our exploration into environmental communication, notably the insights gleaned from longitudinal research concerning pro-environmental knowledge, attitudes, and actions, reveals a decline in citizens' effective inclinations toward embracing pro-environmental behaviors. Meanwhile, the escalation of the climate crisis is fueling heightened levels of echo-anxiety and solastalgia. This trajectory is closely intertwined with a growing global disillusionment within society - not just regarding the future - instilling a sense of disillusionment concerning pro-environmental messages and slogans disseminated by governing bodies and corporations. This has led to a state resembling learned helplessness, as articulated by Seligman, or what we prefer to term "induced" helplessness, rather than fostering conditions conducive to empowerment. This article comprehensively examines various reports and our inquiries, revealing how communication management and its constituents lie at the heart of forging novel narratives, fresh cognitive dissonances, and emerging social representations. Notably emphasized is the pivotal role played by information and communication technologies (ICT), particularly through dissemination on widely-used social networks. Since the 2010s, these platforms have assumed a paramount role in shaping socialization processes, surpassing educational institutions and conventional mass media.

Benefits of Cultural Activities on People with Cognitive Impairment: A Meta-Analysis.

BACKGROUND: Museums and cultural institutions are increasingly aware of both the interests and needs of society. Accordingly, these institutions are becoming allies in terms of health and well-being due to the importance of their social functions. Presently, many institutions create cultural activities aimed at cognitively impaired people, a group on the rise owing to the prevalence of dementia and the aging of society. Nevertheless, scientific evidence in this field remains scarce. As a result, the main objective of this research was to empirically evaluate and identify the benefits that cultural interventions can bring to cognitively impaired participants. METHOD: A meta-analysis (MA) was performed following PRISMA guidelines. When inclusion and eligibility criteria had been established, articles were subsequently selected through a strategic search of Web of Science, SCOPUS, PubMed, and Medline. RESULTS: Twenty-six studies met the eligibility criteria, involving a total of 1201 participants with cognitive impairment. The results showed a statistically non-significant effect size when analyzing these cultural interventions for cognitively impaired people overall. However, when conducting partial meta-analyses (MA'), focusing on studies related to a specific disease, a particular type of treatment, or a specific type of evaluation, the results concurred with the conclusion of the previous systematic review (SR). CONCLUSION: Despite the high heterogeneity of the studies, benefits were identified in emotional well-being and social aspects but not in clinical ones such as the deterioration of cognitive or motor function, among others.

Hypoconnectivity networks in schizophrenia patients: A voxel-wise meta-analysis of Rs-fMRI.

In recent years several meta-analyses regarding resting-state functional connectivity in patients with schizophrenia have been published. The authors have used different data analysis techniques: regional homogeneity, seed-based data analysis, independent component analysis, and amplitude of low frequencies. Hence, we aim to perform a meta-analysis to identify connectivity networks with different activation patterns between people diagnosed with schizophrenia and healthy controls using voxel-wise analysis. METHOD: We collected primary studies exploring whole brain connectivity by functional magnetic resonance imaging at rest in patients with schizophrenia compared with healthy controls. We identified 25 studies included high-quality studies that included 1285 patients with schizophrenia and 1279 healthy controls. RESULTS: The results indicate hypoactivation in the right precentral gyrus and the left superior temporal gyrus of patients with schizophrenia compared with healthy controls. CONCLUSIONS: These regions have been linked with some clinical symptoms usually present in Plea with schizophrenia, such as auditory verbal hallucinations, formal thought disorder, and the comprehension and production of gestures.

Abnormal degree centrality and functional connectivity in Down syndrome: A resting-state fMRI study.

Background/Objective: Neuroimaging studies have shown brain abnormalities in Down syndrome (DS) but have not clarified the underlying mechanisms of dysfunction. Here, we investigated the degree centrality (DC) abnormalities found in the DS group compared with the control group, and we conducted seed-based functional connectivity (FC) with the significant clusters found in DC. Moreover, we used the significant clusters of DC and the seed-based FC to elucidate differences between brain networks in DS compared with controls. Method: The sample comprised 18 persons with DS (M = 28.67, SD = 4.18) and 18 controls (M = 28.56, SD = 4.26). Both samples underwent resting-state functional magnetic resonance imaging. Results: DC analysis showed increased DC in the DS in temporal and right frontal lobe, as well as in the left caudate and rectus and decreased DC in the DS in regions of the left frontal lobe. Regarding seed-based FC, DS showed increased and decreased FC. Significant differences were also found between networks using Yeo parcellations, showing both hyperconnectivity and hypoconnectivity between and within networks. Conclusions: DC, seed-based FC and brain networks seem altered in DS, finding hypo- and hyperconnectivity depending on the areas. Network analysis revealed between- and within-network differences, and these abnormalities shown in DS could be related to the characteristics of the population.

Altered spontaneous brain activity in Down syndrome and its relation with cognitive outcome.

Although Down syndrome (DS) is the most common genetic cause of neurodevelopmental delay, few neuroimaging studies have explored this population. This investigation aimed to study whole-brain resting-state spontaneous brain activity using fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) strategies to find differences in spontaneous brain activity among young people with DS and controls and to correlate these results with cognitive outcomes. The sample comprised 18 persons with DS (age mean = 28.67, standard deviation = 4.18) and 18 controls (age mean = 28.56, standard deviation = 4.26). fALFF and ReHo analyses were performed, and the results were correlated with other cognitive variables also collected (KBIT-2 and verbal fluency test). Increased activity was found in DS using fALFF in areas involving the frontal and temporal lobes and left cerebellum anterior lobe. Decreased activity in DS was found in the left parietal and occipital lobe, the left limbic lobe and the left cerebellum posterior lobe. ReHo analysis showed increased activity in certain DS areas of the left frontal lobe and left rectus, as well as the inferior temporal lobe. The areas with decreased activity in the DS participants were regions of the frontal lobe and the right limbic lobe. Altered fALFF and ReHo were found in the DS population, and this alteration could predict the cognitive abilities of the participants. To our knowledge, this is the first study to explore regional spontaneous brain activity in a population with DS. Moreover, this study suggests the possibility of using fALFF and ReHo as biomarkers of cognitive function, which is highly important given the difficulties in cognitively evaluating this population to assess dementia. More research is needed, however, to demonstrate its utility.

Spontaneous brain activity in healthy aging: An overview through fluctuations and regional homogeneity.

Introduction: This study aims to explore whole-brain resting-state spontaneous brain activity using fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) strategies to find differences among age groups within a population ranging from middle age to older adults. Methods: The sample comprised 112 healthy persons (M = 68.80, SD = 7.99) aged 48-89 who were split into six age groups (< 60, 60-64, 65-69, 70-74, 75-79, and ≥ 80). Fractional amplitude of low-frequency fluctuation and ReHo analyses were performed and were compared among the six age groups, and the significant results commonly found across groups were correlated with the gray matter volume of the areas and the age variable. Results: Increased activity was found using fALFF in the superior temporal gyrus and inferior frontal gyrus when comparing the first group and the fifth. Regarding ReHo analysis, Group 6 showed increased ReHo in the temporal lobe (hippocampus), right and left precuneus, right caudate, and right and left thalamus depending on the age group. Moreover, significant correlations between age and fALFF and ReHo clusters, as well as with their gray matter volume were found, meaning that the higher the age, the higher the regional synchronization, the lower the fALFF activation, and the lower gray matter of the right thalamus. Conclusion: Both techniques have been shown to be valuable and usable tools for disentangling brain changes in activation in a very low interval of years in healthy aging.

Abnormalities in the default mode network in late-life depression: A study of resting-state fMRI.

Background/Objective: Neuroimaging studies have reported abnormalities in the examination of functional connectivity in late-life depression (LLD) in the default mode network (DMN). The present study aims to study resting-state functional connectivity within the DMN in people diagnosed with late-life major depressive disorder (MDD) compared to healthy controls (HCs). Moreover, we would like to differentiate these same connectivity patterns between participants with high vs. low anxiety levels. Method: The sample comprised 56 participants between the ages of 60 and 75; 27 of them were patients with a diagnosis of MDD. Patients were further divided into two samples according to anxiety level: the four people with the highest anxiety level and the five with the lowest anxiety level. Clinical aspects were measured using psychological questionnaires. Each participant underwent functional magnetic resonance imaging (fMRI) acquisition in different regions of interest (ROIs) of the DMN. Results: There was a greater correlation between pairs of ROIs in the control group than in patients with LLD, being this effect preferentially observed in patients with higher anxiety levels. Conclusions: There are differences in functional connectivity within the DMN depending on the level of psychopathology. This can be reflected in these correlations and in the number of clusters and how the brain lateralizes (clustering).

Diagnosis of late-life depression using structural equation modeling and dynamic effective connectivity during resting fMRI.

BACKGROUND: Late-life depression (LLD) is characterized by cognitive and social impairments. Determining neurobiological alterations in connectivity in LLD by means of fMRI may lead to a better understanding of the neural basis underlying this disorder and more precise diagnostic markers. The primary objective of this paper is to identify a structural model that best explains the dynamic effective connectivity (EC) of the default mode network (DMN) in LLD patients compared to controls. METHODS: Twenty-seven patients and 29 healthy controls underwent resting-state fMRI during a period of eight minutes. In both groups, jackknife correlation matrices were generated with six ROIs of the DMN that constitute the posterior DMN (pDMN). The different correlation matrices were used as input to estimate each structural equation model (SEM) for each subject in both groups incorporating dynamic effects. RESULTS: The results show that the proposed LLD diagnosis algorithm achieves perfect accuracy in classifying LLD patients and controls. This differentiation is based on three aspects: the importance of ROIs 4 and 6, which seem to be the most distinctive among the subnetworks; the shape that the specific connections adopt in their networks, or in other words, the directed connections that are established among the ROIs in the pDMN for each group; and the number of dynamic effects that seem to be greater throughout the six ROIs studied [t = 54.346; df = 54; p < .001; 95 % CI difference = 5.486-5.906]. LIMITATIONS: The sample size was moderate, and the participants continued their current medications. CONCLUSIONS: The network models that we developed describe a pattern of dynamic activation in the pDMN that may be considered a possible biomarker for LLD, which may allow early diagnosis of this disorder.

Task-Related Brain Connectivity Activation Functional Magnetic Resonance Imaging in Intellectual Disability Population: A Meta-Analytic Study.

Introduction: Neuroimaging studies of intellectual disability (ID) have been published over the last three decades, but the findings are often inconsistent, and therefore, the neural correlates of ID remain elusive. This article aims to study the different publications in task-functional magnetic resonance imaging (fMRI) and different ID populations to make a qualitative and quantitative analysis on this field. Methods: After duplicates were removed, only 10 studies matching our inclusion criteria were incorporated. Moreover, a quality assessment of the included studies was done. Qualitative results of the different articles were analyzed, separated by type of task and type of ID. Seed-based d mapping (SDM) software was used. Results: The right temporal gyrus was more activated in control subjects than in ID. Concretely, the right temporal gyrus is implicated in many cognitive domains as semantic memory processing and language. Moreover, it can be highly influenced by the type of task used in every study. Heterogeneity was not detected. A jackknife sensitivity analysis was also estimated to improve the analysis reliability, and both results were confirmed. Conclusions: More task-fMRI studies on ID must be published to add larger samples to address the pathophysiological questions more directly. Impact statement In this article, the state-of-the-art in the field of functional magnetic resonance imaging (fMRI) and intellectual disability (ID) is reviewed. Moreover, we perform a meta-analysis of every article's results to summarize the principal outcomes in the field. It is very relevant because it has become the first meta-analytic study to overcome all the principal studies published in fMRI and ID to find the principal neurological substrates while the subjects are performing a task.

Structural equation models to estimate dynamic effective connectivity networks in resting fMRI. A comparison between individuals with Down syndrome and controls.

Emerging evidence suggests that an effective or functional connectivity network does not use a static process over time but incorporates dynamic connectivity that shows changes in neuronal activity patterns. Using structural equation models (SEMs), we estimated a dynamic component of the effective network through the effects (recursive and nonrecursive) between regions of interest (ROIs), taking into account the lag 1 effect. The aim of the paper was to find the best structural equation model (SEM) to represent dynamic effective connectivity in people with Down syndrome (DS) in comparison with healthy controls. Twenty-two people with DS were registered in a functional magnetic resonance imaging (fMRI) resting-state paradigm for a period of six minutes. In addition, 22 controls, matched by age and sex, were analyzed with the same statistical approach. In both groups, we found the best global model, which included 6 ROIs within the default mode network (DMN). Connectivity patterns appeared to be different in both groups, and networks in people with DS showed more complexity and had more significant effects than networks in control participants. However, both groups had synchronous and dynamic effects associated with ROIs 3 and 4 related to the upper parietal areas in both brain hemispheres as axes of association and functional integration. It is evident that the correct classification of these groups, especially in cognitive competence, is a good initial step to propose a biomarker in network complexity studies.

Complexity Analysis of the Default Mode Network Using Resting-State fMRI in Down Syndrome: Relationships Highlighted by a Neuropsychological Assessment.

BACKGROUND: Studies on complexity indicators in the field of functional connectivity derived from resting-state fMRI (rs-fMRI) in Down syndrome (DS) samples and their possible relationship with cognitive functioning variables are rare. We analyze how some complexity indicators estimated in the subareas that constitute the default mode network (DMN) might be predictors of the neuropsychological outcomes evaluating Intelligence Quotient (IQ) and cognitive performance in persons with DS. METHODS: Twenty-two DS people were assessed with the Kaufman Brief Test of Intelligence (KBIT) and Frontal Assessment Battery (FAB) tests, and fMRI signals were recorded in a resting state over a six-minute period. In addition, 22 controls, matched by age and sex, were evaluated with the same rs-fMRI procedure. RESULTS: There was a significant difference in complexity indicators between groups: the control group showed less complexity than the DS group. Moreover, the DS group showed more variance in the complexity indicator distributions than the control group. In the DS group, significant and negative relationships were found between some of the complexity indicators in some of the DMN networks and the cognitive performance scores. CONCLUSIONS: The DS group is characterized by more complex DMN networks and exhibits an inverse relationship between complexity and cognitive performance based on the negative parameter estimates.

Resting-state default mode network connectivity in young individuals with Down syndrome.

BACKGROUND: Down syndrome (DS) is a chromosomal disorder that causes intellectual disability. Few studies have been conducted on functional connectivity using resting-state fMRI (functional magnetic resonance imaging) signals or more specifically, on the relevant structure and density of the default mode network (DMN). Although data on this issue have been reported in adult DS individuals (age: >45 years), the DMN properties in young DS individuals have not been studied. The aim of this study was to describe the density and structure of the DMN network from fMRI signals in young DS (age: <36 years). METHOD: A sample of 22 young people with DS between the ages of 16 and 35 (M = 25.5 and SD = 5.1) was recruited in various centers for people with intellectual disability (ID). In addition to sociodemographic data, a six-minute fMRI session was recorded with a 3. T Philips Ingenia scanner. A control group of 22 young people, matched by age and gender, was obtained from the Human Connectome Project (to compare the networks properties between groups). RESULTS: The values of the 48 ROIs that configured the DMN were obtained, and the connectivity graphs for each subject, the average connectivity graph for each group, the clustering and degree values for each ROI, and the average functional connectivity network were estimated. CONCLUSIONS: A higher density of overactivation was identified in DS group in the ventral, sensorimotor, and visual DMN networks, although within a framework of a wide variability of connectivity patterns in comparison with the control group network. These results extend our understanding of the functional connectivity networks pattern and intrasubject variability in DS.

Eliminate the effect of severity of the Personal Outcomes Scale: Linear regression in persons with intellectual disability.

BACKGROUND: The Personal Outcomes Scale (POS) is used to assess quality of life (QoL) in people with intellectual disability (ID) but the results are influenced by the severity of the disability. To address this issue, we present the standardization of the Spanish adaptation of the POS. One of the limitations of the Classical Test Theory is the differential effect in some items due to the effect of an external variable. For this reason, we propose the use of multiple linear regressions. METHOD: We used a sample of 529 people with ID, along with 522 professionals and 462 parents who were administered the POS in order to carry out an in-depth psychometric study. For the analysis, we used the correction strategy by multiple linear regressions to generate centiles corrected for the severity effect of ID. RESULTS: Following this technique, the results show the centiles from the raw POS score corrected for the effect of the severity of ID. CONCLUSIONS: This standardization technique is a feasible option to provide a QoL scale without biased results due to the severity of ID.

Using fMRI to Assess Brain Activity in People With Down Syndrome: A Systematic Review.

Background: In the last few years, many investigations have focused on brain activity in general and in populations with different pathologies using non-invasive techniques such as electroencefalography (EEG), positron emission tomography (PET), functional magnetic resonance imaging (fMRI) and magnetic resonance imaging (MRI). However, the use of non-invasive techniques to detect brain signals to evaluate the cognitive activity of people with Down syndrome (DS) has not been sufficiently addressed. The objective of this study is to describe the state-of-the-art in fMRI techniques for recording brain signals in people with DS. Method: A systematic review was performed based on PRISMA recommendations; only nine papers on this topic have been published. Three independent researchers selected all relevant information from each paper. Analyses of information concordance showed a high value of agreement between researchers. Results: Although few relevant works have been published, the use of fMRI in people with DS is becoming an appropriate option to study brain function in this population. Of the nine identified papers, five used task designs, and four used resting-state paradigms. Conclusion: Thus, we emphasize the need to incorporate rigorous cognitive activity procedures in evaluations of the DS population. We suggest several factors (such as head correction movements and paired sample techniques) that must be considered when designing an fMRI study with a task or a resting-state paradigm in a DS population.

Relationship between Quality of Life and the Complexity of Default Mode Network in Resting State Functional Magnetic Resonance Image in Down Syndrome.

BACKGROUND: The study of the Default Mode Network (DMN) has been shown to be sensitive for the recognition of connectivity patterns between the brain areas involved in this network. It has been hypothesized that the connectivity patterns in this network are related to different cognitive states. PURPOSE: In this study, we explored the relationship that can be estimated between these functional connectivity patterns of the DMN with the Quality-of-Life levels in people with Down syndrome, since no relevant data has been provided for this population. METHODS: 22 young people with Down syndrome were evaluated; they were given a large evaluation battery that included the Spanish adaptation of the Personal Outcome Scale (POS). Likewise, fMRI sequences were obtained on a 3T resonator. For each subject, the DMN functional connectivity network was studied by estimating the indicators of complexity networks. The variability obtained in the Down syndrome group was studied by taking into account the Quality-of-Life distribution. RESULTS: There is a negative correlation between the complexity of the connectivity networks and the Quality-of-Life values. CONCLUSIONS: The results are interpreted as evidence that, even at rest, connectivity levels are detected as already shown in the community population and that less intense connectivity levels correlate with higher levels of Quality of Life in people with Down syndrome.

Longitudinal Estimation of the Clinically Significant Change in the Treatment of Major Depression Disorder.

Background: Although major depressive disorder is usually treated with antidepressants, only 50-70% of the patients respond to this treatment. This study applied Jacobson and Truax's (1991) methodology (reliable change index, RCI) to a sample of depressive patients being treated with one of two antidepressants to evaluate their functioning and the effect of certain variables such as severity and age. Method: Seventy-three depressive patients medicated with Escitalopram (n = 37) or Duloxetine (n = 36) were assessed using the Hamilton depression rating scale over a 24-week period. Results: They indicate that the RCI stabilizes in an absolute way starting in week 16, and it is not until week 24 that all of the patients become part of the functional population. We found limited statistical significance with respect to the RCI and the external variables. Conclusion: Our study suggests the need to accompany the traditional statistical methodology with some other clinical estimation systems capable of going beyond a simple subtraction between pre and posttreatment values. Hence, it is concluded that RCI estimations could be stronger and more stable than the classical statistical techniques.