Neurogenetic profiles delineate large-scale connectivity dynamics of the human brain

Experimental and modeling work of neural activity has described recurrent and attractor dynamic patterns in cerebral microcircuits. However, it is still poorly understood whether similar dynamic principles exist or can be generalizable to the large-scale level. Here, we applied dynamic graph theory-based analyses to evaluate the dynamic streams of whole-brain functional connectivity over time across cognitive states. Dynamic connectivity in local networks is located in attentional areas during tasks and primary sensory areas during rest states, and dynamic connectivity in distributed networks converges in the default mode network (DMN) in both task and rest states. Importantly, we find that distinctive dynamic connectivity patterns are spatially associated with Allen Human Brain Atlas genetic transcription levels of synaptic long-term potentiation and long-term depression-related genes. Our findings support the neurobiological basis of large-scale attractor-like dynamics in the heteromodal cortex within the DMN, irrespective of cognitive state.This work has been partially supported by the National Institutes of Health (NIH) grant K23EB019023 (to J.S.), Postdoctoral Fellowship Program from the Basque Country Government and Bizkaia Talent (to I.D.)

Measuring cortical connectivity in Alzheimer's disease as a brain neural network pathology: Toward clinical applications

Objectives: The objective was to review the literature on diffusion tensor imaging as well as resting-state functional magnetic resonance imaging and electroencephalography (EEG) to unveil neuroanatomical and neurophysiological substrates of Alzheimer’s disease (AD) as a brain neural network pathology affecting structural and functional cortical connectivity underlying human cognition. Methods: We reviewed papers registered in PubMed and other scientific repositories on the use of these techniques in amnesic mild cognitive impairment (MCI) and clinically mild AD dementia patients compared to cognitively intact elderly individuals (Controls). Results: Hundreds of peer-reviewed (cross-sectional and longitudinal) papers have shown in patients with MCI and mild AD compared to Controls (1) impairment of callosal (splenium), thalamic, and anterior–posterior white matter bundles; (2) reduced correlation of resting state blood oxygen level-dependent activity across several intrinsic brain circuits including default mode and attention-related networks; and (3) abnormal power and functional coupling of resting state cortical EEG rhythms. Clinical applications of these measures are still limited. Conclusions: Structural and functional (in vivo) cortical connectivity measures represent a reliable marker of cerebral reserve capacity and should be used to predict and monitor the evolution of AD and its relative impact on cognitive domains in pre-clinical, prodromal, and dementia stages of AD. (JINS, 2016, 22, 138–163

Visual search task immediate training effects on task-related functional connectivity

This is a pre-print of an article published in [ Brain Imaging and Behavior. The final authenticated version is available online at: https://doi.org/10.1007/s11682-018-9993-yBrain plasticity occurs over the course of the human lifetime. Learning and training modify our neuronal synapses and adapt our brain activity, from priming effects in modal areas to higher-order changes in the association cortex. The current state of the art suggests that learning and training effects might induce large-scale brain connectivity changes. Here, we used task-fMRI data and graph-based approaches to study the immediate brain changes in functional connections associated with training on a visual search task, and the individual differences in learning were studied by means of brain-behavior correlations. In a previous work, we found that trained participants improved their response speed on a visual search task by 31%, whereas the control group hardly changed. In the present study, we showed that trained individuals changed regional connections (local links) in cortical areas devoted to the specific visual search processes and to areas that support information integration, and largely modified distributed connections (distant links) linking primary visual areas to specific attentional and cognitive control areas. In addition, we found that the individuals with the most enhanced connectivity in the dorsolateral prefrontal cortex performed the task faster after training. The observed behavioral and brain connectivity findings expand our understanding of large-scale dynamic readjustment of the human brain after learning experiences

Hubs of belief networks across sociodemographic and ideological groups

Beliefs are essential components of the human mind, as they define personal identity, integration and adaptation to social groups. Most theoretical studies suggest that beliefs are organized as structured networks: the so-called belief system. According to these studies and their empirical implementation using graph-theoretical approaches, a belief is any proposition considered as true by the respondent. In a recent contribution, we introduced a novel operationalization: a proposition is a belief if (1) it is taken to be true; and (2) the subject declares to be willing to hold it even if irrefutable evidence were hypothetically argued against it. Here, we implement this operationalization using a graph theory approach to investigate the network organization of the belief system in a sample of 108 participants, as well as the differences between key ideological (left- vs. right-wingers) and sociodemographic features (younger vs. older, female vs. male). We identified a well-coordinated network of interlocked spiritual, prosocial and nature-related beliefs, which displays a dense core of 10 hub nodes. Moreover, we observed how specific social liberalist beliefs and transcendental or individualistic/prosocial viewpoints are articulated within left- and right-wingers networks or younger and older participants. Interestingly, we observed that females tend to engage in denser belief networks than male respondents. In conclusion, our research expands tangible scientific evidence of the belief system of humans through the network study of belief reports, which in turn opens innovative ways to study belief systems in social and clinical samples

Intrinsic Architecture Underlying the Relations among the Default, Dorsal Attention, and Frontoparietal Control Networks of the Human Brain

Human cognition is increasingly characterized as an emergent property of interactions among distributed, functionally specialized brain networks. We recently demonstrated that the antagonistic “default” and “dorsal attention” networks—subserving internally and externally directed cognition, respectively—are modulated by a third “frontoparietal control” network that flexibly couples with either network depending on task domain. However, little is known about the intrinsic functional architecture underlying this relationship. We used graph theory to analyze network properties of intrinsic functional connectivity within and between these three large-scale networks. Task-based activation from three independent studies were used to identify reliable brain regions (“nodes”) of each network. We then examined pairwise connections (“edges”) between nodes, as defined by resting-state functional connectivity MRI. Importantly, we used a novel bootstrap resampling procedure to determine the reliability of graph edges. Furthermore, we examined both full and partial correlations. As predicted, there was a higher degree of integration within each network than between networks. Critically, whereas the default and dorsal attention networks shared little positive connectivity with one another, the frontoparietal control network showed a high degree of between-network interconnectivity with each of these networks. Furthermore, we identified nodes within the frontoparietal control network of three different types—default-aligned, dorsal attention-aligned, and dual-aligned—that we propose play dissociable roles in mediating internetwork communication. The results provide evidence consistent with the idea that the frontoparietal control network plays a pivotal gate-keeping role in goal-directed cognition, mediating the dynamic balance between default and dorsal attention networks.Psycholog

Complexity Analysis of Cortical Surface Detects Changes in Future Alzheimer’s Disease Converters

Alzheimer’s disease (AD) is a neurological disorder that creates neurodegenerative changes at several structural and functional levels in human brain tissue. The fractal dimension (FD) is a quantitative parameter that characterizes the morphometric variability of the human brain. In this study we investigate spherical harmonic-based FD (SHFD), thickness and local gyrification index (LGI) to assess whether they identify cortical surface abnormalities toward the conversion to AD. We study 33 AD patients, 122 mild cognitive impairment (MCI) patients (50 MCI-converters and 29 MCI-non converters) and 32 healthy controls (HC). SHFD, thickness and LGI methodology allowed us to perform not only global but also local level assessments in each cortical surface vertex. First, we found that global SHFD decreased in AD and future MCI-converters compared to HC, and in MCI-converters compared to MCI-non-converters. Second, we found that local white matter SHFD was reduced in AD compared to HC and MCI mainly in medial temporal lobe. Third, local white matter SHFD was significantly reduced in MCI-converters compared to MCI-non-converters in distributed areas, including the medial frontal lobe. Thickness and LGI metrics presented a reduction in AD compared to HC. Thickness was significantly reduced in MCI-converters compared to healthy controls in entorhinal cortex and lateral temporal. In summary, SHFD was the only surface measure showing differences between MCI individuals that will convert or remain stable in the next four years. We suggest that SHFD may be an optimal complement to thickness loss analysis in monitoring longitudinal changes in preclinical and clinical stages of AD

The Organization of Local and Distant Functional Connectivity in the Human Brain

Information processing in the human brain arises from both interactions between adjacent areas and from distant projections that form distributed brain systems. Here we map interactions across different spatial scales by estimating the degree of intrinsic functional connectivity for the local (≤14 mm) neighborhood directly surrounding brain regions as contrasted with distant (>14 mm) interactions. The balance between local and distant functional interactions measured at rest forms a map that separates sensorimotor cortices from heteromodal association areas and further identifies regions that possess both high local and distant cortical-cortical interactions. Map estimates of network measures demonstrate that high local connectivity is most often associated with a high clustering coefficient, long path length, and low physical cost. Task performance changed the balance between local and distant functional coupling in a subset of regions, particularly, increasing local functional coupling in regions engaged by the task. The observed properties suggest that the brain has evolved a balance that optimizes information-processing efficiency across different classes of specialized areas as well as mechanisms to modulate coupling in support of dynamically changing processing demands. We discuss the implications of these observations and applications of the present method for exploring normal and atypical brain function.Psycholog

Positive Connectivity Predicts the Dynamic Intrinsic Topology of the Human Brain Network

Functional connectivity MRI (fcMRI) has become instrumental in facilitating research of human brain network organization in terms of coincident interactions between positive and negative synchronizations of large-scale neuronal systems. Although there is a common agreement concerning the interpretation of positive couplings between brain areas, a major debate has been made in disentangling the nature of negative connectivity patterns in terms of its emergence in several methodological approaches and its significance/meaning in specific neuropsychiatric diseases. It is still not clear what information the functional negative correlations or connectivity provides or how they relate to the positive connectivity. Through implementing stepwise functional connectivity (SFC) analysis and studying the causality of functional topological patterns, this study aims to shed light on the relationship between positive and negative connectivity in the human brain functional connectome. We found that the strength of negative correlations between voxel-pairs relates to their positive connectivity path-length. More importantly, our study describes how the spatio-temporal patterns of positive connectivity explain the evolving changes of negative connectivity over time, but not the other way around. This finding suggests that positive and negative connectivity do not display equivalent forces but shows that the positive connectivity has a dominant role in the overall human brain functional connectome. This phenomenon provides novel insights about the nature of positive and negative correlations in fcMRI and will potentially help new developments for neuroimaging biomarkers.This research was supported by grants from the National Institutes of Health K23EB019023 to JS, T32EB013180-06 to LO-T, Postdoctoral Fellowship Program from the Basque Country Government to ID and R01EB022574, R01MH108467 to JG, and Indiana Clinical and Translational Sciences Institute (UL1TR001108) to JG

Network interdigitations of Tau and amyloid-beta deposits define cognitive levels in aging

Amyloid-beta (Aβ) plaques and tau neurofibrillary tangles are pathological hallmarks of Alzheimer's disease (AD); their contribution to neurodegeneration and clinical manifestations are critical in understanding preclinical AD. At present, the mechanisms related to Aβ and tau pathogenesis leading to cognitive decline in older adults remain largely unknown. Here, we examined graph theory-based positron emission tomography (PET) analytical approaches, within and between tau and Aβ PET modalities, and tested the effects on cognitive changes in cognitively normal older adults (CN). Particularly, we focused on the network interdigitations of Aβ and tau deposits, along with cognitive test scores in CN at both baseline and 2-year follow-up (FU). We found highly significant Aβ-tau network integrations in AD vulnerable areas, as well as significant associations between those Aβ-tau interdigitations and general cognitive impairment in CN at baseline and FU. Our findings suggest a distinctive contribution of interlinking network relationships between Aβ and tau deposits in heteromodal areas of the human brain. They support a network-based interaction between Aβ and tau accumulations as a key factor for cognitive deterioration in CN prior to dementia. We examined network interaction patterns within single positron emission tomography (PET) modality, such as Aß-to-Aß or Tau-to-Tau correlations, and between different PET modalities, such as Aß-to-Tau or Tau-to-Aß, at high-resolution (voxel-level) in cognitively normal older adults (CN), using a graph theory-based analysis. We observed that the PET uptakes derived from Aß-to-Tau interdigitations were significantly associated with Alzheimer's Disease Assessment Scale-Cognitive Subscale in AD vulnerable brain areas, a finding confirmed by our longitudinal investigation. Therefore, our work suggests the preceding contribution of network interactions between Aß and tau deposits to explain initial cognitive changes in CN prior to the conversion of dementia

Memory decline evolves independently of disease activity in MS

The natural history of cognitive impairment in multiple sclerosis (MS) and its relationship with disease activity is not well known. In this study, we evaluate a prospective cohort of 44 MS patients who were followed every 3 months for 2 years. Cognitive evaluation was done at baseline and by the end of the study using the Brief Repeatable Battery-Neuropsychology. Clinical evaluation included assessment of new relapses and changes in disability (Extended Disability Status Scale (EDSS)) confirmed at 6 months. RESULTS: We found that verbal memory performance deteriorates after 2 years in patients with MS. These changes were observed in stable and active patients both in terms of relapses and disability progression, even at the beginning of the disease, and in patients with or without cognitive impairment at study entry. Attention and executive functions measured with the symbol digit modality test (SDMT) declined after 2 years in patients with confirmed disability progression. Furthermore, SDMT performance correlated with the EDSS change. CONCLUSIONS: Our findings indicate that verbal memory steadily declines in patients with MS from the beginning of the disease and independently of other parameters of disease activity