Nutritional supplement induced modulations in the functional connectivity of a porcine brain.

BACKGROUND: Functional connectivity (FC) measures statistical dependence between cortical brain regions. Studies of FC facilitate understanding of the brain's function and architecture that underpin normal cognition, behavior, and changes associated with various factors (e.g. nutritional supplements) at a large scale. OBJECTIVE: We aimed to identify modifications in FC patterns and targeted brain anatomies in piglets following perinatal intake of different nutritional diets using a graph theory based approach. METHODS: Forty-four piglets from four groups of pregnant sows, who were treated with nutritional supplements, including control diet, docosahexaenoic acid (DHA), egg yolk (EGG), and DHA + EGG, went through resting-state functional magnetic resonance imaging (rs-fMRI). We introduced the use of differential degree test (DDT) to identify differentially connected edges (DCEs). Simulation studies were first conducted to compare the DDT with permutation test, using three network structures at different noise levels. DDT was then applied to rs-fMRI data acquired from piglets. RESULTS: In simulations, the DDT showed a greater accuracy in detecting DCEs when compared with the permutation test. For empirical data, we found that the strength of internodal connectivity is significantly increased for more than 6% of edges in the EGG group and more than 8% of edges in the DHA and DHA + EGG groups, all compared to the control group. Moreover, differential wiring diagrams between group comparisons provided means to pinpoint brain hubs affected by nutritional supplements. CONCLUSION: DDT showed a greater accuracy of detection of DCEs and demonstrated EGG, DHA, and DHA + EGG supplemented diets lead to an improved internodal connectivity in the developing piglet brain.

Prefrontal cortical hemodynamics and functional network organization during Tai Chi standing meditation: an fNIRS study.

Introduction: Tai Chi standing meditation (Zhan Zhuang, also called pile standing) is characterized by meditation, deep breathing, and mental focus based on theories of traditional Chinese medicine. The purpose of the present study was to explore prefrontal cortical hemodynamics and the functional network organization associated with Tai Chi standing meditation by using functional near-infrared spectroscopy (fNIRS). Methods: Twenty-four channel fNIRS signals were recorded from 24 male Tai Chi Quan practitioners (54.71 ± 8.04 years) while standing at rest and standing during Tai Chi meditation. The general linear model and the SPM method were used to analyze the fNIRS signals. Pearson correlation was calculated to determine the functional connectivity between the prefrontal cortical sub-regions. The small world properties of the FC networks were then further analyzed based on graph theory. Results: During Tai Chi standing meditation, significantly higher concentrations of oxygenated hemoglobin were observed in bilateral dorsolateral prefrontal cortex (DLPFC), ventrolateral prefrontal cortex (VLPFC), frontal eye field (FEF), and pre-motor cortex (PMC) compared with the values measured during standing rest (p < 0.05). Simultaneously, significant decreases in deoxygenated hemoglobin concentration were observed in left VLPFC, right PMC and DLPFC during Tai Chi standing meditation than during standing rest (p < 0.05). Functional connectivity between the left and right PFC was also significantly stronger during the Tai Chi standing meditation (p < 0.05). The functional brain networks exhibited small-world architecture, and more network hubs located in DLPFC and VLPFC were identified during Tai Chi standing meditation than during standing rest. Discussion: These findings suggest that Tai Chi standing meditation introduces significant changes in the cortical blood flow and the brain functional network organization.

Study on neural entrainment to continuous speech using dynamic source connectivity analysis.

Objective.Many recent studies investigating the processing of continuous natural speech have employed electroencephalography (EEG) due to its high temporal resolution. However, most of these studies explored the response mechanism limited to the electrode space. In this study, we intend to explore the underlying neural processing in the source space, particularly the dynamic functional interactions among different regions during neural entrainment to speech.Approach.We collected 128-channel EEG data while 22 participants listened to story speech and time-reversed speech using a naturalistic paradigm. We compared three different strategies to determine the best method to estimate the neural tracking responses from the sensor space to the brain source space. After that, we used dynamic graph theory to investigate the source connectivity dynamics among regions that were involved in speech tracking.Main result.By comparing the correlations between the predicted neural response and the original common neural response under the two experimental conditions, we found that estimating the common neural response of participants in the electrode space followed by source localization of neural responses achieved the best performance. Analysis of the distribution of brain sources entrained to story speech envelopes showed that not only auditory regions but also frontoparietal cognitive regions were recruited, indicating a hierarchical processing mechanism of speech. Further analysis of inter-region interactions based on dynamic graph theory found that neural entrainment to speech operates across multiple brain regions along the hierarchical structure, among which the bilateral insula, temporal lobe, and inferior frontal gyrus are key brain regions that control information transmission. All of these information flows result in dynamic fluctuations in functional connection strength and network topology over time, reflecting both bottom-up and top-down processing while orchestrating computations toward understanding.Significance.Our findings have important implications for understanding the neural mechanisms of the brain during processing natural speech stimuli.

The Impact of Mindfulness on Functional Brain Connectivity and Peripheral Inflammation in Breast Cancer Survivors with Cognitive Complaints.

BACKGROUND: Cancer-related cognitive impairment (CRCI) has been linked to functional brain changes and inflammatory processes. Hence, interventions targeting these underlying mechanisms are needed. In this study, we investigated the effects of a mindfulness-based intervention on brain function and inflammatory profiles in breast cancer survivors with CRCI. METHODS: Female breast cancer survivors reporting cognitive complaints (n = 117) were randomly assigned to a mindfulness-based intervention (n = 43), physical training (n = 36), or waitlist control condition (n = 38). Region-of-interest (ROI) and graph theory analyses of resting state functional MRI data were performed to study longitudinal group differences in functional connectivity and organization in the default mode, dorsal attention, salience, and frontoparietal network. Additionally, bead-based immunoassays were used to investigate the differences in inflammatory profiles on serum samples. Measures were collected before, immediately after and three months post-intervention. RESULTS: No ROI-to-ROI functional connectivity changes were identified. Compared to no intervention, graph analysis showed a larger decrease in clustering coefficient after mindfulness and physical training. Additionally, a larger increase in global efficiency after physical training was identified. Furthermore, the physical training group showed a larger decrease in an inflammatory profile compared to no intervention (IL-12p70, IFN-γ, IL-1ß, and IL-8). CONCLUSION: Both mindfulness and physical training induced changes in the functional organization of networks related to attention, emotion processing, and executive functioning. While both interventions reduced functional segregation, only physical training increased functional integration of the neural network. In conclusion, physical training had the most pronounced effects on functional network organization and biomarkers of inflammation, two mechanisms that might be involved in CRCI.

Dysfunctional Cortical Gradient Topography in Treatment-Resistant Major Depressive Disorder.

BACKGROUND: Treatment-resistant depression (TRD) refers to patients with major depressive disorder who do not remit after 2 or more antidepressant trials. TRD is common and highly debilitating, but its neurobiological basis remains poorly understood. Recent neuroimaging studies have revealed cortical connectivity gradients that dissociate primary sensorimotor areas from higher-order associative cortices. This fundamental topography determines cortical information flow and is affected by psychiatric disorders. We examined how TRD impacts gradient-based hierarchical cortical organization. METHODS: In this secondary study, we analyzed resting-state functional magnetic resonance imaging data from a mindfulness-based intervention enrolling 56 patients with TRD and 28 healthy control subjects. Using gradient extraction tools, baseline measures of cortical gradient dispersion within and between functional brain networks were derived, compared across groups, and associated with graph theoretical measures of network topology. In patients, correlation analyses were used to associate measures of cortical gradient dispersion with clinical measures of anxiety, depression, and mindfulness at baseline and following the intervention. RESULTS: Cortical gradient dispersion was reduced within major intrinsic brain networks in patients with TRD. Reduced cortical gradient dispersion correlated with increased network degree assessed through graph theory-based measures of network topology. Lower dispersion among default mode, control, and limbic network nodes related to baseline levels of trait anxiety, depression, and mindfulness. Patients' baseline limbic network dispersion predicted trait anxiety scores 24 weeks after the intervention. CONCLUSIONS: Our findings provide preliminary support for widespread alterations in cortical gradient architecture in TRD, implicating a significant role for transmodal and limbic networks in mediating depression, anxiety, and lower mindfulness in patients with TRD.

Organization of neurochemical interactions in young and older brains as revealed with a network approach: Evidence from proton magnetic resonance spectroscopy (1H-MRS).

Aging is associated with alterations in the brain including structural and metabolic changes. Previous research has focused on neurometabolite level differences associated to age in a variety of brain regions, but the relationship among metabolites across the brain has been much less studied. Investigating these relationships can reveal underlying neurometabolic processes, their interdependency, and their progress throughout the lifespan. Using 1H-MRS, we investigated the relationship among metabolite concentrations of N-acetylaspartate (NAA), creatine (Cr), choline (Cho), myo-Inositol (mIns) and glutamate-glutamine complex (Glx) in seven voxel locations, i.e., bilateral sensorimotor cortex, bilateral striatum, pre-supplementary motor area, right inferior frontal gyrus and occipital cortex. These measurements were performed on 59 human participants divided in two age groups: young adults (YA: 23.2 ± 4.3; 18-34 years) and older adults (OA: 67.5 ± 3.9; 61-74 years). Our results showed age-related differences in NAA, Cho, and mIns across brain regions, suggesting the presence of neurodegeneration and altered gliosis. Moreover, associative patterns among NAA, Cho and Cr were observed across the selected brain regions, which differed between young and older adults. Whereas most of metabolite concentrations were inhomogeneous across different brain regions, Cho levels were shown to be strongly related across brain regions in both age groups. Finally, we found metabolic associations between homologous brain regions (SM1 and striatum) in the OA group, with NAA showing a significant correlation between bilateral sensorimotor cortices (SM1) and mIns levels being correlated between the bilateral striata. We posit that a network perspective provides important insights regarding the potential interactions among neurochemicals underlying metabolic processes at a local and global level and their relationship with aging.

The Effect of dry Needling in Chronic Stroke with a complex Network Approach: A Case Study.

Background: Dry Needling (DN) has been demonstrated to be effective in improving sensorimotor function and spasticity in patients with chronic stroke. Electroencephalogram (EEG) has been used to analyze if DN has effects on the central nervous system of patients with stroke. There are no studies on how DN works in patients with chronic stroke based on EEG analysis using complex networks. Objective: The aim of this study was to assess how DN works when it is applied in a patient with stroke, using the graph theory. Methods: One session of DN was applied to the spastic brachialis muscle of a 62-year-old man with right hemiplegia after stroke. EEG was used to analyze the effects of DN following metrics that measure the topological configuration: 1) network density, 2) clustering coefficient, 3) average shortest path length, 4) betweenness centrality, and 5) small-worldness. Measurements were taken before and during DN. Results: An improvement of the brain activity was observed in this patient with stroke after the application of DN, which led to variations of local parameters of the brain network in the delta, theta and alpha bands, and inclined towards those of the healthy control bands. Conclusions: This case study showed the positive effects of DN on brain network of a patient with chronic stroke.

Subclinical alterations of resting state functional brain network for adjunctive bright light therapy in nonseasonal major depressive disorder: A double blind randomized controlled trial.

Introduction: The treatment effect of bright light therapy (BLT) on major depressive disorder (MDD) has been proven, but the underlying mechanism remains unclear. Neuroimaging biomarkers regarding disease alterations in MDD and treatment response are rarely focused on BLT. This study aimed to identify the modulatory mechanism of BLT in MDD using resting-state functional magnetic resonance imaging (rfMRI). Materials and methods: This double-blind, randomized controlled clinical trial included a dim red light (dRL) control group and a BLT experimental group. All participants received light therapy for 30 min every morning for 4 weeks. The assessment of the Hamilton Depression Rating Scale-24 (HAMD-24) and brain MRI exam were performed at the baseline and the 4-week endpoint. The four networks in interest, including the default mode network (DMN), frontoparietal network (FPN), salience network (SN), and sensorimotor network (SMN), were analyzed. Between-group differences of the change in these four networks were evaluated. Results: There were 22 and 21 participants in the BLT and dRL groups, respectively. Age, sex, years of education, baseline severity, and improvement in depressive symptoms were not significantly different between the two groups. The baseline rfMRI data did not show any significant functional connectivity differences within the DMN, FPN, SN, and SMN between the two groups. Compared with the dRL group, the BTL group showed significantly increased functional connectivity after treatment within the DMN, FPN, SN, and SMN. Graph analysis of the BLT group demonstrated an enhancement of betweenness centrality and global efficiency. Conclusion: BLT can enhance intra-network functional connectivity in the DMN, FPN, SN, and SMN for MDD patients. Furthermore, BLT improves the information processing of the whole brain. Clinical trial registration: The ClinicalTrials.gov identifier was NCT03941301.

Functional brain-wide network mapping during acute stress exposure in rats: Interaction between the lateral habenula and cortical, amygdalar, hypothalamic and monoaminergic regions.

Upon stress exposure, a broad network of structures comes into play in order to provide adequate responses and restore homeostasis. It has been known for decades that the main structures engaged during the stress response are the medial prefrontal cortex, the amygdala, the hippocampus, the hypothalamus, the monoaminergic systems (noradrenaline, dopamine and serotonin) and the periaqueductal gray. The lateral habenula (LHb) is an epithalamic structure directly connected to prefrontal cortical areas and to the amygdala, whereas it functionally interacts with the hippocampus. Also, it is a main modulator of monoaminergic systems. The LHb is activated upon exposure to basically all types of stressors, suggesting it is also involved in the stress response. However, it remains unknown if and how the LHb functionally interacts with the broad stress response network. In the current study we performed in rats a restraint stress procedure followed by immunohistochemical staining of the c-Fos protein throughout the brain. Using graph theory-based functional connectivity analyses, we confirm the principal hubs of the stress network (e.g., prefrontal cortex, amygdala and periventricular hypothalamus) and show that the LHb is engaged during stress exposure in close interaction with the medial prefrontal cortex, the lateral septum and the medial habenula. In addition, we performed DREADD-induced LHb inactivation during the same restraint paradigm in order to explore its consequences on the stress response network. This last experiment gave contrasting results as the DREADD ligand alone, clozapine-N-oxide, was able to modify the network.

Transferring network analysis to the study of potential biogeochemical interactions of phosphorus-relevant elements in floodplain subsoils - A new use case for the Soilscape Network Approach (SNAp).

Subsurface phosphorus (P) loss from deep P stocks in floodplain subsoils can contribute to eutrophication of freshwaters. To date, knowledge on the complex biogeochemical interactions of P in floodplain subsoils is too scarce to enable targeted P management to mitigate subsurface P loss from deep P stocks. We propose using graph theory and the Soilscape Network Approach (SNAp) based on correlations between P-relevant elements to study these complex biogeochemical interactions in the soilscape. Complex interactions of several elements in soils are difficult to investigate from a holistic perspective with conventional data analysis. We translated soil element data from topsoils and subsoils of terrestrial sites, proximal and distal floodplain sites into relational data and analyzed network structure, centrality, and modularity. The results indicate that a higher frequency of groundwater level fluctuations in distal subsoils and proximal topsoils could result in 24-44 % less biogeochemical interaction compared to sites with stable conditions. Impeded microbial processes on the frequently disturbed sites may explain this finding. Our analyses suggest biogeochemical differences between floodplain topsoils and subsoils expressed in 24 % lower and 75 % higher network connectivity in distal and proximal subsoils (respectively). We also found 22 % lower network connectivity in distal than proximal floodplain subsoils, suggesting biogeochemical differences between both soil sections. These findings imply that floodplain P management should not take a whole-floodplain approach but a 3D-approach, which differentiates laterally between floodplain zones and vertically between soil sections. In addition, SNAp indicated that Fe(II) oxides are important in P biogeochemistry of floodplain subsoils but are not the key element. Instead, labile P forms are suggested to have different major associations in distal (Alox, Feox) versus proximal deep P stocks (Alox, Mn, Ca). Our study provides new insights into the biogeochemistry of deep P stocks in floodplain subsoils which require targeted validation by other methods.

Topological changes of brain network during mindfulness meditation: an exploratory source level magnetoencephalographic study.

We have previously evidenced that Mindfulness Meditation (MM) in experienced meditators (EMs) is associated with long-lasting topological changes in resting state condition. However, what occurs during the meditative phase is still debated. Utilizing magnetoencephalography (MEG), the present study is aimed at comparing the topological features of the brain network in a group of EMs (n = 26) during the meditative phase with those of individuals who had no previous experience of any type of meditation (NM group, n = 29). A wide range of topological changes in the EM group as compared to the NM group has been shown. Specifically, in EMs, we have observed increased betweenness centrality in delta, alpha, and beta bands in both cortical (left medial orbital cortex, left postcentral area, and right visual primary cortex) and subcortical (left caudate nucleus and thalamus) areas. Furthermore, the degree of beta band in parietal and occipital areas of EMs was increased too. Our exploratory study suggests that the MM can change the functional brain network and provides an explanatory hypothesis on the brain circuits characterizing the meditative process.

A preliminary study of the effects of mindfulness-based cognitive therapy on structural brain networks in mood-dysregulated youth with a familial risk for bipolar disorder.

BACKGROUND: Mindfulness-based cognitive therapy for children (MBCT-C), as a psychotherapeutic intervention, has been shown to be effective for treating mood dysregulation (MD). While previous neuroimaging studies of MD have reported both pre-treatment structural and functional alterations, the effects of MBCT-C on brain morphological network organisation has not been investigated. METHODS: We investigated brain morphological network organisation in 10 mood-dysregulated youth with familial risk for bipolar disorder and 15 matched healthy comparison youth (HC). Effects of 12 weeks of MBCT-C were examined in the mood-dysregulated youth. Topological properties of brain networks used for analyses were constructed based on morphological similarities in regional grey matter using a graph-theory approach using MRI data. RESULTS: At baseline, compared with the HC group, the mood-dysregulated group exhibited increased global efficiency (Eglob ), decreased path length (Lp ), and abnormal nodal properties, mainly in the limbic system. Right temporal pole alterations at baseline predicted change in Child and Adolescent Mindfulness Measure scores after treatment. The mood-dysregulated group showed significant decreases in both the Eglob and Lp metrics after MBCT-C, suggesting an improved capacity for optimal information processing. Changes in Lp were correlated with changes in Emotion Regulation Checklist scores. Our results show significant topological alterations in the mood-dysregulated group as compared to controls at baseline. After MBCT-C, disrupted topological properties in the mood-dysregulated group were significantly reduced. CONCLUSION: MBCT-C may facilitate clinically meaningful changes in the brain structural network in mood-dysregulated individuals.

Network differentiation: A computational method of pathogenesis diagnosis in traditional Chinese medicine based on systems science.

Resembling the role of disease diagnosis in Western medicine, pathogenesis (also called Bing Ji) diagnosis is one of the utmost important tasks in traditional Chinese medicine (TCM). In TCM theory, pathogenesis is a complex system composed of a group of interrelated factors, which is highly consistent with the character of systems science (SS). In this paper, we introduce a heuristic definition called pathogenesis network (PN) to represent pathogenesis in the form of the directed graph. Accordingly, a computational method of pathogenesis diagnosis, called network differentiation (ND), is proposed by integrating the holism principle in SS. ND consists of three stages. The first stage is to generate all possible diagnoses by Cartesian Product operated on specified prior knowledge corresponding to the input symptoms. The second stage is to screen the validated diagnoses by holism principle. The third stage is to pick out the clinical diagnosis by physician-computer interaction. Some theorems are stated and proved for the further optimization of ND in this paper. We conducted simulation experiments on 100 clinical cases. The experimental results show that our proposed method has an excellent capability to fit the holistic thinking in the process of physician inference.

Increased segregation of structural brain networks underpins enhanced broad cognitive abilities of cognitive training.

A major challenge in the cognitive training field is inducing broad, far-transfer training effects. Thus far, little is known about the neural mechanisms underlying broad training effects. Here, we tested a set of competitive hypotheses regarding the role of brain integration versus segregation underlying the broad training effect. We retrospectively analyzed data from a randomized controlled trial comparing neurocognitive effects of vision-based speed of processing training (VSOP) and an active control consisting of mental leisure activities (MLA) in older adults with MCI. We classified a subset of participants in the VSOP as learners, who showed improvement in executive function and episodic memory. The other participants in the VSOP (i.e., VSOP non-learners) and a subset of participants in the MLA (i.e., MLA non-learners) served as controls. Structural brain networks were constructed from diffusion tensor imaging. Clustering coefficients (CCs) and characteristic path lengths were computed as measures of segregation and integration, respectively. Learners showed significantly greater global CCs after intervention than controls. Nodal CCs were selectively enhanced in cingulate cortex, parietal regions, striatum, and thalamus. Among VSOP learners, those with more severe baseline neurodegeneration had greater improvement in segregation after training. Our findings suggest broad training effects are related to enhanced segregation in selective brain networks, providing insight into cognitive training related neuroplasticity.

Network-level functional topological changes after mindfulness-based cognitive therapy in mood dysregulated adolescents at familial risk for bipolar disorder: a pilot study.

BACKGROUND: Given that psychopharmacological approaches routinely used to treat mood-related problems may result in adverse outcomes in mood dysregulated adolescents at familial risk for bipolar disorder (BD), Mindfulness-Based Cognitive Therapy for Children (MBCT-C) provides an alternative effective and safe option. However, little is known about the brain mechanisms of beneficial outcomes from this intervention. Herein, we aimed to investigate the network-level neurofunctional effects of MBCT-C in mood dysregulated adolescents. METHODS: Ten mood dysregulated adolescents at familial risk for BD underwent a 12-week MBCT-C intervention. Resting-state functional magnetic resonance imaging (fMRI) was performed prior to and following MBCT-C. Topological metrics of three intrinsic functional networks (default mode network (DMN), fronto-parietal network (FPN) and cingulo-opercular network (CON)) were investigated respectively using graph theory analysis. RESULTS: Following MBCT-C, mood dysregulated adolescents showed increased global efficiency and decreased characteristic path length within both CON and FPN. Enhanced functional connectivity strength of frontal and limbic areas were identified within the DMN and CON. Moreover, change in characteristic path length within the CON was suggested to be significantly related to change in the Emotion Regulation Checklist score. CONCLUSIONS: 12-week MBCT-C treatment in mood dysregulated adolescents at familial risk for BD yield network-level neurofunctional effects within the FPN and CON, suggesting enhanced functional integration of the dual-network. Decreased characteristic path length of the CON may be associated with the improvement of emotion regulation following mindfulness training. However, current findings derived from small sample size should be interpreted with caution. Future randomized controlled trials including larger samples are critical to validate our findings.

Neural Mechanisms of Acceptance and Commitment Therapy for Chronic Pain: A Network-Based fMRI Approach.

Over 100 million Americans suffer from chronic pain (CP), which causes more disability than any other medical condition in the United States at a cost of $560-$635 billion per year (Institute of Medicine, 2011). Opioid analgesics are frequently used to treat CP. However, long term use of opioids can cause brain changes such as opioid-induced hyperalgesia that, over time, increase pain sensation. Also, opioids fail to treat complex psychological factors that worsen pain-related disability, including beliefs about and emotional responses to pain. Cognitive behavioral therapy (CBT) can be efficacious for CP. However, CBT generally does not focus on important factors needed for long-term functional improvement, including attainment of personal goals and the psychological flexibility to choose responses to pain. Acceptance and Commitment Therapy (ACT) has been recognized as an effective, non-pharmacologic treatment for a variety of CP conditions (Gutierrez et al., 2004). However, little is known about the neurologic mechanisms underlying ACT. We conducted an ACT intervention in women (n = 9) with chronic musculoskeletal pain. Functional magnetic resonance imaging (fMRI) data were collected pre- and post-ACT, and changes in functional connectivity (FC) were measured using Network-Based Statistics (NBS). Behavioral outcomes were measured using validated assessments such as the Acceptance and Action Questionnaire (AAQ-II), the Chronic Pain Acceptance Questionnaire (CPAQ), the Center for Epidemiologic Studies Depression Scale (CES-D), and the NIH Toolbox Neuro-QoLTM (Quality of Life in Neurological Disorders) scales. Results suggest that, following the 4-week ACT intervention, participants exhibited reductions in brain activation within and between key networks including self-reflection (default mode, DMN), emotion (salience, SN), and cognitive control (frontal parietal, FPN). These changes in connectivity strength were correlated with changes in behavioral outcomes including decreased depression and pain interference, and increased participation in social roles. This study is one of the first to demonstrate that improved function across the DMN, SN, and FPN may drive the positive outcomes associated with ACT. This study contributes to the emerging evidence supporting the use of neurophysiological indices to characterize treatment effects of alternative and complementary mind-body therapies.

Mendelian and Sporadic FTD: Disease Risk and Avenues from Genetics to Disease Pathways Through In Silico Modelling.

Frontotemporal dementia (FTD) is regarded as the second most common form of young-onset dementia after Alzheimer's disease (AD).FTD is a complex neurodegenerative condition characterised by heterogeneous clinical, pathological and genetic features. No efficient measures for early diagnosis and therapy are available.Familial (Mendelian) forms of disease have been studied over the past 20 years. Conversely, the genetics of sporadic forms of FTD (up to 70% of all cases) is understudied and still poorly understood. All this taken together suggests that more powerful and in-depth studies to tackle missing heritability and define the genetic architecture of sporadic FTD, with particular focus on the different subtypes (i.e. clinical and pathological diagnoses), are warranted.In parallel, it will be critical to translate the genetic findings into functional understanding of disease, i.e. moving from the identification of risk genes to the definition of risk pathways. It will be necessary to implement a paradigm shift - from reductionist to holistic approaches - to better interpret genetics and assist functional studies aimed at modelling and validating such risk pathways.In this chapter, we focus on the heterogeneous features of FTD touching upon its complex genetic landscape and discuss how novel approaches (e.g. computationally driven systems biology) promise to revolutionise the translation of genetic information into functional understanding of disease pathogenesis.

Abnormalities in the thalamo-cortical network in patients with functional constipation.

Functional constipation (FCon) is a common functional gastrointestinal disorder (FGID); neuroimaging studies have shown brain functional abnormalities in thalamo-cortical regions in patients with FGID. However, association between FCon and topological characteristics of brain networks remains largely unknown. We employed resting-state functional magnetic resonance imaging (RS-fMRI) and graph theory approach to investigate functional brain topological organization in 42 patients with FCon and 41 healthy controls (HC) from perspectives of global, regional and modular levels. Results showed patients with FCon had a significantly lower normalized clustering coefficient and small-worldness, implying decreased brain functional connectivity. Regions showed altered nodal degree and efficiency mainly located in the thalamus, rostral anterior cingulate cortex (rACC), and supplementary motor area (SMA), which are involved in somatic/sensory, emotional processing and motor-control. For the modular analysis, thalamus, rACC and SMA had an aberrant within-module nodal degree and nodal efficiency, and thalamus-related network exhibited abnormal interaction with the limbic network (amygdala and hippocampal gyrus). Nodal degree in the thalamus was negatively correlated with difficulty of defecation, and nodal degree in the rACC was negatively correlated with sensation of incomplete evacuation. These findings indicated that FCon was associated with abnormalities in the thalamo-cortical network.

Preterm birth leads to impaired rich-club organization and fronto-paralimbic/limbic structural connectivity in newborns.

Prematurity disrupts brain development during a critical period of brain growth and organization and is known to be associated with an increased risk of neurodevelopmental impairments. Investigating whole-brain structural connectivity alterations accompanying preterm birth may provide a better comprehension of the neurobiological mechanisms related to the later neurocognitive deficits observed in this population. Using a connectome approach, we aimed to study the impact of prematurity on neonatal whole-brain structural network organization at term-equivalent age. In this cohort study, twenty-four very preterm infants at term-equivalent age (VPT-TEA) and fourteen full-term (FT) newborns underwent a brain MRI exam at term age, comprising T2-weighted imaging and diffusion MRI, used to reconstruct brain connectomes by applying probabilistic constrained spherical deconvolution whole-brain tractography. The topological properties of brain networks were quantified through a graph-theoretical approach. Furthermore, edge-wise connectivity strength was compared between groups. Overall, VPT-TEA infants' brain networks evidenced increased segregation and decreased integration capacity, revealed by an increased clustering coefficient, increased modularity, increased characteristic path length, decreased global efficiency and diminished rich-club coefficient. Furthermore, in comparison to FT, VPT-TEA infants had decreased connectivity strength in various cortico-cortical, cortico-subcortical and intra-subcortical networks, the majority of them being intra-hemispheric fronto-paralimbic and fronto-limbic. Inter-hemispheric connectivity was also decreased in VPT-TEA infants, namely through connections linking to the left precuneus or left dorsal cingulate gyrus - two regions that were found to be hubs in FT but not in VPT-TEA infants. Moreover, posterior regions from Default-Mode-Network (DMN), namely precuneus and posterior cingulate gyrus, had decreased structural connectivity in VPT-TEA group. Our finding that VPT-TEA infants' brain networks displayed increased modularity, weakened rich-club connectivity and diminished global efficiency compared to FT infants suggests a delayed transition from a local architecture, focused on short-range connections, to a more distributed architecture with efficient long-range connections in those infants. The disruption of connectivity in fronto-paralimbic/limbic and posterior DMN regions might underlie the behavioral and social cognition difficulties previously reported in the preterm population.

Temporal-thalamic and cingulo-opercular connectivity in people with schizophrenia.

A growing body of research has suggested that people with schizophrenia (SZ) exhibit altered patterns of functional and anatomical brain connectivity. For example, many previous resting state functional connectivity (rsFC) studies have shown that, compared to healthy controls (HC), people with SZ demonstrate hyperconnectivity between subregions of the thalamus and sensory cortices, as well as hypoconnectivity between subregions of the thalamus and prefrontal cortex. In addition to thalamic findings, hypoconnectivity between cingulo-opercular brain regions thought to be involved in salience detection has also been commonly reported in people with SZ. However, previous studies have largely relied on seed-based analyses. Seed-based approaches require researchers to define a single a priori brain region, which is then used to create a rsFC map across the entire brain. While useful for testing specific hypotheses, these analyses are limited in that only a subset of connections across the brain are explored. In the current manuscript, we leverage novel network statistical techniques in order to detect latent functional connectivity networks with organized topology that successfully differentiate people with SZ from HCs. Importantly, these techniques do not require a priori seed selection and allow for whole brain investigation, representing a comprehensive, data-driven approach to determining differential connectivity between diagnostic groups. Across two samples, (Sample 1: 35 SZ, 44 HC; Sample 2: 65 SZ, 79 HC), we found evidence for differential rsFC within a network including temporal and thalamic regions. Connectivity in this network was greater for people with SZ compared to HCs. In the second sample, we also found evidence for hypoconnectivity within a cingulo-opercular network of brain regions in people with SZ compared to HCs. In summary, our results replicate and extend previous studies suggesting hyperconnectivity between the thalamus and sensory cortices and hypoconnectivity between cingulo-opercular regions in people with SZ using data-driven statistical and graph theoretical techniques.