Spatiotemporal Correlation between Amyloid and Tau Accumulations Underlies Cognitive Changes in Aging.

It is poorly known how Aß and tau accumulations associate at the spatiotemporal level in the in vivo human brain to impact cognitive changes in older adults prior to AD symptoms onset. In this study, we used a graph theory-based spatiotemporal analysis to characterize the cortical patterns of Aß and tau deposits and their relationship with cognitive changes in the Harvard Aging Brain Study (HABS) cohort. We found that the temporal accumulations of interlinked Aß and tau pathology display distinctive spatiotemporal correlations associated with early cognitive decline. Notably, we observed that baseline Aß deposits-Thal amyloid phase Ⅱ-related to future increase of tau deposits, Braak stages Ⅰ-Ⅳ, both displaying linkage to the decline in multi-domain cognitive scores. We also found unimodal tau-to-tau and cognitive impairment associations in broad areas of Braak stages Ⅰ-Ⅳ. The unimodal Aß-to-Aß progressions were not associated with cognitive changes. Our results revealed a multifaceted correlation of the spatiotemporal Aß and tau associations with cognitive decline over time, in which tau-to-tau and tau-Aß interactions, and not Aß independently, might be critical contributors to clinical trajectories toward AD in older adults.

Amyloid-ß and tau pathologies relate to distinctive brain dysconnectomics in preclinical autosomal-dominant Alzheimer's disease.

The human brain is composed of functional networks that have a modular topology, where brain regions are organized into communities that form internally dense (segregated) and externally sparse (integrated) subnetworks that underlie higher-order cognitive functioning. It is hypothesized that amyloid-ß and tau pathology in preclinical Alzheimer's disease (AD) spread through functional networks, disrupting neural communication that results in cognitive dysfunction. We used high-resolution (voxel-level) graph-based network analyses to test whether in vivo amyloid-ß and tau burden was associated with the segregation and integration of brain functional connections, and episodic memory, in cognitively unimpaired Presenilin-1 E280A carriers who are expected to develop early-onset AD dementia in ∼13 y on average. Compared to noncarriers, mutation carriers exhibited less functional segregation and integration in posterior default-mode network (DMN) regions, particularly the precuneus, and in the retrospenial cortex, which has been shown to link medial temporal regions and cortical regions of the DMN. Mutation carriers also showed greater functional segregation and integration in regions connected to the salience network, including the striatum and thalamus. Greater tau burden was associated with lower segregated and integrated functional connectivity of DMN regions, particularly the precuneus and medial prefrontal cortex. In turn, greater tau pathology was related to higher segregated and integrated functional connectivity in the retrospenial cortex and the anterior cingulate cortex, a hub of the salience network. These findings enlighten our understanding of how AD-related pathology distinctly alters the brain's functional architecture in the preclinical stage, possibly contributing to pathology propagation and ultimately resulting in dementia.

Compressed sensorimotor-to-transmodal hierarchical organization in schizophrenia.

BACKGROUND: Schizophrenia has been primarily conceptualized as a disorder of high-order cognitive functions with deficits in executive brain regions. Yet due to the increasing reports of early sensory processing deficit, recent models focus more on the developmental effects of impaired sensory process on high-order functions. The present study examined whether this pathological interaction relates to an overarching system-level imbalance, specifically a disruption in macroscale hierarchy affecting integration and segregation of unimodal and transmodal networks. METHODS: We applied a novel combination of connectome gradient and stepwise connectivity analysis to resting-state fMRI to characterize the sensorimotor-to-transmodal cortical hierarchy organization (96 patients v. 122 controls). RESULTS: We demonstrated compression of the cortical hierarchy organization in schizophrenia, with a prominent compression from the sensorimotor region and a less prominent compression from the frontal-parietal region, resulting in a diminished separation between sensory and fronto-parietal cognitive systems. Further analyses suggested reduced differentiation related to atypical functional connectome transition from unimodal to transmodal brain areas. Specifically, we found hypo-connectivity within unimodal regions and hyper-connectivity between unimodal regions and fronto-parietal and ventral attention regions along the classical sensation-to-cognition continuum (voxel-level corrected, p < 0.05). CONCLUSIONS: The compression of cortical hierarchy organization represents a novel and integrative system-level substrate underlying the pathological interaction of early sensory and cognitive function in schizophrenia. This abnormal cortical hierarchy organization suggests cascading impairments from the disruption of the somatosensory-motor system and inefficient integration of bottom-up sensory information with attentional demands and executive control processes partially account for high-level cognitive deficits characteristic of schizophrenia.

Central neurogenetic signatures of the visuomotor integration system.

Visuomotor impairments characterize numerous neurological disorders and neurogenetic syndromes, such as autism spectrum disorder (ASD) and Dravet, Fragile X, Prader-Willi, Turner, and Williams syndromes. Despite recent advances in systems neuroscience, the biological basis underlying visuomotor functional impairments associated with these clinical conditions is poorly understood. In this study, we used neuroimaging connectomic approaches to map the visuomotor integration (VMI) system in the human brain and investigated the topology approximation of the VMI network to the Allen Human Brain Atlas, a whole-brain transcriptome-wide atlas of cortical genetic expression. We found the genetic expression of four genes-TBR1, SCN1A, MAGEL2, and CACNB4-to be prominently associated with visuomotor integrators in the human cortex. TBR1 gene transcripts, an ASD gene whose expression is related to neural development of the cortex and the hippocampus, showed a central spatial allocation within the VMI system. Our findings delineate gene expression traits underlying the VMI system in the human cortex, where specific genes, such as TBR1, are likely to play a central role in its neuronal organization, as well as on specific phenotypes of neurogenetic syndromes.

Connectomic-genetic signatures in the cerebral small vessel disease.

Small vessel disease (SVD) is a disorder that causes vascular lesions in the entire parenchyma of the human brain. At present, it is not well understood how primary and secondary damage interact to give rise to the complex scenario of white matter (WM) and grey matter (GM) lesions. Using novel cross-sectional and longitudinal connectomic approaches, we unveil the bidirectional nature of GM and WM changes, that is, primary cortical neurodegeneration that leads to secondary alterations in vascular border zones, and WM lesions that lead to secondary neurodegeneration in cortical projecting areas. We found this GM-WM interaction to be essential for executive cognitive performance. Moreover, we also observed that the interlocked degeneration of GM and WM over time associates with prototypical expression levels of genes potentially linked to SVD. Among these connectomic-genetic intersections, we found that the Androgen Receptor (AR) gene, is a particularly central candidate gene that might confer key vulnerability for brain lesion development in SVD. In conclusion, this study advances in the understanding of the bidirectional relationships between GM and WM lesions, primary and secondary vascular neurodegeneration, and sheds light on the genetic signatures of SVD.

Early-life trauma endophenotypes and brain circuit-gene expression relationships in functional neurological (conversion) disorder.

Functional neurological (conversion) disorder (FND) is a neuropsychiatric condition whereby individuals present with sensorimotor symptoms incompatible with other neurological disorders. Early-life maltreatment (ELM) is a risk factor for developing FND, yet few studies have investigated brain network-trauma relationships in this population. In this neuroimaging-gene expression study, we used two graph theory approaches to elucidate ELM subtype effects on resting-state functional connectivity architecture in 30 patients with motor FND. Twenty-one individuals with comparable depression, anxiety, and ELM scores were used as psychiatric controls. Thereafter, we compared trauma endophenotypes in FND with regional differences in transcriptional gene expression as measured by the Allen Human Brain Atlas (AHBA). In FND patients only, we found that early-life physical abuse severity, and to a lesser extent physical neglect, correlated with corticolimbic weighted-degree functional connectivity. Connectivity profiles influenced by physical abuse occurred in limbic (amygdalar-hippocampal), paralimbic (cingulo-insular and ventromedial prefrontal), and cognitive control (ventrolateral prefrontal) areas, as well as in sensorimotor and visual cortices. These findings held adjusting for individual differences in depression/anxiety, PTSD, and motor phenotypes. In FND, physical abuse also correlated with amygdala and insula coupling to motor cortices. In exploratory analyses, physical abuse correlated connectivity maps overlapped with the AHBA spatial expression of three gene clusters: (i) neuronal morphogenesis and synaptic transmission genes in limbic/paralimbic areas; (ii) locomotory behavior and neuronal generation genes in left-lateralized structures; and (iii) nervous system development and cell motility genes in right-lateralized structures. These circuit-specific architectural profiles related to individual differences in childhood physical abuse burden advance our understanding of the pathophysiology of FND.

Association of cortical microstructure with amyloid-ß and tau: impact on cognitive decline, neurodegeneration, and clinical progression in older adults.

Noninvasive biomarkers of early neuronal injury may help identify cognitively normal individuals at risk of developing Alzheimer's disease (AD). A recent diffusion-weighted imaging (DWI) method allows assessing cortical microstructure via cortical mean diffusivity (cMD), suggested to be more sensitive than macrostructural neurodegeneration. Here, we aimed to investigate the association of cMD with amyloid-ß and tau pathology in older adults, and whether cMD predicts longitudinal cognitive decline, neurodegeneration and clinical progression. The study sample comprised n = 196 cognitively normal older adults (mean[SD] 72.5 [9.4] years; 114 women [58.2%]) from the Harvard Aging Brain Study. At baseline, all participants underwent structural MRI, DWI, 11C-Pittsburgh compound-B-PET, 18F-flortaucipir-PET imaging, and cognitive assessments. Longitudinal measures of Preclinical Alzheimer Cognitive Composite-5 were available for n = 186 individuals over 3.72 (1.96)-year follow-up. Prospective clinical follow-up was available for n = 163 individuals over 3.2 (1.7) years. Surface-based image analysis assessed vertex-wise relationships between cMD, global amyloid-ß, and entorhinal and inferior-temporal tau. Multivariable regression, mixed effects models and Cox proportional hazards regression assessed longitudinal cognition, brain structural changes and clinical progression. Tau, but not amyloid-ß, was positively associated with cMD in AD-vulnerable regions. Correcting for baseline demographics and cognition, increased cMD predicted steeper cognitive decline, which remained significant after correcting for amyloid-ß, thickness, and entorhinal tau; there was a synergistic interaction between cMD and both amyloid-ß and tau on cognitive slope. Regional cMD predicted hippocampal atrophy rate, independently from amyloid-ß, tau, and thickness. Elevated cMD predicted progression to mild cognitive impairment. Cortical microstructure is a noninvasive biomarker that independently predicts subsequent cognitive decline, neurodegeneration and clinical progression, suggesting utility in clinical trials.

Creative Connections: Computational Semantic Distance Captures Individual Creativity and Resting-State Functional Connectivity.

Recent studies of creative cognition have revealed interactions between functional brain networks involved in the generation of novel ideas; however, the neural basis of creativity is highly complex and presents a great challenge in the field of cognitive neuroscience, partly because of ambiguity around how to assess creativity. We applied a novel computational method of verbal creativity assessment-semantic distance-and performed weighted degree functional connectivity analyses to explore how individual differences in assembly of resting-state networks are associated with this objective creativity assessment. To measure creative performance, a sample of healthy adults (n = 175) completed a battery of divergent thinking (DT) tasks, in which they were asked to think of unusual uses for everyday objects. Computational semantic models were applied to calculate the semantic distance between objects and responses to obtain an objective measure of DT performance. All participants underwent resting-state imaging, from which we computed voxel-wise connectivity matrices between all gray matter voxels. A linear regression analysis was applied between DT and weighted degree of the connectivity matrices. Our analysis revealed a significant connectivity decrease in the visual-temporal and parietal regions, in relation to increased levels of DT. Link-level analyses showed higher local connectivity within visual regions was associated with lower DT, whereas projections from the precuneus to the right inferior occipital and temporal cortex were positively associated with DT. Our results demonstrate differential patterns of resting-state connectivity associated with individual creative thinking ability, extending past work using a new application to automatically assess creativity via semantic distance.

A reachable probability approach for the analysis of spatio-temporal dynamics in the human functional network.

The dynamic architecture of the human brain has been consistently observed. However, there is still limited modeling work to elucidate how neuronal circuits are hierarchically and flexibly organized in functional systems. Here we proposed a reachable probability approach based on non-homogeneous Markov chains, to characterize all possible connectivity flows and the hierarchical structure of brain functional systems at the dynamic level. We proved at the theoretical level the convergence of the functional brain network system, and demonstrated that this approach is able to detect network steady states across connectivity structure, particularly in areas of the default mode network. We further explored the dynamically hierarchical functional organization centered at the primary sensory cortices. We observed smaller optimal reachable steps to their local functional regions, and differentiated patterns in larger optimal reachable steps for primary perceptual modalities. The reachable paths with the largest and second largest transition probabilities between primary sensory seeds via multisensory integration regions were also tracked to explore the flexibility and plasticity of the multisensory integration. The present work provides a novel approach to depict both the stable and flexible hierarchical connectivity organization of the human brain.

Longitudinal predictive modeling of tau progression along the structural connectome.

Tau neurofibrillary tangles, a pathophysiological hallmark of Alzheimer's disease (AD), exhibit a stereotypical spatiotemporal trajectory that is strongly correlated with disease progression and cognitive decline. Personalized prediction of tau progression is, therefore, vital for the early diagnosis and prognosis of AD. Evidence from both animal and human studies is suggestive of tau transmission along the brains preexisting neural connectivity conduits. We present here an analytic graph diffusion framework for individualized predictive modeling of tau progression along the structural connectome. To account for physiological processes that lead to active generation and clearance of tau alongside passive diffusion, our model uses an inhomogenous graph diffusion equation with a source term and provides closed-form solutions to this equation for linear and exponential source functionals. Longitudinal imaging data from two cohorts, the Harvard Aging Brain Study (HABS) and the Alzheimer's Disease Neuroimaging Initiative (ADNI), were used to validate the model. The clinical data used for developing and validating the model include regional tau measures extracted from longitudinal positron emission tomography (PET) scans based on the 18F-Flortaucipir radiotracer and individual structural connectivity maps computed from diffusion tensor imaging (DTI) by means of tractography and streamline counting. Two-timepoint tau PET scans were used to assess the goodness of model fit. Three-timepoint tau PET scans were used to assess predictive accuracy via comparison of predicted and observed tau measures at the third timepoint. Our results show high consistency between predicted and observed tau and differential tau from region-based analysis. While the prognostic value of this approach needs to be validated in a larger cohort, our preliminary results suggest that our longitudinal predictive model, which offers an in vivo macroscopic perspective on tau progression in the brain, is potentially promising as a personalizable predictive framework for AD.

Unveiling the neuroimaging-genetic intersections in the human brain.

PURPOSE OF REVIEW: The prevalence of new public datasets of brain-wide and single-cell transcriptome data has created new opportunities to link neuroimaging findings with genetic data. The aim of this study is to present the different methodological approaches that have been used to combine this data. RECENT FINDINGS: Drawing from various sources of open access data, several studies have been able to correlate neuroimaging maps with spatial distribution of brain expression. These efforts have enabled researchers to identify functional annotations of related genes, identify specific cell types related to brain phenotypes, study the expression of genes across life span and highlight the importance of selected brain genes in disease genetic networks. SUMMARY: New transcriptome datasets and methodological approaches complement current neuroimaging work and will be crucial to improve our understanding of the biological mechanism that underlies many neurological conditions.

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

Amyloid-beta (Aß) 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 Aß 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 Aß PET modalities, and tested the effects on cognitive changes in cognitively normal older adults (CN). Particularly, we focused on the network interdigitations of Aß and tau deposits, along with cognitive test scores in CN at both baseline and 2-year follow-up (FU). We found highly significant Aß-tau network integrations in AD vulnerable areas, as well as significant associations between those Aß-tau interdigitations and general cognitive impairment in CN at baseline and FU. Our findings suggest a distinctive contribution of interlinking network relationships between Aß and tau deposits in heteromodal areas of the human brain. They support a network-based interaction between Aß and tau accumulations as a key factor for cognitive deterioration in CN prior to dementia.

Transcriptional signatures of synaptic vesicle genes define myotonic dystrophy type I neurodegeneration.

AIM: To delineate the neurogenetic profiles of brain degeneration patterns in myotonic dystrophy type I (DM1). METHODS: In two cohorts of DM1 patients, brain maps of volume loss (VL) and neuropsychological deficits (NDs) were intersected to large-scale transcriptome maps provided by the Allen Human Brain Atlas (AHBA). For validation, neuropathological and RNA analyses were performed in a small series of DM1 brain samples. RESULTS: Twofold: (1) From a list of preselected hypothesis-driven genes, confirmatory analyses found that three genes play a major role in brain degeneration: dystrophin (DMD), alpha-synuclein (SNCA) and the microtubule-associated protein tau (MAPT). Neuropathological analyses confirmed a highly heterogeneous Tau-pathology in DM1, different to the one in Alzheimer's disease. (2) Exploratory analyses revealed gene clusters enriched for key biological processes in the central nervous system, such as synaptic vesicle recycling, localization, endocytosis and exocytosis, and the serotonin and dopamine neurotransmitter pathways. RNA analyses confirmed synaptic vesicle dysfunction. CONCLUSIONS: The combination of large-scale transcriptome interactions with brain imaging and cognitive function sheds light on the neurobiological mechanisms of brain degeneration in DM1 that might help define future therapeutic strategies and research into this condition.

Functional and Pathological Correlates of Judgments of Learning in Cognitively Unimpaired Older Adults.

Judgments of learning (JOL) pertain to introspective metamemory processes evaluating how well information is learned. Using a functional magnetic resonance imaging (fMRI) task, we investigated the neural substrates of JOL predictions in a group of 105 cognitively unimpaired older adults from the Harvard Aging Brain Study. Associations of JOL performance and its neural correlates with amyloid-ß (Aß) and tau pathology, two proteinopathies associated with Alzheimer's disease (AD) and aging, were also examined. We found that trials judged as learned well relative to trials judged as learned less well (high JOL > low JOL) engaged the ventromedial prefrontal cortex and precuneus, among other midline regions, in addition to bilateral hippocampi. In this cohort of older adults, greater levels of entorhinal tau deposition were associated with overestimation of memory performance and with lower fMRI signal in midline regions during predicted memory success. No associations with Aß were found. The findings suggest that tau pathology in unimpaired older adults may play a role in altered metamemory processes. We discuss our findings in light of the hypothesis that JOLs are partially dependent on a process involving attempts to retrieve a correct answer from memory, as well as implications for clinical research investigating unawareness of memory performance (i.e., anosognosia) in patients with AD dementia.

Distance disintegration characterizes node-level topological dysfunctions in cocaine addiction.

Previous investigations have used global graph theory measures in order to disentangle the complexity of the neural reorganizations occurring in cocaine use disorder (CUD). However, how these global topological alterations map into individual brain network areas remains unknown. In this study, we used resting state functional magnetic resonance imaging (fMRI) data to investigate node-level topological dysfunctions in CUD. The sample was composed of 32 individuals with CUD and 32 healthy controls, matched in age, years of education and intellectual functioning. Graph theory measures of optimal connectivity distance, node strength, nodal efficiency and clustering coefficient were estimated in each participant using voxel-wise functional connectivity connectomes. CUD individuals as compared with healthy controls showed higher optimal connectivity distances in ventral striatum, insula, cerebellum, temporal cortex, lateral orbitofrontal cortex, middle frontal cortex and left hippocampus. Furthermore, clinical measures quantifying severity of dependence were positively related with optimal connectivity distances in the right rolandic operculum and the right lateral orbitofrontal cortex, whereas length of abstinence was negatively associated with optimal connectivity distances in the right temporal pole and the left insula. Our results reveal a topological distancing of cognitive and affective related areas in addiction, suggesting an overall reduction in the communication capacity of these regions.

Sequence Alterations of Cortical Genes Linked to Individual Connectivity of the Human Brain.

Individual differences in humans are driven by unique brain structural and functional profiles, presumably mediated in part through differential cortical gene expression. However, the relationships between cortical gene expression profiles and individual differences in large-scale neural network organization remain poorly understood. In this study, we aimed to investigate whether the magnitude of sequence alterations in regional cortical genes mapped onto brain areas with high degree of functional connectivity variability across individuals. First, human genetic expression data from the Allen Brain Atlas was used to identify protein-coding genes associated with cortical areas, which delineated the regional genetic signature of specific cortical areas based on sequence alteration profiles. Thereafter, we identified brain regions that manifested high degrees of individual variability by using test-retest functional connectivity magnetic resonance imaging and graph-theory analyses in healthy subjects. We found that rates of genetic sequence alterations shared a distinct spatial topography with cortical regions exhibiting individualized (highly-variable) connectivity profiles. Interestingly, gene expression profiles of brain regions with highly individualized connectivity patterns and elevated number of sequence alterations are devoted to neuropeptide-signaling-pathways and chemical-synaptic-transmission. Our findings support that genetic sequence alterations may underlie important aspects of brain connectome individualities in humans. Significance Statement: The neurobiological underpinnings of our individuality as humans are still an unsolved question. Although the notion that genetic variation drives an individual's brain organization has been previously postulated, specific links between neural connectivity and gene expression profiles have remained elusive. In this study, we identified the magnitude of population-based sequence alterations in discrete cortical regions and compared them to the brain topological distribution of functional connectivity variability across an independent human sample. We discovered that brain regions with high degree of connectional individuality are defined by increased rates of genetic sequence alterations; these findings specifically implicated genes involved in neuropeptide-signaling pathways and chemical-synaptic transmission. These observations support that genetic sequence alterations may underlie important aspects of the emergence of the brain individuality across humans.

Brain circuit-gene expression relationships and neuroplasticity of multisensory cortices in blind children.

Sensory deprivation reorganizes neurocircuits in the human brain. The biological basis of such neuroplastic adaptations remains elusive. In this study, we applied two complementary graph theory-based functional connectivity analyses, one to evaluate whole-brain functional connectivity relationships and the second to specifically delineate distributed network connectivity profiles downstream of primary sensory cortices, to investigate neural reorganization in blind children compared with sighted controls. We also examined the relationship between connectivity changes and neuroplasticity-related gene expression profiles in the cerebral cortex. We observed that multisensory integration areas exhibited enhanced functional connectivity in blind children and that this reorganization was spatially associated with the transcription levels of specific members of the cAMP Response Element Binding protein gene family. Using systems-level analyses, this study advances our understanding of human neuroplasticity and its genetic underpinnings following sensory deprivation.

Adaptation of brain functional stream architecture in athletes with fast demands of sensorimotor integration.

Training-induced neuroplasticity has been described in athletes' population. However, it remains largely unknown how regular training and sports proficiency modifies neuronal circuits in the human brain. In this study, we used voxel-based morphometry and stepwise functional connectivity (SFC) analyses to uncover connectivity changes in the functional stream architecture in student-athletes at early stages of sensorimotor skill training. Thirty-two second-year student-athletes whose major was little-ball sports and thirty-four nonathlete controls were recruited for the study. We found that athletes showed greater gray matter volume in the right sensorimotor area, the limbic lobe, and the anterior lobe of the cerebellum. Furthermore, SFC analysis demonstrated that athletes displayed significantly smaller optimal connectivity distance from those seed regions to the dorsal attention network (DAN) and larger optimal connectivity distance to the default mode network (DMN) compared to controls. The Attention Network Test showed that the reaction time of the orienting attention subnetwork was positively correlated with SFC between the seeds and the DAN, while negatively correlated with SFC between the seeds and the DMN. Our findings suggest that neuroplastic adaptations on functional connectivity streams after motor skill training may enable novel information flow from specific areas of the cortex toward distributed networks such as the DAN and the DMN. This could potentially regulate the focus of external and internal attention synchronously in athletes, and consequently accelerate the reaction time of orienting attention in athletes.

Stepwise functional connectivity reveals altered sensory-multimodal integration in medication-naïve adults with attention deficit hyperactivity disorder.

Neuroimaging studies indicate that children with attention-deficit/hyperactivity disorder (ADHD) present alterations in several functional networks of the sensation-to-cognition spectrum. These alterations include functional overconnectivity within sensory regions and underconnectivity between sensory regions and neural hubs supporting higher order cognitive functions. Today, it is unknown whether this same pattern of alterations persists in adult patients with ADHD who had never been medicated for their condition. The aim of the present study was to assess whether medication-naïve adults with ADHD presented alterations in functional networks of the sensation-to-cognition spectrum. Thirty-one medication-naïve adults with ADHD and twenty-two healthy adults underwent resting-state functional magnetic resonance imaging (rs-fMRI). Stepwise functional connectivity (SFC) was used to characterize the pattern of functional connectivity between sensory seed regions and the rest of the brain at direct, short, intermediate, and long functional connectivity distances, thus covering the continuum from the sensory input to the neural hubs supporting higher order cognitive functions. As compared to controls, adults with ADHD presented increased SFC degree within primary sensory regions and decreased SFC degree between sensory seeds and higher order integration nodes. In addition, they exhibited decreased connectivity degree between sensory seeds and regions of the default-mode network. Consistently, the higher the score in clinical severity scales the lower connectivity degree between seed regions and the default mode network.

Corticolimbic fast-tracking: enhanced multimodal integration in functional neurological disorder.

OBJECTIVE: Some individuals with functional neurological disorder (FND) exhibit motor and affective disturbances, along with limbic hyper-reactivity and enhanced motor-limbic connectivity. Given that the multimodal integration network (insula, dorsal cingulate, temporoparietal junction (TPJ)) is implicated in convergent sensorimotor, affective and interoceptive processing, we hypothesised that patients with FND would exhibit altered motor and amygdalar resting-state propagation to this network. Patient-reported symptom severity and clinical outcome were also hypothesised to map onto multimodal integration areas. METHODS: Between-group differences in primary motor and amygdalar nuclei (laterobasal, centromedial) were examined using graph-theory stepwise functional connectivity (SFC) in 30 patients with motor FND compared with 30 healthy controls. Within-group analyses correlated functional propagation profiles with symptom severity and prospectively collected 6-month outcomes as measured by the Screening for Somatoform Symptoms Conversion Disorder subscale and Patient Health Questionnaire-15 composite score. Findings were clusterwise corrected for multiple comparisons. RESULTS: Compared with controls, patients with FND exhibited increased SFC from motor regions to the bilateral posterior insula, TPJ, middle cingulate cortex and putamen. From the right laterobasal amygdala, the FND cohort showed enhanced connectivity to the left anterior insula, periaqueductal grey and hypothalamus among other areas. In within-group analyses, symptom severity correlated with enhanced SFC from the left anterior insula to the right anterior insula and TPJ; increased SFC from the left centromedial amygdala to the right anterior insula correlated with clinical improvement. Within-group associations held controlling for depression, anxiety and antidepressant use. CONCLUSIONS: These neuroimaging findings suggest potential candidate neurocircuit pathways in the pathophysiology of FND.