Gradients Of Functional Connectivity Research Articles

Methods for decoding cortical gradients of functional connectivity

Abstract Macroscale gradients have emerged as a central principle for understanding functional brain organization. Previous studies have demonstrated that a principal gradient of connectivity in the human brain exists, with unimodal primary sensorimotor regions situated at one end and transmodal regions associated with the default mode network and representative of abstract functioning at the other. The functional significance and interpretation of macroscale gradients remains a central topic of discussion in the neuroimaging community, with some studies demonstrating that gradients may be described using meta-analytic functional decoding techniques. However, additional methodological development is necessary to fully leverage available meta-analytic methods and resources and quantitatively evaluate their relative performance. Here, we conducted a comprehensive series of analyses to investigate and improve the framework of data-driven, meta-analytic methods, thereby establishing a principled approach for gradient segmentation and functional decoding. We found that a two-segment solution determined by a k-means segmentation approach and an LDA-based meta-analysis combined with the NeuroQuery database was the optimal combination of methods for decoding functional connectivity gradients. Finally, we proposed a method for decoding additional components of the gradient decomposition. The current work aims to provide recommendations on best practices and flexible methods for gradient-based functional decoding of fMRI data.

Dopamine D1-Receptor Organization Contributes to Functional Brain Architecture.

Recent work has recognized a gradient-like organization in cortical function, spanning from primary sensory to transmodal cortices. It has been suggested that this axis is aligned with regional differences in neurotransmitter expression. Given the abundance of dopamine D1-receptors (D1DR), and its importance for modulation and neural gain, we tested the hypothesis that D1DR organization is aligned with functional architecture, and that inter-regional relationships in D1DR co-expression modulate functional cross talk. Using the world's largest dopamine D1DR-PET and MRI database (N = 180%, 50% female), we demonstrate that D1DR organization follows a unimodal-transmodal hierarchy, expressing a high spatial correspondence to the principal gradient of functional connectivity. We also demonstrate that individual differences in D1DR density between unimodal and transmodal regions are associated with functional differentiation of the apices in the cortical hierarchy. Finally, we show that spatial co-expression of D1DR primarily modulates couplings within, but not between, functional networks. Together, our results show that D1DR co-expression provides a biomolecular layer to the functional organization of the brain.

Multimodal measures of spontaneous brain activity reveal both common and divergent patterns of cortical functional organization

Large-scale functional networks have been characterized in both rodent and human brains, typically by analyzing fMRI-BOLD signals. However, the relationship between fMRI-BOLD and underlying neural activity is complex and incompletely understood, which poses challenges to interpreting network organization obtained using this technique. Additionally, most work has assumed a disjoint functional network organization (i.e., brain regions belong to one and only one network). Here, we employ wide-field Ca2+ imaging simultaneously with fMRI-BOLD in mice expressing GCaMP6f in excitatory neurons. We determine cortical networks discovered by each modality using a mixed-membership algorithm to test the hypothesis that functional networks exhibit overlapping organization. We find that there is considerable network overlap (both modalities) in addition to disjoint organization. Our results show that multiple BOLD networks are detected via Ca2+ signals, and networks determined by low-frequency Ca2+ signals are only modestly more similar to BOLD networks. In addition, the principal gradient of functional connectivity is nearly identical for BOLD and Ca2+ signals. Despite similarities, important differences are also detected across modalities, such as in measures of functional connectivity strength and diversity. In conclusion, Ca2+ imaging uncovers overlapping functional cortical organization in the mouse that reflects several, but not all, properties observed with fMRI-BOLD signals.

Exploring the relationship between genetic patterns and brain properties using the Allen Human Brain Atlas

AbstractBackgroundImaging transcriptomics is a rapidly developing field that combines neuroimaging with genomics to study mechanisms that influence the organization and activity of the nervous system. Using whole‐brain microarray mRNA expression data from the Allen Human Brain Atlas (AHBA), we examined spatial gradients of gene expression in the brain. We then related these gradients to known spatial patterns of brain function.MethodWe mapped regional mRNA expression data from more than 21,000 genes to the 200‐parcel Schaeffer atlas. Principle components analysis (PCA) was used to reduce the dimensionality of the data to ten principle components (PCs). This was done for all genes for the whole brain (WBExp) as well as those specific to Alzheimer Disease (ADExp). We additionally mapped eight other properties: functional connectivity gradients (Fig. 2A), myelin, cortical thickness, cerebral blood volume, cerebral blood flow, glucose consumption, and evolutionary expansion (Fig. 2B) to this atlas to explore their relationships with genetic patterns. Region weights from the PCs were predicted from these eight maps.ResultThe majority of variance for both WBExp (Fig. 1A & 1C) and ADExp (Fig. 1B & 1D) expression was explained by three PCs. Functional connectivity gradients one (β = ‐0.38, β = 0.14), two (β = 0.33, β = ‐0.45), and five (β = ‐0.44, β = 0.32) were moderately related to the first PC of WBExp (Fig. 3A) and ADExp (Fig. 3C) expression patterns (p < 0.05), respectively. Cortical thickness (β = ‐0.32, β = 0.19), cerebral brain volume (β = 0.10, β = ‐0.13), cerebral blood flow (β = 0.42, β = ‐0.52), and evolutionary expansion (β = 0.08, β = ‐0.20) were additionally moderately related to the the WBExp PC1 (Fig. 3B, p < 0.05) and the ADExp PC1 (Fig. 3D, p < 0.05), respectively.ConclusionOur results highlighted that gradients in genetic expressions are related to functional gradients seen using rs‐fMRI as well as biological properties such as cortical thickness, cerebral blood volume, cerebral blood flow, and evolutionary expansion. These findings shed light on mechanisms that influence the structure and function of the brain. Understanding the relationship between genetic patterns and these properties can give insight into healthy and diseased‐brain states such as Alzheimer disease.

Mapping the effects of functional and structural network reorganization on the tau‐cognition relationship in Alzheimer’s disease

AbstractBackgroundTau pathology can spread through connectivity‐based networks, with certain regions (or epicenters) accumulating more tau than others. Such spatial vulnerabilities may be due to their unique apical position in the cortical hierarchy, which can be elucidated through ‘gradients of connectivity’ (Margulies 2016 PNAS). Prior work showed that the primary gradient of functional connectivity unveils a uni‐to‐transmodal topography of the healthy neocortex which highly correlates with a cognitive gradient of perception‐to‐abstraction. Here, we hypothesized that the gradients of functional/structural connectivity interact with tau to affect cognitive functions in Alzheimer’s disease (AD).MethodWe included 213 participants from TRIAD (103 CN Aß‐, 103 CN Aß+, and 75 CI Aß+) with diffusion‐weighted MRI, resting‐state functional MRI, 18F‐MK6240 tau‐PET, and an extensive cognitive battery. We performed non‐linear dimensionality reduction on the individual functional and structural connectomes, and extracted the first components (‘gradients’) ‐explaining most variance (G1FC and G1SC). First, we compared G1FC_or_SC between diagnostic groups. Second, we investigated the interaction effect of G1FC_or_SC*tauSUVR on cognition (across 9 cognitive domains). Last, we investigated whether the tau‐cognition relationship changed in a topography‐specific manner along the cortical hierarchy, within (equally‐sized) gradient‐derived meta‐ROIs along G1FC_or_SC. Results were compared to Braak‐derived regional associations. Analyses were adjusted for age, sex, APOE, education, and multiple comparisons.ResultWe observed reduced segregation of functional networks in AD compared to controls, with unimodal (lower‐order cognitive) and transmodal (higher‐order cognitive) regions moving closer on G1FC. This may indicate loss of network specialization in AD. Participants who had both higher tau and G1FC alterations had more cognitive impairment (Fig.1A; shown for MMSE/language). This interaction‐effect was less pronounced with G1SC (Fig.1B). Last, tau correlated with cognition in a topography‐specific progressive manner (i.e., along the transmodal‐unimodal G1FC axis and anterior‐posterior G1SC axis) (Fig.1C). Notably, tau correlated with delayed memory progressively along the posterior‐anterior G1SC axis (R2 = 0.93 in all and R2 = 0.95 in A+) and BraakI‐VI axis (R2 = 0.77 in all and R2 = 0.28 in A+).ConclusionOur work supports the contribution of connectome‐driven tau distribution on cognitive impairment in AD. Connectome gradients may provide a spatial framework to study tau spreading along the major axes of brain organization underlying specific cognitive domains.

Graded functional organization in the left inferior frontal gyrus: evidence from task-free and task-based functional connectivity.

The left inferior frontal gyrus has been ascribed key roles in numerous cognitive domains, such as language and executive function. However, its functional organization is unclear. Possibilities include a singular domain-general function, or multiple functions that can be mapped onto distinct subregions. Furthermore, spatial transition in function may be either abrupt or graded. The present study explored the topographical organization of the left inferior frontal gyrus using a bimodal data-driven approach. We extracted functional connectivity gradients from (i) resting-state fMRI time-series and (ii) coactivation patterns derived meta-analytically from heterogenous sets of task data. We then sought to characterize the functional connectivity differences underpinning these gradients with seed-based resting-state functional connectivity, meta-analytic coactivation modeling and functional decoding analyses. Both analytic approaches converged on graded functional connectivity changes along 2 main organizational axes. An anterior-posterior gradient shifted from being preferentially associated with high-level control networks (anterior functional connectivity) to being more tightly coupled with perceptually driven networks (posterior). A second dorsal-ventral axis was characterized by higher connectivity with domain-general control networks on one hand (dorsal functional connectivity), and with the semantic network, on the other (ventral). These results provide novel insights into an overarching graded functional organization of the functional connectivity that explains its role in multiple cognitive domains.

Abnormal multi-layered dynamic cortico-subcortical functional connectivity in major depressive disorder and generalized anxiety disorder

Comorbidity has been frequently observed between generalized anxiety disorder (GAD) and major depressive disorder (MDD), however, common and distinguishable alterations in the topological organization of functional brain networks remain poorly understood. We sought to determine a robust and sensitive functional connectivity marker for diagnostic classification and symptom severity prediction. Multi-layered dynamic functional connectivity including whole brain, network-node and node-node layers via graph theory and gradient analyses were applied to functional MRI resting-state data obtained from 31 unmedicated GAD and 34 unmedicated MDD patients as well as 33 age and education matched healthy controls (HC). GAD and MDD symptoms were assessed using Penn State Worry Questionnaire and Beck Depression Inventory II, respectively. Three network measures including global properties (i.e., global efficiency, characteristic path length), regional nodal property (i.e., degree) and connectivity gradients were computed. Results showed that both patient groups exhibited abnormal dynamic cortico-subcortical topological organization compared to healthy controls, with MDD > GAD > HC in degree of randomization. Furthermore, our multi-layered dynamic functional connectivity network model reached 77% diagnostic accuracy between GAD and MDD and was highly predictive of symptom severity, respectively. Gradients of functional connectivity for superior frontal cortex-subcortical regions, middle temporal gyrus-subcortical regions and amygdala-cortical regions contributed more in this model compared to other gradients. We found shared and distinct cortico-subcortical connectivity features in dynamic functional brain networks between GAD and MDD, which together can promote the understanding of common and disorder-specific topological organization dysregulations and facilitate early neuroimaging-based diagnosis.

Fine-grained functional parcellation maps of the infant cerebral cortex.

Resting-state functional MRI (rs-fMRI) is widely used to examine the dynamic brain functional development of infants, but these studies typically require precise cortical parcellation maps, which cannot be directly borrowed from adult-based functional parcellation maps due to the substantial differences in functional brain organization between infants and adults. Creating infant-specific cortical parcellation maps is thus highly desired but remains challenging due to difficulties in acquiring and processing infant brain MRIs. In this study, we leveraged 1064 high-resolution longitudinal rs-fMRIs from 197 typically developing infants and toddlers from birth to 24 months who participated in the Baby Connectome Project to develop the first set of infant-specific, fine-grained, surface-based cortical functional parcellation maps. To establish meaningful cortical functional correspondence across individuals, we performed cortical co-registration using both the cortical folding geometric features and the local gradient of functional connectivity (FC). Then we generated both age-related and age-independent cortical parcellation maps with over 800 fine-grained parcels during infancy based on aligned and averaged local gradient maps of FC across individuals. These parcellation maps reveal complex functional developmental patterns, such as changes in local gradient, network size, and local efficiency, especially during the first 9 postnatal months. Our generated fine-grained infant cortical functional parcellation maps are publicly available at https://www.nitrc.org/projects/infantsurfatlas/ for advancing the pediatric neuroimaging field.

Atypical functional connectivity hierarchy in Rolandic epilepsy

Functional connectivity hierarchy is an important principle in the process of brain functional organization and an important feature reflecting brain development. However, atypical brain network hierarchy organization in Rolandic epilepsy have not been systematically investigated. We examined connectivity alteration with age and its relation to epileptic incidence, cognition, or underlying genetic factors in 162 cases of Rolandic epilepsy and 117 typically developing children, by measuring fMRI multi-axis functional connectivity gradients. Rolandic epilepsy is characterized by contracting and slowing expansion of the functional connectivity gradients, highlighting the atypical age-related change of the connectivity hierarchy in segregation properties. The gradient alterations are relevant to seizure incidence, cognition, and connectivity deficit, and development-associated genetic basis. Collectively, our approach provides converging evidence for atypical connectivity hierarchy as a system-level substrate of Rolandic epilepsy, suggesting this is a disorder of information processing across multiple functional domains, and established a framework for large-scale brain hierarchical research.

Functional connectivity gradients of the cingulate cortex

Heterogeneity of the cingulate cortex is evident in multiple dimensions including anatomy, function, connectivity, and involvement in networks and diseases. Using the recently developed functional connectivity gradient approach and resting-state functional MRI data, we found three functional connectivity gradients that captured distinct dimensions of cingulate hierarchical organization. The principal gradient exhibited a radiating organization with transitions from the middle toward both anterior and posterior parts of the cingulate cortex and was related to canonical functional networks and corresponding behavioral domains. The second gradient showed an anterior–posterior axis across the cingulate cortex and had prominent geometric distance dependence. The third gradient displayed a marked differentiation of subgenual and caudal middle with other parts of the cingulate cortex and was associated with cortical morphology. Aside from providing an updated framework for understanding the multifaceted nature of cingulate heterogeneity, the observed hierarchical organization of the cingulate cortex may constitute a novel research agenda with potential applications in basic and clinical neuroscience.

Functional characterization of macaque insula using task-based and resting-state fMRI

Neurophysiological investigations over the past decades have demonstrated the involvement of the primate insula in a wide array of sensory, cognitive, affective and regulatory functions, yet the complex functional organization of the insula remains unclear. Here we examined to what extent non-invasive task-based and resting-state fMRI provides support for functional specialization and integration of sensory and motor information in the macaque insula. Task-based fMRI experiments suggested a functional specialization related to processing of ingestive/taste/distaste information in anterior insula, grasping-related sensorimotor responses in middle insula and vestibular information in posterior insula. Visual stimuli depicting social information involving conspecific`s lip-smacking gestures yielded responses in middle and anterior portions of dorsal and ventral insula, overlapping partially with the sensorimotor and ingestive/taste/distaste fields. Functional specialization/integration of the insula was further corroborated by seed-based whole brain resting-state analyses, showing distinct functional connectivity gradients across the anterio-posterior extent of both dorsal and ventral insula. Posterior insula showed functional correlations in particular with vestibular/optic flow network regions, mid-dorsal insula with vestibular/optic flow as well as parieto-frontal regions of the sensorimotor grasping network, mid-ventral insula with social/affiliative network regions in temporal, cingulate and prefrontal cortices and anterior insula with taste and mouth motor networks including premotor and frontal opercular regions.

Correspondence of functional connectivity gradients across human isocortex, cerebellum, and hippocampus

Gradient mapping is an important technique to summarize high dimensional biological features as low dimensional manifold representations in exploring brain structure-function relationships at various levels of the cerebral cortex. While recent studies have characterized the major gradients of functional connectivity in several brain structures using this technique, very few have systematically examined the correspondence of such gradients across structures under a common systems-level framework. Using resting-state functional magnetic resonance imaging, here we show that the organizing principles of the isocortex, and those of the cerebellum and hippocampus in relation to the isocortex, can be described using two common functional gradients. We suggest that the similarity in functional connectivity gradients across these structures can be meaningfully interpreted within a common computational framework based on the principles of predictive processing. The present results, and the specific hypotheses that they suggest, represent an important step toward an integrative account of brain function.

Functional re-organization of hippocampal-cortical gradients during naturalistic memory processes

The functional organization of the hippocampus mirrors that of the cortex, changing smoothly along connectivity gradients and abruptly at inter-areal boundaries. Hippocampal-dependent cognitive processes require flexible integration of these hippocampal gradients into functionally related cortical networks. To understand the cognitive relevance of this functional embedding, we acquired fMRI data while participants viewed brief news clips, either containing or lacking recently familiarized cues. Participants were 188 healthy mid-life adults and 31 adults with mild cognitive impairment (MCI) or Alzheimer's disease (AD). We employed a recently developed technique - connectivity gradientography - to study gradually changing patterns of voxel to whole brain functional connectivity and their sudden transitions. We observed that functional connectivity gradients of the anterior hippocampus map onto connectivity gradients across the default mode network during these naturalistic stimuli. The presence of familiar cues in the news clips accentuates a stepwise transition across the boundary from the anterior to the posterior hippocampus. This functional transition is shifted in the posterior direction in the left hippocampus of individuals with MCI or AD. These findings shed new light on the functional integration of hippocampal connectivity gradients into large-scale cortical networks, how these adapt with memory context and how these change in the presence of neurodegenerative disease.

Brain network architecture constrains age-related cortical thinning

Age-related cortical atrophy, approximated by cortical thickness measurements from magnetic resonance imaging, follows a characteristic pattern over the lifespan. Although its determinants remain unknown, mounting evidence demonstrates correspondence between the connectivity profiles of structural and functional brain networks and cortical atrophy in health and neurological disease. Here, we performed a cross-sectional multimodal neuroimaging analysis of 2633 individuals from a large population-based cohort to characterize the association between age-related differences in cortical thickness and functional as well as structural brain network topology. We identified a widespread pattern of age-related cortical thickness differences including “hotspots” of pronounced age effects in sensorimotor areas. Regional age-related differences were strongly correlated within the structurally defined node neighborhood. The overall pattern of thickness differences was found to be anchored in the functional network hierarchy as encoded by macroscale functional connectivity gradients. Lastly, the identified difference pattern covaried significantly with cognitive and motor performance. Our findings indicate that connectivity profiles of functional and structural brain networks act as organizing principles behind age-related cortical thinning as an imaging surrogate of cortical atrophy.

Higher Sensory Sensitivity is Linked to Greater Expansion Amongst Functional Connectivity Gradients

Insofar as the autistic-like phenotype presents in the general population, it consists of partially dissociable traits, such as social and sensory issues. Here, we investigate individual differences in cortical organisation related to autistic-like traits. Connectome gradient decomposition based on resting state fMRI data reliably reveals a principal gradient spanning from unimodal to transmodal regions, reflecting the transition from perception to abstract cognition. In our non-clinical sample, this gradient's expansion, indicating less integration between visual and default mode networks, correlates with subjective sensory sensitivity (measured using the Glasgow Sensory Questionnaire, GSQ), but not other autistic-like traits (measured using the Autism Spectrum Quotient, AQ). This novel brain-based correlate of the GSQ demonstrates sensory issues can be disentangled from the wider autistic-like phenotype.

Functional connectivity gradients of the insula to different cerebral systems.

The diverse functional roles of the insula may emerge from its heavy connectivity to an extensive network of cortical and subcortical areas. Despite several previous attempts to investigate the hierarchical organization of the insula by applying the recently developed gradient approach to insula-to-whole brain connectivity data, little is known about whether and how there is variability across connectivity gradients of the insula to different cerebral systems. Resting-state functional MRI data from 793 healthy subjects were used to discover and validate functional connectivity gradients of the insula, which were computed based on its voxel-wise functional connectivity profiles to distinct cerebral systems. We identified three primary patterns of functional connectivity gradients of the insula to distinct cerebral systems. The connectivity gradients to the higher-order transmodal associative systems, including the prefrontal, posterior parietal, temporal cortices, and limbic lobule, showed a ventroanterior-dorsal axis across the insula; those to the lower-order unimodal primary systems, including the motor, somatosensory, and occipital cortices, displayed radiating transitions from dorsoanterior toward both ventroanterior and dorsoposterior parts of the insula; the connectivity gradient to the subcortical nuclei exhibited an organization along the anterior-posterior axis of the insula. Apart from complementing and extending previous literature on the heterogeneous connectivity patterns of insula subregions, the presented framework may offer ample opportunities to refine our understanding of the role of the insula in many brain disorders.

Allostasis as a core feature of hierarchical gradients in the human brain.

This paper integrates emerging evidence from two broad streams of scientific literature into one common framework: (a) hierarchical gradients of functional connectivity that reflect the brain's large-scale structural architecture (e.g., a lamination gradient in the cerebral cortex); and (b) approaches to predictive processing and one of its specific instantiations called allostasis (i.e., the predictive regulation of energetic resources in the service of coordinating the body's internal systems). This synthesis begins to sketch a coherent, neurobiologically inspired framework suggesting that predictive energy regulation is at the core of human brain function, and by extension, psychological and behavioral phenomena, providing a shared vocabulary for theory building and knowledge accumulation.

A parsimonious description of global functional brain organization in three spatiotemporal patterns.

Resting-state functional magnetic resonance imaging (MRI) has yielded seemingly disparate insights into large-scale organization of the human brain. The brain's large-scale organization can be divided into two broad categories: zero-lag representations of functional connectivity structure and time-lag representations of traveling wave or propagation structure. In this study, we sought to unify observed phenomena across these two categories in the form of three low-frequency spatiotemporal patterns composed of a mixture of standing and traveling wave dynamics. We showed that a range of empirical phenomena, including functional connectivity gradients, the task-positive/task-negative anti-correlation pattern, the global signal, time-lag propagation patterns, the quasiperiodic pattern and the functional connectome network structure, are manifestations of these three spatiotemporal patterns. These patterns account for much of the global spatial structure that underlies functional connectivity analyses and unifies phenomena in resting-state functional MRI previously thought distinct.

Resting-state functional heterogeneity of the right insula contributes to pain sensitivity

Previous studies have described the structure and function of the insular cortex in terms of spatially continuous gradients. Here we assess how spatial features of insular resting state functional organization correspond to individual pain sensitivity. From a previous multicenter study, we included 107 healthy participants, who underwent resting state functional MRI scans, T1-weighted scans and quantitative sensory testing on the left forearm. Thermal and mechanical pain thresholds were determined. Connectopic mapping, a technique using non-linear representations of functional organization was employed to describe functional connectivity gradients in both insulae. Partial coefficients of determination were calculated between trend surface model parameters summarizing spatial features of gradients, modal and modality-independent pain sensitivity. The dominant connectopy captured the previously reported posteroanterior shift in connectivity profiles. Spatial features of dominant connectopies in the right insula explained significant amounts of variance in thermal (R2 = 0.076; p < 0.001 and R2 = 0.031; p < 0.029) and composite pain sensitivity (R2 = 0.072; p < 0.002). The left insular gradient was not significantly associated with pain thresholds. Our results highlight the functional relevance of gradient-like insular organization in pain processing. Considering individual variations in insular connectopy might contribute to understanding neural mechanisms behind pain and improve objective brain-based characterization of individual pain sensitivity.

Contribution of animal models toward understanding resting state functional connectivity

Functional connectivity, which reflects the spatial and temporal organization of intrinsic activity throughout the brain, is one of the most studied measures in human neuroimaging research. The noninvasive acquisition of resting state functional magnetic resonance imaging (rs-fMRI) allows the characterization of features designated as functional networks, functional connectivity gradients, and time-varying activity patterns that provide insight into the intrinsic functional organization of the brain and potential alterations related to brain dysfunction. Functional connectivity, hence, captures dimensions of the brain's activity that have enormous potential for both clinical and preclinical research. However, the mechanisms underlying functional connectivity have yet to be fully characterized, hindering interpretation of rs-fMRI studies. As in other branches of neuroscience, the identification of the neurophysiological processes that contribute to functional connectivity largely depends on research conducted on laboratory animals, which provide a platform where specific, multi-dimensional investigations that involve invasive measurements can be carried out. These highly controlled experiments facilitate the interpretation of the temporal correlations observed across the brain. Indeed, information obtained from animal experimentation to date is the basis for our current understanding of the underlying basis for functional brain connectivity. This review presents a compendium of some of the most critical advances in the field based on the efforts made by the animal neuroimaging community.