scholarly journals Parcellation-induced variation of empirical and simulated brain connectomes at group and subject levels

2021 ◽  
pp. 1-56
Author(s):  
Justin W.M. Domhof ◽  
Kyesam Jung ◽  
Simon B. Eickhoff ◽  
Oleksandr V. Popovych
Keyword(s):  
Functional Connectivity ◽  
Goodness Of Fit ◽  
Brain Activity ◽  
Brain Regions ◽  
Single Subject ◽  
Whole Brain ◽  
Clear Cut ◽  
Recent Developments ◽  
Network Properties ◽  
Brain Models

Abstract Recent developments of whole-brain models have demonstrated their potential when investigating resting-state brain activity. However, it has not been systematically investigated how alternating derivations of the empirical structural and functional connectivity, serving as the model input, from MRI data influence modelling results. Here, we study the influence from one major element: the brain parcellation scheme that reduces the dimensionality of brain networks by grouping thousands of voxels into a few hundred brain regions. We show graph-theoretical statistics derived from the empirical data and modelling results exhibiting a high heterogeneity across parcellations. Furthermore, the network properties of empirical brain connectomes explain the lion’s share of the variance in the modelling results with respect to the parcellation variation. Such a clear-cut relationship is not observed at the subject-resolved level per parcellation. Finally, the graph-theoretical statistics of the simulated connectome correlate with those of the empirical functional connectivity across parcellations. However, this relation is not one-to-one, and its precision can vary between models. Our results imply that network properties of both empirical connectomes can explain the goodness-of-fit of whole-brain models toempirical data at a global group but not a single-subject level, which provides further insights into the personalisation of whole-brain models.

scholarly journals Lynn_etal_MathSkills_CPM_Preprint_V1_05July2021

2021 ◽  
Author(s):  
Andrew Lynn ◽  
Eric D. Wilkey ◽  
Gavin Price
Keyword(s):  
Functional Connectivity ◽  
Predictive Modeling ◽  
Brain Connectivity ◽  
Network Connectivity ◽  
Brain Regions ◽  
Math Skills ◽  
Whole Brain ◽  
Building Models ◽  
State Dependent ◽  
Brain Behavior

The human brain comprises multiple canonical networks, several of which are distributed across frontal, parietal, and temporooccipital regions. Studies report both positive and negative correlations between children’s math skills and the strength of functional connectivity among these regions during math-related tasks and at rest. Yet, it is unclear how the relation between children’s math skills and functional connectivity map onto patterns of distributed whole-brain connectivity, canonical network connectivity, and whether these relations are consistent across different task-states. We used connectome-based predictive modeling to test whether functional connectivity during number comparison and at rest predicts children’s math skills (N=31, Mage=9.21years) using distributed whole-brain connections versus connections among canonical networks. We found that weaker connectivity distributed across the whole brain and weaker connectivity between key math-related brain regions in specific canonical networks predicts better math skills in childhood. The specific connections predicting math skills, and whether they were distributed or mapped onto canonical networks, varied between tasks, suggesting that state-dependent rather than trait-level functional network architectures support children’s math skills. Furthermore, the current predictive modeling approach moves beyond brain-behavior correlations and toward building models of brain connectivity that may eventually aid in predicting future math skills.

Neurocognitive Aging and Functional Connectivity Using Functional Magnetic Resonance Imaging

2018 ◽  
Author(s):  
Hana Burianová
Keyword(s):  
Functional Connectivity ◽  
Cognitive Processes ◽  
Large Scale ◽  
Healthy Aging ◽  
Brain Activity ◽  
Brain Regions ◽  
Effective Strategies ◽  
Cognitive Improvement ◽  
Age Related ◽  
Neurocognitive Aging

Determining the mechanisms that underlie neurocognitive aging, such as compensation or dedifferentiation, and facilitating the development of effective strategies for cognitive improvement is essential due to the steadily rising aging population. One approach to study the characteristics of healthy aging comprises the assessment of functional connectivity, delineating markers of age-related neurocognitive plasticity. Functional connectivity paradigms characterize complex one-to-many (or many-to-many) structure–function relations, as higher-level cognitive processes are mediated by the interaction among a number of functionally related neural areas rather than localized to discrete brain regions. Task-related or resting-state interregional correlations of brain activity have been used as reliable indices of functional connectivity, delineating age-related alterations in a number of large-scale brain networks, which subserve attention, working memory, episodic retrieval, and task-switching. Together with behavioral and regional activation studies, connectivity studies and modeling approaches have contributed to our understanding of the mechanisms of age-related reorganization of distributed functional networks; specifically, reduced neural specificity (dedifferentiation) and associated impairment in inhibitory control and compensatory neural recruitment.

scholarly journals Altered Intra- and Interregional Synchronization in Resting-State Cerebral Networks Associated with Chronic Tinnitus

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Yu-Chen Chen ◽  
Jian Zhang ◽  
Xiao-Wei Li ◽  
Wenqing Xia ◽  
Xu Feng ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Brain Activity ◽  
Inferior Frontal Gyrus ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Chronic Tinnitus ◽  
Healthy Controls ◽  
Tinnitus Distress ◽  
The Right

Objective. Subjective tinnitus is hypothesized to arise from aberrant neural activity; however, its neural bases are poorly understood. To identify aberrant neural networks involved in chronic tinnitus, we compared the resting-state functional magnetic resonance imaging (fMRI) patterns of tinnitus patients and healthy controls.Materials and Methods. Resting-state fMRI measurements were obtained from a group of chronic tinnitus patients (n=29) with normal hearing and well-matched healthy controls (n=30). Regional homogeneity (ReHo) analysis and functional connectivity analysis were used to identify abnormal brain activity; these abnormalities were compared to tinnitus distress.Results. Relative to healthy controls, tinnitus patients had significant greater ReHo values in several brain regions including the bilateral anterior insula (AI), left inferior frontal gyrus, and right supramarginal gyrus. Furthermore, the left AI showed enhanced functional connectivity with the left middle frontal gyrus (MFG), while the right AI had enhanced functional connectivity with the right MFG; these measures were positively correlated with Tinnitus Handicap Questionnaires (r=0.459,P=0.012andr=0.479,P=0.009, resp.).Conclusions. Chronic tinnitus patients showed abnormal intra- and interregional synchronization in several resting-state cerebral networks; these abnormalities were correlated with clinical tinnitus distress. These results suggest that tinnitus distress is exacerbated by attention networks that focus on internally generated phantom sounds.

scholarly journals Linear Input as a Fundamental Motif of Brain Connectivity Organization

2019 ◽  
Author(s):  
Jonathan F. O’Rawe ◽  
Hoi-Chung Leung
Keyword(s):  
Functional Connectivity ◽  
Information Transfer ◽  
Brain Connectivity ◽  
Brain Regions ◽  
Fundamental Aspect ◽  
Biased Sampling ◽  
Whole Brain ◽  
3 Dimensional ◽  
Face Area ◽  
Learning Techniques

AbstractDescribing the pattern of region-to-region functional connectivity is an important step towards understanding information transfer and transformation between brain regions. Although fMRI data are limited in spatial resolution, recent advances in technology afford more precise mapping. Here, we extended previous methods, connective field mapping, to 3 dimensions to provide a more concise estimate of the organization and potential information transformation from one region to another. We first replicated previous work with the 3 dimensional model by showing that the topology of functional connectivity between early visual regions maintained along their eccentricity axis or the anterior-posterior dimension. We then examined higher order visual regions (e,g, fusiform face area) and showed that their pattern of connectivity, the convergence and biased sampling, seem to contribute to some of their core receptive field properties. We further demonstrated that linearity of input is a fundamental aspect of functional connectivity of the whole brain, with higher linearity between regions within a network than across networks; that is, high connective linearity was evident between early visual areas, and between prefrontal areas, but less evident between them. By decomposing the whole brain linearity matrix with manifold learning techniques, we found that the principle mode of the linearity maps onto decompositions in both functional connectivity and genetic expression reported in previous studies. The current work provides evidence supporting that linearity of input is likely a fundamental motif of functional connectivity between regions for information processing across the brain, with high linearity preserving the integrity of information from one region to another within a network.

scholarly journals Longitudinal Spatial Patterns of Intrinsic Brain Activity and Functional Connectivity in Upper Limb Amputees Patients

2020 ◽  
Author(s):  
bingbo bao ◽  
xuyun hua ◽  
haifeng wei ◽  
pengbo luo ◽  
hongyi zhu ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Spatial Patterns ◽  
Brain Plasticity ◽  
Brain Activity ◽  
Low Frequency ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Brain Network ◽  
Intrinsic Connectivity ◽  
Intrinsic Brain Activity

Abstract Background: Amputation in adults is a serious condition and most patients were associated with the remapping of representations in motor and sensory brain network. Methods: The present study includes 8 healthy volunteers and 16 patients with amputation. We use resting-state fMRI to investigate the local and extent brain plasticity in patients suffering from amputation simultaneously. Both the amplitude of low-frequency fluctuations (ALFF) and degree centrality (DC) were used for the assessment of neuroplasticity in central level. Results: We described changes in spatial patterns of intrinsic brain activity and functional connectivity in amputees in the present study and we found that not only the sensory and motor cortex, but also the related brain regions involved in the functional plasticity after upper extremity deafferentation. Conclusion: Our findings showed local and extensive cortical changes in the sensorimotor and cognitive-related brain regions, which may imply the dysfunction in not only sensory and motor function, but also sensorimotor integration and motor plan. The activation and intrinsic connectivity in the brain changed a lot showed correlation with the deafferentation status.

scholarly journals The relationship between spatial configuration and functional connectivity of brain regions

2017 ◽  
Author(s):  
Janine D. Bijsterbosch ◽  
Mark W. Woolrich ◽  
Matthew F. Glasser ◽  
Emma C. Robinson ◽  
Christian F. Beckmann ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Spatial Configuration ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Spatial Arrangement ◽  
Brain Regions ◽  
Imaging Data ◽  
Functional Regions ◽  
Cortical Regions ◽  
The Relationship

AbstractBrain connectivity is often considered in terms of the communication between functionally distinct brain regions. Many studies have investigated the extent to which patterns of coupling strength between multiple neural populations relates to behavior. For example, studies have used "functional connectivity fingerprints" to characterise individuals' brain activity. Here, we investigate the extent to which the exact spatial arrangement of cortical regions interacts with measures of brain connectivity. We find that the shape and exact location of brain regions interact strongly with the modelling of brain connectivity, and present evidence that the spatial arrangement of functional regions is strongly predictive of non-imaging measures of behaviour and lifestyle. We believe that, in many cases, cross-subject variations in the spatial configuration of functional brain regions are being interpreted as changes in functional connectivity. Therefore, a better understanding of these effects is important when interpreting the relationship between functional imaging data and cognitive traits.

scholarly journals Heterogeneity of EEG resting-state brain networks in absolute pitch

2020 ◽  
Author(s):  
Marielle Greber ◽  
Carina Klein ◽  
Simon Leipold ◽  
Silvano Sele ◽  
Lutz Jäncke
Keyword(s):  
Functional Connectivity ◽  
Auditory Cortex ◽  
Resting State ◽  
Large Scale ◽  
Absolute Pitch ◽  
Brain Regions ◽  
Brain Network ◽  
Higher Order ◽  
Neural Basis ◽  
Whole Brain

AbstractThe neural basis of absolute pitch (AP), the ability to effortlessly identify a musical tone without an external reference, is poorly understood. One of the key questions is whether perceptual or cognitive processes underlie the phenomenon as both sensory and higher-order brain regions have been associated with AP. One approach to elucidate the neural underpinnings of a specific expertise is the examination of resting-state networks.Thus, in this paper, we report a comprehensive functional network analysis of intracranial resting-state EEG data in a large sample of AP musicians (n = 54) and non-AP musicians (n = 51). We adopted two analysis approaches: First, we applied an ROI-based analysis to examine the connectivity between the auditory cortex and the dorsolateral prefrontal cortex (DLPFC) using several established functional connectivity measures. This analysis is a replication of a previous study which reported increased connectivity between these two regions in AP musicians. Second, we performed a whole-brain network-based analysis on the same functional connectivity measures to gain a more complete picture of the brain regions involved in a possibly large-scale network supporting AP ability.In our sample, the ROI-based analysis did not provide evidence for an AP-specific connectivity increase between the auditory cortex and the DLPFC. In contrast, the whole-brain analysis revealed three networks with increased connectivity in AP musicians comprising nodes in frontal, temporal, subcortical, and occipital areas. Commonalities of the networks were found in both sensory and higher-order brain regions of the perisylvian area. Further research will be needed to confirm these exploratory results.

scholarly journals Neuropathology in the North American sudden unexpected death in epilepsy registry

2021 ◽  
Vol 3 (3) ◽  
Author(s):  
Dominique F Leitner ◽  
Arline Faustin ◽  
Chloe Verducci ◽  
Daniel Friedman ◽  
Christopher William ◽  
...  
Keyword(s):  
Dentate Gyrus ◽  
North American ◽  
Focal Cortical Dysplasia ◽  
Brain Activity ◽  
Brain Regions ◽  
Sudden Unexpected Death ◽  
Age At Death ◽  
Unexpected Death ◽  
Whole Brain ◽  
The North

Abstract Sudden unexpected death in epilepsy is the leading category of epilepsy-related death and the underlying mechanisms are incompletely understood. Risk factors can include a recent history and high frequency of generalized tonic-clonic seizures, which can depress brain activity postictally, impairing respiration, arousal and protective reflexes. Neuropathological findings in sudden unexpected death in epilepsy cases parallel those in other epilepsy patients, with no implication of novel structures or mechanisms in seizure-related deaths. Few large studies have comprehensively reviewed whole brain examination of such patients. We evaluated 92 North American Sudden unexpected death in epilepsy Registry cases with whole brain neuropathological examination by board-certified neuropathologists blinded to the adjudicated cause of death, with an average of 16 brain regions examined per case. The 92 cases included 61 sudden unexpected death in epilepsy (40 definite, 9 definite plus, 6 probable, 6 possible) and 31 people with epilepsy controls who died from other causes. The mean age at death was 34.4 years and 65.2% (60/92) were male. The average age of death was younger for sudden unexpected death in epilepsy cases than for epilepsy controls (30.0 versus 39.6 years; P = 0.006), and there was no difference in sex distribution respectively (67.3% male versus 64.5%, P = 0.8). Among sudden unexpected death in epilepsy cases, earlier age of epilepsy onset positively correlated with a younger age at death (P = 0.0005) and negatively correlated with epilepsy duration (P = 0.001). Neuropathological findings were identified in 83.7% of the cases in our cohort. The most common findings were dentate gyrus dysgenesis (sudden unexpected death in epilepsy 50.9%, epilepsy controls 54.8%) and focal cortical dysplasia (FCD) (sudden unexpected death in epilepsy 41.8%, epilepsy controls 29.0%). The neuropathological findings in sudden unexpected death in epilepsy paralleled those in epilepsy controls, including the frequency of total neuropathological findings as well as the specific findings in the dentate gyrus, findings pertaining to neurodevelopment (e.g. FCD, heterotopias) and findings in the brainstem (e.g. medullary arcuate or olivary dysgenesis). Thus, like prior studies, we found no neuropathological findings that were more common in sudden unexpected death in epilepsy cases. Future neuropathological studies evaluating larger sudden unexpected death in epilepsy and control cohorts would benefit from inclusion of different epilepsy syndromes with detailed phenotypic information, consensus among pathologists particularly for more subjective findings where observations can be inconsistent, and molecular approaches to identify markers of sudden unexpected death in epilepsy risk or pathogenesis.

scholarly journals The cue-reactivity paradigm: An ensemble of networks driving attention and cognition when viewing drug-related and natural-reward stimuli

2020 ◽  
Author(s):  
Lauren D. Hill-Bowen ◽  
Michael C. Riedel ◽  
Ranjita Poudel ◽  
Taylor Salo ◽  
Jessica S. Flannery ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Brain Activity ◽  
Cue Reactivity ◽  
Dorsal Striatum ◽  
Brain Regions ◽  
Reward Processing ◽  
Resting State Functional Connectivity ◽  
Addictive Disorders ◽  
Natural Reward ◽  
Elemental Nature

ABSTRACTBackgroundThe cue-reactivity paradigm is a widely adopted neuroimaging probe assessing brain activity linked to attention, memory, emotion, and reward processing associated with the presentation of appetitive stimuli. Lacking, is the apperception of more precise brain regions, neurocircuits, and mental operations comprising cue-reactivity’s multi-elemental nature. To resolve such complexities, we employed emergent meta-analytic techniques to enhance insight into drug and natural cue-reactivity in the brain.MethodsOperating from this perspective, we first conducted multiple coordinate-based meta-analyses to define common and distinct brain regions showing convergent activation across studies involving drug-related and natural-reward cue-reactivity paradigms. In addition, we examined the activation profiles of each convergent brain region linked to cue-reactivity as seeds in task-dependent and task-independent functional connectivity analyses. Using methods to cluster regions of interest, we categorized cue-reactivity into cliques, or sub-networks, based on the functional similarities between regions. Cliques were further classified with psychological constructs.ResultsWe identified a total of 164 peer-reviewed articles: 108 drug-related, and 56 natural-reward. When considering cue-reactivity collectively, across both drug and natural studies, activity convergence was observed in the dorsal striatum, limbic, insula, parietal, occipital, and temporal regions. Common convergent neural activity between drug and natural cue-reactivity was observed in the caudate, amygdala, thalamus, cingulate, and temporal regions. Drug distinct convergence was observed in the putamen, cingulate, and temporal regions, while natural distinct convergence was observed in the caudate, parietal, occipital, and frontal regions. We seeded identified cue-reactivity regions in meta-analytic connectivity modeling and resting-state functional connectivity analyses. Consensus hierarchical clustering of both connectivity analyses identified six distinct cliques that were further functionally characterized using the BrainMap and Neurosynth databases.ConclusionsWe examined the multifaceted nature of cue-reactivity and decomposed this construct into six elements of visual, executive function, sensorimotor, salience, emotion, and self-referential processing. Further, we demonstrated that these elements are supported by perceptual, sensorimotor, tripartite, and affective networks, which are essential to understanding the neural mechanisms involved in the development and or maintenance of addictive disorders.

scholarly journals Multifractal and entropy analysis of resting-state electroencephalography reveals spatial organization in local dynamic functional connectivity

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Frigyes Samuel Racz ◽  
Orestis Stylianou ◽  
Peter Mukli ◽  
Andras Eke
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Spatial Organization ◽  
Brain Activity ◽  
Surrogate Data ◽  
Brain Regions ◽  
Local Dynamic ◽  
Dynamic Functional Connectivity ◽  
Multifractal Scaling ◽  
The Brain

Abstract Functional connectivity of the brain fluctuates even in resting-state condition. It has been reported recently that fluctuations of global functional network topology and those of individual connections between brain regions expressed multifractal scaling. To expand on these findings, in this study we investigated if multifractality was indeed an inherent property of dynamic functional connectivity (DFC) on the regional level as well. Furthermore, we explored if local DFC showed region-specific differences in its multifractal and entropy-related features. DFC analyses were performed on 62-channel, resting-state electroencephalography recordings of twelve young, healthy subjects. Surrogate data testing verified the true multifractal nature of regional DFC that could be attributed to the presumed nonlinear nature of the underlying processes. Moreover, we found a characteristic spatial distribution of local connectivity dynamics, in that frontal and occipital regions showed stronger long-range correlation and higher degree of multifractality, whereas the highest values of entropy were found over the central and temporal regions. The revealed topology reflected well the underlying resting-state network organization of the brain. The presented results and the proposed analysis framework could improve our understanding on how resting-state brain activity is spatio-temporally organized and may provide potential biomarkers for future clinical research.

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