scholarly journals Rethinking Measures of Functional Connectivity via Feature Extraction

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Rosaleena Mohanty ◽  
William A. Sethares ◽  
Veena A. Nair ◽  
Vivek Prabhakaran
Keyword(s):  
Functional Connectivity ◽  
Large Scale ◽  
Linear Time ◽  
Adult Population ◽  
Resting State Fmri ◽  
Blood Oxygen Level Dependent ◽  
Blood Oxygen Level ◽  
Pearson’S Correlation ◽  
Functional Connections ◽  
Pearson's Correlation

AbstractFunctional magnetic resonance imaging (fMRI)-based functional connectivity (FC) commonly characterizes the functional connections in the brain. Conventional quantification of FC by Pearson's correlation captures linear, time-domain dependencies among blood-oxygen-level-dependent (BOLD) signals. We examined measures to quantify FC by investigating: (i) Is Pearson's correlation sufficient to characterize FC? (ii) Can alternative measures better quantify FC? (iii) What are the implications of using alternative FC measures? FMRI analysis in healthy adult population suggested that: (i) Pearson's correlation cannot comprehensively capture BOLD inter-dependencies. (ii) Eight alternative FC measures were similarly consistent between task and resting-state fMRI, improved age-based classification and provided better association with behavioral outcomes. (iii) Formulated hypotheses were: first, in lieu of Pearson’s correlation, an augmented, composite and multi-metric definition of FC is more appropriate; second, canonical large-scale brain networks may depend on the chosen FC measure. A thorough notion of FC promises better understanding of variations within a given population.

scholarly journals Resting-State Functional Connectivity in Mathematical Expertise

2021 ◽  
Vol 11 (4) ◽  
pp. 430
Author(s):  
Miseon Shim ◽  
Han-Jeong Hwang ◽  
Ulrike Kuhl ◽  
Hyeon-Ae Jeon
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Resting State Fmri ◽  
Blood Oxygen Level Dependent ◽  
Brain Regions ◽  
Resting State Functional Connectivity ◽  
Blood Oxygen Level ◽  
Orbital Gyrus ◽  
Neural Efficiency ◽  
Mathematical Expertise

To what extent are different levels of expertise reflected in the functional connectivity of the brain? We addressed this question by using resting-state functional magnetic resonance imaging (fMRI) in mathematicians versus non-mathematicians. To this end, we investigated how the two groups of participants differ in the correlation of their spontaneous blood oxygen level-dependent fluctuations across the whole brain regions during resting state. Moreover, by using the classification algorithm in machine learning, we investigated whether the resting-state fMRI networks between mathematicians and non-mathematicians were distinguished depending on features of functional connectivity. We showed diverging involvement of the frontal–thalamic–temporal connections for mathematicians and the medial–frontal areas to precuneus and the lateral orbital gyrus to thalamus connections for non-mathematicians. Moreover, mathematicians who had higher scores in mathematical knowledge showed a weaker connection strength between the left and right caudate nucleus, demonstrating the connections’ characteristics related to mathematical expertise. Separate functional networks between the two groups were validated with a maximum classification accuracy of 91.19% using the distinct resting-state fMRI-based functional connectivity features. We suggest the advantageous role of preconfigured resting-state functional connectivity, as well as the neural efficiency for experts’ successful performance.

scholarly journals Abnormal interhemispheric functional connectivity in patients with strabismic amblyopia: a resting-state fMRI study using voxel-mirrored homotopic connectivity

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Shuang Zhang ◽  
Gui-Ping Gao ◽  
Wen-Qing Shi ◽  
Biao Li ◽  
Qi Lin ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Brain Activity ◽  
Characteristic Curve ◽  
Clinical Manifestations ◽  
Resting State Fmri ◽  
Diagnostic Value ◽  
Functional Connections ◽  
Receiver Operating

Abstract Background Previous studies have demonstrated that strabismus amblyopia can result in markedly brain function alterations. However, the differences in spontaneous brain activities of strabismus amblyopia (SA) patients still remain unclear. Therefore, the current study intended to employthe voxel-mirrored homotopic connectivity (VMHC) method to investigate the intrinsic brain activity changes in SA patients. Purpose To investigate the changes in cerebral hemispheric functional connections in patients with SA and their relationship with clinical manifestations using the VMHC method. Material and methods In the present study, a total of 17 patients with SA (eight males and nine females) and 17 age- and weight-matched healthy control (HC) groups were enrolled. Based on the VMHC method, all subjects were examined by functional magnetic resonance imaging. The functional interaction between cerebral hemispheres was directly evaluated. The Pearson’s correlation test was used to analyze the clinical features of patients with SA. In addition, their mean VMHC signal values and the receiver operating characteristic curve were used to distinguish patients with SA and HC groups. Results Compared with HC group, patients with SA had higher VMHC values in bilateral cingulum ant, caudate, hippocampus, and cerebellum crus 1. Moreover, the VMHC values of some regions were positively correlated with some clinical manifestations. In addition, receiver operating characteristic curves presented higher diagnostic value in these areas. Conclusion SA subjects showed abnormal brain interhemispheric functional connectivity in visual pathways, which might give some instructive information for understanding the neurological mechanisms of SA patients.

scholarly journals Large-scale DCMs for resting-state fMRI

2017 ◽  
Vol 1 (3) ◽  
pp. 222-241 ◽  
Author(s):  
Adeel Razi ◽  
Mohamed L. Seghier ◽  
Yuan Zhou ◽  
Peter McColgan ◽  
Peter Zeidman ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Large Scale ◽  
Effective Connectivity ◽  
Directed Graphs ◽  
Resting State Fmri ◽  
Causal Modeling ◽  
Large Graphs ◽  
Model Inversion ◽  
Graph Theoretic

This paper considers the identification of large directed graphs for resting-state brain networks based on biophysical models of distributed neuronal activity, that is, effective connectivity. This identification can be contrasted with functional connectivity methods based on symmetric correlations that are ubiquitous in resting-state functional MRI (fMRI). We use spectral dynamic causal modeling (DCM) to invert large graphs comprising dozens of nodes or regions. The ensuing graphs are directed and weighted, hence providing a neurobiologically plausible characterization of connectivity in terms of excitatory and inhibitory coupling. Furthermore, we show that the use of Bayesian model reduction to discover the most likely sparse graph (or model) from a parent (e.g., fully connected) graph eschews the arbitrary thresholding often applied to large symmetric (functional connectivity) graphs. Using empirical fMRI data, we show that spectral DCM furnishes connectivity estimates on large graphs that correlate strongly with the estimates provided by stochastic DCM. Furthermore, we increase the efficiency of model inversion using functional connectivity modes to place prior constraints on effective connectivity. In other words, we use a small number of modes to finesse the potentially redundant parameterization of large DCMs. We show that spectral DCM—with functional connectivity priors—is ideally suited for directed graph theoretic analyses of resting-state fMRI. We envision that directed graphs will prove useful in understanding the psychopathology and pathophysiology of neurodegenerative and neurodevelopmental disorders. We will demonstrate the utility of large directed graphs in clinical populations in subsequent reports, using the procedures described in this paper.

scholarly journals Human subsystems of medial temporal lobes extend locally to amygdala nuclei and globally to an allostatic-interoceptive system

2019 ◽  
Author(s):  
Adriana L. Ruiz-Rizzo ◽  
Florian Beissner ◽  
Kathrin Finke ◽  
Hermann J. Müller ◽  
Claus Zimmer ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Large Scale ◽  
Local Level ◽  
Resting State Fmri ◽  
Medial Temporal Lobes ◽  
Default Mode ◽  
Temporal Lobes ◽  
Dual Regression ◽  
Slow Activity ◽  
Global Brain

AbstractIn mammals, the hippocampus, entorhinal, perirhinal, and parahippocampal cortices (i.e., core regions of the human medial temporal lobes, MTL) are locally interlaced with the adjacent amygdala nuclei at the structural and functional levels. At the global brain level, the human MTL has been described as part of the default mode network whereas amygdala nuclei as parts of the salience network, with both networks forming collectively a large-scale brain system supporting allostatic-interoceptive functions. We hypothesized (i) that intrinsic functional connectivity of slow activity fluctuations would reveal human MTL subsystems locally extending to the amygdala; and (ii) that these extended local subsystems would be globally embedded in large-scale brain systems supporting allostatic-interoceptive functions. From the resting-state fMRI data of three independent samples of cognitively healthy adults (one main and two replication samples: Ns = 101, 61, and 29, respectively), we analyzed the functional connectivity of fluctuating ongoing BOLD-activity within and outside the amygdala-MTL in a data-driven way using masked independent component and dual-regression analyses. We found that at the local level MTL subsystems extend to the amygdala and are functionally organized along the longitudinal amygdala-MTL axis. These subsystems were characterized by a consistent involvement of amygdala, hippocampus, and entorhinal cortex, but a variable participation of perirhinal and parahippocampal regions. At the global level, amygdala-MTL subsystems selectively connected to salience, thalamic-brainstem, and default mode networks – the major cortical and subcortical parts of the allostatic-interoceptive system. These results provide evidence for integrated amygdala-MTL subsystems in humans, which are embedded within a larger allostatic-interoceptive system.

scholarly journals Advanced Meditation Alters Resting-State Brain Network Connectivity Correlating With Improved Mindfulness

2021 ◽  
Vol 12 ◽  
Author(s):  
Ramana V. Vishnubhotla ◽  
Rupa Radhakrishnan ◽  
Kestas Kveraga ◽  
Rachael Deardorff ◽  
Chithra Ram ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Network Connectivity ◽  
Blood Oxygen Level Dependent ◽  
Brain Network ◽  
Resting State Functional Connectivity ◽  
Blood Oxygen Level ◽  
Default Mode ◽  
Before And After ◽  
Brain Network Connectivity

Purpose: The purpose of this study was to investigate the effect of an intensive 8-day Samyama meditation program on the brain functional connectivity using resting-state functional MRI (rs-fMRI).Methods: Thirteen Samyama program participants (meditators) and 4 controls underwent fMRI brain scans before and after the 8-day residential meditation program. Subjects underwent fMRI with a blood oxygen level dependent (BOLD) contrast at rest and during focused breathing. Changes in network connectivity before and after Samyama program were evaluated. In addition, validated psychological metrics were correlated with changes in functional connectivity.Results: Meditators showed significantly increased network connectivity between the salience network (SN) and default mode network (DMN) after the Samyama program (p < 0.01). Increased connectivity within the SN correlated with an improvement in self-reported mindfulness scores (p < 0.01).Conclusion: Samyama, an intensive silent meditation program, favorably increased the resting-state functional connectivity between the salience and default mode networks. During focused breath watching, meditators had lower intra-network connectivity in specific networks. Furthermore, increased intra-network connectivity correlated with improved self-reported mindfulness after Samyama.Clinical Trials Registration: [https://clinicaltrials.gov], Identifier: [NCT04366544]. Registered on 4/17/2020.

scholarly journals Thresholding Functional Connectivity Matrices to Recover the Topological Properties of Large-Scale Neuronal Networks

2021 ◽  
Vol 15 ◽  
Author(s):  
Alessio Boschi ◽  
Martina Brofiga ◽  
Paolo Massobrio
Keyword(s):  
Functional Connectivity ◽  
Large Scale ◽  
Neuronal Networks ◽  
Brain Connectivity ◽  
Structural Connectivity ◽  
Synthetic Data ◽  
Connectivity Matrix ◽  
Causal Connection ◽  
Topological Properties ◽  
Functional Connections

The identification of the organization principles on the basis of the brain connectivity can be performed in terms of structural (i.e., morphological), functional (i.e., statistical), or effective (i.e., causal) connectivity. If structural connectivity is based on the detection of the morphological (synaptically mediated) links among neurons, functional and effective relationships derive from the recording of the patterns of electrophysiological activity (e.g., spikes, local field potentials). Correlation or information theory-based algorithms are typical routes pursued to find statistical dependencies and to build a functional connectivity matrix. As long as the matrix collects the possible associations among the network nodes, each interaction between the neuron i and j is different from zero, even though there was no morphological, statistical or causal connection between them. Hence, it becomes essential to find and identify only the significant functional connections that are predictive of the structural ones. For this reason, a robust, fast, and automatized procedure should be implemented to discard the “noisy” connections. In this work, we present a Double Threshold (DDT) algorithm based on the definition of two statistical thresholds. The main goal is not to lose weak but significant links, whose arbitrary exclusion could generate functional networks with a too small number of connections and altered topological properties. The algorithm allows overcoming the limits of the simplest threshold-based methods in terms of precision and guaranteeing excellent computational performances compared to shuffling-based approaches. The presented DDT algorithm was compared with other methods proposed in the literature by using a benchmarking procedure based on synthetic data coming from the simulations of large-scale neuronal networks with different structural topologies.

scholarly journals Differential effects of anesthetics on resting state functional connectivity in the mouse

2019 ◽  
Vol 40 (4) ◽  
pp. 875-884 ◽  
Author(s):  
Hongyu Xie ◽  
David Y Chung ◽  
Sreekanth Kura ◽  
Kazutaka Sugimoto ◽  
Sanem A Aykan ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Chloral Hydrate ◽  
Low Frequency ◽  
Blood Oxygen Level Dependent ◽  
Resting State Functional Connectivity ◽  
Blood Oxygen Level ◽  
Intrinsic Signal ◽  
Optical Intrinsic Signal ◽  
Important Approach

Blood oxygen level-dependent (BOLD) functional MRI (fMRI) is a standard approach to examine resting state functional connectivity (RSFC), but fMRI in animal models is challenging. Recently, functional optical intrinsic signal imaging—which relies on the same hemodynamic signal underlying BOLD fMRI—has been developed as a complementary approach to assess RSFC in mice. Since it is difficult to ensure that an animal is in a truly resting state while awake, RSFC measurements under anesthesia remain an important approach. Therefore, we systematically examined measures of RSFC using non-invasive, widefield optical intrinsic signal imaging under five different anesthetics in male C57BL/6J mice. We find excellent seed-based, global, and interhemispheric connectivity using tribromoethanol (Avertin) and ketamine–xylazine, comparable to results in the literature including awake animals. Urethane anesthesia yielded intermediate results, while chloral hydrate and isoflurane were both associated with poor RSFC. Furthermore, we found a correspondence between the strength of RSFC and the power of low-frequency hemodynamic fluctuations. In conclusion, Avertin and ketamine–xylazine provide robust and reproducible measures of RSFC in mice, whereas chloral hydrate and isoflurane do not.

scholarly journals Static and dynamic aspects of cerebro-cerebellar functional connectivity are associated with self-reported measures of impulsivity: A resting-state fMRI study

2020 ◽  
Vol 4 (3) ◽  
pp. 891-909
Author(s):  
Majd Abdallah ◽  
Nicolas Farrugia ◽  
Valentine Chirokoff ◽  
Sandra Chanraud
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Sensation Seeking ◽  
Large Scale ◽  
Resting State Fmri ◽  
Posterior Cingulate Cortex ◽  
Impulsive Behavior ◽  
Dynamic Features ◽  
Behavioral Correlates ◽  
Total Strength

Human and animal brain studies bring converging evidence of a possible role for the cerebellum and the cerebro-cerebellar system in impulsivity. However, the precise nature of the relation between cerebro-cerebellar coupling and impulsivity is far from understood. Characterizing functional connectivity (FC) patterns between large-scale brain networks that mediate different forms of impulsivity, and the cerebellum may improve our understanding of this relation. Here, we analyzed static and dynamic features of cerebro-cerebellar FC using a highly sampled resting-state functional magnetic resonance imaging (rs-fMRI) dataset and tested their association with two widely used self-reports of impulsivity: the UPPS-P impulsive behavior scale and the behavioral inhibition/approach systems (BIS/BAS) in a large group of healthy subjects ( N = 134, ≈ 1 hr of rs-fMRI/subject). We employed robust data-driven techniques to identify cerebral and cerebellar resting-state networks and extract descriptive summary measures of static and dynamic cerebro-cerebellar FC. We observed evidence linking BIS, BAS, sensation seeking, and lack of premeditation to the total strength and temporal variability of FC within networks connecting regions of the prefrontal cortex, precuneus, posterior cingulate cortex, basal ganglia, and thalamus with the cerebellum. Overall, our findings improve the existing knowledge of the neural correlates of impulsivity and the behavioral correlates of the cerebro-cerebellar system.

Functional connectivity during smooth pursuit eye movements

2020 ◽  
Vol 124 (6) ◽  
pp. 1839-1856
Author(s):  
Rebekka Schröder ◽  
Anna-Maria Kasparbauer ◽  
Inga Meyhöfer ◽  
Maria Steffens ◽  
Peter Trautner ◽  
...  
Keyword(s):  
Eye Movements ◽  
Functional Connectivity ◽  
Smooth Pursuit ◽  
Potential Role ◽  
Blood Oxygen Level Dependent ◽  
Smooth Pursuit Eye Movements ◽  
Blood Oxygen Level ◽  
Comprehensive Investigation ◽  
Pursuit Eye Movements ◽  
Healthy Participants

This study provides a comprehensive investigation of blood oxygen level-dependent (BOLD) functional connectivity during smooth pursuit eye movements. Results from a large sample of healthy participants suggest that key oculomotor regions interact closely with each other but also with regions not primarily associated with eye movements. Understanding functional connectivity during smooth pursuit is important, given its potential role as an endophenotype of psychoses.

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