scholarly journals The frontoparietal network: function, electrophysiology, and importance of individual precision mapping

2018 ◽  
Vol 20 (2) ◽  
pp. 133-140 ◽  
Keyword(s):  
Resting State ◽  
Resting State Networks ◽  
Individual Subject ◽  
Network Function ◽  
Hyperactivity Disorder ◽  
Frontoparietal Network ◽  
Functional Brain Networks ◽  
Network Coordination ◽  
Functional Topography ◽  
Human Brains

The frontoparietal network is critical for our ability to coordinate behavior in a rapid, accurate, and flexible goal-driven manner. In this review, we outline support for the framing of the frontoparietal network as a distinct control network, in part functioning to flexibly interact with and alter other functional brain networks. This network coordination likely occurs in a 4 Hz to13 Hz θ/α rhythm, both during resting state and task state. Precision mapping of individual human brains has revealed that the functional topography of the frontoparietal network is variable between individuals, underscoring the notion that group-average studies of the frontoparietal network may be obscuring important typical and atypical features. Many forms of psychopathology implicate the frontoparietal network, such as schizophrenia and attention-deficit/hyperactivity disorder. Given the interindividual variability in frontoparietal network organization, clinical studies will likely benefit greatly from acquiring more individual subject data to accurately characterize resting-state networks compromised in psychopathology

scholarly journals Quantifying the Variability in Resting-State Networks

Entropy ◽  
2019 ◽  
Vol 21 (9) ◽  
pp. 882 ◽  
Author(s):  
Isaura Oliver ◽  
Jaroslav Hlinka ◽  
Jakub Kopal ◽  
Jörn Davidsen
Keyword(s):  
Resting State ◽  
Similarity Measures ◽  
Brain Network ◽  
Brain Atlas ◽  
Resting State Networks ◽  
Brain Organization ◽  
Hyperactivity Disorder ◽  
Network Topologies ◽  
Open Question ◽  
Human Brains

Recent precision functional mapping of individual human brains has shown that individual brain organization is qualitatively different from group average estimates and that individuals exhibit distinct brain network topologies. How this variability affects the connectivity within individual resting-state networks remains an open question. This is particularly important since certain resting-state networks such as the default mode network (DMN) and the fronto-parietal network (FPN) play an important role in the early detection of neurophysiological diseases like Alzheimer’s, Parkinson’s, and attention deficit hyperactivity disorder. Using different types of similarity measures including conditional mutual information, we show here that the backbone of the functional connectivity and the direct connectivity within both the DMN and the FPN does not vary significantly between healthy individuals for the AAL brain atlas. Weaker connections do vary however, having a particularly pronounced effect on the cross-connections between DMN and FPN. Our findings suggest that the link topology of single resting-state networks is quite robust if a fixed brain atlas is used and the recordings are sufficiently long—even if the whole brain network topology between different individuals is variable.

scholarly journals Abnormal Static and Dynamic Functional Network Connectivity in Patients With Presbycusis

2022 ◽  
Vol 13 ◽  
Author(s):  
Chunhua Xing ◽  
Yu-Chen Chen ◽  
Song’an Shang ◽  
Jin-Jing Xu ◽  
Huiyou Chen ◽  
...  
Keyword(s):  
Resting State ◽  
Network Connectivity ◽  
Functional Network ◽  
Resting State Networks ◽  
Cognitive Assessments ◽  
Functional Network Connectivity ◽  
Frontoparietal Network ◽  
Group Independent Component Analysis ◽  
Visual Network ◽  
Dynamic Functional Network Connectivity

Aim: This study aimed to investigate abnormal static and dynamic functional network connectivity (FNC) and its association with cognitive function in patients with presbycusis.Methods: In total, 60 patients with presbycusis and 60 age-, sex-, and education-matched healthy controls (HCs) underwent resting-state functional MRI (rs-fMRI) and cognitive assessments. Group independent component analysis (ICA) was carried out on the rs-fMRI data, and eight resting-state networks (RSNs) were identified. Static and dynamic FNCs (sFNC and dFNC) were then constructed to evaluate differences in RSN connectivity between the patients with presbycusis and the HCs. Furthermore, the correlations between these differences and cognitive scores were analyzed.Results: Patients with presbycusis had differences in sFNC compared with HCs, mainly reflected in decreased sFNC in the default mode network (DMN)-left frontoparietal network (LFPN) and attention network (AN)-cerebellum network (CN) pairs, but they had increased sFNC in the auditory network (AUN) between DMN domains. The decreased sFNC in the DMN-LFPN pair was negatively correlated with their TMT-B score (r = –0.441, p = 0.002). Patients with presbycusis exhibited aberrant dFNCs in State 2 and decreased dFNCs between the CN and AN and the visual network (VN). Moreover, the presbycusis group had a shorter mean dwell time (MDT) and fraction time (FT) in State 3 (p = 0.0027; p = 0.0031, respectively).Conclusion: This study highlighted differences in static and dynamic functional connectivity in patients with presbycusis and suggested that FNC may serve as an important biomarker of cognitive performance since abnormal alterations can better track cognitive impairment in presbycusis.

Identification of Brain Functional Networks Using a Model-Based Approach

2019 ◽  
Vol 34 (08) ◽  
pp. 2057004
Author(s):  
Vangelis P. Oikonomou ◽  
Konstantinos Blekas ◽  
Loukas Astrakas
Keyword(s):  
Time Series ◽  
Resting State ◽  
Probabilistic Method ◽  
Resting State Fmri ◽  
Model Parameters ◽  
Resting State Networks ◽  
Model Based ◽  
Functional Brain Networks ◽  
Regression Mixture ◽  
The Brain

Functional MRI (fMRI) is a valuable brain imaging technique. A significant problem, when analyzing fMRI time series, is the finding of functional brain networks when the brain is at rest, i.e. no external stimulus is applied to the subject. In this work, we present a probabilistic method to estimate the Resting State Networks (RSNs) using a model-based approach. More specifically, RSNs are assumed to be the result of a clustering procedure. In order to perform the clustering, a mixture of regression models are used. Furthermore, special care has been given in order to incorporate important functionalities, such as spatial and embedded sparsity enforcing properties, through the use of informative priors over the model parameters. Another interesting feature of the proposed scheme is the flexibility to handle all the brain time series at once, allowing more robust solutions. We provide comparative experimental results, using an artificial fMRI dataset and two real resting state fMRI datasets, that empirically illustrate the efficiency of the proposed regression mixture model.

Assessing brain connectivity at rest is clinically relevant in early multiple sclerosis

2012 ◽  
Vol 18 (9) ◽  
pp. 1251-1258 ◽  
Author(s):  
Anthony Faivre ◽  
Audrey Rico ◽  
Wafaa Zaaraoui ◽  
Lydie Crespy ◽  
Françoise Reuter ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Independent Component Analysis ◽  
Functional Mri ◽  
Resting State ◽  
Surrogate Marker ◽  
Component Analysis ◽  
Independent Component ◽  
Resting State Networks ◽  
Frontoparietal Network ◽  
Multiple Sclerosis Patients

Objective: The present study aims to determine the clinical counterpart of brain resting-state networks reorganization recently evidenced in early multiple sclerosis. Methods: Thirteen patients with early relapsing–remitting multiple sclerosis and 14 matched healthy controls were included in a resting state functional MRI study performed at 3 T. Data were analyzed using group spatial Independent Component Analysis using concatenation approach (FSL 4.1.3) and double regression analyses (SPM5) to extract local and global levels of connectivity inside various resting state networks (RSNs). Differences in global levels of connectivity of each network between patients and controls were assessed using Mann–Whitney U-test. In patients, relationship between clinical data (Expanded Disability Status Scale and Multiple Sclerosis Functional Composite Score – MSFC) and global RSN connectivity were assessed using Spearman rank correlation. Results: Independent component analysis provided eight consistent neuronal networks involved in motor, sensory and cognitive processes. For seven RSNs, the global level of connectivity was significantly increased in patients compared with controls. No significant decrease in RSN connectivity was found in early multiple sclerosis patients. MSFC values were negatively correlated with increased RSN connectivity within the dorsal frontoparietal network ( r = −0.811, p = 0.001), the right ventral frontoparietal network ( r = − 0.587, p = 0.045) and the prefronto-insular network ( r = −0.615, p = 0.033). Conclusions: This study demonstrates that resting state networks reorganization is strongly associated with disability in early multiple sclerosis. These findings suggest that resting state functional MRI may represent a promising surrogate marker of disease burden.

scholarly journals Altered Functional Organization within and between Resting-State Networks in Chronic Subcortical Infarction

2014 ◽  
Vol 34 (4) ◽  
pp. 597-605 ◽  
Author(s):  
Caihong Wang ◽  
Wen Qin ◽  
Jing Zhang ◽  
Tian Tian ◽  
Ying Li ◽  
...  
Keyword(s):  
Resting State ◽  
Functional Organization ◽  
Resting State Networks ◽  
Imaging Data ◽  
Functional Magnetic Resonance ◽  
Magnetic Resonance Imaging Data ◽  
Stroke Patients ◽  
Frontoparietal Network ◽  
Normal Controls ◽  
Subcortical Infarction

This study aimed to investigate the changes in functional connectivity (FC) within each resting-state network (RSN) and between RSNs in subcortical stroke patients who were well recovered in global motor function. Eleven meaningful RSNs were identified via functional magnetic resonance imaging data from 25 subcortical stroke patients and 22 normal controls using independent component analysis. Compared with normal controls, stroke patients exhibited increased intranetwork FC in the sensorimotor (SMN), visual (VN), auditory (AN), dorsal attention (DAN), and default mode (DMN) networks; they also exhibited decreased intranetwork FC in the frontoparietal network (FPN) and anterior DMN. Stroke patients displayed a shift from no FC in controls to negative internetwork FC between the VN and AN as well as between the VN and SMN. Stroke patients also exhibited weakened positive (anterior and posterior DMN; posterior DMN and right FPN) or negative (AN and right FPN; posterior DMN and dorsal SMN) internetwork FC when compared with normal controls. We suggest that subcortical stroke may induce connectivity changes in multiple functional networks, affecting not only the intranetwork FC within RSNs but also the internetwork FC between these RSNs.

scholarly journals Resting-state networks in the course of aging—differential insights from studies across the lifespan vs. amongst the old

2021 ◽  
Vol 473 (5) ◽  
pp. 793-803 ◽  
Author(s):  
C. Jockwitz ◽  
S. Caspers
Keyword(s):  
Resting State ◽  
Adult Population ◽  
Brain Networks ◽  
Individual Variability ◽  
Resting State Networks ◽  
Resting State Functional Connectivity ◽  
Differential Effects ◽  
Adult Lifespan ◽  
Age Related ◽  
Functional Brain Networks

AbstractResting-state functional connectivity (RSFC) has widely been used to examine reorganization of functional brain networks during normal aging. The extraction of generalizable age trends, however, is hampered by differences in methodological approaches, study designs and sample characteristics. Distinct age ranges of study samples thereby represent an important aspect between studies especially due to the increase in inter-individual variability over the lifespan. The current review focuses on comparing age-related differences in RSFC in the course of the whole adult lifespan versus later decades of life. We summarize and compare studies assessing age-related differences in within- and between-network RSFC of major resting-state brain networks. Differential effects of the factor age on resting-state networks can be identified when comparing studies focusing on younger versus older adults with studies investigating effects within the older adult population. These differential effects pertain to higher order and primary processing resting-state networks to a varying extent. Especially during later decades of life, other factors beyond age might come into play to understand the high inter-individual variability in RSFC.

scholarly journals Pig Brains Have Homologous Resting-State Networks with Human Brains

2019 ◽  
Vol 9 (7) ◽  
pp. 566-579 ◽  
Author(s):  
Gregory Simchick ◽  
Alice Shen ◽  
Brandon Campbell ◽  
Hea Jin Park ◽  
Franklin D. West ◽  
...  
Keyword(s):  
Resting State ◽  
Resting State Networks ◽  
Human Brains

scholarly journals Association of Network Connectivity via Resting State Functional MRI with Consciousness, Mortality, and Outcomes in Neonatal Acute Brain Injury

2021 ◽  
Author(s):  
Varina L. Boerwinkle ◽  
Bethany Sussman ◽  
Iliana Manjon ◽  
Lucia Mirea ◽  
Saher Suleman ◽  
...  
Keyword(s):  
Brain Injury ◽  
Developmental Delay ◽  
Functional Mri ◽  
Resting State ◽  
Brain Network ◽  
Acute Brain Injury ◽  
Discharge Condition ◽  
Resting State Networks ◽  
Network Function ◽  
Neurological Exam

Background An accurate and comprehensive test of integrated brain network function is needed for neonates during the acute brain injury period to inform on morbidity. This retrospective cohort study aimed to assess whether integrated brain network function by resting state functional MRI, acquired during the acute period in neonates with brain injury, is associated with acute exam, neonatal mortality, and 5-month outcomes. Methods This study included 40 consecutive neonates with resting state functional MRI acquired 1-22 days after suspected brain insult from March 2018 to July 2019 at Phoenix Childrens Hospital. Acute period exam and test results were assigned ordinal scores based on severity as documented by respective treating specialists. Analyses (Fisher exact, Wilcoxon-rank sum test, ordinal/multinomial logistic regression) examined association of resting state networks with demographics, presentation, neurological exam, electroencephalogram, anatomical MRI, magnetic resonance spectroscopy, passive task functional MRI, and outcomes of discharge condition, outpatient development, motor tone, seizure, and mortality. Results Subjects had a mean (standard deviation) gestational age of 37.8 (2.6) weeks, a majority were male (63%), with diagnosis of hypoxic ischemic encephalopathy (68%). Other findings at birth included mild distress (48%), moderately abnormal neurological exam (33%), and consciousness characterized as awake but irritable (40%). Significant associations after multiple testing corrections were detected for resting state networks: basal ganglia with outpatient developmental delay (odds ratio [OR], 14.5; 99.4% confidence interval [CI], 2.00-105; P<.001) and motor tone/weakness (OR, 9.98; 99.4% CI, 1.72-57.9; P<.001); language/frontal-parietal network with discharge condition (OR, 5.13; 99.4% CI, 1.22-21.5; P=.002) and outpatient developmental delay (OR, 4.77; 99.4% CI, 1.21-18.7; P=.002); default mode network with discharge condition (OR, 3.72; 99.4% CI, 1.01-13.78; P=.006) and neurological exam (P=.002 (FE); OR, 11.8; 99.4% CI, 0.73-191; P=.01 (OLR)); seizure onset zone with motor tone/weakness (OR, 3.31; 99.4% CI, 1.08-10.1; P=.003). Resting state networks were not detected in only three neonates, who died prior to discharge. Conclusions This study provides level 3 evidence (OCEBM Levels of Evidence Working Group) that the degree of abnormality of resting state networks in neonatal acute brain injury is associated with acute exam and outcomes. Total lack of brain network detection was only found in patients who did not survive.

scholarly journals Aberrant Interhemispheric Functional Organization in Children with Dyskinetic Cerebral Palsy

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Yun Qin ◽  
Bo Sun ◽  
Huali Zhang ◽  
Yanan Li ◽  
Tao Zhang ◽  
...  
Keyword(s):  
Cerebral Palsy ◽  
Resting State ◽  
Functional Organization ◽  
Fundamental Principle ◽  
Pathophysiological Mechanism ◽  
Healthy Children ◽  
Resting State Networks ◽  
Frontoparietal Network ◽  
Interhemispheric Connectivity ◽  
Visual Motor

Background. Hemispheric asymmetry is one fundamental principle of neuronal organization. Interhemispheric connectivity and lateralization of intrinsic networks in the resting-state brain demonstrate the interhemispheric functional organization and can be affected by disease processes. This study aims to investigate the interhemispheric organization in children with dyskinetic cerebral palsy (DCP) based on resting-state functional MRI (fMRI). Methods. 24 children with DCP and 20 healthy children were included. Voxel-mirrored homotopic connectivity (VMHC) was calculated to detect the interhemispheric connectivity, and the lateralization of the resting-state networks was performed to examine the asymmetry of the intrinsic networks of brain. Results. Decreased interhemispheric connectivity was found at visual, motor, and motor-control related regions in children with DCP, while high cognitive related networks including the central executive network, the frontoparietal network, and the salience network represented decreased asymmetry in children with DCP. Abnormal VMHC in visual areas, as well as the altered lateralization in inferior parietal lobule and supplementary motor area, showed correlation with the gross motor function and activities of daily living in children with DCP. Conclusion. These findings indicate that the interhemispheric functional organization alteration exists in children with DCP, suggesting that abnormal interhemispheric interaction may be a pathophysiological mechanism of motor and cognitive dysfunction of CP.

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