functional connectivity
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2022 ◽  
Vol 186 ◽  
pp. 111385
Wojciech Łukasz Dragan ◽  
Andrzej Sokołowski ◽  
Monika Folkierska-Żukowska

2022 ◽  
Fatemeh Tabassi Mofrad ◽  
Niels O. Schiller

The cytoarchitectonically tripartite organization of the inferior parietal cortex (IPC) into the rostral, the middle and the caudal clusters has been generally ignored when associating different functions to this part of the cortex, resulting in inconsistencies about how IPC is understood. In this study, we investigated the patterns of functional connectivity of the caudal IPC in a task requiring cognitive control of language, using multiband EPI. This part of the cortex demonstrated functional connectivity patterns dissimilar to a cognitive control area and at the same time the caudal IPC showed negative functional associations with both task-related brain areas and the precuneus cortex, which is active during resting state. We found evidence suggesting that the traditional categorization of different brain areas into either task-related or resting state-related networks cannot accommodate the functions of the caudal IPC. This underlies the hypothesis about a modulating cortical area proposing that its involvement in task performance, in a modulating manner, is marked by deactivation in the patterns of functional associations with parts of the brain that are recognized to be involved in doing a task, proportionate to task difficulty; however, their patterns of functional connectivity in some other respects do not correspond to the resting state-related parts of the cortex.

2022 ◽  
Maria Semeli Frangopoulou ◽  
Maryam Alimardani

Alzheimers disease (AD) is a brain disorder that is mainly characterized by a progressive degeneration of neurons in the brain, causing a decline in cognitive abilities and difficulties in engaging in day-to-day activities. This study compares an FFT-based spectral analysis against a functional connectivity analysis based on phase synchronization, for finding known differences between AD patients and Healthy Control (HC) subjects. Both of these quantitative analysis methods were applied on a dataset comprising bipolar EEG montages values from 20 diagnosed AD patients and 20 age-matched HC subjects. Additionally, an attempt was made to localize the identified AD-induced brain activity effects in AD patients. The obtained results showed the advantage of the functional connectivity analysis method compared to a simple spectral analysis. Specifically, while spectral analysis could not find any significant differences between the AD and HC groups, the functional connectivity analysis showed statistically higher synchronization levels in the AD group in the lower frequency bands (delta and theta), suggesting that the AD patients brains are in a phase-locked state. Further comparison of functional connectivity between the homotopic regions confirmed that the traits of AD were localized in the centro-parietal and centro-temporal areas in the theta frequency band (4-8 Hz). The contribution of this study is that it applies a neural metric for Alzheimers detection from a data science perspective rather than from a neuroscience one. The study shows that the combination of bipolar derivations with phase synchronization yields similar results to comparable studies employing alternative analysis methods.

2022 ◽  
Vol 12 (1) ◽  
Kinga Gecse ◽  
Dóra Dobos ◽  
Csaba Sándor Aranyi ◽  
Attila Galambos ◽  
Daniel Baksa ◽  

AbstractAltered periaqueductal gray matter (PAG) functional connectivity contributes to brain hyperexcitability in migraine. Although tryptophan modulates neurotransmission in PAG projections through its metabolic pathways, the effect of plasma tryptophan on PAG functional connectivity (PAG-FC) in migraine has not been investigated yet. In this study, using a matched case-control design PAG-FC was measured during a resting-state functional magnetic resonance imaging session in migraine without aura patients (n = 27) and healthy controls (n = 27), and its relationship with plasma tryptophan concentration (TRP) was assessed. In addition, correlations of PAG-FC with age at migraine onset, migraine frequency, trait-anxiety and depressive symptoms were tested and the effect of TRP on these correlations was explored. Our results demonstrated that migraineurs had higher TRP compared to controls. In addition, altered PAG-FC in regions responsible for fear-cascade and pain modulation correlated with TRP only in migraineurs. There was no significant correlation in controls. It suggests increased sensitivity to TRP in migraine patients compared to controls. Trait-anxiety and depressive symptoms correlated with PAG-FC in migraine patients, and these correlations were modulated by TRP in regions responsible for emotional aspects of pain processing, but TRP did not interfere with processes that contribute to migraine attack generation or attack frequency.

2022 ◽  
Vol 15 ◽  
Wenzhuo Cui ◽  
Shanshan Wang ◽  
Boyu Chen ◽  
Guoguang Fan

Functional magnetic resonance imaging (fMRI) studies have suggested that there is a functional reorganization of brain areas in patients with sensorineural hearing loss (SNHL). Recently, graph theory analysis has brought a new understanding of the functional connectome and topological features in central neural system diseases. However, little is known about the functional network topology changes in SNHL patients, especially in infants. In this study, 34 infants with profound bilateral congenital SNHL and 28 infants with normal hearing aged 11–36 months were recruited. No difference was found in small-world parameters and network efficiency parameters. Differences in global and nodal topologic organization, hub distribution, and whole-brain functional connectivity were explored using graph theory analysis. Both normal-hearing infants and SNHL infants exhibited small-world topology. Furthermore, the SNHL group showed a decreased nodal degree in the bilateral thalamus. Six hubs in the SNHL group and seven hubs in the normal-hearing group were identified. The left middle temporal gyrus was a hub only in the SNHL group, while the right parahippocampal gyrus and bilateral temporal pole were hubs only in the normal-hearing group. Functional connectivity between auditory regions and motor regions, between auditory regions and default-mode-network (DMN) regions, and within DMN regions was found to be decreased in the SNHL group. These results indicate a functional reorganization of brain functional networks as a result of hearing loss. This study provides evidence that functional reorganization occurs in the early stage of life in infants with profound bilateral congenital SNHL from the perspective of complex networks.

2022 ◽  
Joseph Kuchling ◽  
Betty Jurek ◽  
Mariya Kents ◽  
Jakob Kreye ◽  
Christian Geis ◽  

Introduction: While decreased hippocampal connectivity and disruption of functional networks are established MRI features in human anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis, the underlying pathophysiology for brain network alterations remains poorly understood. Application of patient-derived monoclonal antibodies against the NR1 subunit of the NMDAR allows for the investigation of potential functional connectivity alterations in experimental murine NMDAR antibody disease models. Objective: To explore functional connectivity changes in NR1 antibody mouse models using resting-state functional MRI (rs-fMRI). Methods: Adult C57BL/6J mice (n=10) were intrathecally injected with a recombinant human NR1 antibody over 14 days and then studied using rs-fMRI at 7 Tesla. In addition, a newly established mouse model with in utero exposure to a human recombinant NR1 antibody characterized by a neurodevelopmental disorder (NR1-offspring) was investigated with rs-fMRI at the age of 8 weeks (n=15) and 10 months (n=14). Mice exposed to isotype-matched control antibodies served as controls. Independent component analysis (ICA) and dual regression analysis were performed to compare functional connectivity between NMDAR antibody mouse models and control mice. Results: Adult NR1-antibody injected mice showed significantly impaired functional connectivity within the dentate gyrus of the left hippocampus in comparison to controls, resembling impaired hippocampal functional connectivity patterns observed in human patients with NMDAR encephalitis. Similarly, analyses showed significantly reduced functional connectivity in the dentate gyrus in NR1-offspring compared after 8 weeks, and impaired connectivity in the dentate gyrus and CA3 hippocampal subregion in NR1-offspring at the age of 10 months. Conclusion: Functional connectivity changes within the hippocampus resulting from both direct application and in utero exposure to NMDAR antibodies can be modeled in experimental murine systems. With this translational approach, we successfully reproduced functional MRI alterations previously observed in human NMDAR encephalitis patients. Future experimental studies will identify the detailed mechanisms that cause functional network alterations and may eventually allow for non-invasive monitoring of disease activity and therapeutic effects in autoimmune encephalitis.

2022 ◽  
Mary Beth Nebel ◽  
Daniel Lidstone ◽  
Liwei Wang ◽  
David Benkeser ◽  
Stewart H Mostofsky ◽  

The exclusion of high-motion participants can reduce the impact of motion in functional Magnetic Resonance Imaging (fMRI) data. However, the exclusion of high-motion participants may change the distribution of clinically relevant variables in the study sample, and the resulting sample may not be representative of the population. Our goals are two-fold: 1) to document the biases introduced by common motion exclusion practices in functional connectivity research and 2) to introduce a framework to address these biases by treating excluded scans as a missing data problem. We use a study of autism spectrum disorder to illustrate the problem and the potential solution. We aggregated data from 545 children (8-13 years old) who participated in resting-state fMRI studies at Kennedy Krieger Institute (173 autistic and 372 typically developing) between 2007 and 2020. We found that autistic children were more likely to be excluded than typically developing children, with 29.1% and 16.1% of autistic and typically developing children excluded, respectively, using a lenient criterion and 80.8% and 59.8% with a stricter criterion. The resulting sample of autistic children with usable data tended to be older, have milder social deficits, better motor control, and higher intellectual ability than the original sample. These measures were also related to functional connectivity strength among children with usable data. This suggests that the generalizability of previous studies reporting naïve analyses (i.e., based only on participants with usable data) may be limited by the selection of older children with less severe clinical profiles because these children are better able to remain still during an rs-fMRI scan. We adapt doubly robust targeted minimum loss based estimation with an ensemble of machine learning algorithms to address these data losses and the resulting biases. The proposed approach selects more edges that differ in functional connectivity between autistic and typically developing children than the naïve approach, supporting this as a promising solution to improve the study of heterogeneous populations in which motion is common.

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