scholarly journals Resting-state brain function in schizophrenia and psychotic bipolar probands and their first-degree relatives

2014 ◽  
Vol 45 (1) ◽  
pp. 97-108 ◽  
Author(s):  
S. Lui ◽  
L. Yao ◽  
Y. Xiao ◽  
S. K. Keedy ◽  
J. L. Reilly ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Low Frequency ◽  
Network Connectivity ◽  
Orbital Frontal Cortex ◽  
Cortical Networks ◽  
First Degree Relatives ◽  
Family Associations ◽  
Brain Functional Connectivity ◽  
Psychotic Bipolar Disorder

BackgroundSchizophrenia (SCZ) and psychotic bipolar disorder (PBD) share considerable overlap in clinical features, genetic risk factors and co-occurrence among relatives. The common and unique functional cerebral deficits in these disorders, and in unaffected relatives, remain to be identified.MethodA total of 59 healthy controls, 37 SCZ and 57 PBD probands and their unaffected first-degree relatives (38 and 28, respectively) were studied using resting-state functional magnetic resonance imaging (rfMRI). Regional cerebral function was evaluated by measuring the amplitude of low-frequency fluctuations (ALFF). Areas with ALFF alterations were used as seeds in whole-brain functional connectivity analysis. We then tested whether abnormalities identified in probands were present in unaffected relatives.ResultsSCZ and PBD probands both demonstrated regional hypoactivity in the orbital frontal cortex and cingulate gyrus, as well as abnormal connectivity within striatal-thalamo-cortical networks. SCZ probands showed greater and more widely distributed ALFF alterations including the thalamus and bilateral parahippocampal gyri. Increased parahippocampal ALFF was related to positive symptoms and cognitive deficit. PBD patients showed uniquely increased functional connectivity between the thalamus and bilateral insula. Only PBD relatives showed abnormal connectivity within striatal-thalamo-cortical networks seen in both proband groups.ConclusionsThe present findings reveal a common pattern of deficits in frontostriatal circuitry across SCZ and PBD, and unique regional and functional connectivity abnormalities that distinguish them. The abnormal network connectivity in PBD relatives that was present in both proband groups may reflect genetic susceptibility associated with risk for psychosis, but within-family associations of this measure were not high.

scholarly journals Improvising at Rest: Differentiating Jazz and Classical Music Training with Resting State Functional Connectivity

2019 ◽  
Author(s):  
Alexander Belden ◽  
Tima Zeng ◽  
Emily Przysinda ◽  
Sheeba Arnold Anteraper ◽  
Susan Whitfield-Gabrieli ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Divergent Thinking ◽  
Network Connectivity ◽  
Salience Network ◽  
Resting State Functional Connectivity ◽  
Cortical Networks ◽  
Music Training ◽  
Classical Musicians ◽  
Visual Network

AbstractJazz improvisation offers a model for creative cognition, as it involves the real-time creation of a novel, information-rich product. Previous research has shown that when musicians improvise, they recruit regions in the Default Mode Network (DMN) and Executive Control Network (ECN). Here, we ask whether these findings from task-fMRI studies might extend to intrinsic differences in resting state functional connectivity. We compared Improvising musicians, Classical musicians, and Minimally Musically Trained (MMT) controls in seed-based functional connectivity and network analyses in resting state functional MRI. We also examined the functional correlates of behavioral performance in musical improvisation and divergent thinking. Seed-based analysis consistently showed higher connectivity in ventral DMN (vDMN) and bilateral ECN in both groups of musically trained individuals as compared to MMT controls, with additional group differences in primary visual network, precuneus network, and posterior salience network. In particular, primary visual network connectivity to DMN and ECN was highest in Improvisational musicians, whereas within-network connectivity of vDMN and precuneus network was higher in both Improvisational and Classical musicians than in MMT controls; in contrast, connectivity between posterior salience network and superior parietal lobule was highest in Classical musicians. Furthermore, graph-theoretical analysis indicated heightened betweenness centrality, clustering, and local efficiency in Classical musicians. Taken together, results suggest that heightened functional connectivity among musicians can be explained by higher within-network connectivity (more tight-knit cortical networks) in Classical musicians, as opposed to more disperse, globally-connected cortical networks in Improvisational musicians.HighlightsMusic training is associated with higher resting state connectivityHigher connectivity in Improvisational musicians from visual network to ECN and DMNClassical musicians show higher vDMN and Precuneus within-network connectivityImprovisation and divergent thinking performance correlate with similar connectivity patterns

scholarly journals Resting-State Functional Magnetic Resonance Imaging Networks as a Quantitative Metric for Impact of Neurosurgical Interventions

2021 ◽  
Vol 15 ◽  
Author(s):  
Peter H. Yang ◽  
Carl D. Hacker ◽  
Bhuvic Patel ◽  
Andy G. S. Daniel ◽  
Eric C. Leuthardt
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Functional Organization ◽  
Network Connectivity ◽  
Brain Network ◽  
Computational Method ◽  
Patient Specific ◽  
Neurosurgical Procedures ◽  
Brain Functional Connectivity ◽  
The Impact

Objective: Resting-state functional MRI (rs-fMRI) has been used to evaluate brain network connectivity as a result of intracranial surgery but has not been used to compare different neurosurgical procedures. Laser interstitial thermal therapy (LITT) is an alternative to conventional craniotomy for the treatment of brain lesions such as tumors and epileptogenic foci. While LITT is thought of as minimally invasive, its effect on the functional organization of the brain is still under active investigation and its impact on network changes compared to conventional craniotomy has not yet been explored. We describe a novel computational method for quantifying and comparing the impact of two neurosurgical procedures on brain functional connectivity.Methods: We used a previously described seed-based correlation analysis to generate resting-state network (RSN) correlation matrices, and compared changes in correlation patterns within and across RSNs between LITT and conventional craniotomy for treatment of 24 patients with singular intracranial tumors at our institution between 2014 and 2017. Specifically, we analyzed the differences in patient-specific changes in the within-hemisphere correlation patterns of the contralesional hemisphere.Results: In a post-operative follow-up period up to 2 years within-hemisphere connectivity of the contralesional hemisphere after surgery was more highly correlated to the pre-operative state in LITT patients when compared to craniotomy patients (P = 0.0287). Moreover, 4 out of 11 individual RSNs demonstrated significantly higher degrees of correlation between pre-operative and post-operative network connectivity in patients who underwent LITT (all P < 0.05).Conclusion: Rs-fMRI may be used as a quantitative metric to determine the impact of different neurosurgical procedures on brain functional connectivity. Global and individual network connectivity in the contralesional hemisphere may be more highly preserved after LITT when compared to craniotomy for the treatment of brain tumors.

scholarly journals Aberrant Brain Functional Connectivity Related to Insulin Resistance in Type 2 Diabetes: A Resting-State fMRI Study

Diabetes Care ◽  
2014 ◽  
Vol 37 (6) ◽  
pp. 1689-1696 ◽  
Author(s):  
Yu-Chen Chen ◽  
Yun Jiao ◽  
Ying Cui ◽  
Song-An Shang ◽  
Jie Ding ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Functional Connectivity ◽  
Resting State ◽  
Resting State Fmri ◽  
Fmri Study ◽  
Brain Functional Connectivity

scholarly journals Neural basis underlying the trait of attachment anxiety and avoidance revealed by the amplitude of low-frequency fluctuations and resting-state functional connectivity

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Min Deng ◽  
Xing Zhang ◽  
Xiaoyan Bi ◽  
Chunhai Gao
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Low Frequency ◽  
Cingulate Cortex ◽  
Posterior Cingulate Cortex ◽  
Attachment Anxiety ◽  
Frequency Fluctuation ◽  
Resting State Functional Connectivity ◽  
Attachment Avoidance ◽  
Posterior Cingulate

Abstract Background Attachment theory demonstrates that early attachment experience shapes internal working models with mental representations of self and close relationships, which affects personality traits and interpersonal relationships in adulthood. Although research has focused on brain structural and functional underpinnings to disentangle attachment styles in healthy individuals, little is known about the spontaneous brain activity associated with self-reported attachment anxiety and avoidance during the resting state. Methods One hundred and nineteen individuals participated in the study, completing the Experience in Close Relationship scale immediately after an 8-min fMRI scanning. We used the resting-state functional magnetic resonance imaging (rs-fMRI) signal of the amplitude of low-frequency fluctuation and resting-state functional connectivity to identify attachment-related regions and networks. Results Consequently, attachment anxiety is closely associated with the amplitude of low-frequency fluctuations in the right posterior cingulate cortex, over-estimating emotional intensity and exaggerating outcomes. Moreover, the functional connectivity between the posterior cingulate cortex and fusiform gyrus increases detection ability for potential threat or separation information, facilitating behavior motivation. The attachment avoidance is positively correlated with the amplitude of low-frequency fluctuation in the bilateral lingual gyrus and right postcentral and negatively correlated with the bilateral orbital frontal cortex and inferior temporal gyrus. Functional connection with attachment avoidance contains critical nodes in the medial temporal lobe memory system, frontal-parietal network, social cognition, and default mode network necessary to deactivate the attachment system and inhibit attachment-related behavior. Conclusion and implications These findings clarify the amplitude of low-frequency fluctuation and resting-state functional connectivity neural signature of attachment style, associated with attachment strategies in attachment anxiety and attachment avoidance individuals. These findings may improve our understanding of the pathophysiology of the attachment-related disorder.

scholarly journals Beyond the low frequency fluctuations morning and evening differences in human brain

2019 ◽  
Author(s):  
Magdalena Fafrowicz ◽  
Bartosz Bohaterewicz ◽  
Anna Ceglarek ◽  
Monika Cichocka ◽  
Koryna Lewandowska ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Human Performance ◽  
Brain Activity ◽  
Activity Patterns ◽  
Low Frequency ◽  
Basic Mechanism ◽  
Time Of Day ◽  
Resting State Functional Connectivity ◽  
Circadian Typology

Human performance, alertness, and most biological functions express rhythmic fluctuations across a 24-hour-period. This phenomenon is believed to originate from differences in both circadian and homeostatic sleep-wake regulatory processes. Interactions between these processes result in time-of-day modulations of behavioral performance as well as brain activity patterns. Although the basic mechanism of the 24-hour clock is conserved across evolution, there are interindividual differences in the timing of sleep-wake cycles, subjective alertness and functioning throughout the day. The study of circadian typology differences has increased during the last few years, especially research on extreme chronotypes, which provide a unique way to investigate the effects of sleep-wake regulation on cerebral mechanisms. Using functional magnetic resonance imaging (fMRI), we assessed the influence of chronotype and time-of-day on resting-state functional connectivity. 29 extreme morning- and 34 evening-type participants underwent two fMRI sessions: about one hour after wake-up time (morning) and about ten hours after wake-up time (evening), scheduled according to their declared habitual sleep-wake pattern on a regular working day. Analysis of obtained neuroimaging data disclosed only an effect of time of day on resting-state functional connectivity; there were different patterns of functional connectivity between morning and evening sessions. The results of our study showed no differences between extreme morning-type and evening-type individuals. We demonstrate that circadian and homeostatic influences on the resting-state functional connectivity have a universal character, unaffected by circadian typology.

scholarly journals Local GABA concentration is related to network-level resting functional connectivity

eLife ◽  
2014 ◽  
Vol 3 ◽  
Author(s):  
Charlotte J Stagg ◽  
Velicia Bachtiar ◽  
Ugwechi Amadi ◽  
Christel A Gudberg ◽  
Andrei S Ilie ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Primary Motor Cortex ◽  
Empirical Studies ◽  
Network Connectivity ◽  
Resting State Fmri ◽  
Resonance Spectroscopy ◽  
Resting State Networks ◽  
Inhibitory Neurotransmitter ◽  
Motor Network

Anatomically plausible networks of functionally inter-connected regions have been reliably demonstrated at rest, although the neurochemical basis of these ‘resting state networks’ is not well understood. In this study, we combined magnetic resonance spectroscopy (MRS) and resting state fMRI and demonstrated an inverse relationship between levels of the inhibitory neurotransmitter GABA within the primary motor cortex (M1) and the strength of functional connectivity across the resting motor network. This relationship was both neurochemically and anatomically specific. We then went on to show that anodal transcranial direct current stimulation (tDCS), an intervention previously shown to decrease GABA levels within M1, increased resting motor network connectivity. We therefore suggest that network-level functional connectivity within the motor system is related to the degree of inhibition in M1, a major node within the motor network, a finding in line with converging evidence from both simulation and empirical studies.

scholarly journals The effect of global signal regression on DCM estimates of noise and effective connectivity from resting state fMRI

2019 ◽  
Author(s):  
Hannes Almgren ◽  
Frederik Van de Steen ◽  
Adeel Razi ◽  
Karl Friston ◽  
Daniele Marinazzo
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Effective Connectivity ◽  
Network Connectivity ◽  
Resting State Fmri ◽  
Measurement Noise ◽  
Resting State Networks ◽  
Cross Sectional ◽  
Global Signal ◽  
Leibler Divergence

AbstractThe influence of the global BOLD signal on resting state functional connectivity in fMRI data remains a topic of debate, with little consensus. In this study, we assessed the effects of global signal regression (GSR) on effective connectivity within and between resting-state networks – as estimated with dynamic causal modelling (DCM) for resting state fMRI (rsfMRI). DCM incorporates a forward (generative) model that quantifies the contribution of different types of noise (including global measurement noise), effective connectivity, and (neuro)vascular processes to functional connectivity measurements. DCM analyses were applied to two different designs; namely, longitudinal and cross-sectional designs. In the modelling of longitudinal designs, we included four extensive longitudinal resting state fMRI datasets with a total number of 20 subjects. In the analysis of cross-sectional designs, we used rsfMRI data from 361 subjects from the Human Connectome Project. We hypothesized that (1) GSR would have no discernible impact on effective connectivity estimated with DCM, and (2) GSR would be reflected in the parameters representing global measurement noise. Additionally, we performed comparative analyses of the informative value of data with and without GSR. Our results showed negligible to small effects of GSR on connectivity within small (separately estimated) RSNs. For between-network connectivity, we found two important effects: the effect of GSR on between-network connectivity (averaged over all connections) was negligible to small, while the effect of GSR on individual connections was non-negligible. Contrary to our expectations, we found either no effect (in the longitudinal designs) or a non-specific (cross-sectional design) effect of GSR on parameters representing (global) measurement noise. Data without GSR were found to be more informative than data with GSR; however, in small resting state networks the precision of posterior estimates was greater using data after GSR. In conclusion, GSR is a minor concern in DCM studies; however, individual between-network connections (as opposed to average between-network connectivity) and noise parameters should be interpreted quantitatively with some caution. The Kullback-Leibler divergence of the posterior from the prior, together with the precision of posterior estimates, might offer a useful measure to assess the appropriateness of GSR, when nuancing data features in resting state fMRI.

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