scholarly journals T156. FUNCTIONAL CONNECTIVITY AND RISK OF PSYCHOSIS: AN ACTIVATION LIKELIHOOD ESTIMATION (ALE) META-ANALYSIS OF FUNCTIONAL MAGNETIC RESONANCE IMAGING STUDIES

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S290-S290
Author(s):  
Lorenzo Del Fabro ◽  
André Schmidt ◽  
Giuseppe Delvecchio ◽  
Armando D’Agostino ◽  
Stefan Borgwardt ◽  
...  
Keyword(s):  
At Risk ◽  
High Risk ◽  
Resting State ◽  
Large Scale ◽  
Meta Analysis ◽  
A Priori ◽  
Resting State Fmri ◽  
Healthy Controls ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging

Abstract Background Disrupted communication involving large-scale neural networks is hypothesized to underlie the pathophysiology of schizophrenia, as demonstrated by impaired resting-state functional connectivity (rsFC). Seed-based functional magnetic resonance imaging (fMRI) studies in subjects at increased risk of developing psychosis have begun to identify abnormalities in rsFC, although reported findings remain mixed. The aim of this study was to conduct a meta-analysis of seed-based resting-state fMRI studies to test whether high-risk subjects show rsFC alterations relative to healthy controls within and between the default mode network (DMN), control executive network (CEN), and salience network (SN). Methods A literature search was performed to identify seed-based resting-state fMRI studies comparing subjects with genetic risk factors, psychotic-like experiences, and clinical high-risk for psychosis to healthy controls. Then, coordinates of seed regions were extracted and categorized into networks by their location within a priori templates. Activation likelihood estimate (ALE) analysis examined the reported coordinates for hypo-connectivity and hyper-connectivity with each a priori network. Results The meta-analysis included 15 studies (774 subjects at risk, 628 healthy controls) on clinical high-risk for psychosis, 6 studies (123 subjects at risk, 147 healthy controls) on psychotic-like experiences, and 5 studies (173 subjects at risk, 256 healthy controls) on genetic risk factors of developing psychosis. We found specific patterns of hypo- and hyper-connectivity within and between large-scale networks. Our results showed that subjects with high-risk for psychosis were characterized by hypo-connectivity within the SN and CEN and hyper-connectivity within the DMN and CEN. Network seeds in the DMN, CEN, and SN displayed hyper-connectivity with regions in other networks. The DMN seeds displayed hypo-connectivity with regions in the CEN, while CEN and SN seeds displayed hypo-connectivity with regions in the DMN. Discussion This meta-analysis provides evidence that subjects at risk for psychosis present distinctive abnormalities of hyper- and hypo-connectivity within and between the DMN, CEN and SN, particularly implicating network dys-connectivity as a core deficit underlying the psychopathology of psychosis in the preclinical phase. More studies are needed to investigate whether subjects at risk to develop psychosis present patterns of dysfunction between the rsFC of healthy subjects and that of patients with established psychosis.

A Critical, Event-Related Appraisal of Denoising in Resting-State fMRI Studies

2020 ◽  
Vol 30 (10) ◽  
pp. 5544-5559 ◽  
Author(s):  
Jonathan D Power ◽  
Charles J Lynch ◽  
Babatunde Adeyemo ◽  
Steven E Petersen
Keyword(s):  
Resting State ◽  
Resting State Fmri ◽  
Critical Event ◽  
Head Motion ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Decay Properties ◽  
Signal Decay ◽  
Biological Variables ◽  
Related Approach

Abstract This article advances two parallel lines of argument about resting-state functional magnetic resonance imaging (fMRI) signals, one empirical and one conceptual. The empirical line creates a four-part organization of the text: (1) head motion and respiration commonly cause distinct, major, unwanted influences (artifacts) in fMRI signals; (2) head motion and respiratory changes are, confoundingly, both related to psychological and clinical and biological variables of interest; (3) many fMRI denoising strategies fail to identify and remove one or the other kind of artifact; and (4) unremoved artifact, due to correlations of artifacts with variables of interest, renders studies susceptible to identifying variance of noninterest as variance of interest. Arising from these empirical observations is a conceptual argument: that an event-related approach to task-free scans, targeting common behaviors during scanning, enables fundamental distinctions among the kinds of signals present in the data, information which is vital to understanding the effects of denoising procedures. This event-related perspective permits statements like “Event X is associated with signals A, B, and C, each with particular spatial, temporal, and signal decay properties”. Denoising approaches can then be tailored, via performance in known events, to permit or suppress certain kinds of signals based on their desirability.

scholarly journals Resting-State Functional Magnetic Resonance Imaging Connectivity Between Semantic and Phonological Regions of Interest May Inform Language Targets in Aphasia

2020 ◽  
Vol 63 (9) ◽  
pp. 3051-3067
Author(s):  
Amy E. Ramage ◽  
Semra Aytur ◽  
Kirrie J. Ballard
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Resting State ◽  
Brain Regions ◽  
Regions Of Interest ◽  
Healthy Controls ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Language Performance

Purpose Brain imaging has provided puzzle pieces in the understanding of language. In neurologically healthy populations, the structure of certain brain regions is associated with particular language functions (e.g., semantics, phonology). In studies on focal brain damage, certain brain regions or connections are considered sufficient or necessary for a given language function. However, few of these account for the effects of lesioned tissue on the “functional” dynamics of the brain for language processing. Here, functional connectivity (FC) among semantic–phonological regions of interest (ROIs) is assessed to fill a gap in our understanding about the neural substrates of impaired language and whether connectivity strength can predict language performance on a clinical tool in individuals with aphasia. Method Clinical assessment of language, using the Western Aphasia Battery–Revised, and resting-state functional magnetic resonance imaging data were obtained for 30 individuals with chronic aphasia secondary to left-hemisphere stroke and 18 age-matched healthy controls. FC between bilateral ROIs was contrasted by group and used to predict Western Aphasia Battery–Revised scores. Results Network coherence was observed in healthy controls and participants with stroke. The left–right premotor cortex connection was stronger in healthy controls, as reported by New et al. (2015) in the same data set. FC of (a) connections between temporal regions, in the left hemisphere and bilaterally, predicted lexical–semantic processing for auditory comprehension and (b) ipsilateral connections between temporal and frontal regions in both hemispheres predicted access to semantic–phonological representations and processing for verbal production. Conclusions Network connectivity of brain regions associated with semantic–phonological processing is predictive of language performance in poststroke aphasia. The most predictive connections involved right-hemisphere ROIs—particularly those for which structural adaptions are known to associate with recovered word retrieval performance. Predictions may be made, based on these findings, about which connections have potential as targets for neuroplastic functional changes with intervention in aphasia. Supplemental Material https://doi.org/10.23641/asha.12735785

Depression is associated with disconnection of neurotransmitter-related nuclei in multiple sclerosis

2020 ◽  
pp. 135245852094821
Author(s):  
Matteo Martino ◽  
Paola Magioncalda ◽  
Mohamed Mounir El Mendili ◽  
Amgad Droby ◽  
Swetha Paduri ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Resting State ◽  
Depressive Symptomatology ◽  
Healthy Controls ◽  
Diffusion Weighted Mri ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Functional Connections ◽  
Brainstem Nuclei ◽  
And Diffusion

Background: Depression is frequently associated with multiple sclerosis (MS). However, the biological background underlying such association is poorly understood. Objective: Investigating the functional connections of neurotransmitter-related brainstem nuclei, along with their relationship with white matter (WM) microstructure, in MS patients with depressive symptomatology (MS-D) and without depressive symptomatology (MS-nD). Methods: Combined resting-state functional magnetic resonance imaging (fMRI) and diffusion-weighted MRI (dMRI) study on 50 MS patients, including 19 MS-D and 31 MS-nD patients, along with 37 healthy controls (HC). Main analyses performed are (1) comparison between groups of raphe nuclei (RN)-related functional connectivity (FC); (2) correlation between RN-related FC and whole brain dMRI-derived fractional anisotropy (FA) map; and (3) comparison between groups of FA in the RN-related WM area. Results: (1) RN-related FC was reduced in MS-D when compared to MS-nD and HC; (2) RN-related FC positively correlated with FA in a WM cluster mainly encompassing thalamic/basal ganglia regions, including the fornix; and (3) FA in such WM area was reduced in MS-D. Conclusion: Depressive symptomatology in MS is specifically associated to a functional disconnection of neurotransmitter-related nuclei, which in turn may be traced to a distinct spatial pattern of WM alterations mainly involving the limbic network.

scholarly journals Correlation between the Effects of Acupuncture atTaichong(LR3) and Functional Brain Areas: A Resting-State Functional Magnetic Resonance Imaging Study Using True versus Sham Acupuncture

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Chunxiao Wu ◽  
Shanshan Qu ◽  
Jiping Zhang ◽  
Junqi Chen ◽  
Shaoqun Zhang ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Data Processing ◽  
Resting State ◽  
Resting State Fmri ◽  
Sham Acupuncture ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Brain Areas

Functional magnetic resonance imaging (fMRI) has been shown to detect the specificity of acupuncture points, as proved by numerous studies. In this study, resting-state fMRI was used to observe brain areas activated by acupuncture at theTaichong(LR3) acupoint. A total of 15 healthy subjects received brain resting-state fMRI before acupuncture and after sham and true acupuncture, respectively, at LR3. Image data processing was performed using Data Processing Assistant for Resting-State fMRI and REST software. The combination of amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) was used to analyze the changes in brain function during sham and true acupuncture. Acupuncture at LR3 can specifically activate or deactivate brain areas related to vision, movement, sensation, emotion, and analgesia. The specific alterations in the anterior cingulate gyrus, thalamus, and cerebellar posterior lobe have a crucial effect and provide a valuable reference. Sham acupuncture has a certain effect on psychological processes and does not affect brain areas related to function.

scholarly journals Network variants are similar between task and rest states

2020 ◽  
Author(s):  
Brian T. Kraus ◽  
Diana Perez ◽  
Zach Ladwig ◽  
Benjamin A. Seitzman ◽  
Ally Dworetsky ◽  
...  
Keyword(s):  
Resting State ◽  
Resting State Fmri ◽  
Functional Networks ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Brain Organization ◽  
Precision Data ◽  
Specific Effects ◽  
Multiple Tasks ◽  
Over Time

AbstractRecent work has demonstrated that individual-specific variations in functional networks (that we call “network variants”) can be identified in individuals using functional magnetic resonance imaging (fMRI). These network variants exhibit reliability over time with resting-state fMRI data. These properties have suggested that network variants may be trait-like markers of individual differences in brain organization. Another test of this conclusion would be to examine if network variants are stable between task and rest states. Here, we use precision data from the Midnight Scan Club (MSC) to demonstrate that (1) task data can be used to identify network variants reliably, (2) these network variants show substantial spatial overlap with those observed in rest, although state-specific effects are present, (3) network variants assign to similar canonical functional networks in different states, and (4) single tasks or a combination of multiple tasks produce similar network variants to rest. Together, these findings further reinforce the trait-like nature of network variants and demonstrate the utility of using task data to define network variants.

scholarly journals Investigating the effects of healthy cognitive aging on brain functional connectivity using 4.7 T resting-state functional Magnetic Resonance Imaging

2020 ◽  
Author(s):  
Stanislau Hrybouski ◽  
Ivor Cribben ◽  
John McGonigle ◽  
Fraser Olsen ◽  
Rawle Carter ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Connectivity ◽  
Functional Magnetic Resonance Imaging ◽  
Age Differences ◽  
Resting State ◽  
Cognitive Aging ◽  
Resting State Fmri ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging

ABSTRACTIntroductionFunctional changes in the aging human brain have been previously reported using functional magnetic resonance imaging (fMRI). Earlier resting-state fMRI studies revealed an age-associated weakening of intra-system functional connectivity (FC) and age-associated strengthening of inter-system FC. However, the majority of such FC studies did not investigate the relationship between age and network amplitude, without which correlation-based measures of FC can be challenging to interpret. Consequently, the main aim of this study was to investigate how three primary measures of resting-state fMRI signal – network amplitude, network topography, and inter-network FC – are affected by healthy cognitive aging.MethodsWe acquired resting-state fMRI data on a 4.7 T scanner for 105 healthy participants representing the entire adult lifespan (18-85 years of age). To study age differences in network structure, we combined ICA-based network decomposition with sparse graphical models.ResultsOlder adults displayed lower blood-oxygen-level-dependent (BOLD) signal amplitude in all functional systems with sensorimotor networks showing the largest age differences. Our age comparisons of network topography and inter-network FC demonstrated a substantial amount of age-invariance in the brain’s functional architecture. Despite architecture similarities, old adults displayed a loss of communication efficiency in our inter-network FC comparisons, driven primarily by FC reduction in frontal and parietal association cortices. Together, our results provide a comprehensive overview of age effects on fMRI-based FC.

Reduced connectivity of the auditory cortex in patients with auditory hallucinations: a resting state functional magnetic resonance imaging study

2009 ◽  
Vol 40 (7) ◽  
pp. 1149-1158 ◽  
Author(s):  
M. Gavrilescu ◽  
S. Rossell ◽  
G. W. Stuart ◽  
T. L. Shea ◽  
H. Innes-Brown ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Connectivity ◽  
Resting State ◽  
Auditory Hallucinations ◽  
Fmri Data ◽  
Healthy Controls ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Interhemispheric Connectivity

BackgroundPrevious research has reported auditory processing deficits that are specific to schizophrenia patients with a history of auditory hallucinations (AH). One explanation for these findings is that there are abnormalities in the interhemispheric connectivity of auditory cortex pathways in AH patients; as yet this explanation has not been experimentally investigated. We assessed the interhemispheric connectivity of both primary (A1) and secondary (A2) auditory cortices in n=13 AH patients, n=13 schizophrenia patients without auditory hallucinations (non-AH) and n=16 healthy controls using functional connectivity measures from functional magnetic resonance imaging (fMRI) data.MethodFunctional connectivity was estimated from resting state fMRI data using regions of interest defined for each participant based on functional activation maps in response to passive listening to words. Additionally, stimulus-induced responses were regressed out of the stimulus data and the functional connectivity was estimated for the same regions to investigate the reliability of the estimates.ResultsAH patients had significantly reduced interhemispheric connectivity in both A1 and A2 when compared with non-AH patients and healthy controls. The latter two groups did not show any differences in functional connectivity. Further, this pattern of findings was similar across the two datasets, indicating the reliability of our estimates.ConclusionsThese data have identified a trait deficit specific to AH patients. Since this deficit was characterized within both A1 and A2 it is expected to result in the disruption of multiple auditory functions, for example, the integration of basic auditory information between hemispheres (via A1) and higher-order language processing abilities (via A2).

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