WE-FG-206-02: Brief Variations of BOLD Signal in Resting State FMRI Leading to Functional Connectivity Pattern Identification

2016 ◽  
Vol 43 (6Part41) ◽  
pp. 3831-3831
Author(s):  
N Ball ◽  
N Chen
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Resting State Fmri ◽  
Pattern Identification ◽  
Connectivity Pattern ◽  
Bold Signal

scholarly journals Typicality of Functional Connectivity robustly captures motion artifacts in rs-fMRI across datasets, atlases and preprocessing pipelines

2020 ◽  
Author(s):  
Jakub Kopal ◽  
Anna Pidnebesna ◽  
David Tomeček ◽  
Jaroslav Tintěra ◽  
Jaroslav Hlinka
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Resting State Fmri ◽  
Motion Artifacts ◽  
Connectivity Pattern ◽  
Head Motion ◽  
Connectivity Matrix ◽  
Normal Brain ◽  
Functional Connections ◽  
Human Connectome Project

AbstractFunctional connectivity analysis of resting state fMRI data has recently become one of the most common approaches to characterizing individual brain function. It has been widely suggested that the functional connectivity matrix, calculated by correlating signals from regions of interest, is a useful approximate representation of the brain’s connectivity, potentially providing behaviorally or clinically relevant markers. However, functional connectivity estimates are known to be detrimentally affected by various artifacts, including those due to in-scanner head motion. Treatment of such artifacts poses a standing challenge because of their high variability. Moreover, as individual functional connections generally covary only very weakly with head motion estimates, motion influence is difficult to quantify robustly, and prone to be neglected in practice. Although the use of individual estimates of head motion, or group-level correlation of motion and functional connectivity has been suggested, a sufficiently sensitive measure of individual functional connectivity quality has not yet been established. We propose a new intuitive summary index, the Typicality of Functional Connectivity, to capture deviations from normal brain functional connectivity pattern. Based on results of resting state fMRI for 245 healthy subjects we show that this measure is significantly correlated with individual head motion metrics. The results were further robustly reproduced across atlas granularity and preprocessing options, as well as other datasets including 1081 subjects from the Human Connectome Project. The Typicality of Functional Connectivity provides individual proxy measure of motion effect on functional connectivity and is more sensitive to inter-individual variation of motion than individual functional connections. In principle it should be sensitive also to other types of artifacts, processing errors and possibly also brain pathology, allowing wide use in data quality screening and quantification in functional connectivity studies as well as methodological investigations.

Functional Connectivity Pattern of the Internal Hippocampal Network in Awake Pigeons: A Resting-State fMRI Study

2017 ◽  
Vol 90 (1) ◽  
pp. 62-72 ◽  
Author(s):  
Mehdi Behroozi ◽  
Felix Ströckens ◽  
Martin Stacho ◽  
Onur Güntürkün
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Hippocampal Formation ◽  
Structural Connectivity ◽  
Resting State Fmri ◽  
Blood Oxygenation ◽  
Lateral Septum ◽  
Connectivity Pattern ◽  
Oxygenation Level ◽  
Hippocampal Network

In the last two decades, the avian hippocampus has been repeatedly studied with respect to its architecture, neurochemistry, and connectivity pattern. We review these insights and conclude that we unfortunately still lack proper knowledge on the interaction between the different hippocampal subregions. To fill this gap, we need information on the functional connectivity pattern of the hippocampal network. These data could complement our structural connectivity knowledge. To this end, we conducted a resting-state fMRI experiment in awake pigeons in a 7-T MR scanner. A voxel-wise regression analysis of blood oxygenation level-dependent (BOLD) fluctuations was performed in 6 distinct areas, dorsomedial (DM), dorsolateral (DL), triangular shaped (Tr), dorsolateral corticoid (CDL), temporo-parieto-occipital (TPO), and lateral septum regions (SL), to establish a functional connectivity map of the avian hippocampal network. Our study reveals that the system of connectivities between CDL, DL, DM, and Tr is the functional backbone of the pigeon hippocampal system. Within this network, DM is the central hub and is strongly associated with DL and CDL BOLD signal fluctuations. DM is also the only hippocampal region to which large Tr areas are functionally connected. In contrast to published tracing data, TPO and SL are only weakly integrated in this network. In summary, our findings uncovered a structurally otherwise invisible architecture of the avian hippocampal formation by revealing the dynamic blueprints of this network.

070 Respiratory, cardiac, EEG, BOLD signals and functional connectivity over multiple microsleep episodes

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A29-A29
Author(s):  
Chun Siong Soon ◽  
Ksenia Vinogradova ◽  
Ju Lynn Ong ◽  
Vince Calhoun ◽  
Thomas Liu ◽  
...  
Keyword(s):  
Heart Rate ◽  
Functional Connectivity ◽  
Resting State ◽  
Sleep Onset ◽  
Resting State Fmri ◽  
Bold Signal ◽  
Falling Asleep ◽  
Eye Opening ◽  
Signal Changes ◽  
Eye Closure

Abstract Introduction Brief intrusions of unintended sleep can occur in various contexts, for example during resting-state fMRI scans. In addition to changes in neural activity, such microsleep episodes are also associated with shifts in respiration and heartrate. Here we investigated how these concurrent changes alter the dynamics of the BOLD signal in the brain and estimates of functional connectivity. Methods Ten participants underwent 6 runs of 20 minute resting-state fMRI scans with concurrent respiration, PPG and EEG recording. Realtime eye-closure monitoring combined with post eye-opening self-reports were used to identify microsleep episodes of different durations. Results During microsleep, sustained reductions were observed in arousal as assessed by EEG (ratio of alpha to delta and theta bands), as expected. In comparison, cortical BOLD signal exhibited more complex, temporally multiphasic changes which were consistent across different microsleep durations from 4 to 44s: (i) an initial sleep-onset dip reaching a nadir after ~6s, followed by (ii) an increase above wake baseline that plateaued till awakening. On awakening, (iii) a transient positive bump occurred up to 6s, followed by (iv) an undershoot below baseline lasting ~30s. While seen across the whole brain, these changes showed regional variations, e.g., the signal plateau in the thalamus remained below wake baseline. Sleep onset and awakening were also associated with respective reductions and increases in respiration and heart rate, which affect blood oxygen levels. Brain functional connectivity estimates were altered by the frequency of falling asleep, and this was not resolved by global signal regression. Conclusion Falling asleep and awakening are shown here to be associated with large, widespread BOLD signal changes consistent across varied durations of microsleep. These signal changes are intimately intertwined with shifts in respiration and heart rate, which are influenced by common brainstem nuclei controlling sleep. These autonomic contributions to ‘brain signal’ changes at microsleep onset and awakening are integral to sleep, and urge the integration of autonomic and central nervous system contributions to BOLD signal into frameworks for understanding brain function using fMRI. In addition, the correlation between frequency of microsleep and extent of altered functional connectivity highlight the need to minimize sleep during resting state scans. Support (if any) NMRC/STaR/015/2013

Altered functional connectivity of right inferior frontal gyrus subregions in bipolar disorder: a resting state fMRI study

2020 ◽  
Vol 272 ◽  
pp. 58-65 ◽  
Author(s):  
Li Zhang ◽  
Wenfei Li ◽  
Long Wang ◽  
Tongjian Bai ◽  
Gong-Jun Ji ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Functional Connectivity ◽  
Resting State ◽  
Inferior Frontal Gyrus ◽  
Resting State Fmri ◽  
Fmri Study

scholarly journals Resting State fMRI Reveals Diminished Functional Connectivity in a Mouse Model of Amyloidosis

PLoS ONE ◽  
2013 ◽  
Vol 8 (12) ◽  
pp. e84241 ◽  
Author(s):  
Disha Shah ◽  
Elisabeth Jonckers ◽  
Jelle Praet ◽  
Greetje Vanhoutte ◽  
Rafael Delgado y Palacios ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Mouse Model ◽  
Resting State ◽  
Resting State Fmri
Sign in / Sign up

Export Citation Format

Share Document