Integrated PET/MR for Resting State Functional and Metabolic Imaging in Human Brain: What is Correlated and What is Impacted

Purpose We aimed to, for the first time, investigate the interplay of simultaneous functional MRI (fMRI) and FDG PET using a randomized self-control protocol on an integrated PET/MR. Materials and methods 24 healthy volunteers underwent PET/MR scan 30 to 40 minutes after the injection of FDG. A 22-minute brain scan was separated into MRI-off (without fMRI pulsing) and MRI-on modes (with fMRI pulsing) with each one lasting for 11 minutes. We calculated the voxel-wise fMRI metric (ReHo, ALFF, fALFF and DC), resting networks, relative standardized uptake value ratios (SUVr), Patlak Ki and regional cerebral metabolic rate of glucose (rCMRGlu) maps. Paired two-sample t-tests were applied to assess the statistical differences between SUVr, Ki, correlation coefficients of fMRI metrics and rCMRGlu between MRI-off and MRI-on mode, respectively. Results Voxel-wise whole brain SUVr in MRI-off mode and MRI-on mode revealed no statistical difference, while Ki was significantly elevated in the whole brain (P༜0.05) during fMRI scan. Task-based group ICA revealed that the most active network components derived from combined MRI-off and MRI-on static PET images were frontal pole, superior frontal gyrus, middle temporal gyrus and occipital pole. High correlation coefficients were found among the four-fMRI metrics with rCMRGlu in MRI-off and MRI-on mode (P༜0.05). The highest correlation coefficients between rCMRGlu and all fMRI metrics were found in the visual network (R, 0.523 ± 0.057) and default network (R, 0.461 ± 0.099). Conclusions Static PET quantitation SUVr as an indicator of the accumulative effect of FDG update post-injection does not exhibit immediate change between MRI-on and MRI-off modes. Dynamic PET quantitation Ki is instantly elevated during MRI-on mode due to the additional impact of MRI sequence on imaging subjects. Network connectivity analysis also demonstrated intermediate modulation of brain function in MRI-on mode as compared to MRI-off mode.

Deriving Autism Spectrum Disorder Functional Networks from RS-FMRI Data using Group ICA and Dictionary Learning

The objective of this study is to derive functional networks for the autism spectrum disorder (ASD) population using the group ICA and dictionary learning model together and to classify ASD and typically developing (TD) participants using the functional connectivity calculated from the derived functional networks. In our experiments, the ASD functional networks were derived from resting-state functional magnetic resonance imaging (rs-fMRI) data. We downloaded a total of 120 training samples, including 58 ASD and 62 TD participants, which were obtained from the public repository: Autism Brain Imaging Data Exchange I (ABIDE I). Our methodology and results have five main parts. First, we utilize a group ICA model to extract functional networks from the ASD group and rank the top 20 regions of interest (ROIs). Second, we utilize a dictionary learning model to extract functional networks from the ASD group and rank the top 20 ROIs. Third, we merged the 40 selected ROIs from the two models together as the ASD functional networks. Fourth, we generate three corresponding masks based on the 20 selected ROIs from group ICA, the 20 ROIs selected from dictionary learning, and the 40 combined ROIs selected from both. Finally, we extract ROIs for all training samples using the above three masks, and the calculated functional connectivity was used as features for ASD and TD classification. The classification results showed that the functional networks derived from ICA and dictionary learning together outperform those derived from a single ICA model or a single dictionary learning model.

Within- and across-network alterations of the sensorimotor network in Parkinson’s disease

Purpose Parkinson’s disease (PD) is primarily defined by motor symptoms and is associated with alterations of sensorimotor areas. Evidence for network changes of the sensorimotor network (SMN) in PD is inconsistent and a systematic evaluation of SMN in PD yet missing. We investigate functional connectivity changes of the SMN in PD, both, within the network, and to other large-scale connectivity networks. Methods Resting-state fMRI was assessed in 38 PD patients under long-term dopaminergic treatment and 43 matched healthy controls (HC). Independent component analysis (ICA) into 20 components was conducted and the SMN was identified within the resulting networks. Functional connectivity within the SMN was analyzed using a dual regression approach. Connectivity between the SMN and the other networks from group ICA was investigated with FSLNets. We investigated for functional connectivity changes between patients and controls as well as between medication states (OFF vs. ON) in PD and for correlations with clinical parameters. Results There was decreased functional connectivity within the SMN in left inferior parietal and primary somatosensory cortex in PD OFF. Across networks, connectivity between SMN and two motor networks as well as two visual networks was diminished in PD OFF. All connectivity decreases partially normalized in PD ON. Conclusion PD is accompanied by functional connectivity losses of the SMN, both, within the network and in interaction to other networks. The connectivity changes in short- and long-range connections are probably related to impaired sensory integration for motor function in PD. SMN decoupling can be partially compensated by dopaminergic therapy.

Healthy Aging Alters the Functional Connectivity of Creative Cognition in the Default Mode Network and Cerebellar Network

Creativity is a higher-order neurocognitive process that produces unusual and unique thoughts. Behavioral and neuroimaging studies of younger adults have revealed that creative performance is the product of dynamic and spontaneous processes involving multiple cognitive functions and interactions between large-scale brain networks, including the default mode network (DMN), fronto-parietal executive control network (ECN), and salience network (SN). In this resting-state functional magnetic resonance imaging (rs-fMRI) study, group independent component analysis (group-ICA) and resting state functional connectivity (RSFC) measures were applied to examine whether and how various functional connected networks of the creative brain, particularly the default-executive and cerebro-cerebellar networks, are altered with advancing age. The group-ICA approach identified 11 major brain networks across age groups that reflected age-invariant resting-state networks. Compared with older adults, younger adults exhibited more specific and widespread dorsal network and sensorimotor network connectivity within and between the DMN, fronto-parietal ECN, and visual, auditory, and cerebellar networks associated with creativity. This outcome suggests age-specific changes in the functional connected network, particularly in the default-executive and cerebro-cerebellar networks. Our connectivity data further elucidate the critical roles of the cerebellum and cerebro-cerebellar connectivity in creativity in older adults. Furthermore, our findings provide evidence supporting the default-executive coupling hypothesis of aging and novel insights into the interactions of cerebro-cerebellar networks with creative cognition in older adults, which suggest alterations in the cognitive processes of the creative aging brain.

Group-ICA with Functional Connectivity During Inhibition Control in Young Adults With Autistic-like Traits: an fMRI Study of a Stop-Signal Task

BackgroundFew studies explored response inhibition in autistic-like traits people, using task fMRI. In this study, we examine the functional connectivity of the brain using a stop-signal task based on fMRI among young adults with autistic-like traits and investigated their ability to achieve inhibition control.Methods29 of Chinese individuals measured with AQ. Then applied stop signal task to explore the difference in brain functional connectivity in individuals with autistic-like traits.ResultsThe results showed autistic-like traits people the longer the SSRT, the worse the inhibition ability. And we used networks obtained from groupICA analysis at the functional connectivity analysis level, the SN had a negative connection with left SMG; the DAN had a negative connection with left LG; the FPN had a positive connection with left PCG; the LN had a positive connection with vermis 4 5 and negative connection with left ITG. Furthermore, the SMG, LG, PCG, and temporal gyrus were also obtained in ROI-to-ROI analysis.LimitationsOur sample size smaller, still need to multicenter, large sample confirmed this conclusion. We want to use more task paradigms to explore inhibition control in autistic-like traits people.ConclusionsWe found that autistic-like traits people had atypical functional connectivity within brain networks in the SN, DAN, FPN, and LN, and had atypical brain areas centered on the SMG, LG, PCG, and temporal gyrus. And also highlight the importance of considering executive control function of whole-brain functional connections to better characterize brain connectivity in young adults with autistic-like traits.

Aberrant functional connectivity in resting state networks of ADHD patients revealed by independent component analysis

Background ADHD is one of the most common psychiatric disorders in children and adolescents. Altered functional connectivity has been associated with ADHD symptoms. This study aimed to investigate abnormal changes in the functional connectivity of resting-state brain networks (RSNs) among adolescent patients with different subtypes of ADHD. Methods The data were obtained from the ADHD-200 Global Competition, including fMRI data from 88 ADHD patients (56 patients of ADHD-Combined, ADHD-C and 32 patients of ADHD-Inattentive, ADHD-I) and 67 typically developing controls (TD-C). Group ICA was utilized to research aberrant brain functional connectivity within the different subtypes of ADHD. Results In comparison with the TD-C group, the ADHD-C group showed clusters of decreased functional connectivity in the left inferior occipital gyrus (p = 0.0041) and right superior occipital gyrus (p = 0.0011) of the dorsal attention network (DAN), supplementary motor area (p = 0.0036) of the executive control network (ECN), left supramarginal gyrus (p = 0.0081) of the salience network (SN), middle temporal gyrus (p = 0.0041), and superior medial frontal gyrus (p = 0.0055) of the default mode network (DMN), while the ADHD-I group showed decreased functional connectivity in the right superior parietal gyrus (p = 0.0017) of the DAN and left middle temporal gyrus (p = 0.0105) of the DMN. In comparison with the ADHD-I group, the ADHD-C group showed decreased functional connectivity in the superior temporal gyrus (p = 0.0062) of the AN, inferior temporal gyrus (p = 0.0016) of the DAN, and the dorsolateral superior frontal gyrus (p = 0.0082) of the DMN. All the clusters surviving at p < 0.05 (AlphaSim correction). Conclusion The results suggested that decreased functional connectivity within the DMN and DAN was responsible, at least in part, for the symptom of inattention in ADHD-I patients. Similarly, we believed that the impaired functional connectivity within networks may contribute to the manifestations of ADHD-C patients, including inattention, hyperactivity/impulsivity, and unconscious movements.

Aberrant Functional Connectivity in Resting State Networks of ADHD Patients Revealed by Independent Component Analysis

Background: ADHD is one of the most common psychiatric disorders in children and adolescents. Altered functional connectivity has been associated with ADHD symptoms. This study aimed to investigate abnormal changes in the functional connectivity of resting-state brain networks (RSNs) among adolescent patients with different subtypes of ADHD. Methods: The data were obtained from the ADHD-200 Global Competition, including fMRI data from 88 ADHD patients (56 patients of ADHD-Combined, ADHD-C and 32 patients of ADHD-Inattentive, ADHD-I) and 67 typically developing controls (TD-C). Group ICA was utilized to research aberrant brain functional connectivity within the different subtypes of ADHD. Results: In comparison with the TD-C group, the ADHD-C group showed clusters of decreased functional connectivity in the left inferior occipital gyrus (p = 0.0041) and right superior occipital gyrus (p = 0.0011) of the dorsal attention network (DAN), supplementary motor area (p = 0.0036) of the executive control network (ECN), left supramarginal gyrus (p = 0.0081) of the salience network (SN), middle temporal gyrus (p = 0.0041), and superior medial frontal gyrus (p = 0.0055) of the default mode network (DMN), while the ADHD-I group showed decreased functional connectivity in the right superior parietal gyrus (p = 0.0017) of the DAN and left middle temporal gyrus (p = 0.0105) of the DMN. In comparison with the ADHD-I group, the ADHD-C group showed decreased functional connectivity in the superior temporal gyrus (p = 0.0062) of the AN, inferior temporal gyrus (p = 0.0016) of the DAN, and the dorsolateral superior frontal gyrus (p = 0.0082) of the DMN. All the clusters surviving at p < 0.05 (AlphaSim correction). Conclusion: The results suggested that decreased functional connectivity within the DMN and DAN was responsible, at least in part, for the symptom of inattention in ADHD-I patients. Similarly, we believed that the impaired functional connectivity within networks may contribute to the manifestations of ADHD-C patients, including inattention, hyperactivity/impulsivity, and unconscious movements.