Increased attentional network activity in premature ejaculation patients with anxiety revealed by resting‐state fMRI

2021 ◽  
Author(s):  
Shaowei Liu ◽  
Xing Zhang ◽  
Qing Wang ◽  
Yan Xu ◽  
Xinfei Huang ◽  
...  
Keyword(s):  
Resting State ◽  
Premature Ejaculation ◽  
Resting State Fmri ◽  
Network Activity ◽  
Attentional Network

scholarly journals Multiscale network activity in resting state fMRI

2016 ◽  
Author(s):  
Shella D. Keilholz ◽  
Jacob C.W. Billings ◽  
Kai Wang ◽  
Anzar Abbas ◽  
Claudia Hafeneger ◽  
...  
Keyword(s):  
Resting State ◽  
Resting State Fmri ◽  
Network Activity

scholarly journals Assessing the function of the fronto-parietal attention network: Insights from resting-state fMRI and the attentional network test

2013 ◽  
Vol 35 (4) ◽  
pp. 1700-1709 ◽  
Author(s):  
Sebastian Markett ◽  
Martin Reuter ◽  
Christian Montag ◽  
Gesine Voigt ◽  
Bernd Lachmann ◽  
...  
Keyword(s):  
Resting State ◽  
Resting State Fmri ◽  
Attention Network ◽  
Attentional Network ◽  
Attentional Network Test

Fluctuations of Attentional Networks and Default Mode Network during the Resting State Reflect Variations in Cognitive States: Evidence from a Novel Resting-state Experience Sampling Method

2017 ◽  
Vol 29 (1) ◽  
pp. 95-113 ◽  
Author(s):  
Laurens Van Calster ◽  
Arnaud D'Argembeau ◽  
Eric Salmon ◽  
Frédéric Peters ◽  
Steve Majerus
Keyword(s):  
Default Mode Network ◽  
Resting State ◽  
Experience Sampling ◽  
Resting State Fmri ◽  
Mental States ◽  
Network Activity ◽  
Attentional Processes ◽  
Default Mode ◽  
Cognitive States ◽  
Attentional Networks

Neuroimaging studies have revealed the recruitment of a range of neural networks during the resting state, which might reflect a variety of cognitive experiences and processes occurring in an individual's mind. In this study, we focused on the default mode network (DMN) and attentional networks and investigated their association with distinct mental states when participants are not performing an explicit task. To investigate the range of possible cognitive experiences more directly, this study proposes a novel method of resting-state fMRI experience sampling, informed by a phenomenological investigation of the fluctuation of mental states during the resting state. We hypothesized that DMN activity would increase as a function of internal mentation and that the activity of dorsal and ventral networks would indicate states of top–down versus bottom–up attention at rest. Results showed that dorsal attention network activity fluctuated as a function of subjective reports of attentional control, providing evidence that activity of this network reflects the perceived recruitment of controlled attentional processes during spontaneous cognition. Activity of the DMN increased when participants reported to be in a subjective state of internal mentation, but not when they reported to be in a state of perception. This study provides direct evidence for a link between fluctuations of resting-state neural activity and fluctuations in specific cognitive processes.

146. Effects of low-dose LPS on resting-state fMRI network activity

2014 ◽  
Vol 40 ◽  
pp. e42 ◽  
Author(s):  
M. Lekander ◽  
B. Karshikoff ◽  
G. Nilsonne ◽  
M. Ingvar ◽  
E. Johansson ◽  
...  
Keyword(s):  
Resting State ◽  
Low Dose ◽  
Resting State Fmri ◽  
Network Activity

Effects of aging on default mode network activity in resting state fMRI: Does the method of analysis matter?

NeuroImage ◽  
2010 ◽  
Vol 51 (1) ◽  
pp. 280-287 ◽  
Author(s):  
W. Koch ◽  
S. Teipel ◽  
S. Mueller ◽  
K. Buerger ◽  
A.L.W. Bokde ◽  
...  
Keyword(s):  
Default Mode Network ◽  
Resting State ◽  
Resting State Fmri ◽  
Network Activity ◽  
Default Mode ◽  
Effects Of Aging

scholarly journals Abnormal Functional Connectivity Between the Left Medial Superior Frontal Gyrus and Amygdala Underlying Abnormal Emotion and Premature Ejaculation: A Resting State fMRI Study

2021 ◽  
Vol 15 ◽  
Author(s):  
Yan Xu ◽  
Xing Zhang ◽  
Ziliang Xiang ◽  
Qing Wang ◽  
Xinfei Huang ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Premature Ejaculation ◽  
Critical Role ◽  
Superior Temporal Gyrus ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Superior Frontal Gyrus ◽  
Eysenck Personality Inventory ◽  
Positive Correlations

IntroductionPremature ejaculation (PE) is a common sexual dysfunction and is found to be associated with abnormal emotion. The amygdala plays an important role in the processing of emotion. The process of ejaculation is found to be mediated by the frontal-limbic neural circuits. However, the correlations between PE and emotion are still unclear.MethodsResting-state functional magnetic resonance imaging (rs-fMRI) data were acquired in 27 PE patients with stable emotion (SPE), 27 PE patients with abnormal emotion (NPE), and 30 healthy controls (HC). We used rs-fMRI to explore the underlying neural mechanisms in SPE, NPE, and HC by measuring the functional connectivity (FC). Differences of FC values among the three groups were compared when choosing bilateral amygdala as the regions of interest (ROIs). We also explored the correlations between the brain regions showing altered FC values and scores of the premature ejaculation diagnostic tool (PEDT)/Eysenck Personality Inventory about neuroticism (EPQ-N) in the PE group.ResultsWhen the left amygdala was chosen as the ROI, the SPE group exhibited an increased FC between the left medial superior frontal gyrus (SFGmed) and amygdala compared with the NPE or HC group. When the right amygdala was chosen as the ROI, the NPE group exhibited a decreased FC between the left SFGmed and right amygdala compared with the HC group. In addition, FC values of the left SFGmed had positive correlations with PEDT and negative correlations with EPQ-N scores in the PE group. Moreover, FC values of the left superior temporal gyrus had positive correlations with EPQ-N scores in the PE group.ConclusionThe increased FC values between the left SFGmed and amygdala could reflect a compensatory cortical control mechanism with the effect of stabilized emotion in the limbic regions of PE patients. Abnormal FC between these brain regions could play a critical role in the physiopathology of PE and could help us in dividing PE into more subtypes.

scholarly journals Spatiotemporal Trajectories in Resting-state FMRI Revealed by Convolutional Variational Autoencoder

2021 ◽  
Author(s):  
Xiaodi Zhang ◽  
Eric Maltbie ◽  
Shella Keilholz
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Spatiotemporal Patterns ◽  
Network Activity ◽  
Fmri Data ◽  
Variational Autoencoder ◽  
Spatiotemporal Trajectories ◽  
The Brain

AbstractRecent resting-state fMRI studies have shown that brain activity exhibits temporal variations in functional connectivity by using various approaches including sliding window correlation, co-activation patterns, independent component analysis, quasi-periodic patterns, and hidden Markov models. These methods often model the brain activity as a discretized hopping among several brain states that are defined by the spatial configurations of network activity. However, the discretized states are merely a simplification of what is likely to be a continuous process, where each network evolves over time following its unique path. To model these characteristic spatiotemporal trajectories, we trained a variational autoencoder using rs-fMRI data and evaluated the spatiotemporal features of the latent variables obtained from the trained networks. Our results suggest that there are a relatively small number of approximately orthogonal whole-brain spatiotemporal patterns that capture the most prominent features of rs-fMRI data, which can serve as the building blocks to construct all possible spatiotemporal dynamics in resting state fMRI. These spatiotemporal patterns provide insight into how activity flows across the brain in concordance with known network structures and functional connectivity gradients.

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