An orderly sequence of autonomic and neural events at transient arousal changes

Gu, Yameng; Han, Feng; Sainburg, Lucas E; Schade, Margeaux M.; Buxton, Orfeu M.; Duyn, Jeff H.; Liu, Xiao

doi:10.1016/j.neuroimage.2022.119720

Cited by 17 publications

(27 citation statements)

References 111 publications

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“…The paradox might be explained by an observation about the gBOLD and its coupling with CSF flow. They were more specifically related to ultra-slow (0.6-1 Hz) component of SWA (often related to Kcomplexes) (Özbay et al, 2019) and phasic changes of SWA power (Fultz et al, 2019;Gu et al, 2022), which could be stronger during the light sleep than SWS. Indeed, the SWA was found to decrease in subjects with more cortical Aβ and poorer memory consolidation (Mander et al, 2015;Winer et al, 2020), as well as AD patients (De Gennaro et al, 2017), but the reduction was specific to its ultra-slow component (0.6-1 Hz) with the delta-band (1-4 Hz) power showing opposite changes.…”

Section: Discussionmentioning

confidence: 99%

Sex-specific age-related changes in glymphatic function assessed by resting-state functional magnetic resonance imaging

Han

Liu

Yang

et al. 2023

Preprint

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The glymphatic system that clears out brain wastes, such as amyloid-beta (Abeta) and tau, through cerebrospinal fluid (CSF) flow may play an important role in aging and dementias. However, a lack of non-invasive tools to assess the glymphatic function in humans hindered the understanding of the glymphatic changes in healthy aging. The global infra-slow (<0.1 Hz) brain activity measured by the global mean resting-state fMRI signal (gBOLD) was recently found to be coupled by large CSF movements. This coupling has been used to measure the glymphatic process and found to correlate with various pathologies of Alzheimer's disease (AD), including Abeta pathology. Using resting-state fMRI data from a large group of 719 healthy aging participants, we examined the sex-specific changes of the gBOLD-CSF coupling, as a measure of glymphatic function, over a wide age range between 36-100 years old. We found that this coupling index remains stable before around age 55 and then starts to decline afterward, particularly in females. Menopause may contribute to the accelerated decline in females.

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Section: Discussionmentioning

confidence: 99%

Sex-specific age-related changes in glymphatic function assessed by resting-state functional magnetic resonance imaging

Han

Liu

Yang

et al. 2023

Preprint

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“…The third sample is from the healthy control candidates collected by Gu et al (2022) . The subjects had no history of medical, neurological, or psychiatric disease.…”

Section: Methodsmentioning

confidence: 99%

Functional and effective connectivity analysis of drug-resistant epilepsy: a resting-state fMRI analysis

Bacon

Jin

et al. 2023

Front. Neurosci.

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ObjectiveEpilepsy is considered as a neural network disorder. Seizure activity in epilepsy may disturb brain networks and damage brain functions. We propose using resting-state functional magnetic resonance imaging (rs-fMRI) data to characterize connectivity patterns in drug-resistant epilepsy.MethodsThis study enrolled 47 participants, including 28 with drug-resistant epilepsy and 19 healthy controls. Functional and effective connectivity was employed to assess drug-resistant epilepsy patients within resting state networks. The resting state functional connectivity (FC) analysis was performed to assess connectivity between each patient and healthy controls within the default mode network (DMN) and the dorsal attention network (DAN). In addition, dynamic causal modeling was used to compute effective connectivity (EC). Finally, a statistical analysis was performed to evaluate our findings.ResultsThe FC analysis revealed significant connectivity changes in patients giving 64.3% (18/28) and 78.6% (22/28) for DMN and DAN, respectively. Statistical analysis of FC was significant between the medial prefrontal cortex, posterior cingulate cortex, and bilateral inferior parietal cortex for DMN. For DAN, it was significant between the left and the right intraparietal sulcus and the frontal eye field. For the DMN, the patient group showed significant EC connectivity in the right inferior parietal cortex and the medial prefrontal cortex for the DMN. There was also bilateral connectivity between the medial prefrontal cortex and the posterior cingulate cortex, as well as between the left and right inferior parietal cortex. For DAN, patients showed significant connectivity in the right frontal eye field and the right intraparietal sulcus. Bilateral connectivity was also found between the left frontal eye field and the left intraparietal sulcus, as well as between the right frontal eye field and the right intraparietal sulcus. The statistical analysis of the EC revealed a significant result in the medial prefrontal cortex and the right intraparietal cortex for the DMN. The DAN was found significant in the left frontal eye field, as well as the left and right intraparietal sulcus.ConclusionOur results provide preliminary evidence to support that the combination of functional and effective connectivity analysis of rs-fMRI can aid in diagnosing epilepsy in the DMN and DAN networks.

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“…We next aimed to determine whether our findings during pharmacological states of unconsciousness induced by propofol extend to physiological states of unconsciousness during natural sleep. We analyzed an fMRI dataset acquired during various stages of sleep in humans (Dataset-5) 36,37 . Integration showed statistically significant decrease during N2 sleep compared to wakefulness and N1 sleep ( Notably, the relationships between integration, segregation, metastability, and complexity observed under anesthesia (Fig.…”

Section: Integration-segregation Balance Shifts Towards Segregation D...mentioning

confidence: 99%

Measuring the dynamic balance of integration and segregation underlying consciousness, anesthesia, and sleep

Jang,

Mashour,

Hudetz

et al. 2024

Preprint

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Consciousness requires a dynamic balance of integration and segregation in functional brain networks. An optimal integration-segregation balance depends on two key aspects of functional connectivity: global efficiency (i.e., integration) and clustering (i.e., segregation). We developed a new fMRI-based measure, termed the integration-segregation difference (ISD), which captures both aspects. We used this metric to quantify changes in brain state from conscious wakefulness to loss of responsiveness induced by the anesthetic propofol. The observed changes in ISD suggest a profound shift to segregation in both whole brain and all brain subnetworks during anesthesia. Moreover, brain networks displayed similar sequences of disintegration and subsequent reintegration during, respectively, loss and return of responsiveness. Random forest machine learning models, trained with the integration and segregation of brain networks, identified the awake vs. unresponsive states and their transitions with accuracy up to 93%. We found that metastability (i.e., the dynamic recurrence of non-equilibrium transient states) is more effectively explained by integration, while complexity (i.e., diversity and intricacy of neural activity) is more closely linked with segregation. The analysis of a sleep dataset revealed similar findings. Our results demonstrate that the integration-segregation balance is a useful index that can differentiate among various conscious and unconscious states.

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An orderly sequence of autonomic and neural events at transient arousal changes

Cited by 17 publications

References 111 publications

Sex-specific age-related changes in glymphatic function assessed by resting-state functional magnetic resonance imaging

Sex-specific age-related changes in glymphatic function assessed by resting-state functional magnetic resonance imaging

Functional and effective connectivity analysis of drug-resistant epilepsy: a resting-state fMRI analysis

Measuring the dynamic balance of integration and segregation underlying consciousness, anesthesia, and sleep

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