Corrigendum: Altered Brain Microstate Dynamics in Adolescents With Narcolepsy

Drissi, Natasha Morales; Szakács, Attila; Witt, Suzanne T.; Wretman, Anna; Ulander, Martin; Ståhlbrandt, Henriettæ; Darín, Niklas; Hallböök, Tove; Landtblom, Anne‐Marie; Engström, Maria

doi:10.3389/fnhum.2019.00385

Cited by 3 publications

(2 citation statements)

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“…46 Indeed, abnormalities in the efficiency of the WM network topology may reduce the connectivity between the brain gray matter areas, as has been suggested for the salience and executive, 22 default mode, sensory-motor, auditory, visual, and dorsal attention networks. 47 The reduced interactions may result in the cognitive deficits in NT1 patients. Therefore, the inefficiency of the brain WM structure network in NT1 patients may cause a decline in information processing abilities, which may extend to cognitive impairment in the awake state.…”

Section: Discussionmentioning

confidence: 99%

Changed Cerebral White Matter Structural Network Topological Characters and Its Correlation with Cognitive Behavioral Abnormalities in Narcolepsy Type 1

Ni¹,

Liu²,

Zhu³

et al. 2022

NSS

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In the current study we investigated topological abnormalities of the cerebral white matter networks in narcolepsy type 1 (NT1) patients and its relationship with their cognitive abnormalities using diffusion tensor imaging (DTI) technology. Methods: DTI and the Beijing version of the Montreal Cognitive Assessment (MoCA-BJ) were applied to 30 NT1 patients and 30 age-matched healthy controls. DTI studies were also carried using the 3T MRI system. Next, DTI data was used to establish a cerebral white matter network for all subjects and graph theory was applied to analyze the topological characteristics of the white matter structural network. Topographical parameters (such as local efficiency (Eloc), global efficiency (Eglob) and small-world (σ)) between NT1 patients and controls were then compared. The correlation between MoCA-BJ scores and topological parameters was also analyzed. Results: MoCA-BJ scores in NT1 patients were lower than those in the healthy controls. Compared with healthy controls, the global efficiency of the white matter network and attributes of the small world network were significantly reduced in NT1 patients. Finally, the global efficiency of the white matter structural network was related to the MoCA-BJ score of NT1 patients. Conclusion:The abnormal topological characteristics of the white matter structural network in NT1 patients may be associated with their cognitive impairment.

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Section: Discussionmentioning

confidence: 99%

Changed Cerebral White Matter Structural Network Topological Characters and Its Correlation with Cognitive Behavioral Abnormalities in Narcolepsy Type 1

Ni¹,

Liu²,

Zhu³

et al. 2022

NSS

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“…In addition, several studies have reported that resting-state EEG microstates are altered in neuropsychiatric and neurodegenerative disorders, such as Alzheimer’s disease (Musaeus et al 2019 ; Smailovic et al 2019 ), Parkinson’s disease (Chu et al 2019 ), schizophrenia (Andreou et al 2014 ; Baradits et al 2020 ; da Cruz et al 2020 ; de Bock et al 2020 ; Giordano et al 2018 ; Kindler et al 2011 ; Koenig et al 1999 ; Lehmann et al 2005 ; Murphy et al 2020a ; Nishida et al 2013 ; Soni et al 2018 ; Strelets et al 2003 ; Tomescu et al 2014 ; Tomescu et al 2015 ), multiple sclerosis (Gschwind et al 2016 ), fibromyalgia (Gonzalez-Villar et al 2020 ), panic disorder (Kikuchi et al 2011 ), bipolar disorder (Damborska et al 2019 ; Vellante et al 2020 ), obsessive–compulsive disorder (Yoshimura et al 2019 ), depressive disorder (Murphy et al 2020b ), narcolepsy (Drissi et al 2016 ; Drissi et al 2019 ), stroke (Zappasodi et al 2017 ) or autism (D’Croz-Baron et al 2019 ; Jia and Yu 2019 ; Portnova et al 2020 ). EEG microstate analyses might therefore provide another tool for the development of a non-invasive assessment of healthy cognitive aging.…”

Section: Introductionmentioning

confidence: 99%

Resting‐State EEG Microstates Parallel Age‐Related Differences in Allocentric Spatial Working Memory Performance

et al. 2021

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Alterations of resting-state EEG microstates have been associated with various neurological disorders and behavioral states. Interestingly, age-related differences in EEG microstate organization have also been reported, and it has been suggested that resting-state EEG activity may predict cognitive capacities in healthy individuals across the lifespan. In this exploratory study, we performed a microstate analysis of resting-state brain activity and tested allocentric spatial working memory performance in healthy adult individuals: twenty 25–30-year-olds and twenty-five 64–75-year-olds. We found a lower spatial working memory performance in older adults, as well as age-related differences in the five EEG microstate maps A, B, C, C′ and D, but especially in microstate maps C and C′. These two maps have been linked to neuronal activity in the frontal and parietal brain regions which are associated with working memory and attention, cognitive functions that have been shown to be sensitive to aging. Older adults exhibited lower global explained variance and occurrence of maps C and C′. Moreover, although there was a higher probability to transition from any map towards maps C, C′ and D in young and older adults, this probability was lower in older adults. Finally, although age-related differences in resting-state EEG microstates paralleled differences in allocentric spatial working memory performance, we found no evidence that any individual or combination of resting-state EEG microstate parameter(s) could reliably predict individual spatial working memory performance. Whether the temporal dynamics of EEG microstates may be used to assess healthy cognitive aging from resting-state brain activity requires further investigation.

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Altered cortical activity in patients with lower limb amputation based on EEG microstate

Shan¹,

Wei²,

Liu³

et al. 2021

J. Integr. Neurosci.

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Previous studies have revealed significant changes in electroencephalogram (EEG) microstates in neuropsychiatric diseases, including schizophrenia, depression, and dementia. To explore the restingstate EEG microstate with amputation, we collected the EEG datasets from 15 patients with lower limb amputation and 20 healthy controls. Then, we analyzed the parameters of four classical EEG microstates (A-D) between the two groups. Specifically, the parameters were statistically analyzed, including duration, occurrence rate, time coverage, and transition rate. According to the results, the duration of microstate C (t = 2.95, p = 0.005) in the lower limb amputation group was significantly smaller compared with the control group, while the occurrence rate of microstate B (t = -2.22, p = 0.03) and D (t = -3.35, p = 0.002) were significantly larger in the lower limb amputation group. In addition, the transition rate of microstate differed significantly in AC, CA, DB between the two groups. Our results implied: (1) amputation has changed the resting-state EEG microstate; (2) EEG microstate analysis can be an approach to explore the alteration of cortical function.

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Corrigendum: Altered Brain Microstate Dynamics in Adolescents With Narcolepsy

Cited by 3 publications

References 0 publications

Changed Cerebral White Matter Structural Network Topological Characters and Its Correlation with Cognitive Behavioral Abnormalities in Narcolepsy Type 1

Changed Cerebral White Matter Structural Network Topological Characters and Its Correlation with Cognitive Behavioral Abnormalities in Narcolepsy Type 1

Resting‐State EEG Microstates Parallel Age‐Related Differences in Allocentric Spatial Working Memory Performance

Altered cortical activity in patients with lower limb amputation based on EEG microstate

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