Spatiotemporal EEG microstate analysis in drug-free patients with Parkinson's disease

Chu, Chunguang; Wang, Xing; Cai, Lihui; Zhang, Lei; Wang, Jiang; Zhu, Xiaodong

doi:10.1016/j.nicl.2019.102132

Cited by 63 publications

(51 citation statements)

References 52 publications

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“…Furthermore, the study results also showed that the PD groups (w/ and w/o ICD) exhibited weakened N2 and P3 peak amplitudes with respect to the HC group (c.f., Figure 4), which replicated early findings [14,32]. While previous studies mostly focused on EEG differences between different PD stages [33][34][35] or between PD vs. HC individuals [14,31,32], less effort has been devoted to assess PD patients against PD patients diagnosed with ICD. In order to address this issue, the present work conducted two sessions of the Go/NoGo task interleaved with the DA-pharmacological treatment for PD groups.…”

Section: Discussionsupporting

confidence: 84%

“…The use of a nonmedicalgrade EEG-sensing platform is a harsh yet realistic setup, closer to a practical wearable-device for ubiquitous ICD monitoring. While most previous studies focused on the EEG/ERP distinction between PD patients and healthy subjects [14,31,32] or between different PD stages [33][34][35], the present work attempted to address whether ERP signatures can be regarded as neuro-markers reflecting the DA-triggered ICD adverse effect in PD patients. This work also contributes to the practical application of EEG by using a customized, cost-efficient EEGsensing setup rather than an expense laboratory-oriented product.…”

Section: Introductionmentioning

confidence: 99%

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Objective Assessment of Impulse Control Disorder in Patients with Parkinson’s Disease Using a Low-Cost LEGO-Like EEG Headset

Lin¹,

Liang²,

Chen³

et al. 2020

Preprint

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BackgroundPatients with Parkinson’s disease (PD) can develop the cognitive adverse effect of impulse control disorders (ICDs) while undergoing a pharmacological treatment for motor control dysfunctions with a dopamine agonist (DA). Conventional clinical interviews or questionnaires can be biased and may not provide an accurate diagnosis in the early stage. A wearable electroencephalogram (EEG)-sensing headset paired with an examination procedure can be a potential user-friendly method to explore ICD-related biomarkers that can reflect brain activity abnormalities and detect its early signs and progression.MethodsA stereotypical Go/NoGo test that targets impulse inhibition was performed with 59 individuals, including heathy controls, patients with PD, and patients with PD diagnosed with ICD. A low-cost LEGO-like EEG headset was used to record concurrent EEG signals. The event-related potential (ERP) analytical framework was then used to explore ICD-related EEG abnormalities after DA treatment.ResultsOnly PD patients with ICD exhibited a tendency for N2 and P3 amplitude deterioration at the fronto-central regions (i.e., Fz, FCz, and Cz); in particular, the P3 counterpart reached statistical significance (p<0.05). Neither PD patients nor healthy controls (without DA) replicated such findings. Furthermore, N2 amplitude deterioration was found to be related to ICD severity at Fz (r=-0.28, p=0.04).ConclusionsA low-cost LEGO-like EEG headset successfully captured ERP neuromarkers for the objective assessment of ICD in PD patients undergoing DA treatment. The present objective neuro-evidence could provide complementary information to conventional clinical scales used to diagnose the ICD adverse effect.

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Section: Discussionsupporting

confidence: 84%

Section: Introductionmentioning

confidence: 99%

Objective Assessment of Impulse Control Disorder in Patients with Parkinson’s Disease Using a Low-Cost LEGO-Like EEG Headset

Lin¹,

Liang²,

Chen³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…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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“…To explore this further, some studies have also mapped out the distribution of high alpha state durations ( Quinn et al, 2018 ). Such measures have been shown to correlate with motor and cognitive function in Parkinson’s disease ( Chu et al, 2020 ) and schizophrenia ( Khanna et al, 2015 ) and furthermore, cognitive manipulation of these states can be achieved through interventions ( Seitzman et al, 2017 ). However, no studies have used these dynamic parameters of alpha rhythm to measure neurophysiological changes in chronic pain.”…”

Section: Introductionmentioning

confidence: 99%

Using EEG Alpha States to Understand Learning During Alpha Neurofeedback Training for Chronic Pain

et al. 2021

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ObjectiveAlpha-neurofeedback (α-NFB) is a novel therapy which trains individuals to volitionally increase their alpha power to improve pain. Learning during NFB is commonly measured using static parameters such as mean alpha power. Considering the biphasic nature of alpha rhythm (high and low alpha), dynamic parameters describing the time spent by individuals in high alpha state and the pattern of transitioning between states might be more useful. Here, we quantify the changes during α-NFB for chronic pain in terms of dynamic changes in alpha states.MethodsFour chronic pain and four healthy participants received five NFB sessions designed to increase frontal alpha power. Changes in pain resilience were measured using visual analogue scale (VAS) during repeated cold-pressor tests (CPT). Changes in alpha state static and dynamic parameters such as fractional occupancy (time in high alpha state), dwell time (length of high alpha state) and transition probability (probability of moving from low to high alpha state) were analyzed using Friedman’s Test and correlated with changes in pain scores using Pearson’s correlation.ResultsThere was no significant change in mean frontal alpha power during NFB. There was a trend of an increase in fractional occupancy, mean dwell duration and transition probability of high alpha state over the five sessions in chronic pain patients only. Significant correlations were observed between change in pain scores and fractional occupancy (r = −0.45, p = 0.03), mean dwell time (r = -0.48, p = 0.04) and transition probability from a low to high state (r = -0.47, p = 0.03) in chronic pain patients but not in healthy participants.ConclusionThere is a differential effect between patients and healthy participants in terms of correlation between change in pain scores and alpha state parameters. Parameters providing a more precise description of the alpha power dynamics than the mean may help understand the therapeutic effect of neurofeedback on chronic pain.

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Spatiotemporal EEG microstate analysis in drug-free patients with Parkinson's disease

Cited by 63 publications

References 52 publications

Objective Assessment of Impulse Control Disorder in Patients with Parkinson’s Disease Using a Low-Cost LEGO-Like EEG Headset

Objective Assessment of Impulse Control Disorder in Patients with Parkinson’s Disease Using a Low-Cost LEGO-Like EEG Headset

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

Using EEG Alpha States to Understand Learning During Alpha Neurofeedback Training for Chronic Pain

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