Power spectra for screening parkinsonian patients for mild cognitive impairment

Abstract

ObjectiveMild cognitive impairment in Parkinson’s disease (PD-MCI) is diagnosed based on the results of a standardized set of cognitive tests. We investigate whether quantitative EEG (qEEG) measures could identify differences between cognitively normal PD (PD-CogNL) and PD-MCI patients.MethodsHigh-resolution EEG was recorded in 53 patients with Parkinson’s disease (PD). Relative power in five frequency bands was calculated globally and for ten regions. Peak and median frequencies were determined. qEEG results were compared between groups. Effect sizes of all variables were calculated. The best separating variable was used to demonstrate subject-wise classification.ResultsLower mean values were observed in global alpha1 power and alpha1 power in five brain regions (left hemisphere: frontal, central, temporal, occipital; right hemisphere: temporal, P < 0.05), differentiating between PD-CogNL and PD-MCI groups. Effect sizes were high, ranging from 0.79 to 0.87. Median frequency was 8.56 ± 0.74 Hz and was not different between the groups. The variable with the best subject-wise classification was the power in the alpha1 band in the right temporal region. The area under the corresponding receiver operating characteristic (ROC) curve was 0.72. The optimal classification threshold yielded a sensitivity of 65.9% and a specificity of 66.7%. The positive and negative predictive values were 87.1% and 36.4%, respectively.InterpretationReduction in alpha1 band power in nondemented PD patients, particularly in the right temporal region, is highly indicative of MCI in PD patients. The results might be used to assist in time-efficient diagnosis of PD-MCI and avoid the drawbacks of test–retest effect in repeated neuropsychological testing.

Differential spectral quantitative electroencephalography patterns between control and Parkinson's disease cohorts

“…First, our data show that spectral QEEG measures track differentially across control, ILBD, PD‐CogNl, PD‐MCI and PD‐D. There are strong differences amongst spectral QEEG measures between control and groups with different PD cognitive decline severity (Table ), and this validates our earlier reported findings and those of others in this larger cohort . However, the present analysis adds significant new findings in that these spectral QEEG biomarker measures are particularly meaningful as surrogates at certain stages of LTS and PD cognitive severity compared to others.…”

Investigating the ability of post-stroke EEG measures of brain dysfuntion to inform early prediction of cognitive impairment or depression outcomes

“…They found a significant association between EEG slowing with performance of attention, executive function, verbal fluency and long-term memory tasks (Zimmermann et al, 2015). Similar results were found in another Parkinson's population (Bousleiman et al, 2014). Fifty-three patients underwent neuropsychological testing and resting state EEG.…”

“…Fifty-three patients underwent neuropsychological testing and resting state EEG. They found that regional decreases in alpha power were linked to poorer cognitive function (Bousleiman et al, 2014). Although these results were found in Parkinson's disease populations they support the use of QEEG indices as a measure of cognitive impairment in samples with neurological disease/disorders, such as stroke, in particular the investigation of EEG slowing.…”

“…Bousleiman et al (2014) developed a cut-off value in the alpha frequency band to classify Parkinson's patients as cognitively impaired or normal. They report that decreased power in the alpha band (between 8-10Hz) in the temporal region was the strongest marker of cognitive impairment in Parkinson's patients and propose this as a potential biomarker of cognitive impairment (Bousleiman et al, 2014). In addition the same research group used a linear regression model to assess the relationship between EEG slowing and several cognitive domains.…”

Cortical phosphorylated α-Synuclein levels correlate with brain wave spectra in Parkinson's disease

“…Physiological changes in cortical activity have been established to correlate with PD cognitive decline. [8][9][10][11][12][13] The resting EEG is simple to acquire, requires minimal patient cooperation, and is not dependent on verbal or motor responses, which may be affected in PD. QEEG measures may be ideal biomarkers to complement neuropsychological testing with physiological corroboration for studying cognitive decline among patients with PD.…”