| Background and ObjectiveCognitive impairment is one of the most common and important motor symptoms of Parkinson’s disease (PD). It may appears in the early stages of the PD disease, even before motor symptoms and for its highly disability degree, patient’s quality of life would be seriously influenced. Although routine EEG analysis technology has been widely applied in diagnosis of cognitive disorder diseases (Alzheimer’s disease and dementia with Lewy bodies, etc.), it is not perfect in the early diagnosis of PD cognitive impairment, especially in patients with mild cognitive impairment, this may be related to insensitivity of traditional EEG analysis technology and dormant also complex pathogenesis of PD cognitive impairment. Quantitative analyses of EEG (QEEG) transformed the original EEG into quantitative data using mathematics and computer technology. Compared with traditional reading method of analyzing the electroencephalogram, it overcomed the subjective influence of analysis by naked eyes. At the same time, it can make some invisible characteristics more prominent and make assessment of EEG more objective and quantitative. It can analysis distribution characteristics and occurrence rule of different brain waves spectrum in different brain area, as well as the spectrum energy. Currently there is a few QEEG studies associated with PD cognitive function, especially with PD mild cognitive impairment, and they were limited to the analysis of the whole brain electrical activity, there is little comparison of electrical activity in different parts of brain. Due to the diversity of cognitive impairment manifestations in PD, of which the executive function impairment, attention impairment and visual spatial ability impairment are outstanding, therefore, to explore the change of electrical activity in different brain regions, and the correlation between these changes and neuropsychological characteristics change are especially meaningful. Dynamic follow-up of EEG change and cognitive trend and in progressed PD patients can help looking for risk factors which can predict of the development of cognitive impairment in patients. According to the consensus of American Academy of Neurology in Application of QEEG, QEEG is an effective auxiliary part of routine EEG report, especially for the early cognitive impairment. The first part of this study plan to:①Analysis the change features of brain activity of PD patients with cognitive impairment in sober also quiet state using method combined GTE rating scale under routine reading figure method and QEEG parameter. At the same time, follow-up tracking EEG and cognitive function of some patients, to investigate the correlation between EEG change and cognitive.②Using polysomnography combining QEEG to explore the correlation between the change of sleep structure parameters and QEEG parameters of different sleep stages and cognitive function. To assess the application value of EEG analysis for cognitive function in Parkinson’s disease, and to discuss the tendency of brain activity changes in different physiological cycles of PD with cognitive function change.In addition, there were some studies showed that there may have some nonspecific changes in electroencephalogram of PD patients without dementia, and these changes may be associated with movement function. Therefore, we hypothesized that PD patients may have some local electrical activity change in the early stage, these changes may be related to clinical characteristics such as severity of the disease and motor symptoms. In addition, because of its prominent curative effect in control movement symptoms of PD, levodopa drugs (Madopar) has been widely used in the diagnosis and differential diagnosis of PD. The latest international PD treatment guidelines also proposed:set unconspicuous response to large dose levodopa therapy as the absolute exclusion criteria of PD diagnosis. The mechanism of levodopa drugs improve the symptoms of motion is unknown, may be related to reduced internal and its pathological synchronization with basal ganglia cortex, so as to improve the function of nerve of the contact. Recently some scholars use EEG analysis technique observed levodopa drugs can obviously reduce the synchronization of EEG activity of both sides brain. Therefore, to discuss the early diagnosis value of EEG analysis technology in PD, the second part of this study plan: ①To just analyse the EEG change characteristics and its correlation with the severity of the disease, motor symptoms of PD patients without cognitive impairment in order to eliminate the influence of the cognitive function of brain electrical activity, to find out potential markers for early diagnosis of Parkinson’s disease. ② To study the correlation of Madopar test and EEG change, for preliminary discussion the possibility of EEG analysis technology in assisting judging Madopar’s drug efficacy.Methods1. Correlation study of EEG changes and PD’s cognitive function under sober, quiet state:We conducted scalp EEG examination on 213 PD patients and 50 healthy controls (age and sex matched) using combined GTE rating scale under the routine EEG and QEEG parameters. After recording we got their GTE scores under regular reading and corresponding quantitative EEG data (including relative wave spectrum, the correlation coefficient, aEEG, alpha coefficient of variation, etc.) by QEEG software. At the same time, according to the results of the clinical symptoms and neuropsychological assessment, Parkinson’s disease group can be divided into three groups:normal cognitive group (PD-NC), mild cognitive impairment group (PD-MCI) and Parkinson’s disease dementia group (PDD). Considered the age influence on EEG, we used age as stratification factors, compared the routine EEG change and QEEG parameters of different cognitive function group in early-onset and late-onset PD respectively, and discussed the correlation of these changes and cognitive function. At the same time, in order to investigate the predictive ability of EEG change in cognitive impairment, part of PD patients were followed up, and evaluated EEG and cognitive function at different time points.2.Correlation study of QEEG and sleep structure parameters changes and PD’s cognitive function in different sleep stages:Our of normal group were, using quantitative analysis software output in different stage in the central and the quantitative EEG data of the pillow (coherent coefficient and frequency band energy). We conducted polysomnography to 75 PD patients and 49 controls and got QEEG data of central region and occipital region (coherent coefficient and frequency band energy) in different sleep stages. According to the results of the clinical symptoms and neuropsychological assessment, Parkinson’s disease patients can be divided into three groups:normal cognitive group (PD-NC), mild cognitive impairment (PD-MCI) and Parkinson’s disease dementia (PDD). At the same time, we analyzed the sleep indexes and compared QEEG parameters and sleep structure parameters in different cognitive function groups in order to investigate their correlation.3.Correlation study of EEG changes and severity of the disease, motor symptoms among PD patients without cognitive impairment:By neuropsychological assessment, we conducted scalp EEG examination on 58 PD patients without cognitive impairment and 50 healthy controls and got their corresponding QEEG data (including relative wave spectrum, the correlation coefficient, aEEG, etc.) using QEEG software. We compared these QEEG parameters and to explored the correlation relationship of these parameters and the movement symptom scores, severity of disease in early-onset and late-onset PD.4.Correlation study of Madopar test and EEG changesWe enrolled 12 PD patients never received levodopa drug treatment and 7 health controls, and conducted evaluation movement symptom scores and QEEG before and after Madopar taking, compared EEG changes and rheir relationship with motor symptoms.Results1. In correlation study of EEG changes and PD’s cognitive function under sober, quiet state:①According to the result of the cognitive evaluation, after the analysis of clinical data, we found that:in the 213 PD patients enrolled, PD-NC (23.8%), PD-MCI (64.9%), PDD (11.3%),151 were late-onset,62 were early-onset (stratified at 50 years old). In the late-onset PD, PD-MCI(64.9%,PDD(11.3%),on the modified H-Y classification, PD-NC group, PD-MCI group and PDD group gradually increased in classification and the different was statistically significant (P< 0.05). In addition, the education level of PDD group were lower than PD-NC group and PD-MCI group (P< 0.05).In early-onset PD, PD-MCI(54.8%), PDD(3.2%),both showed lower rate than late-onset PD, and PD-NC group’s onset time were earlier than PD-MCI group (P< 0.05).②According to analysis of routine EEG results of different cognitive function group, we found that:both early and late onset PD, no matter GTE total score of two component scores (including background wave frequency, diffuse slow waves), scores of PD-NC group, PD-MCI group, PDD group and the control group increased gradually (P< 0.05). On the background wave reactive score, PDD scores were statistically significant higer than PD-NC group, PD-MCI group and control group (P< 0.05).③According to analysis of QEEG results in different cognitive function group, we found that:in the late-onset PD, compared to PD-NC group, the recorded theta relative band power of PDD and PD-MCI group in the bilateral occipital area, bilateral frontal area, left parietal area, left temporal region, bilateral central area lead location were significantly increased(P< 0.05). In early-onset PD, compared with normal control group, the recorded beta relative band power of PDD and PD-MCI group at bilateral occipital area, bilateral parietal area, bilateral temporal area, left central region, left frontal area were significantly decreased (P< 0.05), but there was no statistical difference between PD-MCI and PD-NC group (P> 0.05). Moreover, the coherence coefficient of recorded theta and beta band of bilateral temporal and frontal region in PD-NC group and PD-MCI group were larger than normal control group, but there was no statistical difference between PD-NC and PD-MCI groups.④To explore the correlation of PD clinical characteristics and EEG changes and the cognitive impairment, we use the Logistic stepwise regression method in the late-onset PD considered the close relationship of GTE rating scale and QEEG. The patients’ gender, age, course of the disease, severity of disease, degree of culture and GTE scale and the previous significant QEEG index (recorded theta relative band power in bilateral occipital area, bilateral frontal area, left parietal area, left temporal area, bilateral central area) were included in the regression analysis. Results showed that:GTE scale and theta relative wave spectrum in frontal area is associated with PD cognitive impairment.⑤According to correlation research of EEG trends and cognitive function among 30 PD patients showed that there is no significant correlation.2.1n correlation study of QEEG and sleep structure parameters changes and PD’s cognitive function in different sleep stages, we found:compared with normal control group PD-MCI group are more likely to be have fast rem sleep disorder (P< 0.05) while there was no significant difference compared with PD-NC group (P> 0.05). There was no statistical difference between PD-MCI group, PD-NC group and normal control group in rest sleep indicators (including sleep efficiency, total sleep time, sleep efficiency, sleep latency, N1, N2 and N3 periods percentage, etc.). We also compared EEG data of PD-MCI group, PD-NC group and normal control group sleep stages (including N2 and REM of NREM stage), quantitative analyzed the occipital region and central region which showed no significant statistical difference (P> 0.05).3. In correlation study of EEG changes and severity of the disease, motor symptoms among PD patients without cognitive impairment, we found:In early-onset PD, compared with normal control group, higher score of GTE score and the subscore of diffuse slow waves were showed in PD group. Additionally,beta relative band power in bilateral occipital area, bilateral parietal area, bilateral post-temporal area, left central area, left frontal area were significantly decreased (P< 0.05) in PD group. After control the sex and age, we used the partial correlation analysis method to explore the correlation of upper brain regions beta relative wave spectrum and motor symptoms (UPDRS-III score) and modified H-Y grading respectively, the results showed significantly statistical relationship between beta relative band power and H-Y grading.However, no change was found in late-onset PD.4.1n correlation study of Madopar test and EEG changes, based on the results in front part of the research, we assessed the theta and beta relative wave spectrum and changes of correlation coefficient before and after Madopar test in part of the brain regions respectively. Results showed that compared with the PD group (both for PD syndrome or overlay syndrome patients), UPDRS-III score of PD group after taking Madopar 1.5h improved significantly (P< 0.05), but QEEG parameters between more than two groups showed no statistically significant difference.Conclution1.The present study analysed the Characteristic of routine EEG and QEEG in early-onset and late-onset PD including GTE,relative band power,coherence coefficient, alpha variability and aEEG in order to explore the correlation between cognitive dysfunction and brain activities change in different regions for the first time.Additionally, This is a domestic leading research on taking the advantage of QEEG combined with routine EEG to observe related EEG parameters both in awake and sleep stage. We were aimed to investigate EEG changes characteristics in PD patients cognitive impairment and their correlation and provide a new assessment angle of means to the early diagnosis of PD cognitive impairment. Furthermore, The clinical sample size of our research was large, and it covered PDD and PD-MCI patients in different age and enriched the clinical and EEG data of diffent cognitive impairment groups.2. Analysis PD clinical characteristics of different age groups, our study confirmed: ①The dementia incidence rate of early-onset PD was lower than late-onset PD. ②Cognitive impairment in the late-onset PD is associated with the severity of disease. In addition, low education levels are more susceptible to PDD.③In early-onset PD, onset time of PD-NC group are earlier than PD-MCI group.3. By using the GTE scale to score the routine EEG, our study confirmed that both early-onset and late-onset PD, compared with PD patients without cognitive impairment and normal ages, the routine EEG of PD-MCI and PDD group tend to appears such characteristics: ①Background wave frequency slower ②Diffuse slow waves increase③Background rhythm reactivity weaken. Among which ①Background wave frequency slower ②Diffuse slow waves increase particularly outstanding. And these changes aggravate with the deterioration of cognitive impairment.4. Combining QEEG analysis and routine EEG technology, this study confirmed that in late-onset PD, both PDD and PD-MCI patients have relative theta wave frequencies increase in local regions and affected brain area distribute diffusely, mainly for the brain part associated with cognitive function. The theta relatively wave frequencies increased frontal zone is especially associated with PD cognitive impairment, joint GTE scale is helpful for PD cognitive impairment early diagnosis.5.The present study explored the correlation between cognitive dysfunction and brain activities change in different regions for the first time by routine EEG combined QEEG in PD without cognitive impairment.By using QEEG, we confirmed that EEG activity of early-onset PD without cognitive impairment in early stage tend to appear diffuse slow waves,and showed the existence of local beta relative band power significantly decrease,and areas of the brain affected are relatively dispersive which including bilateral occipital area, bilateral parietal area, bilateral post-temporal area, left central area, left frontal area. And the beta coherence coefficient increased in temporal area and frontal area. Additionally, beta relative band power in right temporal area was related to the severity of disease.But no change was found in late-onset PD.6. Although our study confirmed that compared with normal healthy people, the PD-MCI patients are more likely to have REM sleep disorder, but it can’t be clear that REM sleep disorder is associated with cognitive function without large sample research.7.This is a domestic leading research on taking the advantage of QEEG to observe its application value of judging the of Madopar drug efficacy,aimed to investigate EEG changes characteristics in PD patients without cognitive impairment and provide a new assessment angle of means to the early diagnosis of PD. We found that the motor symptoms improved significantly in PD group than control group but no significant difference was found between the two QEEG indicators. Small sample size in this part research and lack of normal control group resulted in a decline in test power. Thus, a well designed further study with large sample is required to explore the possibility of EEG analysis technology in assisting judging the of Madopar drug efficacy. At present, there is no similar research in domestic.8. EEG analysis technology is a sensitive markers for early Diagnosis of Parkinson’s Disease Complicated with Cognitive Impairment and without Cognitive Impairment. |
