The role of cognitive event-related potentials in executive dysfunction

Impact of Cardiac Autonomic Dysfunction on Cognitive Event-Related Potential in Type 2 Diabetes Mellitus Patients: A Cross-Sectional Study

Introduction

Type 2 diabetes mellitus (T2DM) is a chronic metabolic condition that is responsible for various long-term complications. Cognitive impairment is one of the most common complications, but the underlying mechanisms are still undetermined. The autonomic imbalance is a major cause for CVS morbidity in T2DM which could also potentially affect cognition. But there is sparse data available in the literature to prove the association between autonomic dysfunction and cognitive impairment.

Methodology

We recruited 40 T2DM patients and 40 healthy controls. The assessment of cognitive functions was done by cognitive P300 event-related potential (ERP) and MoCA. Heart rate variability (HRV) was done to assess autonomic function.

Results

The P300 ERP latency in Fz, Cz and Pz sites was significantly prolonged in T2DM patients (P < 0.001). We found moderate correlation is present between P300 latency and total power (r = -0.466, P < 0.01) and LFnu (r = -0.423, P < 0.01) in T2DM patients. The total power and HbA1C show independent association with P300 latency after adjustment for confounding factors like age and duration of diabetes (P < 0.05).

Conclusion

As the incidence of Alzheimer's disease is rising among T2DM patients increasing their dependency, making necessary lifestyle measures at earliest to improve autonomic balance may prevent or delay the onset of cognitive decline and alleviate its consequences and improve the quality of life in T2DM patients.

A combination of P300 and eye movement data improves the accuracy of auxiliary diagnoses of depression

BACKGROUND

Exploratory eye movements (EEMs) and P300 are often used to facilitate the clinical diagnosis of depression. However, There were few studies using the combination of EEMs and P300 to build a model for detecting depression and predicting a curative effect.

METHODS

Sixty patients were recruited for 2 groups: high frequency repetitive transcranial magnetic stimulation(rTMS) combined with paroxetine group and simple paroxetine group. Clinical efficacy was evaluated by the Hamilton Depression scale-24(HAMD-24), EEMs and P300. The classification model of the auxiliary diagnosis of depression and the prediction model of the two treatments were developed based on a machine learning algorithm.

RESULTS

The classification model with the greatest accuracy for patients with depression and healthy controls was 95.24% (AUC = 0.75, recall = 1.00, precision = 0.95, F1-score = 0.97). The root mean square error (RMSE) of the model for predicting the efficacy of high frequency rTMS combined with paroxetine was 3.54 (MAE [mean absolute error] = 2.56, R² = -0.53). The RMSE of the model for predicting the efficacy of paroxetine was 4.97 (MAE = 4.00, R² = -0.91).

CONCLUSION

Based on the machine learning algorithm, P300 and EEMs data was suitable for modeling to distinguish depression patients and healthy individuals. However, it was not suitable for predicting the efficacy of high frequency rTMS combined with paroxetine or to predict the efficacy of paroxetine.

Can P300 aid in the differential diagnosis of unipolar disorder versus bipolar disorder depression? A meta-analysis of comparative studies

BACKGROUND

It is difficult to distinguish between bipolar disorder (BD) and unipolar disorder (UD) depression. Given the different pattern of cognitive impairments between BD and UD, P300 is potentially useful for the differential diagnosis. This meta-analysis was performed to estimate the extent of difference in P300 in patients with BD versus UD depression.

METHODS

Studies comparing P300 between depressed BD and UD patients with or without healthy controls (HCs) were retrieved from major English and Chinese databases. Studies with BD and UD samples that were comparable in terms of age, gender, and depression severity, were rated as having high quality. Standardized mean differences (SMDs) of P300 latency and amplitude were calculated.

RESULTS

In total, eight studies with a total of 397 depressed BD patients, 390 depressed UD patients, and 497 HCs, were included. Among included studies, six were rated as having good quality and three followed BD (n = 146) and UD (n = 144) patients during remission. BD patients had significantly longer P300 latency than UD patients during major depressive episode [SMD (95%CI): 0.580 (0.309, 0.850)] and remission [SMD (95%CI): 1.583 (1.322, 1.844)]. Compared to HCs, remitted BD patients still had significantly longer P300 latency [SMD (95%CI): 0.857 (0.059, 1.656)] but P300 latency of remitted UD patients had decreased to normal [SMD (95%CI): 0.536 (-0.272, 1.343)].

LIMITATIONS

Sample sizes of depressed and remitted patients with BD and UD of included studies are small.

CONCLUSIONS

P300 latency can be used as an auxiliary diagnostic marker for differentiating BD from UD depression.

Event-Related Potentials in Parkinson’s Disease Patients with Visual Hallucination

Using neuropsychological investigation and visual event-related potentials (ERPs), we aimed to compare the ERPs and cognitive function of nondemented Parkinson's disease (PD) patients with and without visual hallucinations (VHs) and of control subjects. We recruited 12 PD patients with VHs (PD-H), 23 PD patients without VHs (PD-NH), and 18 age-matched controls. All subjects underwent comprehensive neuropsychological assessment and visual ERPs measurement. A visual odd-ball paradigm with two different fixed interstimulus intervals (ISI) (1600 ms and 5000 ms) elicited visual ERPs. The frontal test battery was used to assess attention, visual-spatial function, verbal fluency, memory, higher executive function, and motor programming. The PD-H patients had significant cognitive dysfunction in several domains, compared to the PD-NH patients and controls. The mean P3 latency with ISI of 1600 ms in PD-H patients was significantly longer than that in controls. Logistic regression disclosed UPDRS-on score and P3 latency as significant predictors of VH. Our findings suggest that nondemented PD-H patients have worse cognitive function and P3 measurements. The development of VHs in nondemented PD patients might be implicated in executive dysfunction with altered visual information processing.