The cognitive impairment of type 2 diabetes patients caused by long-term metabolic disorders has been the current focus of attention. In order to find the related electroencephalogram (EEG) characteristics to the mild cognitive impairment (MCI) of diabetes patients, this study analyses the EEG synchronization with the method of multi-channel synchronization analysis--S estimator based on phase synchronization. The results showed that the S estimator values in each frequency band of diabetes patients with MCI were almost lower than that of control group. Especially, the S estimator values decreased significantly in the delta and alpha band, which indicated the EEG synchronization decrease. The MoCA scores and S value had a significant positive correlation in alpha band.
Post-stroke cognitive dysfunction is a common complication of stroke, and active rehabilitation therapy can effectively promote the recovery of patients. As a new treatment method, telecognitive rehabilitation is used in rehabilitation treatment of cognitive disorders. Its main technologies include computer-assisted cognitive rehabilitation, virtual reality technology, and artificial intelligence technology. It can use the Internet platform to provide homogeneous treatment, make patients more convenient for cognitive rehabilitation treatment, help to ensure the continuity of rehabilitation treatment, and save medical costs. This article describes the definition of cognitive telerehabilitation, the development and application of cognitive telerehabilitation technology, and summarizes the existing problems. The purpose is to provide a reference for the clinical application of cognitive telerehabilitation in China and future research directions.
Hypoxia and other factors are related to cognitive impairment. Hyperbaric oxygen therapy can improve tissue oxygen supply to improve brain hypoxia. Based on the basic principle of hyperbaric oxygen therapy, hyperbaric oxygen has been widely used in recent years for cognitive impairment caused by stroke, brain injury, neurodegenerative disease, neuroinflammatory disease and metabolic encephalopathy. This article will review the basic mechanism of hyperbaric oxygen, and summarize and discuss the improvement of hyperbaric oxygen therapy on cognitive and brain diseases, in order to provide relevant reference for clinical treatment.
Cerebral small vessel disease refers to a series of clinical, imaging, and pathological syndromes caused by various factors affecting small blood vessels in the brain. Cognitive impairment is one of the most common complications of cerebral small vessel disease. Current researches have found that cognitive impairment is related to various factors such as hypoxia. Hyperbaric oxygen therapy can achieve certain therapeutic effects by improving hypoxia. This article reviews the pathogenesis of cerebral small vessel disease, biomarkers of cerebral small vessel disease, research progress on hyperbaric oxygen therapy for cognitive impairment, and focuses on the research progress of hyperbaric oxygen therapy for mild cognitive impairment and dementia, providing more references for clinical treatment.
Alzheimer's disease (AD) is a typical neurodegenerative disease, which is clinically manifested as amnesia, loss of language ability and self-care ability, and so on. So far, the cause of the disease has still been unclear and the course of the disease is irreversible, and there has been no cure for the disease yet. Hence, early prognosis of AD is important for the development of new drugs and measures to slow the progression of the disease. Mild cognitive impairment (MCI) is a state between AD and healthy controls (HC). Studies have shown that patients with MCI are more likely to develop AD than those without MCI. Therefore, accurate screening of MCI patients has become one of the research hotspots of early prognosis of AD. With the rapid development of neuroimaging techniques and deep learning, more and more researchers employ deep learning methods to analyze brain neuroimaging images, such as magnetic resonance imaging (MRI), for early prognosis of AD. Hence, in this paper, a three-dimensional multi-slice classifiers ensemble based on convolutional neural network (CNN) and ensemble learning for early prognosis of AD has been proposed. Compared with the CNN classification model based on a single slice, the proposed classifiers ensemble based on multiple two-dimensional slices from three dimensions could use more effective information contained in MRI to improve classification accuracy and stability in a parallel computing mode.
Mild cognitive impairment (MCI) is a clinical transition state between age-related cognitive decline and dementia. Researchers can use neuroimaging and neurophysiological techniques to obtain structural and functional information about the human brain. Using this information researchers can construct the brain network based on complex network theory. The literature on graph theory shows that the large-scale brain network of MCI patient exhibits small-world property, which ranges intermediately between Alzheimer's disease and that in the normal control group. But brain connectivity of MCI patients presents topologically structural disorder. The disorder is significantly correlated to the cognitive functions. This article reviews the recent findings on brain connectivity of MCI patients from the perspective of multimodal data. Specifically, the article focuses on the graph theory evidences of the whole brain structural and functional and the joint covariance network disorders. At last, the article shows the limitations and future research directions in this field.
The recurrent neural network architecture improves the processing ability of time-series data. However, issues such as exploding gradients and poor feature extraction limit its application in the automatic diagnosis of mild cognitive impairment (MCI). This paper proposed a research approach for building an MCI diagnostic model using a Bayesian-optimized bidirectional long short-term memory network (BO-BiLSTM) to address this problem. The diagnostic model was based on a Bayesian algorithm and combined prior distribution and posterior probability results to optimize the BO-BiLSTM network hyperparameters. It also used multiple feature quantities that fully reflected the cognitive state of the MCI brain, such as power spectral density, fuzzy entropy, and multifractal spectrum, as the input of the diagnostic model to achieve automatic MCI diagnosis. The results showed that the feature-fused Bayesian-optimized BiLSTM network model achieved an MCI diagnostic accuracy of 98.64% and effectively completed the diagnostic assessment of MCI. In conclusion, based on this optimization, the long short-term neural network model has achieved automatic diagnostic assessment of MCI, providing a new diagnostic model for intelligent diagnosis of MCI.
Objective To systematically review the efficacy of six cognitive interventions on cognitive function of patients with mild cognitive impairment after stroke. Methods The PubMed, EMbase, Cochrane Library, SinoMed, WanFang Data and CNKI databases were electronically searched to collect randomized controlled trials on the effects of non-drug interventions on the cognitive function of patients with mild cognitive impairment after stroke from inception to March 2023. Two reviewers independently screened the literature, extracted data, and assessed the risk of bias of the included studies. Network meta-analysis was then performed using Openbugs 3.2.3 and Stata 16.0 software. Results A total of 72 studies involving 4 962 patients were included. The results of network meta-analysis showed that the following five cognitive interventions improved the cognitive function of stroke patients with mild cognitive impairment: cognitive control intervention (SMD=−1.28, 95%CI −1.686 to −0.90, P<0.05) had the most significant effect on the improvement of cognitive function, followed by computer cognitive training (SMD=−1.02, 95%CI −1.51 to −0.53, P<0.05), virtual reality cognitive training (SMD=−1.20, 95%CI −1.78 to −0.62, P<0.05), non-invasive neural regulation (SMD=−1.09, 95%CI −1.58 to −0.60, P<0.05), and cognitive stimulation (SMD=−0.94, 95%CI −1.82 to −0.07, P<0.05). Conclusion Five cognitive interventions are effective in improving cognitive function for stroke patients with mild cognitive impairment, among which cognitive control intervention is the most effective. Due to the limited quantity and quality of the included studies, more high-quality studies are needed to verify the above conclusion.
Chemotherapy-related cognitive impairment (CRCI) is one of the treatment-related side effects in cancer patients, which can reduce patients’ participation in medical decision-making and treatment, seriously affecting their daily function and quality of life. This article reviews the definition, research status, and influencing factors of CRCI in lung cancer patients, in order to provide basis and ideas for the subsequent evaluation and management of CRCI in lung cancer patients, and promote the optimization and improvement of the overall rehabilitation process of lung cancer patients.
Post-stroke cognitive impairment (PSCI) is the most common dysfunction after stroke, which seriously affects patients’ quality of life and survival time. To strengthen the management and prevention of PSCI, the European Stroke Organization and the European Academy of Neurology jointly developed the guidelines for PSCI in 2021. This paper introduces the background, compilation method and structure, management suggestions and expert consensus of PSCI, the next research direction, etc. Compared with the current prevention and treatment measures of PSCI in China, it aims to provide methodological reference for Chinese scholars to develope PSCI guidelines and reference evidence for clinical prevention and treatment of PSCI.