Cognitive Scale Research Articles

Enhancing identification performance of cognitive impairment high-risk based on a semi-supervised learning method

BackgroundCognitive assessment plays a pivotal role in the early detection of cognitive impairment, particularly in the prevention and management of cognitive diseases such as Alzheimer’s and Lewy body dementia. Large-scale screening relies heavily on cognitive assessment scales as primary tools, with some low sensitivity and others expensive. Despite significant progress in machine learning for cognitive function assessment, its application in this particular screening domain remains underexplored, often requiring labor-intensive expert annotations. AimsThis paper introduces a semi-supervised learning algorithm based on pseudo-label with putback (SS-PP), aiming to enhance model efficiency in predicting the high risk of cognitive impairment (HR-CI) by utilizing the distribution of unlabeled samples. DataThe study involved 189 labeled samples and 215,078 unlabeled samples from real world. A semi-supervised classification algorithm was designed and evaluated by comparison with supervised methods composed by 14 traditional machine-learning methods and other advanced semi-supervised algorithms. ResultsThe optimal SS-PP model, based on GBDT, achieved an AUC of 0.947. Comparative analysis with supervised learning models and semi-supervised methods demonstrated an average AUC improvement of 8% and state-of-art performance, repectively. ConclusionThis study pioneers the exploration of utilizing limited labeled data for HR-CI predictions and evaluates the benefits of incorporating physical examination data, holding significant implications for the development of cost-effective strategies in relevant healthcare domains.

Clinical study of chemotherapy-related cognitive impairment in patients with non-Hodgkin lymphoma.

Chemotherapy for malignant tumors can cause brain changes and cognitive impairment, leading to chemotherapy-induced cognitive impairment (CICI). Current research on CICI has focused on breast cancer and Hodgkin's lymphoma. Whether patients with non-Hodgkin's lymphoma (NHL) undergoing chemotherapy have cognitive impairment has not been fully investigated. To investigate whether NHL patients undergoing chemotherapy had cognitive impairments. The study included 100 NHL patients who were required to complete a comprehensive psychological scale including the Brief Psychiatric Examination Scale (MMSE) at two time points: before chemotherapy and within 2 wk of two chemotherapy courses. A language proficiency test (VFT), Symbol Number Pattern Test (SDMT), Clock Drawing Test (CDT), Abbreviated Daily Cognition Scale (ECog-12), Prospective and Retrospective Memory Questionnaire, and Karnofsky Performance Status were used to assess cognitive changes before and after chemotherapy. The VFT scores for before treatment (BT) and after treatment (AT) groups were 45.20 ± 15.62, and 42.30 ± 17.53, respectively (t -2.16, P < 0.05). The CDT scores were 8 (3.5-9.25) for BT and 7 (2.5-9) for AT groups (Z -2.1, P < 0.05). Retrospective memory scores were 13.5 (9-17) for BT and 15 (13-18) for AT (Z -3.7, P < 0.01). The prospective memory scores were 12.63 ± 3.61 for BT and 14.43 ± 4.32 for AT groups (t -4.97, P < 0.01). The ECog-12 scores were 1.71 (1.25-2.08) for BT and 1.79 (1.42-2.08) for AT groups (Z -2.84, P < 0.01). The SDMT and MMSE values did not show a significant difference between BT and AT groups. Compared to the AT group, the BT group showed impaired language, memory, and subjective cognition, but objective cognition and execution were not significantly affected.

The evolution of subjective cognition after meditation training in older people: a secondary analysis of the three-arm age-well randomized controlled trial

ABSTRACT Aging is associated with cognitive changes, even in the absence of brain pathology. This study aimed to determine if meditation training, by comparison to active and passive control groups, is linked to changes in the perception of cognitive functioning in older adults. One hundred thirty-four healthy older participants from the Age-Well Randomized Clinical Trial were included: 45 followed a meditation training, 45 a non-native language training and 44 had no intervention. Subjective cognition was assessed at baseline and following the 18-month intervention period. Perception of attentional efficiency was assessed using internal and external Attentional Style Questionnaire (ASQ) subscale scores. Perception of global cognitive capacities was measured via the total score of Cognitive Difficulties Scale (CDS). Deltas ([posttest minus pretest scores]/standard deviation at pretest) were calculated for the analyses. Generalized mixed effects models controlling for age, sex, education and baseline scores revealed that meditation training decreased the vulnerability score toward external distractors measured by the ASQ compared to non-native language training. However, no between-groups differences on ASQ internal or CDS total scores were observed. Results suggest a beneficial effect of meditation practice on perceived management of external distracting information in daily life. Meditation training may cultivate the ability to focus on specific information (e.g., breath) and ignore stimulation from other kinds of stimuli (e.g., noise).

Measurement invariance of the Suicide Cognitions Scale-Revised (SCS-R).

The Suicide Cognitions Scale-Revised (SCS-R) is a unidimensional measure of suicidal cognitions theorized to assess the suicide belief system. Several solutions have been proposed for the Suicide Cognitions Scale and SCS-R (e.g., bifactor model with two specific factors, bifactor model with two specific factors, three correlated factors model). Research indicates the endorsement of thoughts of suicide and suicide-related cognitions varies across demographics. Thus, the current investigation tested the measurement invariance (MI) of the SCS-R across gender, race, and sexual orientation within these proposed solutions and a unidimensional model. A national sample of N = 10,625 adults completed an online survey that included the SCS-R and self-report measures of demographics. Results indicated that the bifactor model with three specific factors, the bifactor model with two specific factors, and the three correlated factors models achieved scalar invariance across gender, race, and sexual orientation; a unidimensional model was not scalar invariant by gender. Tests of latent mean differences revealed significant differences in the general factor (i.e., suicidal belief system) and the specific unlovability, unbearability, and unsolvability factors between a few demographic groups. Implications for theory, measurement, and modeling are discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Machine learning for predicting cognitive decline within five years in Parkinson's disease: Comparing cognitive assessment scales with DAT SPECT and clinical biomarkers.

Parkinson's disease (PD) is an age-related neurodegenerative condition characterized mostly by motor symptoms. Although a wide range of non-motor symptoms (NMS) are frequently experienced by PD patients. One of the important and common NMS is cognitive impairment, which is measured using different cognitive scales. Monitoring cognitive impairment and its decline in PD is essential for patient care and management. In this study, our goal is to identify the most effective cognitive scale in predicting cognitive decline over a 5-year timeframe initializing clinical biomarkers and DAT SPECT. Machine Learning has previously shown superior performance in image and clinical data classification and detection. In this study, we propose to use machine learning with different types of data, such as DAT SPECT and clinical biomarkers, to predict PD-CD based on various cognitive scales. We collected 330 DAT SPECT images and their clinical data in baseline, years 2,3,4, and 5 from Parkinson's Progression Markers Initiative (PPMI). We then designed a 3D Autoencoder to extract deep radiomic features (DF) from DAT SPECT images, and we then concatenated it with 17 clinical features (CF) to predict cognitive decline based on Montreal Cognitive Assessment (MoCA) and The Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS-I). The utilization of MoCA as a cognitive decline scale yielded better performance in various years compared to MDS-UPDRS-I. In year 4, the application of the deep radiomic feature resulted in the highest achievement, with a cross-validation AUC of 89.28, utilizing the gradient boosting classifier. For the MDS-UPDRS-I scale, the highest achievement was obtained by utilizing the deep radiomic feature, resulting in a cross-validation AUC of 81.34 with the random forest classifier. The study findings indicate that the MoCA scale may be a more effective predictor of cognitive decline within 5 years compared to MDS-UPDRS-I. Furthermore, deep radiomic features had better performance compared to sole clinical biomarkers or clinical and deep radiomic combined. These results suggest that using the MoCA score and deep radiomic features extracted from DAT SPECT could be a promising approach for identifying individuals at risk for cognitive decline in four years. Future research is needed to validate these findings and explore their utility in clinical practice.

Dynamic functional network connectivity in patients with a mismatch between white matter hyperintensity and cognitive function.

White matter hyperintensity (WMH) in patients with cerebral small vessel disease (CSVD) is strongly associated with cognitive impairment. However, the severity of WMH does not coincide fully with cognitive impairment. This study aims to explore the differences in the dynamic functional network connectivity (dFNC) of WMH with cognitively matched and mismatched patients, to better understand the underlying mechanisms from a quantitative perspective. The resting-state functional magnetic resonance imaging (rs-fMRI) and cognitive function scale assessment of the patients were acquired. Preprocessing of the rs-fMRI data was performed, and this was followed by dFNC analysis to obtain the dFNC metrics. Compared the dFNC and dFNC metrics within different states between mismatch and match group, we analyzed the correlation between dFNC metrics and cognitive function. Finally, to analyze the reasons for the differences between the mismatch and match groups, the CSVD imaging features of each patient were quantified with the assistance of the uAI Discover system. The 149 CSVD patients included 20 cases of "Type I mismatch," 51 cases of Type I match, 38 cases of "Type II mismatch," and 40 cases of "Type II match." Using dFNC analysis, we found that the fraction time (FT) and mean dwell time (MDT) of State 2 differed significantly between "Type I match" and "Type I mismatch"; the FT of States 1 and 4 differed significantly between "Type II match" and "Type II mismatch." Correlation analysis revealed that dFNC metrics in CSVD patients correlated with executive function and information processing speed among the various cognitive functions. Through quantitative analysis, we found that the number of perivascular spaces and bilateral medial temporal lobe atrophy (MTA) scores differed significantly between "Type I match" and "Type I mismatch," while the left MTA score differed between "Type II match" and "Type II mismatch." Different mechanisms were implicated in these two types of mismatch: Type I affected higher-order networks, and may be related to the number of perivascular spaces and brain atrophy, whereas Type II affected the primary networks, and may be related to brain atrophy and the years of education.

Alterations of resting-state network dynamics in Alzheimer's disease based on leading eigenvector dynamics analysis.

Alzheimer's disease (AD) is a neurodegenerative disease, and mild cognitive impairment (MCI) is considered a transitional stage between healthy aging and dementia. Early detection of MCI can help slow down the progression of AD. At present, there are few studies exploring the characteristics of abnormal dynamic brain activity in AD. This article uses a method called leading eigenvector dynamics analysis (LEiDA) to study resting-state functional magnetic resonance imaging (rs-fMRI) data of AD, MCI, and cognitively normal (CN) participants. By identifying repetitive states of phase coherence, intergroup differences in brain dynamic activity indicators are examined, and the neurobehavioral scales were used to assess the relationship between abnormal dynamic activities and cognitive function. The results showed that in the indicators of occurrence probability and lifetime, the globally synchronized state of the patient group decreased. The activity state of the limbic regions significantly detected the difference between AD and the other two groups. Compared to CN, AD and MCI have varying degrees of increase in default and visual region activity states. In addition, in the analysis related to the cognitive scales, it was found that individuals with poorer cognitive abilities were less active in the globally synchronized state and more active in limbic region activity state and visual region activity state. Taken together, these findings reveal abnormal dynamic activity of resting-state networks in patients with AD and MCI, provide new insights into the dynamic analysis of brain networks, and contribute to a deeper understanding of abnormal spatial dynamic patterns in AD patients.NEW & NOTEWORTHY Alzheimer's disease (AD) is a neurodegenerative disease, but few studies have explored the characteristics of abnormal dynamic brain activity in AD patients. Here, our report reveals the abnormal dynamic activity of the patients' resting-state network, providing new insights into the dynamic analysis of brain networks and helping to gain a deeper understanding of the abnormal spatial dynamic patterns in AD patients.

A survey of the prevalence and patterns of neuropsychological assessment practices across epilepsy surgery centers in India: Toward establishing a national guideline.

Neuropsychology plays an important role in optimizing epilepsy management, but there are no practice guidelines for low- and middle-income countries with emerging services. The National Epilepsy Surgery Support Activity Network (NESSAN), a national working group that supports and optimizes epilepsy surgery programs in India, explored the present status of pre- and post epilepsy surgery neuropsychological assessment practices across India as an initial step in developing national evidence-based test guidelines. An online survey was conducted using two questionnaires, one for neurologists and the second for neuropsychologists and speech-language pathologists working in epilepsy surgery centers. The questions to neurologists covered the setting, description, and nature of the neuropsychology services provided for adults and children as part of the epilepsy surgery program, and their perceptions about the importance and indications for neuropsychological assessment in epilepsy surgery. The questions to neuropsychologists inquired about their qualifications and training, pre- and postsurgical assessment procedures, and domain-specific cognitive tests and scales for mood, quality of life, and language evaluations. Forty-three centers responded, and neuropsychology services were available at three fourth of the centers, but a dedicated full-time neuropsychologist was available in only 16% of centers. Ninety percent of the neurologists considered neuropsychological evaluation an indispensable part of presurgical evaluation. However, only a few of them believed that the results influenced their decision about the extent of resection and ruling against surgery. The survey found considerable heterogeneity in terms of qualifications and training of neuropsychologists, evaluation procedures, test protocols, and normative data that will need to be harmonized to ensure uniform practice across the country. We believe that the results from this survey provide a road map for implementing measures to minimize existing inadequacies and harmonize neuropsychology services in India and as well as in other countries with emerging neuropsychology services. PLAIN LANGUAGE SUMMARY: Neuropsychological assessment is an integral part of the pre- and post epilepsy surgery evaluations. In India, the National Epilepsy Surgery Support Activity Network (NESSAN), a body of multidisciplinary professionals, conducted a survey to examine existing neuropsychology practices. The responses from 43 centers across the country revealed considerable heterogeneity in tests and few trained and qualified neuropsychologists. In low- and middle-income countries (LMIC) with emerging neuropsychology services, there is a need to have uniform test protocols, specialized training, and guidelines for optimizing neuropsychology services across all the epilepsy surgery centers.

Anticholinergic burden and health-related quality of life among adult patients in a resource-limited setting: a cross-sectional study.

Anticholinergic medications are now widely acknowledged for their unfavorable risk-to-benefit profile owing to their adverse effects. Health-related quality of life (HRQoL) is commonly regarded as a crucial person-centered outcome. This study aimed to investigate the association between anticholinergic burden and HRQoL in hospitalized and ambulatory patients seen in Ethiopia. This cross-sectional study utilized a questionnaire and medical records to collect data from a convenience sample of adult patients attending both inpatient wards and ambulatory clinic of University of Gondar Comprehensive Specialized Hospital between April and September 2022. Anticholinergic burden was measured by anticholinergic cognitive burdens scale (ACBS), while HRQoL was measured using EQ5D-index (Euroqol-5 dimensions-5-Levels index) and EQ5D-VAS (visual analogue scale). Linear regression was used to assess the influence of high anticholinergic burden (ACBS score ≥ 3) on EQ5D-index and EQ5D-VAS, with adjustments made for sociodemographic and clinical confounders. A total of 828 patients participated in this study (median (IQR) age was 45.0 (30, 60) and 55.9% were female). On multiple linear regression analysis, high anticholinergic burden was associated with a statistically significant decline in HRQoL, as evidenced by reductions in both EQ5D index (- 0.174 (- 0.250, - 0.098)) and EQ5D-VAS scores (- 9.4 (- 13.3, - 5.2)). A significant association between high anticholinergic burden and diminished HRQoL was found among a relatively younger cohort in a resource-limited setting, even after adjustment for important confounding variables. Clinicians should be cognizant of the cumulative impact of anticholinergic burden on HRQoL outcomes and strive to minimize anticholinergic burden.

Supplemental Material for Measurement Invariance of the Suicide Cognitions Scale–Revised (SCS-R)

Supplemental Material for Measurement Invariance of the Suicide Cognitions Scale–Revised (SCS-R)

Construction and Validation of a Cognitive Engagement Scale and Its Relationship with Ball Movement Sequence Performance in Rhythmic Gymnastics

The research aims to: build and record a measure of cognitive participation among second-year female students at the College of Physical Education and Sports Sciences, University of Baghdad. The researchers used the descriptive approach in the survey style for the research sample. The sample was selected from female students and divided into: (10) female students for the survey sample, and (80) female students for the construction and codification sample. The data were statistically analyzed by the researchers using SPSS, the T-test for independent and correlated samples, Pearson's simple correlation coefficient, Cronbach's alpha, Chi-square, and Spearman-Brown. They were recruited for the samples. The study concluded that constructing a measure of cognitive participation for students in the second stage could be applied through the ease and difficulty of its expressions that are appropriate to the research sample, as well as the grades and levels that were reached, which showed that the sample fell within the rating (good and acceptable), and on the other hand the sample was characterized by participation. Cognitive through the results of the scale and its four axes. In conclusion, cognitive participation plays a positive role in performing the ball movement sequence in rhythmic gymnastics.

Association between reduced plasma BDNF concentration and MMSE scores in both chronic schizophrenia and mild cognitive impairment

Reduced brain derived neurotrophic factor (BDNF) concentration is reported to be associated with a cognitive decline in schizophrenia, depending on the stage of the disease. Aim of the study was to examine the possible association between plasma BDNF and cognitive decline in chronic stable schizophrenia and mild cognitive impairment (MCI). The study included 123 inpatients of both sexes with schizophrenia, 123 patients with MCI and 208 healthy control subjects. Cognitive abilities were assessed using mini mental state examination (MMSE), Clock Drawing test (CDT) and cognitive subscale of the Positive and Negative Syndrome Scale (PANSS). Plasma BDNF concentration was determined using ELISA. BDNF concentration was lower in patients with schizophrenia and MCI compared to age-matched healthy controls and was similar in carriers of different BDNF Val/66Met genotypes. The MMSE and CDT scores were lower in patients with schizophrenia compared to healthy controls and subjects with MCI. Reduced plasma BDNF was significantly associated with lower MMSE scores in all subjects. BDNF concentration in patients with schizophrenia was not affected by clinical and demographic factors. BDNF Val66Met polymorphism was not associated with the MMSE scores in all participants. Further studies should include longitudinal follow-up and other cognitive scales to confirm these results and offer cognition-improving strategies to prevent cognitive decline in chronic schizophrenia.

Relationship between burden of cerebral small vessel disease on imaging and cognitive impairment of COPD patients

ObjectiveThis study aims to explore the relationship between the burden of cerebral small vessel disease (CSVD) on imaging and cognitive impairment (CI) in patients with chronic obstructive pulmonary disease (COPD). MethodsThe study included 118 COPD patients admitted to Changxing People’s Hospital between July 2020 and July 2023. All patients received a 1.5 T MRI of the brain and pulmonary function tests. A cognitive function assessment was conducted via the Montreal Cognitive Assessment (MoCA) scale, and patients were divided into two groups. The relationship between the MoCA and CSVD burden score was analyzed by Pearson correlation, and to identify risk factors, multiple logistic regression analysis was performed. ResultsThe study showed a negative correlation between the MoCA and CSVD burden score in COPD patients (r=-0.479, P<0.001). Multiple logistic regression analysis found that age (OR=2.264, 95 % CI: 1.426–3.596, P<0.001), COPD grade (OR=3.139, 95 % CI: 2.012–4.898, P<0.001), as well as CSVD burden score (OR=5.336, 95 % CI: 1.191–23.900, P<0.001) were the independent risk factors for CI in COPD patients (P<0.05). ConclusionWhen screening for cognitive impairment in COPD patients, the CSVD burden score can be used in conjunction with cognitive assessment scales to make judgments.

Cognitive Distortions as Barriers to Seeking Smoking Cessation Treatment: A Comparative Study.

Background/Objectives: Despite the availability of effective pharmacotherapy and evidence-based treatments, a substantial proportion of smokers do not seek treatment. This study aims to explore the cognitive distortions associated with not seeking evidence-based smoking cessation treatment and to identify cognitive barriers. Methods: The research conducted in Istanbul between October and December 2017 employs a cross-sectional design and includes two groups: a treatment-seeking group comprising 156 patients diagnosed with tobacco use disorder and a non-treatment seeking group of 78 patients with tobacco use disorder who had never sought professional help for smoking cessation. A comprehensive data collection process was used, including sociodemographic information, cognitive distortion assessment using the cognitive distortions scale, a smoking-related cognitive distortions interview and the Fagerström Test for Nicotine Dependence. Results: While no significant sociodemographic differences were observed between the treatment-seeking and non-treatment-seeking groups, the study found that higher nicotine dependence was associated with a higher likelihood of seeking treatment. The treatment-seeking group displayed significantly higher levels of "all-or-nothing thinking" cognitive distortions related to smoking and smoking cessation. Conversely, the non-treatment-seeking group exhibited elevated levels of cognitive distortions such as "labeling", "mental filtering", "should statements" and "minimizing the positive" regarding receiving smoking cessation treatment. Conclusions: Understanding the cognitive distortions associated with treatment-seeking behavior for tobacco use disorder is crucial for developing targeted public-based interventions, public service announcements for tobacco use prevention and encouraging individuals to seek evidence-based treatment. Addressing these cognitive distortions can also potentially enhance the effectiveness of smoking cessation programs and reduce the global burden of tobacco-related diseases and mortality.

Emotional awareness for self and others and empathic abilities in clinical depression during acute illness and recovery

BackgroundThe present longitudinal investigation had two major goals. First, we intended to clarify whether depressed patients are characterized by impairments of emotional awareness for the self and the other during acute illness and whether these impairments diminish in the course of an inpatient psychiatric treatment program. Previous research based on the performance measure Levels of Emotional Awareness Scale (LEAS) provided inconsistent findings concerning emotional self-awareness in clinical depression. Second, we investigated whether cognitive and affective empathic abilities change from acute illness to recovery in depressed patients.MethodsFifty-eight depressed patients were tested on admission and after 6–8 weeks of inpatient psychiatric treatment. A sample of fifty-three healthy individuals were also examined twice at an interval of 6–8 weeks. The LEAS and the Interpersonal Reactivity Index (IRI) were administered to assess emotional awareness and empathic abilities. Written texts were digitalized and then analyzed using the electronic scoring program geLEAS, the German electronic Levels of Emotional Awareness Scale.ResultsDepressed patients reported more depressive symptoms than healthy controls and less severe depressive symptomatology at time 2 compared to time 1. Independent of time, depressed individuals tended to show lower geLEAS self scores and had lower geLEAS other scores than healthy individuals. Depressed patients showed higher personal distress scores than healthy individuals at both measurement times. No group differences were observed for the cognitive empathy scales of the IRI (perspective taking and fantasy) and empathic concern, but empathic concern decreased significantly in depressed patients from time 1 to time 2. Empathic abilities as assessed by the IRI were not significantly correlated with emotional awareness for others, neither in the whole sample, nor in the patient and control subsample.ConclusionsDepressed patients seem to be characterized by impairments in emotional awareness of others during acute illness and recovery, but they also tend to show deficits in emotional self-awareness compared to healthy individuals. Self-reported cognitive empathic abilities seem to be at normal levels in depressed patients, but their heightened self-focused affective empathy may represent a vulnerability factor for depressive disorders.

Engaging Mood Brain Circuits with Psilocybin (EMBRACE): a study protocol for a randomized, placebo-controlled and delayed-start, neuroimaging trial in depression

BackgroundMajor depressive disorder (MDD) is a leading cause of disability worldwide across domains of health and cognition, affecting overall quality of life. Approximately one third of individuals with depression do not fully respond to treatments (e.g., conventional antidepressants, psychotherapy) and alternative strategies are needed. Recent early phase trials suggest psilocybin may be a safe and efficacious intervention with rapid-acting antidepressant properties. Psilocybin is thought to exert therapeutic benefits by altering brain network connectivity and inducing neuroplastic changes that endure for weeks post-treatment. Although early clinical results are encouraging, psilocybin’s acute neurobiological effects on neuroplasticity have not been fully investigated. We aim to examine for the first time how psilocybin acutely (intraday) and subacutely (weeks) alters functional brain networks implicated in depression.MethodsFifty participants diagnosed with MDD or persistent depressive disorder (PDD) will be recruited from a tertiary mood disorders clinic and undergo 1:1 randomization into either an experimental or control arm. Participants will be given either 25 mg psilocybin or 25 mg microcrystalline cellulose (MCC) placebo for the first treatment. Three weeks later, those in the control arm will transition to receiving 25 mg psilocybin. We will investigate whether treatments are associated with changes in arterial spin labelling and blood oxygenation level-dependent contrast neuroimaging assessments at acute and subacute timepoints. Primary outcomes include testing whether psilocybin demonstrates acute changes in (1) cerebral blood flow and (2) functional brain activity in networks associated with mood regulation and depression when compared to placebo, along with changes in MADRS score over time compared to placebo. Secondary outcomes include changes across complementary clinical psychiatric, cognitive, and functional scales from baseline to final follow-up. Serum peripheral neurotrophic and inflammatory biomarkers will be collected at baseline and follow-up to examine relationships with clinical response, and neuroimaging measures.DiscussionThis study will investigate the acute and additive subacute neuroplastic effects of psilocybin on brain networks affected by depression using advanced serial neuroimaging methods. Results will improve our understanding of psilocybin’s antidepressant mechanisms versus placebo response and whether biological measures of brain function can provide early predictors of treatment response.Trial registrationClinicalTrials.gov Identifier: NCT06072898. Registered on 6 October 2023.

A Comparative Study on Cognitive Assessment in Cerebellar and Supratentorial Stroke.

This study aims to understand the cognitive profiles of cerebellar infarction patients and compare them to those with supratentorial infarctions, particularly frontal infarctions. This current study also aims to find reliable assessment tools for detecting cognitive impairment in cerebellar infarction patients. A total of fifty cerebellar infarction patients, sixty supratentorial infarction patients, and thirty-nine healthy controls were recruited. The Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Addenbrooke's Cognitive Examination III (ACE-III), and Cerebellar Cognitive Affective Syndrome scale (CCAS-s) were used to assess global cognitive function. An extensive neuropsychological assessment battery was also tested to evaluate the characteristics of each cognitive domain. To assess the features of cognitive function, a comprehensive neuropsychological evaluation tool was also utilized. The cerebral infarction patients demonstrated cognitive impairment comparable to those with frontal infarcts, notably characterized by disturbance in attention and executive function. However, the degree of cognitive impairment was comparatively milder in cerebellar infarction patients. Furthermore, the patients in the cerebellar group had worse scores in the ACE-III and CCAS-s compared to healthy controls. The two assessments also demonstrated a significant area under the curve values, indicating their effectiveness in distinguishing cognitive impairment in cerebellar infarctions. In conclusion, cognitive impairment in a cerebellar infarction resembles frontal lobe dysfunction but is generally mild. It can be accurately assessed using the ACE-III and CCAS-s scales.

Efficacy and safety of acupuncture for cognitive impairment in Alzheimer's disease: a systematic review and meta-analysis.

To systematically evaluate the efficacy of acupuncture in the treatment of cognitive impairment in Alzheimer's disease (AD) by meta-analysis, in order to provide evidence-based evidence for the application of acupuncture therapy in the clinical process of AD. From the establishment of the database to December 31, 2022, China Biomedical Literature Database (CBM), China National Knowledge Network (CNKI), VIP database, WanFang Database, Pubmed, Embase and Cochrane Library Database were systematically searched. To collect published randomized controlled clinical trials (RCTS) of acupuncture in the treatment of cognitive impairment in AD. The subjects in the intervention group were given acupuncture alone or combined with other treatments the same as the control group; the control group received conventional Western medicine treatment. The main outcome indicators of the study were cognitive function assessment of subjects, including: Simple Mental State Examination Scale (MMSE), Assessment of daily Living Ability Scale (ADL), Alzheimer's Disease Cognitive Function Assessment Scale (ADAS-Cog), TCM syndrome score (SDSD), Montreal Cognitive Test (MoCA), Secondary outcome indicators were the occurrence of adverse reactions. Literature screening, data extraction, and quality evaluation of the included literature were performed independently by two researchers, according to bias risk assessment tools recommended in the Cochrane manual. Data were analyzed by RevMan5.3 software. Dichotomous variables were represented by risk ratio (OR) and 95% CI, and continuity variables were represented by mean difference (MD) and 95% CI. For heterogeneity analysis, when P > 0.1 and I 2 ≤ 50%, fixed effect model was applied. When P ≤ 0.1 and I 2 > 50%, the random effects model is applied. A total of 1,172 eligible subjects were included in 18 RCTS, including 595 in the intervention group and 577 in the control group. The results of meta-analysis are as follows: acupuncture intervention group improved MMSE [MD = 1.67, 95% CI (0.94, 2.41), P < 0.00001], ADL [MD = -1.18, 95% CI (-3.09, 0.72), P = 0.22], ADAS-Cog [MD = 3.31, 95% CI (5.84, 0.78), P = 0.01], SDSD [MD = 2.40, 95% CI (3.53, 1.26), P < 0.0001], MoCA [MD = 4.80, 95% CI (3.74, 5.86), P = 0.04] were better than the control group. No serious adverse reactions related to acupuncture were observed in the intervention group, and the incidence and severity of adverse reactions were lower than those in the control group, with statistical significance [OR = 0.17, 95% CI (0.04, 0.67), P = 0.01]. Existing data show that acupuncture therapy has certain advantages in improving cognitive dysfunction and improving self-care ability of patients with Alzheimer's disease. However, due to the small number of RCTS and cases evaluating the efficacy of acupuncture, and the possibility of measurement bias and selectivity bias in included studies, it is still unable to conduct high-intensity demonstration on its effectiveness. Further large-scale, high-quality randomized, double-blind controlled trials are needed to evaluate its efficacy. https://inplasy.com/inplasy-2021-12-0125/, identifier: INPLASY2021120125.

Reliability and validity study of the Chinese version of the Cerebellar Cognitive Affective Syndrome Scale in patients with cerebellar injury.

To preliminarily investigate the reliability and validity of the Chinese version of the Cerebellar Cognitive Affective Syndrome Scale (CCAS scale) in the cerebellar injury population. In this study, 40 patients with cerebellar injury and 39 normal individuals hospitalized in a stroke center were assessed using the Chinese version of the CCAS scale A, MMSE, and PHQ2, and the results were analyzed using content validity, structural validity, internal consistency, inter- rater agreement, and test-retest reliability. The correlation coefficients of semantic fluency, phonemic fluency, category switching, digit span forward, digit span backward, cube, verbal recall, similarities and Go No-Go subscores in the Chinese version of the CCAS scale A were 0.586-0.831 (P ≤ 0.05) with the total score, but there was no significant correlation between the affect and the total score (P = 0.110). The total cognitive score of the Chinese version of the CCAS scale A was correlated with the (r = 0.807, P ≤ 0.01), and the total score of the Chinese version of the CCAS scale A affect was correlated with the total score of PHQ2 (r = 0.884, P ≤ 0.01). The 2 factors were extracted using principal component analysis, and the cumulative variance contribution rate was 59.633%. The factor loadings of each of the corresponding factors were > 0.5, indicating good structural validity of the Chinese version of the CCAS scale A. Cronbach α = 0.827 indicated good internal consistency, and inter-rater reliability (ICC > 0.95) and test-retest reliability (ICC = 0.717-0.895)indicated that the Chinese version of the CCAS scale A had good inter-rater reliability and test-retest reliability. The Chinese version of the CCAS scale A has good reliability and validity in the cerebellar injury population and is useful for screening cerebellar cognitive-emotional syndrome.

Development of a machine learning algorithm to predict the residual cognitive reserve index.

Elucidating the mechanisms by which late-life neurodegeneration causes cognitive decline requires understanding why some individuals are more resilient than others to the effects of brain change on cognition (cognitive reserve). Currently, there is no way of measuring cognitive reserve that is valid (e.g. capable of moderating brain-cognition associations), widely accessible (e.g. does not require neuroimaging and large sample sizes), and able to provide insight into resilience-promoting mechanisms. To address these limitations, this study sought to determine whether a machine learning approach to combining standard clinical variables could (i) predict a residual-based cognitive reserve criterion standard and (ii) prospectively moderate brain-cognition associations. In a training sample combining data from the University of California (UC) Davis and the Alzheimer's Disease Neuroimaging Initiative-2 (ADNI-2) cohort (N = 1665), we operationalized cognitive reserve using an MRI-based residual approach. An eXtreme Gradient Boosting machine learning algorithm was trained to predict this residual reserve index (RRI) using three models: Minimal (basic clinical data, such as age, education, anthropometrics, and blood pressure), Extended (Minimal model plus cognitive screening, word reading, and depression measures), and Full [Extended model plus Clinical Dementia Rating (CDR) and Everyday Cognition (ECog) scale]. External validation was performed in an independent sample of ADNI 1/3/GO participants (N = 1640), which examined whether the effects of brain change on cognitive change were moderated by the machine learning models' cognitive reserve estimates. The three machine learning models differed in their accuracy and validity. The Minimal model did not correlate strongly with the criterion standard (r = 0.23) and did not moderate the effects of brain change on cognitive change. In contrast, the Extended and Full models were modestly correlated with the criterion standard (r = 0.49 and 0.54, respectively) and prospectively moderated longitudinal brain-cognition associations, outperforming other cognitive reserve proxies (education, word reading). The primary difference between the Minimal model-which did not perform well as a measure of cognitive reserve-and the Extended and Full models-which demonstrated good accuracy and validity-is the lack of cognitive performance and informant-report data in the Minimal model. This suggests that basic clinical variables like anthropometrics, vital signs, and demographics are not sufficient for estimating cognitive reserve. Rather, the most accurate and valid estimates of cognitive reserve were obtained when cognitive performance data-ideally augmented by informant-reported functioning-was used. These results indicate that a dynamic and accessible proxy for cognitive reserve can be generated for individuals without neuroimaging data and gives some insight into factors that may promote resilience.