Diagnosis Of Cognitive Impairment Research Articles

EEG biomarkers analysis in different cognitive impairment after stroke: an exploration study

EEG biomarkers analysis in different cognitive impairment after stroke: an exploration study

Comparison of Cognitive Impairment Diagnosis Criteria in Clinical Settings: Conventional vs. Neuropsychological

Comparison of Cognitive Impairment Diagnosis Criteria in Clinical Settings: Conventional vs. Neuropsychological

The cingulate island sign in a mixed memory clinical cohort: Prevalence and diagnostic accuracy

IntroductionVisual rating of the cingulate island sign (CIS) on [18F]fluorodeoxyglucose ([18F]FDG) positron emission tomography (PET) has a high specificity for dementia with Lewy bodies (DLB) in selected cohorts such as DLB versus Alzheimer's disease (AD). In a mixed memory clinical population this study aimed to uncover the prevalence of CIS, the diagnostic accuracy for DLB, and the relationship between CIS and disease severity. MethodsCIS on [18F]FDG-PET was retrospectively assessed with the visual CIS rating scale (CISRs) in 1000 patients with a syndrome diagnosis of mild cognitive impairment (MCI) or dementia with no restrictions in etiological diagnosis. ResultsIn this cohort 24.3 % had a CISRs score ≥1 and 3.5 % had a CISRs score = 4. The prevalence of a CISRs score ≥1 was highest in DLB (74.0 %, n = 57). A CISRs score ≥1 was present in at least 9 % in other diagnostic groups. The prevalence of CIS across disease severities showed no statistically significant difference (p = 0.23). To differentiate DLB from non-DLB the optimal cut-off was a CISRs score ≥1 (balanced accuracy = 77.1 %) in MCI/mild dementia and a CISRs score ≥2 (balanced accuracy = 80.6 %) in moderate/severe dementia. The positive predictive value of a CISRs score = 4 for DLB was 57.7 % in MCI/mild dementia and 33.3 % in moderate/severe dementia. ConclusionThe CISRs is useful in differentiating DLB from other etiologies in a mixed memory clinical population. Balanced accuracy and positive predictive value may vary across disease severities in the population studied.

Structural and microstructural predictors of cognitive decline in deep brain stimulation of subthalamic nucleus in Parkinson’s disease

Background and objectivesThe intricate relationship between deep brain stimulation (DBS) in Parkinson’s disease (PD) and cognitive impairment has lately garnered substantial attention. The presented study evaluated pre-DBS structural and microstructural cerebral patterns as possible predictors of future cognitive decline in PD DBS patients. MethodsPre-DBS MRI data in 72 PD patients were combined with neuropsychological examinations and follow-up for an average of 2.3 years after DBS implantation procedure using a screening cognitive test validated for diagnosis of mild cognitive impairment in PD in a Czech population – Dementia Rating Scale 2. ResultsPD patients who would exhibit post-DBS cognitive decline were found to have, already at the pre-DBS stage, significantly lower cortical thickness and lower microstructural complexity than cognitively stable PD patients. Differences in the regions directly related to cognition as bilateral parietal, insular and cingulate cortices, but also occipital and sensorimotor cortex were detected. Furthermore, hippocampi, putamina, cerebellum and upper brainstem were implicated as well, all despite the absence of pre-DBS differences in cognitive performance and in the position of DBS leads or stimulation parameters between the two groups. ConclusionsOur findings indicate that the cognitive decline in the presented PD cohort was not attributable primarily to DBS of the subthalamic nucleus but was associated with a clinically silent structural and microstructural predisposition to future cognitive deterioration present already before the DBS system implantation.

Cognitive function in different motor subtypes of Parkinson's disease: A systematic review protocol.

As the fastest-growing neurological disorder globally, a better understanding of Parkinson's disease (PD) is needed to improve patient outcomes and reduce the increasing economic and healthcare burden associated with the disease. Whilst classified as a movement disorder, this disease is highly heterogeneous, encompassing a broad range of both motor and non-motor symptoms (NMS). Cognitive impairment, presenting as either mild cognitive impairment or PD-dementia, is one of the most prevalent and disabling NMS. To better understand heterogeneity in PD, researchers have sought to identify subtypes of individuals who share similar symptom profiles. To date, this research has predominantly focused on motor subtyping, with many studies comparing these motor subtypes on non-motor outcomes, such as cognitive impairment. However, despite evidence of a motor-cognitive relationship in healthy aging, findings regarding the presence of a motor-cognitive relationship in PD are inconsistent. In our proposed systematic review, we will investigate motor subtyping studies that have evaluated the relationship between motor and cognitive function in PD. We aim to examine what is currently known about the relationship between motor and cognitive impairment in PD and evaluate the state of the field with respect to the subtyping methods and quality of cognitive assessment tools used. Systematic literature searches will be conducted in PubMed, PsycINFO, CINAHL, Scopus, and Web of Science. Results will be synthesized using meta-analysis and, where meta-analysis is not feasible, narrative synthesis. Despite the preponderance of motor subtyping research in PD, our study will be the first to systematically review evidence regarding the association between motor subtypes and cognitive impairment. Understanding the nature of the motor-cognitive relationship in PD may lead to important insights regarding shared underlying disease pathology, which would have significant implications for early diagnosis, prognosis, and treatment of cognitive impairment in PD.

Prevalence of and Annual Conversion Rates to Mild Cognitive Impairment and Dementia: Prospective, Longitudinal Study of an Essential Tremor Cohort.

Despite recent attention to cognitive impairment in essential tremor, few studies examine rates of conversion to diagnoses of mild cognitive impairment and dementia. Development of dementia in essential tremor is associated with loss of functional ability and a doubling of mortality rate. This prospective, longitudinal study comprehensively reports the prevalence and incidence of, and the annual rates of conversion to, mild cognitive impairment and dementia in an essential tremor cohort. Patients underwent detailed cognitive assessments and were assigned diagnoses of normal cognition, mild cognitive impairment, or dementia. There were 222 patients at baseline (mean age = 79.3 ± 9.7 years), and 177 patients participated in follow-up evaluations at 18, 36, 54, and 72 months (mean years of observation = 5.1 ± 1.7). Data were compared to those of historical controls and Parkinson disease patients. The cumulative prevalence of dementia and average annual conversion rate of mild cognitive impairment to dementia were 18.5% and 12.2%, nearly three times higher than rates in the general population, and approximately one half the magnitude of those reported for Parkinson disease patients. The cumulative prevalence of mild cognitive impairment (26.6%) was almost double that of the general population, but less than that in Parkinson disease populations. We present the most complete exposition of the longitudinal trajectory of cognitive impairment in an essential tremor cohort yet presented. The prevalence of and conversion rates to dementia in essential tremor fall between those associated with the natural course of aging and the more pronounced rates observed in Parkinson disease. ANN NEUROL 2024.

Management of cognitive impairment associated with post-COVID-19 syndrome: recommendations for primary care.

Introduction: Although post-COVID-19 syndrome (PCS) with cognitive impairment is increasingly encountered in primary care, evidence-based recommendations for its appropriate management are lacking. Methods: A systematic literature search evaluating the diagnosis and treatment of cognitive impairment associated with PCS was conducted. Practical recommendations for the management of PCS-associated cognitive impairment in primary care are summarized, based on an evaluation of pharmacological plausibility and clinical applications. Results: Currently, the pathology of cognitive impairment associated with PCS remains unclear with no high-quality data to support targeted interventions. Existing treatment approaches are directed towards symptom relief where counseling on the chronicity of the disease and regular reassessments at 4- to 8-week intervals is considered reasonable. Patients should be informed and encouraged to adopt a healthy lifestyle that centers around balanced nutrition and appropriate physical activities. They may also benefit from the intake of vitamins, micronutrients, and probiotics. The administration of Ginkgo biloba extract could offer a safe and potentially beneficial treatment option. Other non-pharmacological measures include physiotherapy, digitally supported cognitive training, and, if indicated, ergotherapy or speech therapy. In most patients, symptoms improve within 8 weeks. If serious, ambiguous, or when new symptoms occur, specialized diagnostic measures such as comprehensive neurocognitive testing or neuroimaging should be initiated. Very few patients would require inpatient rehabilitation. Conclusion: PCS with cognitive impairment is a debilitating condition that could affect daily functioning and reduce work productivity. Management in primary care should adopt a multidisciplinary approach, centering around physical, cognitive, and pharmacological therapies.

Selective vulnerability of hippocampal sub-regions in patients with subcortical vascular mild cognitive impairment.

Early diagnosis of subcortical vascular mild cognitive impairment (svMCI) is clinically essential because it is the most reversible subtype of all cognitive impairments. Since structural alterations of hippocampal sub-regions have been well studied in neurodegenerative diseases with pathophysiological cognitive impairments, we were eager to determine whether there is a selective vulnerability of hippocampal sub-fields in patients with svMCI. Our study included 34 svMCI patients and 34 normal controls (NCs), with analysis of T1 images and Montreal Cognitive Assessment (MoCA) scores. Gray matter volume (GMV) of hippocampal sub-regions was quantified and compared between the groups, adjusting for age, sex, and education. Additionally, we explored correlations between altered GMV in hippocampal sub-fields and MoCA scores in svMCI patients. Patients with svMCI exhibited selectively reduced GMV in several left hippocampal sub-regions, such as the hippocampal tail, hippocampal fissure, CA1 head, ML-HP head, CA4 head, and CA3 head, as well as decreased GMV in the right hippocampal tail. Specifically, GMV in the left CA3 head was inversely correlated with MoCA scores in svMCI patients. Our findings indicate that the atrophy pattern of patients with svMCI was predominantly located in the left hippocampal sub-regions. The left CA3 might be a crucial area underlying the distinct pathophysiological mechanisms of cognitive impairments with subcortical vascular origins.

Neuropsychiatric symptoms and white matter hyperintensities in older adults without dementia.

We aimed to examine associations between neuropsychiatric symptoms (NPS) and white matter hyperintensities (WMH) status in older adults without dementia under the hypothesis that WMH increased the odds of having NPS. Longitudinal analysis of data acquired from the National Alzheimer's Coordinating Center Uniform Data Set. Data were derived from 46 National Institute on Aging - funded Alzheimer's Disease Research Centers. NACC participants aged ≥50 years with available data on WMH severity with a diagnosis of mild cognitive impairment (MCI) or who were cognitively unimpaired (CU) were studied. Among 4617 CU participants, 376 had moderate and 54 extensive WMH. Among 3170 participants with MCI, 471 had moderate and 88 had extensive WMH. Using Cardiovascular Health Study (CHS) scores, WMH were coded as no to mild (CHS score: 0-4), moderate (score: 5-6) or extensive (score: 7-8). NPS were quantified on the Neuropsychiatric Inventory Questionnaire. Binary logistic regression models estimated the odds of reporting each of 12 NPS by WMH status separately for individuals with MCI or who were CU. Compared to CU individuals with no to mild WMH, the odds of having elation [9.87, (2.63-37.10)], disinhibition [4.42, (1.28-15.32)], agitation [3.51, (1.29-9.54)] or anxiety [2.74, (1.28-5.88)] were higher for the extensive WMH group, whereas the odds of having disinhibition were higher for the moderate WMH group [1.94, (1.05-3.61)]. In the MCI group, he odds of NPS did not vary by WMH status. Extensive WMH were associated with higher odds of NPS in CU older adults but not in those with MCI.

Development of Improved Weighed Quantum Lion Optimization with Smooth Support Vector Machine for Alzheimer’s Disease

Accurate diagnosis of Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI) was identified on an early stage is essential in the healthcare industry to stop degeneration. The Smooth Support Vector Machine (SSVM) model, Principal Component Analysis (PCA), feature extraction, and Magnetic Resonance Imaging (MRI) image prepossessing are the components for the diagnosis of AD is proposed in this research at early stage. To assist in the classifier's training, we proposed a novel Improved Weighed Quantum Lion Optimization (IWQLO). The SSVM parameters are specifically proposed to be optimized using a new Switching delayed Lion Optimization (SLO) algorithm. The IWQLO-SSVM approach was effectively used to classify AD and MCI utilizing MRI scans of the Alzheimer's disease Neuroimaging Initiative (ADNI) database and Outcome and Assessment Information Set (OASIS) database. For six example scenarios, the classification accuracy of our proposed method is acceptable. Testing show that the proposed approach improves the performance measures such as accuracy, precision, specificity, sensitivity and recall for detecting the early stage AD diagnosis.

Development of a smartphone screening test for preclinical Alzheimer’s disease and validation across the dementia continuum

BackgroundDementia prevalence is predicted to triple to 152 million globally by 2050. Alzheimer’s disease (AD) constitutes 70% of cases. There is an urgent need to identify individuals with preclinical AD, a 10–20-year period of progressive brain pathology without noticeable cognitive symptoms, for targeted risk reduction. Current tests of AD pathology are either too invasive, specialised or expensive for population-level assessments. Cognitive tests are normal in preclinical AD. Emerging evidence demonstrates that movement analysis is sensitive to AD across the disease continuum, including preclinical AD. Our new smartphone test, TapTalk, combines analysis of hand and speech-like movements to detect AD risk. This study aims to [1] determine which combinations of hand-speech movement data most accurately predict preclinical AD [2], determine usability, reliability, and validity of TapTalk in cognitively asymptomatic older adults and [3], prospectively validate TapTalk in older adults who have cognitive symptoms against cognitive tests and clinical diagnoses of Mild Cognitive Impairment and AD dementia.MethodsAim 1 will be addressed in a cross-sectional study of at least 500 cognitively asymptomatic older adults who will complete computerised tests comprising measures of hand motor control (finger tapping) and oro-motor control (syllabic diadochokinesis). So far, 1382 adults, mean (SD) age 66.20 (7.65) years, range 50–92 (72.07% female) have been recruited. Motor measures will be compared to a blood-based AD biomarker, phosphorylated tau 181 to develop an algorithm that classifies preclinical AD risk. Aim 2 comprises three sub-studies in cognitively asymptomatic adults: (i) a cross-sectional study of 30–40 adults to determine the validity of data collection from different types of smartphones, (ii) a prospective cohort study of 50–100 adults ≥ 50 years old to determine usability and test-retest reliability, and (iii) a prospective cohort study of ~1,000 adults ≥ 50 years old to validate against cognitive measures. Aim 3 will be addressed in a cross-sectional study of ~200 participants with cognitive symptoms to validate TapTalk against Montreal Cognitive Assessment and interdisciplinary consensus diagnosis.DiscussionThis study will establish the precision of TapTalk to identify preclinical AD and estimate risk of cognitive decline. If accurate, this innovative smartphone app will enable low-cost, accessible screening of individuals for AD risk. This will have wide applications in public health initiatives and clinical trials.Trial registrationClinicalTrials.gov identifier: NCT06114914, 29 October 2023. Retrospectively registered.

Health system implementation of the PROMIS Cognitive Function Screener in the Medicare Annual Wellness Visit: framing as abilities versus concerns

BackgroundCognitive assessment is a required component of the Medicare Annual Wellness Visit (AWV). In this prospective study, we evaluated acceptability and usefulness of a patient-reported outcome measure (the PROMIS® Cognitive Function Screener, or PRO-CS) to screen for cognitive impairment during the AWV. We compared two versions of the PRO-CS: Abilities and Concerns.MethodsWe developed PRO-CS Abilities and PRO-CS Concerns using items from the PROMIS Cognitive Function item banks. We partnered with a large health system in Pennsylvania to implement an electronic health record (EHR)-integrated version of the 4-item PRO-CS into their AWV workflow. PRO-CS Abilities was implemented in June 2022 and then replaced with PRO-CS Concerns in October 2022. We used EHR data to evaluate scores on Abilities versus Concerns and their association with patient characteristics. We gathered feedback from providers on experiences with the PRO-CS and conducted cognitive interviews with patients to evaluate their preferences for Abilities versus Concerns.ResultsBetween June 2022 and January 2023, 3,088 patients completed PRO-CS Abilities and 2,614 patients completed PRO-CS Concerns. Mean T-scores for Abilities (54.8) were slightly higher (indicating better cognition) than for Concerns (52.6). 10% of scores on Abilities and 13% of scores on Concerns indicated concern for cognitive impairment (T-score < 45). Both Abilities and Concerns were associated with clinical characteristics as hypothesized, with lower scores for patients with cognitive impairment diagnoses and those requiring assistance with instrumental activities of daily living. Abilities and Concerns had similar negative correlations with depression (r= -0.31 versus r= -0.33) and anxiety (r= -0.28 for both), while Abilities had a slightly stronger positive correlation with self-rated health (r = 0.34 versus r = 0.28). In interviews, providers commented that the PRO-CS could be useful to facilitate conversations about cognition, though several providers noted potential limitations of patient self-report. Feedback from patients indicated a preference for PRO-CS Concerns.ConclusionsOur findings suggest potential utility of the PRO-CS for cognitive screening in the Medicare AWV. PRO-CS Abilities and Concerns had similar associations with patient clinical characteristics, but the Concerns version was more acceptable to patients.

Unearthing Subtle Cognitive Variations: A Digital Screening Tool for Detecting and Monitoring Mild Cognitive Impairment

Early diagnosis of mild cognitive impairment (MCI) is pivotal in mitigating the risk of cognitive impairment and the onset of dementia. However, prevailing clinical cognitive screening tests and biomarker assessment approaches often suffer from drawbacks such as high cost, invasiveness, time consumption, or subjectivity. In China, existing digital cognitive assessment tools face multiple challenges due to their distinctive cultural, language, and healthcare landscape. Therefore, we embarked on a study to develop a digital cognitive assessment tool, evaluate its efficacy in distinguishing between healthy individuals and MCI patients, and examine its acceptability among Chinese older adults. Through a series of symposiums, programming, and interviews with stakeholders, we iteratively designed the "BrainNursing" mobile application. The system consists of eleven single tasks and three dual tasks, each taking only 1–3 minutes. Subsequently, we conducted statistical comparisons of movement kinetics and physiological signals recorded during cognitive testing in 181 older adults to investigate which parameters could serve as effective digital biomarkers for MCI screening. Leveraging machine learning classifiers and a majority voting principle, we evaluated the classification performance of the BrainNursing system in detecting MCI, yielding an accuracy rate of 90.3%. Furthermore, our analysis of movement kinetics revealed that time, score, and sequence features are crucial in cognitive assessment. Contrasting with their healthy counterparts, MCI patients exhibited decreased heart rate variability, increased sympathetic nervous system activity, and weakened autonomic nervous system regulation in response to stimuli during cognitive testing. Finally, user experience feedback indicated that participants universally perceived BrainNursing as a convenient and user-friendly cognitive screening tool and provided valuable insights for further improvement.

Protocol for a construct and clinical validation study of MyCog Mobile: a remote smartphone-based cognitive screener for older adults

IntroductionAnnual cognitive screening in older adults is essential for early detection of cognitive impairment, yet primary care settings face time constraints that present barriers to routine screening. A remote cognitive...

Diagnosis of Early Mild Cognitive Impairment Based on Associated High-Order Functional Connection Network Generated by Multimodal MRI

Diagnosis of Early Mild Cognitive Impairment Based on Associated High-Order Functional Connection Network Generated by Multimodal MRI

Predictive models for Alzheimer's disease diagnosis and MCI identification: The use of cognitive scores and artificial intelligence algorithms

The paper presents a comprehensive study on predictive models for Alzheimer's disease (AD) and Mild cognitive impairment (MCI) diagnosis, implementing a combination of cognitive scores and artificial intelligence algorithms. The research includes detailed analyses of clinical and demographic variables such as age, education, and various cognitive and functional scores, investigating their distributions and correlations with AD and MCI. The study utilizes several machine-learning classifiers, comparing their performance through metrics like accuracy, precision, and area under the ROC curve (AUC). Key findings include the influence of gender on AD prevalence, the potential protective effect of education, and the significance of functional decline and cognitive performance scores in the models. The results demonstrate the effectiveness of ensemble methods and the robustness of the models across different data subsets, highlighting the potential of artificial intelligence in enhancing diagnostic accuracy for Alzheimer's disease and Mild cognitive impairment.

Brodmann Areas, V1 Atlas and Cognitive Impairment: Assessing Cortical Thickness for Cognitive Impairment Diagnostics.

Background and Objectives: Magnetic resonance imaging is vital for diagnosing cognitive decline. Brodmann areas (BA), distinct regions of the cerebral cortex categorized by cytoarchitectural variances, provide insights into cognitive function. This study aims to compare cortical thickness measurements across brain areas identified by BA mapping. We assessed these measurements among patients with and without cognitive impairment, and across groups categorized by cognitive performance levels using the Montreal Cognitive Assessment (MoCA) test. Materials and Methods: In this cross-sectional study, we included 64 patients who were divided in two ways: in two groups with (CI) or without (NCI) impaired cognitive function and in three groups with normal (NC), moderate (MPG) and low (LPG) cognitive performance according to MoCA scores. Scans with a 3T MRI scanner were carried out, and cortical thickness data was acquired using Freesurfer 7.2.0 software. Results: By analyzing differences between the NCI and CI groups cortical thickness of BA3a in left hemisphere (U = 241.000, p = 0.016), BA4a in right hemisphere (U = 269.000, p = 0.048) and BA28 in left hemisphere (U = 584.000, p = 0.005) showed significant differences. In the LPG, MPG and NC cortical thickness in BA3a in left hemisphere (H (2) = 6.268, p = 0.044), in V2 in right hemisphere (H (2) = 6.339, p = 0.042), in BA28 in left hemisphere (H (2) = 23.195, p < 0.001) and in BA28 in right hemisphere (H (2) = 10.015, p = 0.007) showed significant differences. Conclusions: Our study found that cortical thickness in specific Brodmann Areas-BA3a and BA28 in the left hemisphere, and BA4a in the right-differ significantly between NCI and CI groups. Significant differences were also observed in BA3a (left), V2 (right), and BA28 (both hemispheres) across LPG, MPG, NC groups. Despite a small sample size, these findings suggest cortical thickness measurements can serve as effective biomarkers for cognitive impairment diagnosis, warranting further validation with a larger cohort.

Age-Dependent Cerebral Microangiopathy Associated with Vascular Risk Factors: How to  Recognize the Signs?

The focus of  this article is  on  cerebral  microangiopathy (CMA), also known as  cerebral small vessel disease, which is commonly linked to age and vascular risk factors. It is a major contributor to both vascular and mixed cognitive decline in  older individuals. The leading causes of  vascular cognitive impairment and dementia include hypertension, high cholesterol, type 2 diabetes mellitus, smoking, and atrial fibrillation. The main manifestations of CMA in patients over 60 are outlined in this article, with supporting evidence from both domestic and foreign studies. By examining a specific clinical case, the characteristics, diagnosis, and treatment of cognitive impairment caused by CMA and vascular risk factors in an older patient were analyzed.

Induced erotomania by online romance fraud - a novel form of de Clérambault’s syndrome

BackgroundAlthough the impact of internet usage on mental health is extensively documented, there is a notable scarcity of reports in the literature concerning internet-induced erotomania. Erotomania is a rare and likely underdiagnosed delusional disorder. It is characterized by an irrational belief held by the affected persons that someone of higher socioeconomic status harbor romantic feelings toward them. Here, we describe the psychopathology of erotomanic delusion induced by online romantic fraud in a female patient. Employing this case as a focal point, we illuminate novel aspects of erotomania that warrant attention and examination.Case presentationWe present a compelling case involving a 70-year-old married Caucasian woman diagnosed with medically controlled persistent depressive disorder for several years. The intricacies of her condition became evident as she became deeply engrossed in online profiles featuring the image of a renowned musician, inadvertently falling victim to an online romantic fraud. Subsequently, this distressing experience triggered the emergence of erotomanic delusions and a suicide attempt. The patient's history reveals an array of medical conditions and stressful life events, contributing to her vulnerability. The diagnosis of erotomanic delusional disorder, dysthymia, and mild cognitive impairment with cerebral vascular background was established. Treatment involved her previous antidepressant with low-dose risperidone, alongside supportive individual and group therapy. Her delusion showed remission four weeks later, prompting her discharge for outpatient follow-up. Although she retained some false beliefs, the intensity of the symptoms had notably diminished and her functionality improved.ConclusionThis case underscores the complex interplay between mental health, online activities, and the consequences of delusions, including suicidal thoughts, shedding light on the need for a comprehensive approach in addressing such challenging psychiatric scenarios.

The Interplay between Gut Microbiota and Cognitive Functioning in the Healthy Aging Population: A Systematic Review.

The gut microbiota in healthy older individuals typically show a decrease in beneficial bacteria like Bifidobacterium and Lactobacillus, alongside an increase in pro-inflammatory microbes such as Enterobacteriaceae and Clostridia. These changes contrast with younger and middle-aged individuals and appear to correlate with cognitive status. Although there is extensive research on gut microbiota and cognitive functions in cognitively impaired elderly individuals, its impact on cognitively healthy elderly populations has not been extensively studied. A comprehensive literature search was conducted across PubMed, EBSCO, Web of Science, and Scopus databases to identify studies exploring the relationship between gut microbiota composition and cognitive functioning in healthy older adults. During the literature screening process, each record was initially assessed by its title, abstract, and keywords to exclude articles that did not align with the scope of this review. Three authors independently screened and retrieved the records. The inclusion criteria included: (1) publication in peer-reviewed journals; (2) studies involving neurologically, cognitively, and medically healthy populations; (3) participants identified as older adults, defined for this review as individuals aged 45 years and older due to the limited number of records; (4) analysis of gut microbiota; and (5) assessment of cognitive function. Subsequently, full texts were analyzed to determine eligibility. The exclusion criteria encompassed: (1) incorrect publication type; (2) inappropriate sample population; (3) unsuitable study design; (4) absence of one or more inclusion criteria; and (5) studies based on animal research. A risk of bias assessment was performed for each included study using the Joanna Briggs Institute (JBI) checklist, ensuring all selected studies met established quality standards. A total of 6 eligible research articles from a possible 1752 published until March 2024 were identified and included. We categorized the included studies into two groups based on their focus: the taxonomic composition of gut microbiota and the alpha diversity, which is the variety of organisms within a sample. Additionally, two methods were identified for assessing cognition: neuropsychological tests and physiological measurements, notably electroencephalography (EEG). The studies show varying results regarding the abundance of specific bacterial taxa and their cognitive associations. Notably, the relationship between certain bacteria and cognition may vary when analyzed at different taxonomic levels, such as phylum versus family. Changes in gut microbiota composition in the elderly, even without a cognitive impairment diagnosis, could potentially serve as early biological markers for Alzheimer's disease or other dementias before mild cognitive impairment appears.