Changes in Functional Connectivity in Mild Cognitive Impairment: A Meta-Analysis of M/EEG Studies

Background and Objectives

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by memory loss and cognitive impairment. AD is the leading cause of cognitive disorders in the elderly, accounting for approximately 60% to 80% of global cases. With increasing age, the prevalence of Alzheimer’s disease significantly rises, with a prevalence of 3% in the 65-74 age group, 17% in the 75-84 age group, and reaching 32% in individuals aged 85 and above. Therefore, Alzheimer’s disease has become a major global public health issue, significantly affecting health systems and societal costs.

Neuropathological changes in AD include extracellular β-amyloid (Aβ) accumulation and neurofibrillary tangles caused by hyperphosphorylated tau protein (p-tau), leading to neuronal death, and ultimately resulting in brain atrophy and synaptic dysfunction. The earliest lesions begin in the entorhinal cortex and hippocampus and progressively spread to neocortical regions as the disease advances. However, increasing evidence suggests that AD neuropathology is not global but may initially target specific functionally connected regions, which are considered key nodes of larger brain networks.

During the neurodegenerative process of AD, there is a silent period that may last for years or even decades, during which neuropathophysiological processes have begun and are ongoing, but clinical signs are not yet apparent. Subsequently, neurodegeneration may lead to a preclinical stage known as mild cognitive impairment (MCI), which gradually and irreversibly leads to autonomy loss, ultimately progressing to dementia. MCI is defined as an intermediate stage between normal aging and the onset of AD, characterized by objective cognitive impairment in memory (amnestic MCI, aMCI) or other cognitive domains (non-amnestic MCI, nMCI), while basic cognitive function and activities of daily living remain intact.

Neurophysiological measurement methods, such as electroencephalography (EEG) and magnetoencephalography (MEG), are non-invasive techniques used to record electromagnetic signals generated by neural activity. These methods are more cost-effective and practical than functional magnetic resonance imaging (fMRI) and offer high temporal resolution. Existing studies have demonstrated that early synchronous changes can be observed in the mild cognitive impairment stage through these techniques. However, the direction (hypersynchrony/hypersynchrony), region, and frequency bands of these changes remain inconsistent. This study aims to clarify existing evidence related to potential AD neurophysiological biomarkers through a meta-analysis.

Study Source

This paper was co-authored by Giulia Buzi, Chiara Fornari, Alessio Perinelli, and Veronica Mazza, from the following research institutions: - Inserm-EPHE-Unicaen, Caen, France - Center for Mind/Brain Sciences (CIMeC), University of Trento, Rovereto, Italy - Department of Physics, University of Trento, Trento, Italy - INFN-TIFPA, Trento, Italy

The study was published in Clinical Neurophysiology, Volume 156, 2023, Pages 183-195. This is an open-access article published by Elsevier B.V., under CC BY license.

Research Workflow

Literature Search and Screening

The literature search was conducted from December 10, 2022, to June 2023, covering databases including PubMed, Scopus, Web of Science, and PsycInfo. Search keywords included “EEG” or “MEG,” “connectivity,” “synchronization,” “Alzheimer,” among others. From 3852 articles screened, 12 met the inclusion criteria for analysis. Articles included in the analysis had to report effect sizes and describe changes in brain region functional connectivity in patients with mild cognitive impairment.

Meta-Analysis Methodology

The study employed a random-effects meta-analysis to objectively remove non-significant unreported effect sizes (NSUES). It primarily compared functional connectivity changes in resting-state between mild cognitive impairment (MCI) and healthy controls (HC). To avoid sample size imbalance, only the comparison between HC and MCI was considered. Standardized mean differences (SMD) were used to analyze connectivity changes across different frequency bands between brain regions, specifically including: - Frontal-Temporal (FT) - Frontal-Parietal (FP) - Frontal-Occipital (FO) - Temporal-Parietal (TP)

Data Extraction and Analysis

Extracted study data included basic bibliographic information, experimental parameters (such as the number and location of electrodes), sample demographics, connectivity measurement indices, type of task or resting state, and effect sizes of connectivity changes. In statistical analysis, connectivity changes between different brain regions were compared, and effect estimates and confidence intervals were displayed through forest plots. Additionally, leave-one-out analysis and publication bias tests were performed.

Main Results

Alpha Band

Comparisons between MCI and HC revealed a significant decrease in Alpha synchrony in the Temporal-Parietal (d=-0.26) and Frontal-Parietal (d=-0.25) regions, suggesting reduced functional connectivity between these brain regions in mild cognitive impairment patients. Leave-one-out analysis demonstrated high reproducibility of these results in most cases.

Theta Band

A significant reduction in Theta synchrony in the Frontal-Parietal region was not confirmed in most studies but showed moderate effects in individual cases (when certain studies were excluded).

Delta Band

No significant synchrony changes were found in the Delta band across various brain region comparisons.

Beta Band

No significant synchrony changes were found in the Beta band either.

Conclusion and Significance

This meta-analysis expands the consistency with the existing literature, emphasizing significantly reduced Alpha band synchrony in the Temporal-Parietal and Frontal-Parietal regions in MCI patients. These findings further support the “disconnection syndrome” hypothesis, suggesting that cognitive impairment may be related to reduced functional integration between brain regions. These functional connectivity changes are evident at the MCI stage, highlighting their importance for early diagnosis and treatment of Alzheimer’s disease.

The feasibility of electrophysiological techniques enables early detection of neuropathological changes, providing new strategies for managing the disease’s progression. Further research can help develop therapies to alter the disease course and implement early interventions at the initial stages of neurodegeneration.

Highlights

• Significant reduction in Alpha band functional connectivity in the Temporal-Parietal and Frontal-Parietal regions during the MCI stage.
• The newly adopted meta-analysis method enhances the reliability of results, avoiding publication bias.
• Electrophysiological measurements provide an efficient tool for early AD diagnosis, with substantial clinical application value.

A deeper understanding of functional connectivity changes during the MCI stage can provide more effective detection tools and treatment plans for clinical application, aiding early intervention and optimizing disease management strategies. This study presents significant scientific and applied value in exploring functional biomarkers for the early stages of Alzheimer’s disease.