Age-related hearing loss associated with differences in the neural correlates of feature binding in visual working memory

Electrophysiological correlates of visual short-term memory binding deficits in community-dwelling seniors at risk of dementia

BACKGROUND

Visual Short-Term Memory Binding (VSTMB) is a preclinical marker of Alzheimer's disease (AD). Reduced early event-related potentials (ERPs) (100-250 ms) over fronto-central (FC) and parieto-occipital (PO) regions have been reported in patients with Mild Cognitive Impairment (MCI) seen in the clinic. We investigated such ERPs in a larger sample of community-dwelling older adults who had not sought medical advice.

METHODS

Participants (n = 215) were assessed with a neuropsychological battery and the VSTMB Task. The latter assessed the ability to detect changes between two consecutive arrays of shapes or colored shapes (the Binding condition). Time-locked EEG signals were collected during the task.

RESULTS

Those who met the MCI criteria (n = 108) showed binding impairment. ERP analyses revealed significant Group x Time Windows interactions. Early ERP showed reduced neural recruitment (MCI < healthy controls (HC)) over the right FC regions, left PO, and right centro-parietal (CP) regions during Binding encoding, and over PO regions bilaterally and left FC during retrieval. Late ERP showed increased neural recruitment (MCI > HC) on left FC and PO regions during retrieval.

CONCLUSIONS

Hyper-recruitment may reflect functional reorganization aimed at behavioral compensation in the early stages of MCI. The role of such amplitude shifts as pointers of transition points in the AD continuum needs further investigation.

Alpha and theta oscillations on a visual strategic processing task in age-related hearing loss

Introduction

Emerging evidence suggests changes in several cognitive control processes in individuals with age-related hearing loss (ARHL). However, value-directed strategic processing, which involves selectively processing salient information based on high value, has been relatively unexplored in ARHL. Our previous work has shown behavioral changes in strategic processing in individuals with ARHL. The current study examined event-related alpha and theta oscillations linked to a visual, value-directed strategic processing task in 19 individuals with mild untreated ARHL and 17 normal hearing controls of comparable age and education.

Methods

Five unique word lists were presented where words were assigned high- or low-value based on the letter case, and electroencephalography (EEG) data was recorded during task performance.

Results

The main effect of the group was observed in early time periods. Specifically, greater theta synchronization was seen in the ARHL group relative to the control group. Interaction between group and value was observed at later time points, with greater theta synchronization for high- versus low-value information in those with ARHL.

Discussion

Our findings provide evidence for oscillatory changes tied to a visual task of value-directed strategic processing in individuals with mild untreated ARHL. This points towards modality-independent neurophysiological changes in cognitive control in individuals with mild degrees of ARHL and adds to the rapidly growing literature on the cognitive consequences of ARHL.

Mendelian randomization reveals the causal association between gout and hearing impairment in older adults

With the global aging trend escalating, the holistic well-being of the elderly has become a paramount concern within public health. Traditional observational studies often struggle with confounding factors and establishing causality, leaving the relationship between age-related hearing loss (ARHL) and gout largely unexplored. Employing bidirectional two-sample Mendelian randomization (MR) analysis, this investigation elucidated the genetic underpinnings associated with age-related hearing impairment, gout, and urate levels within the IEU Open-GWAS database, thereby uncovering potential causal connections that underlie the intricate interplay between gout, serum urate concentrations, and auditory decline in the geriatric demographic. In the forward MR phase, a cohort of 30 single nucleotide polymorphisms was leveraged to dissect the causal dynamics between ARHL and both gout and urate concentrations. Conversely, in the reverse MR phase, gout and urate levels were posited as the exposome to delineate their impact on hearing acuity, employing an array of models for rigorous validation and sensitivity scrutiny. In the forward MR analysis, a statistically significant correlation was discerned between ARHL and gout (P = .003, odds ratio = 1.01, 95% confidence interval: 1.00-1.02), alongside a notable association with serum urate levels (P = .031, odds ratio = 1.39, 95% confidence interval: 1.03-1.88), intimating that ARHL could potentially influence the incidence of gout and urate concentrations. Conversely, the reverse MR investigation revealed that neither gout nor serum urate levels exerted significant impact on auditory degradation (P > .05), insinuating that these factors might not predominantly contribute to hearing loss. Sensitivity analyses concurred with this inference. This study enriches the comprehension of geriatric health intricacies and unveils that ARHL potentially influences gout and serum urate concentrations. This suggests that monitoring ARHL may play a crucial role in the early identification and management of gout and hyperuricemia, potentially contributing to a comprehensive approach to improving geriatric health outcomes.

The applied principles of EEG analysis methods in neuroscience and clinical neurology

Electroencephalography (EEG) is a non-invasive measurement method for brain activity. Due to its safety, high resolution, and hypersensitivity to dynamic changes in brain neural signals, EEG has aroused much interest in scientific research and medical fields. This article reviews the types of EEG signals, multiple EEG signal analysis methods, and the application of relevant methods in the neuroscience field and for diagnosing neurological diseases. First, three types of EEG signals, including time-invariant EEG, accurate event-related EEG, and random event-related EEG, are introduced. Second, five main directions for the methods of EEG analysis, including power spectrum analysis, time-frequency analysis, connectivity analysis, source localization methods, and machine learning methods, are described in the main section, along with different sub-methods and effect evaluations for solving the same problem. Finally, the application scenarios of different EEG analysis methods are emphasized, and the advantages and disadvantages of similar methods are distinguished. This article is expected to assist researchers in selecting suitable EEG analysis methods based on their research objectives, provide references for subsequent research, and summarize current issues and prospects for the future.