Biology subjects

Strzelczyk, D.

Publications and source records attributed to Strzelczyk, D..

4 recordsLinked to original sources

bioRxiv2025

Impact of Aging on Theta-Phase Gamma-Amplitude Coupling During Learning: A Multivariate Analysis

Aging is associated with cognitive decline and memory impairment, but the underlying neural mechanisms remain unclear. Phase-amplitude coupling (PAC) between mid-frontal theta (5 Hz) and occipital gamma (>30 Hz) oscillations is a proposed marker for parallel storage of multiple items in working memory. However, research has mainly focused on young individuals and epilepsy patients, with only a few studies on aging populations. Moreover, these studies have relied on univariate PAC methods, which can be flawed by potential spurious or biased PAC estimates due to non-stationarity of EEG signals. Additionally, these methods typically assess PAC at the level of individual electrodes, potentially overlooking the broader functional significance of theta-gamma coupling in coordinating neural activity across distant brain regions. To address these gaps, we employed multivariate PAC (mPAC) through generalized eigendecomposition (GED) analysis, which avoids the pitfalls of non-sinusoidal oscillations. 113 young and 117 older healthy participants engaged in a sequence learning paradigm (6423 sequence repetitions, 55944 stimuli), in which they learned a fixed sequence of visual stimuli over repeated observations, allowing us to track the mPAC during the incremental process of learning. Behavioral results revealed that younger participants learned significantly faster than older participants. Neurophysiological data showed that mPAC increased over the course of learning in both age groups and could identify fast and slow learners. However, older participants exhibited lower mPAC compared to younger counterparts, which suggest compromised parallel storage of items in working memory in older age. Finally, stratification analysis revealed that mPAC effects persist across performance groups with similar mid-frontal theta levels, suggesting that theta alone does not account for these effects. These findings shed light on the age-related differences in memory formation processes and may guide interventions to enhance memory performance in older adults and slow learners.

neuroscience↗

bioRxiv2024

Pre-stimulus Activity Mediates Event-Related Theta Synchronization and Alpha Desynchronization During Memory Formation in Healthy Aging

The capacity to learn is a key determinant for the quality of life but is known to decline to varying degrees with age. However, despite mounting evidence of memory deficits in older age, the neural mechanisms contributing to successful or impeded memory remain unclear. Previous research has primarily focused on memory formation through remembered versus forgotten comparisons, lacking the ability to capture the incremental nature of learning. Moreover, previous EEG studies have primarily examined oscillatory brain activity during the encoding phase, such as event-related synchronization (ERS) of mid-frontal theta and desynchronisation (ERD) of parietal alpha, while neglecting the potential influence of pre-stimulus activity. To address these limitations, we employed a sequence learning paradigm, where 113 young and 117 older participants learned a fixed sequence of visual locations through repeated observations (6423 sequence repetitions, 55 944 stimuli). This paradigm enabled us to investigate mid-frontal theta ERS, parietal alpha ERD, and how they are affected by pre-stimulus activity during the incremental learning process. Behavioral results revealed that young subjects learned significantly faster than older subjects, in line with expected age-related cognitive decline. Successful incremental learning was directly linked to decreases of mid-frontal theta ERS and increases of parietal alpha ERD. Notably, these neurophysiological changes were less pronounced in older individuals, reflecting a slower rate of learning. Importantly, the mediation analysis revealed that in both age groups, mid-frontal pre-stimulus theta partially mediated the relationship between learning and mid-frontal theta ERS. Furthermore, the overall impact of learning on parietal alpha ERD was primarily driven by its positive influence on pre-stimulus alpha activity. Our findings offer new insights into the age-related differences in memory formation and highlight the importance of pre-stimulus activity in explaining post-stimulus responses during learning.

neuroscience↗

bioRxiv2022

Neurophysiological markers of successful learning in healthy aging

The capacity to learn and memorize is a key determinant for the quality of life, but is known to decline to varying degrees with age. Previous ERP research methods had the limitation that their design did not allow to track the gradual memory formation process. Thus, the neural mechanisms underlying memory formation and the critical features that determine the extent to which aging affects learning are still unknown. By using a visual sequence learning task, which consists of the repeated presentation of a simple sequence of tokens, we are able to track the progress of gradual memory formation through both neurophysiological and behavioral markers. On a neurophysiological level, we focused on two learning related centroparietal ERP components: the P300 and broad positivity. Our results revealed that although both age groups showed significant learning progress, young individuals learned faster and remembered more stimuli than older participants. Successful learning was directly linked to a decrease of P300 amplitude. However, young participants showed larger P300 amplitude with a sharper decrease during the memory formation process. The P300 amplitude predicted learning success in both age groups, was associated with increased fronto-parietal brain network activation and showed good test-retest reliability. Highly, similar results were found for the broad positivity component, which raises the questions if the BP is a distinct component or just a prolonged P300. In a series of analyses, including topographic analysis of variance (TANOVA), equivalence testing and source reconstruction analysis, we addressed the unresolved questions. These analyses revealed concordant distributed brain activation patterns within parietal circuits. Thus, there is no evidence (rather evidence for equivalence) for distinct underlying neural generators for the two components. Taken together, the results highlight the importance of the P300 as a neurophysiological marker of learning and may enable the development of preventive measures for age-related impeded learning.

neuroscience↗

bioRxiv2022

The AI Neuropsychologist: Automatic scoring of memory deficits with deep learning

BackgroundMemory deficits are a hallmark of many different neurological and psychiatric conditions. The Rey-Osterrieth complex figure (ROCF) is the state-of-the-art assessment tool for neuropsychologists across the globe to assess the degree of non-verbal visual memory deterioration. To obtain a score, a trained clinician inspects a patients ROCF drawing and quantifies deviations from the original figure. This manual procedure is time-consuming, slow and scores vary depending on the clinicians experience, motivation and tiredness. MethodsHere, we leverage novel deep learning architectures to automatize the rating of memory deficits. For this, we collected more than 20k hand-drawn ROCF drawings from patients with various neurological and psychiatric disorders as well as healthy participants. Unbiased ground truth ROCF scores were obtained from crowdsourced human intelligence. This dataset was used to train and evaluate a multi-head convolutional neural network. ResultsThe model performs highly unbiased as it yielded predictions very close to the ground truth and the error was similarly distributed around zero. The neural network outperforms both online raters and clinicians. The scoring system can reliably identify and accurately score individual figure elements in previously unseen ROCF drawings, which facilitates explainability of the AI-scoring system. To ensure generalizability and clinical utility, the model performance was successfully replicated in a large independent prospective validation study that was pre-registered prior to data collection. ConclusionsOur AI-powered scoring system provides healthcare institutions worldwide with a digital tool to assess objectively, reliably and time-efficiently the performance in the ROCF test from hand-drawn images.

neuroscience↗