Enhanced Written vs. Verbal Recall Accuracy Associated With Greater Prefrontal Activation: A Near-Infrared Spectroscopy Study

Stroke analysis and recognition in functional near-infrared spectroscopy signals using machine learning methods

Stroke is a high-incidence disease with high disability and mortality rates. It is a serious public health problem worldwide. Shortened onset-to-image time is very important for the diagnosis and treatment of stroke. Functional near-infrared spectroscopy (fNIRS) is a noninvasive monitoring tool with real-time, noninvasive, and convenient features. In this study, we propose an automatic classification framework based on cerebral oxygen saturation signals to identify patients with hemorrhagic stroke, patients with ischemic stroke, and normal subjects. The reflected fNIRS signals were used to detect the cerebral oxygen saturation and the relative value of oxygen and deoxyhemoglobin concentrations of the left and right frontal lobes. The wavelet time-frequency analysis-based features from these signals were extracted. Such features were used to analyze the differences in cerebral oxygen saturation signals among different types of stroke patients and healthy humans and were selected to train the machine learning models. Furthermore, an important analysis of the features was performed. The accuracy of the models trained was greater than 85%, and the accuracy of the models after data augmentation was greater than 90%, which is of great significance in distinguishing patients with hemorrhagic stroke or ischemic stroke. This framework has the potential to shorten the onset-to-diagnosis time of stroke.

Longitudinal episodic memory trajectories in older adults with normal cognition

OBJECTIVE

To determine the longitudinal trajectories and normative standards of episodic memory in older adults.

METHODS

Participants were drawn from the cognitively normal(CN) subgroup of the population-based HELIAD cohort, a fairly representative cohort of the older Greek population. Verbal and non-verbal memory were assessed using the Greek Verbal Learning Test and Medical College of Georgia-Complex Figure Test. Baseline and longitudinal associations of memory performance with age, sex and formal education were explored with linear regression analysis and generalized estimated equations.

RESULTS

A total of 1607 predominantly female (60%) individuals (73.82 ± 5.43 years), with a mean educational attainment of 8.17(±4.86) years were CN at baseline. Baseline analysis revealed a continuum of memory decline with aging and lower educational attainment. Women performed better in composite and verbal memory measures, while men performed better in non-verbal memory tasks. A subgroup of 761 participants with available assessments after 3.07(±0.82) years remained CN at follow-up. Composite memory scores yearly diminished by an additional 0.007 of a SD for each additional year of age at baseline. Regarding verbal learning, immediate free verbal recall, delayed free verbal recall and delayed cued verbal recall, an additional yearly decrease of 0.107, 0.043, 0.036 and 0.026 words were respectively recorded at follow-up, for each additional year of age at baseline. Women underwent steeper yearly decreases of 0.227 words in delayed cued verbal recall. No significant longitudinal associations emerged for immediate non-verbal memory, delayed non-verbal memory and immediate cued verbal recall.

CONCLUSIONS

In the present study, aging (but not educational attainment) was consistently associated with steeper verbal memory decline.

Supplemental data for this article is available online at https://doi.org/10.1080/13854046.2022.2059011 .