Speech in noise listening correlates identified in resting state and DTI MRI images.

This study presents an examination of the neural connectivity associated with processing speech in noisy environments, an ability that declines with age. We correlated subjects' speech-in-noise (SIN) ability with resting-state MRI scans and Fractional Anisotropy (FA) values from the auditory section of the corpus callosum, both with and without correcting for age. The results revealed that subjects who performed poorly on the right ear SIN test (QuickSIN, MedRx) had higher correlations between the primary auditory cortex and regions of the brain that process language.

Impact of remote social interaction during the COVID-19 pandemic on the cognitive and psychological status of older adults with and without cognitive impairment: A randomized controlled study.

Background: Social isolation and loneliness have both been associated with psychological health and cognitive decline in older adults. This study investigated the impact of social interaction through remote communication technologies during the COVID-19 pandemic on the cognitive and psychological status of older adults with and without cognitive impairment.

Methods: Participants were recruited from Boston (USA) and Chieti (Italy).

Algorithmic Spaced Retrieval Enhances Long-Term Memory in Alzheimer Disease: Case-Control Pilot Study.

Background: Spaced retrieval is a learning technique that involves engaging in repeated memory testing after increasingly lengthy intervals of time. Spaced retrieval has been shown to improve long-term memory in Alzheimer disease (AD), but it has historically been difficult to implement in the everyday lives of individuals with AD.

Objective: This research aims to determine, in people with mild cognitive impairment (MCI) due to AD, the efficacy and feasibility of a mobile app that combines spaced retrieval with a machine learning algorithm to enhance memory retention.

A machine learning eye movement detection algorithm using electrooculography.

Study Objectives: Eye movement quantification in polysomnograms (PSG) is difficult and resource intensive. Automated eye movement detection would enable further study of eye movement patterns in normal and abnormal sleep, which could be clinically diagnostic of neurologic disorders, or used to monitor potential treatments. We trained a long short-term memory (LSTM) algorithm that can identify eye movement occurrence with high sensitivity and specificity.

One and done? The effect of number of Pipeline embolization devices on aneurysm treatment outcomes.

Background: Controversy exists regarding the optimum number of flow diverters for the treatment of intracranial aneurysms. We explored the effect of the number of Pipeline embolization devices (PEDs; Medtronic, Dublin, Ireland) deployed on rates of aneurysm occlusion and complications.

Methods: Consecutive patients who underwent saccular intracranial aneurysm treatment solely with the PED were included in this retrospective study.