Development of a Speech-based Composite Score for Remotely Quantifying Language Changes in Frontotemporal Dementia.

Background: Changes to speech and language are common symptoms across different subtypes of frontotemporal dementia (FTD). These changes affect the ability to communicate, impacting everyday functions. Accurately assessing these changes may help clinicians to track disease progression and detect response to treatment.

Using Digital Speech Assessments to Detect Early Signs of Cognitive Impairment.

Detecting early signs of cognitive decline is crucial for early detection and treatment of Alzheimer's Disease. Most of the current screening tools for Alzheimer's Disease represent a significant burden, requiring invasive procedures, or intensive and costly clinical testing. Recent findings have highlighted changes to speech and language patterns that occur in Alzheimer's Disease, and may be detectable prior to diagnosis.

Correlating natural language processing and automated speech analysis with clinician assessment to quantify speech-language changes in mild cognitive impairment and Alzheimer's dementia.

Background: Language impairment is an important marker of neurodegenerative disorders. Despite this, there is no universal system of terminology used to describe these impairments and large inter-rater variability can exist between clinicians assessing language. The use of natural language processing (NLP) and automated speech analysis (ASA) is emerging as a novel and potentially more objective method to assess language in individuals with mild cognitive impairment (MCI) and Alzheimer's dementia (AD).

Evaluation of Speech-Based Digital Biomarkers: Review and Recommendations.

Speech represents a promising novel biomarker by providing a window into brain health, as shown by its disruption in various neurological and psychiatric diseases. As with many novel digital biomarkers, however, rigorous evaluation is currently lacking and is required for these measures to be used effectively and safely. This paper outlines and provides examples from the literature of evaluation steps for speech-based digital biomarkers, based on the recent V3 framework (Goldsack et al.

Human fMRI reveals that delayed action re-recruits visual perception.

Behavioral and neuropsychological research suggests that delayed actions rely on different neural substrates than immediate actions; however, the specific brain areas implicated in the two types of actions remain unknown. We used functional magnetic resonance imaging (fMRI) to measure human brain activation during delayed grasping and reaching. Specifically, we examined activation during visual stimulation and action execution separated by a 18-s delay interval in which subjects had to remember an intended action toward the remembered object.

Executive deficits detected in mild Alzheimer's disease using the antisaccade task.

The antisaccade task, a hands- and language-free metric, may provide a functional index of the dorsolateral prefrontal cortex (DLPFC), a region damaged in the later stages of Alzheimer's disease (AD). Our objective was to determine if patients with mild AD made more errors relative to age-matched controls. Thirty patients with mild AD (Mini Mental Status Exam [MMSE] ≥ 17) and 31 age-matched controls completed a laptop version of the prosaccades and antisaccades tasks.

Antisaccades: a probe into the dorsolateral prefrontal cortex in Alzheimer's disease. A critical review.

The number of people living with Alzheimer's disease (AD), the major cause of dementia, is projected to increase dramatically over the next few decades, making the search for treatments and tools to measure the progression of AD increasingly urgent. The antisaccade task, a hands- and language-free measure of inhibitory control, has been utilized in AD as a potential diagnostic test. While antisaccades do not appear to differentiate AD from healthy aging better than measures of episodic memory, they may still be beneficial.