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Cortex Cognition

Paula Bolger, Cortex Cognition


Cortex Cognition is a neuroscience technology spin-out company from TCD developing state-of-the-art Virtual Reality-based neuropsychological assessments for use in clinical trials, academic research and healthcare provision.

Cortex Cognition has developed a suite of immersive Virtual Reality neuropsychological assessments which are designed to address the limitations of traditional neuropsychological paper-and-pencil assessments which are lengthy, labour-intensive, vulnerable to human error, and associated with practice effects.

Cortex Cognition’s neuropsychological assessments are designed to be more cognitively challenging, to minimise variability in learning strategies and to assess for crucial everyday processes of spatial memory which are related to early stage Alzheimer’s disease impairment.

Cortex Cognition assessments incorporate improvements in test administration including sophisticated speech recognition, Virtual Reality, eye-tracking and other advanced human–computer interface and machine learning technologies.

Cortex Cognition aims to detect subtle changes in cognition which will improve the sensitivity and specificity of diagnosis, help identify appropriate participants for clinical trials, and improve the assessment of therapeutic responses.

According to the World Health Organisation, dementia is the biggest healthcare challenge of the 21st century. In the U.S. and U.K. 1 in 2 people never receive a formal diagnosis and 1 in 3 seniors die with a form of dementia. There is a need for cost-effective and sensitive tests for the early screening and diagnosis of dementia. According to the Alzheimer’s Association International (2018), early and accurate diagnosis could save up to $7.9 billion dollars in medical and healthcare costs. Cortex Cognition is working with Trinity College Dublin, neurology clinics and Clinical Research Organisations (CROs) to complete a series of clinical studies which focus on demonstrating that the neuropsychological assessments are sensitive to detecting early disease states and converge with biological markers of Alzheimer’s disease pathology.


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