CENT Computerised Extrapersonal Neglect Test

The Computerized Extrapersonal Neglect Test (CENT) is a clinical neuropsychological test that assesses visual attentional performance in far space (extrapersonal/out of reach). Attentional problems are very common in several conditions such as stroke, traumatic brain injury or dementia. Patients often report missing things, having trouble with reading, finding it hard to locate their belongings or even failing to notice things around them.

CENT is a quick (5-min), automated assessment of attention in far space (extrapersonal/ out-of-reach space), suitable for individuals with cognitive, reading and/or language impairments. It was developed with brain injury survivors, their unpaid carers and clinicians. It uses a visual search task to produce precise attentional metrics automatically.

It is an openly available computerised assessment tool for attention in far space that, unlike most available tests, provides precise metrics of attentional performance, such as quality of search, search speed, search path and measures of both allocentric (object-centred) and egocentric (spatial) inattention/neglect. In addition, it allows immediate comparison of an individual’s performance to a large normative sample of people without history of a neurological disease. All calculations are done automatically so it’s easy for users to quickly detect deficits.

CENT is easy to use and research in the healthy and aging population has already been published (Morse et al., 2024). Our results with stroke survivors show that CENT is valid, sensitive to aging and attentional deficits and is correlated to stroke recovery and daily life functioning deficits (Morse et al., 2024 and Morse et al., in preparation). We therefore would like to encourage you to implement this measure in your clinical or research practice. For this reason, we have made the test open-source and free to download and use for clinicians and researchers.

The development of CENT was led by Dr. Stephanie Rossit, working the CENT research team at UEA and Evolv Rehabilitation Technologies and is shared here with their permission.