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Visual Agnosia

Visual Agnosia

Visual agnosia is a condition characterized by the inability to recognize visually presented objects despite having normal vision. For instance, a person with visual agnosia can describe the shape and color of an object but cannot identify or name it. This impairment does not affect their visual field, acuity, color vision, brightness discrimination, language, or memory. An example of this condition in a social setting is someone at a dinner party asking for "that silver thing with a round end"...

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Related Experiment Video

Updated: May 28, 2026

Virtual Reality Tools for Assessing Unilateral Spatial Neglect: A Novel Opportunity for Data Collection

Virtual Reality Tools for Assessing Unilateral Spatial Neglect: A Novel Opportunity for Data Collection

Published on: March 10, 2021

Paper to Pixels: Enhancing Unilateral Neglect Assessment Using the New Computer Vision-Based Tool CANDO.

Lisa Beckmann¹, Rylan Donohoe^1,2, Doris Schmid¹

¹Clinical Neuropsychology, Department of Psychology, Ludwig-Maximilians-Universität München, 80802 Munich, Germany.

|May 27, 2026

Summary

This summary is machine-generated.

A new computer vision tool automates scoring for the Behavioural Inattention Test (BIT) and Neglect Test (NET), reducing diagnostic variability and improving the efficiency and reproducibility of unilateral neglect assessments.

Keywords:

behavioural inattention test computer vision neuropsychological assessment spatial neglect subjective scoring unilateral neglect

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Last Updated: May 28, 2026

Virtual Reality Tools for Assessing Unilateral Spatial Neglect: A Novel Opportunity for Data Collection

Virtual Reality Tools for Assessing Unilateral Spatial Neglect: A Novel Opportunity for Data Collection

Published on: March 10, 2021

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss

Published on: April 11, 2025

Area of Science:

Neuroscience
Computer Science
Medical Diagnostics

Background:

The Behavioural Inattention Test (BIT) and Neglect Test (NET) are standard tools for diagnosing neglect.
Manual scoring of these tests can be inconsistent due to subjective judgment and system limitations.

Purpose of the Study:

Introduce a novel computer vision tool for automatic scoring of BIT and NET subtests.
Evaluate the diagnostic validity and efficacy of this automated scoring tool.

Main Methods:

Manual scoring consistency was assessed across raters with varying expertise.
A computer vision tool (CANDO) was developed for automated scoring using a deterministic pipeline.
CANDO's performance was compared against ground truth for cancellation, line bisection, and copying tasks.

Main Results:

Manual scoring showed inconsistencies in diagnostic classification across raters and assessments, particularly in drawing and copying tasks.
The CANDO tool achieved high accuracy in cancellation and line bisection tasks and strong agreement in copying tasks.
Automated scoring reduced variability associated with subjective judgment, time pressure, and oversight, with minimal impact on diagnostic outcomes.

Conclusions:

Manual assessment of unilateral neglect is prone to inconsistencies.
Computer vision-based automation enhances the reproducibility and efficiency of neglect assessment.
The CANDO tool offers a practical solution for higher-quality neglect diagnosis.