Cognitive and motor behaviors in Alzheimer’s, Parkinson’s, and Healthy individuals during the ViewMind 3-D Task

Sep 30, 2026

Uploaded by Theodore

Background: Oculomotor behaviors linked to cognitive performance can distinguish neurodegeneration trajectories leading to Alzheimer’s disease (AD) or Parkinson’s disease (PD). The study evaluated whether ViewMind technology (virtual reality, hand movement sensors, eye tracking, and the 3D Spheres Touching Task) differentiates cognitive and motor profiles among symptomatic AD, asymptomatic mutation carriers (ASYMPTAD), PD patients with and without MCI (PDMCI), and controls (HC). Methods: 76 ASYMPTAD, 16 AD, 45 PD, 10 PDMCI, and 62 HC completed standard neuropsychological tests and the 3DT, measuring visual detection, tracking, and hand initiation. Results: Tracking accuracy and visual and hand reaction times varied by clinical group, with ASYMPTAD and HC showing the most targets and PDMCI/PD/AD patterns in accuracy and reaction-time metrics. Conclusion: ViewMind’s 3DT identifies discriminable cognitive and motor profiles across neurodegenerative diseases during ecologically valid tasks.

LanguageEnglish

CategoryHealthcare

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Pages2

Reading Time5 min

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Abstract

Background

Methods

Results

Conclusion

References

DOI: 10. 1002/alz70856_106668 BIOMARKERS POSTER PRESENTATION BIOMARKERS (NON-NEUROIMAGING) Cognitive and motor behaviors in Alzheimer’s, Parkinson’s, and Healthy individuals during the ViewMind 3-D Task Gerardo Fernández1 Luis Mendez2 Ramiro Linares4 Gustavo Sgrilli4 David Aguillon2 Gustavo Echeverria5 David Orozco3 Danilo Verge6 Mario AA Parra7 1ViewMind Inc., New York, NY, USA 2 Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellin, Colombia 3 Clínica Privada Bahiense, Bahía Blanca, Argentina 4Axis Neurociencias, Bahia Blanca, Argentina 5AXIS, Bahia Blanca, San Martín 724, Argentina 6ViewMind, NY, NY, USA 7 University of Strathcylde, Glasgow, Glasgow, United Kingdom Correspondence Gerardo Fernández, ViewMind Inc., New York, NY, USA. [Email:](Email: gerardofernandez480@gmail.com)[ gerardofernandez480@gmail.com](Email: gerardofernandez480@gmail.com) Abstract Background: Oculomotor behaviors linked to cognitive performance can differentiate between the trajectories of neurodegeneration (ND) that lead to Alzheimer’s disease (AD) (Fernández (Fernandez et al., 2022) or Parkinson’s Disease (PD) (Mosimann et al., 2005). We investigated whether ViewMind technology, which combines Virtual Reality, Hand Movement Sensors (HMS), eye tracking (ET) and 3D Spheres Touching Task (3DT) identifies different cognitive and motor behaviors among symptomatic (AD) and asymptomatic carriers (ASYMPTAD) of the mutation E280A-PSEN1 from Antioquia, Colombia, PD patients (without and with MCI – PDMCI), and Controls (HC). Methods: We recruited 76 ASYMPTAD (age 32.5±8. 1), 16 AD (age 66.6±8. 5), 45 PD (age 64.5±9.4, 10 PDMCI (age 68.2±9.8) and 62 HC (age 34± 10. 2). All performed standard neuropsychological tests and the 3DT. The task assesses the ability to detect 3D visual targets (i.e., visual accuracy and reaction time), to track these targets as they move from the background to the subject (i.e., tracking accuracy), and hand movement initiation towards targets (i.e., hand accuracy and reaction time). Results: Tracking accuracy, hand reaction time, and visual reaction time as a function of the number of touched targets were more affected in AD, PD, and PDMCI patients when compared to ASYMPTAD and HC. ASYMPTAD and HC reached the most significant number of targets. Mean tracking accuracy followed the pattern PDMCI> PD > AD > HC & ASYMPTAD (p <0.0001). Mean hand reaction time followed the pattern PDMCI > AD> PD> HC&ASYMPTAD(p <0.0001). Mean visual reaction time followed the pattern AD > PDMCI > PD > HC & ASYMPTAD (p = 0.006). Conclusion: ViewMind’s 3DT identifies cognitive and motor profiles across neurodegenerative diseases. Impairments were apparent in and discriminable between clinical groups with (PD) or without (AD) predominant movement disordersand lacking in non-clinical samples (HC & ASYMPTAD). Available assessments cannot This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2025 The Alzheimer’s Association. Alzheimer’s & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer’s Association. Alzheimer’s Dement. 2025;21(Suppl. 2):e106668. [https://doi.org/10.1002/alz70856_106668](https://doi.org/10.1002/alz70856_106668) wi[leyonlinelibrary.com/journal/alz](leyonlinelibrary.com/journal/alz) 1of2 BIOMARKERS identify the interplay of motor and cognitive control during ongoing ecologically valid tasks. This highlights the role of this novel technology in refining theories and applications of visual-motor integration tasks in ND diseases. References 1. Fernandez et al. (2022). Alzheimer’s & Dementia, 18(S5), e066784. 2. Mosimann et al. (2005). Brain, 128: 1267–76.

FAQs

What technology and task were used to assess cognitive and motor behavior?

The study used ViewMind technology combining virtual reality, hand movement sensors, eye tracking, and the 3D Spheres Touching Task (3DT). The 3DT evaluated visual detection, tracking as targets moved, and hand initiation toward targets.

Which participant groups were compared in the analysis?

Participants included symptomatic AD, asymptomatic mutation carriers (ASYMPTAD of E280A-PSEN1), PD patients without MCI, PD patients with MCI (PDMCI), and healthy controls (HC).

What were the main outcome differences across groups?

Tracking accuracy, hand reaction time, and visual reaction time differed across AD, PD, and PDMCI compared with ASYMPTAD and HC. Mean tracking accuracy and hand reaction time showed group-specific ordering, while mean visual reaction time followed a different significant pattern.

Sep 30, 2026

Uploaded by Theodore