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. 2021 Jul-Aug;23(4):143-149.
doi: 10.7224/1537-2073.2020-007. Epub 2020 Oct 16.

Effectiveness of Three-Dimensional Multiple-Object Tracking in Patients with Multiple Sclerosis: A Pilot Trial

Sebastian Harenberg, Jennifer St Onge, Jill Robinson, Omorowa Eguakun, Anthony Feinstein, Kim Dorsch, Rumit Singh Kakar, Raghig Abdulhakim, Zia Rehman, Melad Shawush, Vinesh Pillay

Effectiveness of Three-Dimensional Multiple-Object Tracking in Patients with Multiple Sclerosis: A Pilot Trial

Sebastian Harenberg et al. Int J MS Care. 2021 Jul-Aug.

Abstract

Background: Computerized cognitive training remains an attractive supplemental modality to enhance rehabilitation in multiple sclerosis (MS). The objective of the present study was to assess the usability of three-dimensional multiple-object tracking (3D-MOT) in patients with MS.

Methods: In this pilot study, 16 patients with relapsing-remitting MS and nine age-matched controls participated in four 30-minute training sessions of 3D-MOT. Computerized neuropsychological tests, including driving readiness (ie, Useful Field of View) and cognitive function (ie, Stroop Color and Word Test, Paced Visual Serial Addition Test, Symbol Digit Modalities Test) were conducted at baseline and at the conclusion of training.

Results: Although scoring lower in 3D-MOT, the MS group improved their 3D-MOT scores in similar magnitude as the control group. The 3D-MOT training led to significant improvements in driving readiness in the MS group. Taken together, 3D-MOT training showed similar effectiveness in patients with MS as in age-matched controls.

Conclusions: Training with 3D-MOT may be an accessible and remotely administrable supplement to cognitive rehabilitation protocols for patients with MS.

Keywords: Attention; Cognition; Multiple sclerosis (MS); Multiple-object tracking; Rehabilitation.

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Conflict of interest statement

Financial Disclosures: Dr Feinstein has received speakers’ honoraria from Novartis, Merck Serono, Roche, and Sanofi Genzyme. The other authors declare no conflicts of interest.

Figures

Figure 1.
Figure 1.
Example of three-dimensional (3D) multiple-object tracking task steps a) Eight spheres are displayed in a 3D space; b) four of the spheres are indexed and highlighted by a red halo for 1 second. c) The highlighted spheres return to normal color, and all spheres begin to move in the 3D space for 8 seconds. d) The spheres come to a halt and the observer needs to identify the previously highlighted spheres. e) Feedback is provided regarding whether the selected spheres were the correct choice. Images reprinted from Faubert J. Professional athletes have extraordinary skills for rapidly learning complex and neutral dynamic visual scenes. Sci Rep. 2013;3:1154. doi:10.1038/srep01154. Creative Commons Attribution (CC-BY 3.0).
See this image and copyright information in PMC

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