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Updated: Oct 9, 2025
The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool
Published on: June 30, 2014
Computational basis of decision-making impairment in multiple sclerosis
Rodrigo S Fernández1, Lucia Crivelli2, María E Pedreira3
1Instituto de Fisiología, Biología Molecular y Neurociencias (IFIBYNE-CONICET), Ciudad de Buenos Aires, Argentina/Laboratorio de Neurociencia de la Memoria, IFIBYNE-CONICET, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad de Buenos Aires, Argentina.
Multiple sclerosis (MS) patients exhibit altered decision-making due to impaired learning and risk assessment. These changes correlate with cognitive deficits and mood symptoms, impacting daily functioning.
Area of Science:
- Neuroscience
- Computational Psychiatry
- Cognitive Psychology
Background:
- Multiple sclerosis (MS) is linked to decision-making, cognitive, and mood impairments.
- Traditional scoring methods may obscure the complex relationships between these MS-related symptoms.
Purpose of the Study:
- Investigate the computational underpinnings of decision-making deficits in MS.
- Examine the interaction between decision-making, neurocognition, and neuropsychiatric measures in MS.
Main Methods:
- Employed the Iowa Gambling Task (IGT) and a comprehensive neurocognitive battery.
- Utilized Hierarchical Bayesian Analysis to model decision-making parameters in 29 MS patients and 26 controls.
Main Results:
- MS patients demonstrated increased learning rates and reduced loss aversion compared to controls.
- These decision-making alterations were associated with poorer performance on the IGT, cognitive impairments (processing speed, executive function, memory), and increased depression and apathy.
Conclusions:
- Decision-making deficits in MS are influenced by a combination of computational processes, neurocognitive impairments, and mood/motivational symptoms.
- Understanding these interplays offers a more nuanced view of MS-related functional impairments.
