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Delayed and More Variable Unimanual and Bimanual Finger Tapping in Alzheimer's Disease: Associations with Biomarkers
Vincent Koppelmans1,2, Marit F L Ruitenberg3,4, Sydney Y Schaefer5
1Department of Psychiatry, University of Utah, Salt Lake City, UT, USA.
Background:
Despite reports of gross motor problems in mild cognitive impairment (MCI) and Alzheimer's disease (AD), fine motor function has been relatively understudied.
Objective:
We examined if finger tapping is affected in AD, related to AD biomarkers, and able to classify MCI or AD.
Methods:
Forty-seven cognitively normal, 27 amnestic MCI, and 26 AD subjects completed unimanual and bimanual computerized tapping tests. We tested 1) group differences in tapping with permutation models; 2) associations between tapping and biomarkers (PET amyloid-β, hippocampal volume, and APOEɛ4 alleles) with linear regression; and 3) the predictive value of tapping for group classification using machine learning.
Results:
AD subjects had slower reaction time and larger speed variability than controls during all tapping conditions, except for dual tapping. MCI subjects performed worse than controls on reaction time and speed variability for dual and non-dominant hand tapping. Tapping speed and variability were related to hippocampal volume, but not to amyloid-β deposition or APOEɛ4 alleles. Random forest classification (overall accuracy = 70%) discriminated control and AD subjects, but poorly discriminated MCI from controls or AD.
Conclusions:
MCI and AD are linked to more variable finger tapping with slower reaction time. Associations between finger tapping and hippocampal volume, but not amyloidosis, suggest that tapping deficits are related to neuropathology that presents later during the disease. Considering that tapping performance is able to differentiate between control and AD subjects, it can offer a cost-efficient tool for augmenting existing AD biomarkers.
Insights
Fine motor skills, specifically finger tapping, are impaired in Alzheimer's disease (AD) and mild cognitive impairment (MCI). Tapping performance can help differentiate AD from controls, offering a potential biomarker.
Area of Science:
- Neuroscience
- Gerontology
- Biomarkers
Background:
- Fine motor function is understudied in mild cognitive impairment (MCI) and Alzheimer's disease (AD), despite known gross motor deficits.
- Investigating fine motor impairments can provide new insights into the progression of cognitive decline.
Purpose of the Study:
- To assess finger tapping performance in individuals with AD, MCI, and healthy controls.
- To determine the relationship between finger tapping metrics and established AD biomarkers.
- To evaluate the potential of finger tapping for classifying cognitive status (MCI/AD).
Main Methods:
- Computerized unimanual and bimanual finger tapping tests were administered to 47 cognitively normal, 27 MCI, and 26 AD subjects.
- Group differences were analyzed using permutation models.
- Associations with biomarkers (amyloid-β PET, hippocampal volume, APOEɛ4) were examined via linear regression.
- Machine learning (random forest) was employed to assess classification accuracy.
Main Results:
- AD subjects exhibited slower reaction times and greater speed variability than controls, except in dual-task tapping.
- MCI subjects showed deficits in reaction time and speed variability, particularly with non-dominant hand and dual-task tapping.
- Finger tapping speed and variability correlated with hippocampal volume but not with amyloid-β deposition or APOEɛ4 status.
- Random forest classification achieved 70% accuracy in distinguishing controls from AD, but struggled to differentiate MCI from controls or AD.
Conclusions:
- Impaired finger tapping, characterized by slower reaction times and increased variability, is associated with MCI and AD.
- Finger tapping deficits may reflect neuropathological changes related to hippocampal volume, suggesting later-stage disease involvement.
- Finger tapping offers a cost-effective method for augmenting existing Alzheimer's disease biomarkers, particularly for differentiating AD from healthy controls.
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