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Updated: Sep 28, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Behavioral characterization of mild cognitive impairment
Alexander Collie1, Paul Maruff, Jon Currie
1Neuropsychology Laboratory, Mental Health Research Institute of Victoria, Parkville, Victoria, Australia. acollie@cogstate.com
Abstract:
Results from recent investigations of behavioral and genetic outcomes in older people with mild cognitive impairment (MCI) have been inconsistent. These conflicting results may be attributed to between-study differences in the diagnostic systems employed, as well as the use of unreliable neuropsychological measures. We investigated behavioral and genetic outcomes in older people classified as having MCI according to novel criterion that required evidence of cognitive impairment on three consecutive neurological/neuropsychological assessments. One hundred and seventy four healthy older people were evaluated semi-annually for 12 months. Of these, 23 subjects were rated as having MCI on three consecutive assessments and were compared to 23 matched control subjects. Subjects rated as impaired on one or two of the three semi-annual assessments were also identified. MCI and matched control groups were compared on a range of behavioral measures. The prevalence of the Apolipoprotein E4 (ApoE4) allele was determined in all groups, and estimates of anxiety and depressive symptomatology were obtained. Subjective cognitive complaints were also assessed. Many subjects were classified as impaired on one or two assessments, however relatively few (n = 23) recorded consistent cognitive deficits. The most severe impairment observed in MCI subjects was on a test of pattern-location associative learning, however MCI subjects did not have insight into this impairment. The prevalence of the ApoE4 allele was not different between matched control and MCI groups. These results indicate that individuals with MCI can be differentiated from healthy older people and older people with transient cognitive impairments, but that such differentiation requires serial assessment of cognitive function.
Insights
Consistent mild cognitive impairment (MCI) in older adults requires serial assessment for accurate diagnosis. This study differentiated MCI from transient cognitive issues using novel criteria, highlighting pattern-location learning deficits.
Area of Science:
- Neuroscience
- Gerontology
- Cognitive Psychology
Background:
- Inconsistent findings in mild cognitive impairment (MCI) research stem from varied diagnostic criteria and unreliable neuropsychological tests.
- Differentiating true MCI from temporary cognitive changes is crucial for accurate diagnosis and intervention in older adults.
Purpose of the Study:
- To investigate behavioral and genetic outcomes in older adults with MCI using a novel, stringent diagnostic criterion.
- To compare individuals with consistent MCI to healthy controls and those with transient cognitive impairments.
Main Methods:
- Evaluated 174 healthy older adults semi-annually for 12 months.
- Applied a novel MCI criterion requiring cognitive impairment on three consecutive assessments.
- Compared 23 MCI subjects with 23 matched controls on behavioral measures, including pattern-location associative learning.
- Assessed Apolipoprotein E4 (ApoE4) allele prevalence, anxiety, depressive symptoms, and subjective cognitive complaints.
Main Results:
- Few subjects (n=23) met the strict MCI criteria, distinguishing them from those with transient impairments.
- MCI subjects showed the most significant deficits in pattern-location associative learning.
- No difference in Apolipoprotein E4 (ApoE4) allele prevalence was found between MCI and control groups.
- MCI subjects lacked insight into their associative learning impairment.
Conclusions:
- Individuals with mild cognitive impairment (MCI) can be reliably differentiated from healthy older adults and those with temporary cognitive deficits.
- Serial neuropsychological assessment is essential for accurate diagnosis of MCI.
- Pattern-location associative learning deficits may be a key indicator of MCI, even without subjective awareness.
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