Spatial navigation in elderly healthy subjects, amnestic and non amnestic MCI patients

Maria Luisa Rusconi1, Angelo Suardi1, Marina Zanetti2

  • 1Department of Human and Social Sciences, University of Bergamo, Italy.

Abstract

Insights

A new spatial navigation test effectively identifies differences in mild cognitive impairment (MCI) subtypes, particularly amnestic MCI. This tool aids in distinguishing MCI from normal aging and supports early detection of cognitive decline.

Area of Science:

  • Neuroscience
  • Gerontology
  • Cognitive Psychology

Background:

  • Mild cognitive impairment (MCI) represents an early stage of cognitive decline.
  • Identifying early markers for MCI conversion to dementia is crucial.
  • Topographical disorientation (TD) may help differentiate normal aging from MCI and prodromal Alzheimer's disease (AD).

Purpose of the Study:

  • To propose and validate a novel spatial navigation instrument.
  • To assess elderly healthy subjects and patients with amnestic (aMCI) and non-amnestic (naMCI) subtypes of MCI.

Main Methods:

  • A cohort of 18 healthy subjects and 18 MCI patients (9 aMCI, 9 naMCI) was studied.
  • Participants underwent a neuropsychological battery.
  • A new experimental small-scale spatial navigation test using an ideal city model was administered.

Main Results:

  • Amnestic MCI patients showed deficits in learning new routes, landmark recall, and map drawing.
  • Non-amnestic MCI patients exhibited only a slight delay in Route Forward learning compared to controls.
  • Distinct correlations between experimental subtests and neuropsychological measures were observed in MCI and healthy groups.

Conclusions:

  • The developed spatial navigation task is sensitive to spatial ability differences in MCI subtypes.
  • Subtests involving route learning, landmark retrieval, and map construction are particularly informative.
  • This tool shows promise for evaluating spatial navigation in healthy elderly individuals and MCI patients, offering a less complex alternative to existing methods.

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