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Paper   IPM / Cognitive Sciences / 17495
School of Cognitive Sciences
  Title:   Brain Representation of Animal and Non-Animal Images in Patients with Mild Cognitive Impairment and Alzheimer's Disease
1.  H. Marefat
2.  Z. Vahabi
3.  N. Afzalian
4.  M. Khanbagi
5.  H. Karimi
6.  F. Ebrahiminia
7.  C. Kalafatis
8.  M. Modarres
9.  S. Khaligh-Razavi
  Status:   Published
  Journal: J Alzheimers Dis Rep .
  Vol.:  7
  Year:  2023
  Supported by:  IPM
Background: In early Alzheimer's disease (AD), high-level visual functions and processing speed are impacted. Few functional magnetic resonance imaging (fMRI) studies have investigated high-level visual deficits in AD, yet none have explored brain activity patterns during rapid animal/non-animal categorization tasks. Objective: To address this, we utilized the previously known Integrated Cognitive Assessment (ICA) to collect fMRI data and compare healthy controls (HC) to individuals with mild cognitive impairment (MCI) and mild AD. Methods: The ICA encompasses a rapid visual categorization task that involves distinguishing between animals and non-animals within natural scenes. To comprehensively explore variations in brain activity levels and patterns, we conducted both univariate and multivariate analyses of fMRI data. Results: The ICA task elicited activation across a range of brain regions, encompassing the temporal, parietal, occipital, and frontal lobes. Univariate analysis, which compared responses to animal versus non-animal stimuli, showed no significant differences in the regions of interest (ROIs) across all groups, with the exception of the left anterior supramarginal gyrus in the HC group. In contrast, multivariate analysis revealed that in both HC and MCI groups, several regions could differentiate between animals and non-animals based on distinct patterns of activity. Notably, such differentiation was absent within the mild AD group. Conclusions: Our study highlights the ICA task's potential as a valuable cognitive assessment tool designed for MCI and AD. Additionally, our use of fMRI pattern analysis provides valuable insights into the complex changes in brain function associated with AD. This approach holds promise for enhancing our understanding of the disease's progression.

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