Neural Correlates of Alzheimer's Disease and Mild Cognitive Impairment: A Systematic and Quantitative Meta-Analysis involving 1,351 Patients

By Matthias L. Schroeter, Timo Stein, Nina Maslowski, Jane Neumann. NeuroImage, 2009

340 citations recorded by the source corpus.

Alzheimer's disease is the most common form of dementia. Its prodromal stage amnestic mild cognitive impairment is characterized by deficits of anterograde episodic memory. The development of standardized imaging inclusion criteria has to be regarded as a prerequisite for future diagnostic systems. Moreover, successful treatment requires isolating imaging markers predicting the disease. Accordingly, we conducted a systematic and quantitative meta-analysis to reveal the prototypical neural correlates of Alzheimer's disease and its prodromal stage. To prevent any a priori assumptions and enable a data-driven approach only studies applying quantitative automated whole brain analysis were included. Finally, 40 studies were identified involving 1,351 patients and 1,097 healthy control subjects reporting either atrophy or decreases in glucose utilization and perfusion. The currently most sophisticated and best-validated of coordinate-based voxel-wise meta-analyses was applied (anatomical likelihood estimates). The meta-analysis reveals that early Alzheimer's disease affects structurally the (trans-)entorhinal and hippocampal region, functionally the inferior parietal lobules and precuneus. Results further may suggest that atrophy in the (trans-)entorhinal area/hippocampus and hypometabolism/hypoperfusion in the inferior parietal lobules predict most reliably the progression from amnestic mild cognitive impairment to Alzheimer's disease, whereas changes in the posterior cingulate cortex and precuneus are unspecific. Fully developed Alzheimer's disease involved additionally a frontomedian-thalamic network. In conclusion, the meta-analysis characterizes the prototypical neural substrates of Alzheimer's disease and its prodromal stage amnestic mild cognitive impairment. By isolating predictive markers it enables successful treatment strategies in the future and contributes to standardized imaging inclusion criteria for Alzheimer's disease as suggested for future diagnostic systems.

Subfields: Cognitive Neuroscience, Physiology, Psychiatry and Mental health

View Paper: https://www.semanticscholar.org/paper/32df114d104e302aa865c27ddbac2828d56529d9

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In Cognitive Neuroscience

1. Heung-Il Suk
2. Dinggang Shen
3. Seong-Whan Lee

In Physiology

1. Heung-Il Suk
2. Dinggang Shen
3. Seong-Whan Lee

In Psychiatry and Mental health

1. Heung-Il Suk
2. Dinggang Shen
3. Seong-Whan Lee
4. Yanqing Zhang
5. Jyoti Islam
6. Guorong Wu

Citations in the corpus

• Latent feature representation with stacked auto-encoder for AD/MCI diagnosis (2013, background): “…et al. 2012; Wal-hovd et al. 2010), and also the regions of supramarginal gyrus (Buckner et al. 2005; Desikan et al. 2009; Dickerson et al. 2009; Schroeter et al. 2009), angular gyrus (Schroeter et al. 2009; Nobili et al. 2013; Yao et al. 2012), superior parietal lobule, precuneus, cuneus…”