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Alzheimer's Association International Conference 2026

July 12-15, 2026 | London, United Kingdom, and Online

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Brain Networks In Motion: EEG Signatures Distinguishing Amnestic And Non-amnestic MCI In A Visual Short-term Memory Binding Task

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Brain Networks in Motion: EEG Signatures Distinguishing Amnestic and Non-Amnestic MCI in a Visual Short-Term Memory Binding Task. 

Mild cognitive impairment (MCI) is a transitional state between healthy aging and dementia, encompassing subtypes like amnestic (aMCI) and non-amnestic MCI (naMCI). While aMCI often precedes Alzheimer’s disease, naMCI may progress to other dementias.  Task-based Electroencephalography (EEG) offers a cost-effective, non-invasive means to measure brain activity during cognitive processes. Here, we analysed EEG source-space signals from individuals with aMCI, naMCI and healthy controls to uncover functional connectivity patterns that could aid in early MCI subtype differentiation.

Figure 1: Generalized linear models adjusting for age, sex and schooling showhigher global synchrony in all canonical bands during recall in naMCIindividuals compared to controls. 

Figure 2: Wilcoxon tests show higher synchrony in naMCI compared to during encoding, and naMCI and controls during recall in the theta band, and  aMCI and controls in alpha band. 

Figure 3: Nodal synchrony shows higher activity in naMCI individuals compared to controls and aMCI in alpha band during recall.

Figure 4: Difference of activity across groups highlight disruption in cognition-specific functional pathways in  aMCI and naMCI during recall in alpha band. 

- Disruption of posterior cortical association networks involving default mode, visuospatial and thalamocortical systems. 

- Disruption of memory-guided perception and attentional integration networks. 

- Disruption in posterior visuospatial and memory networks. 

Figure 5: Nodal synchrony shows trends of higher activity in naMCIindividuals in limbic, parietal and occipital regions during recall compared to encoding phase in alpha band. 

Figure 6: Nodal synchrony showed lower trends during recall than encoding. Controls showed expected prefrontal increase during recall, while aMCI showed a slight increase and naMCI showed widespread hypersynchrony, especially in medial and posterior regions during recall.

Figure 7: Increase in global synchrony during recall is associated with lowermemory in individuals with aMCI. 

Figure 8: Individuals with aMCI shows higher synchrony is associated with poorer task performance, while naMCI showed trends of higher synchronyassociated with better performance. 

Discussion:

•During recall, naMCI exhibited global and nodalhypersynchrony, consistent with compensatorymechanisms under cognitive load. 
•In the alpha band, controls showed expected frontal recall > encoding pattern, aMCI showed a slight increase, and naMCI showed widespread increase, focused in the limbic, parietal and occipital regions. 
•Nodal differences suggest that naMCI is characterised by recall-related synchrony changes focused on posterior visuospatial and attentional systems, while differences between controls and aMCI are consistent with memory-related network disruptions.
•Higher synchrony correlates negatively with memoryduring recall, and task performance during encoding, consistent with inefficient compensation in aMCI.

Limitations: 

•Underpowered sample in naMCI group. 
•Source-space EEG estimation may lead to unreliable results within the deeper layers of the brain. 

 

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