Virtual brain and electroencephalography explain the variance of memory alterations in mild cognitive impairment

Background Mild Cognitive Impairment (MCI) is a heterogeneous clinical condition characterized by a wide spectrum of cognitive and behavioural manifestations. Despite numerous studies, the link between neuropsychological performance and pathophysiological signatures of the disease - including Aβ and tau accumulation along with altered excitation/inhibition (E/I) balance and brain rhythms - remains elusive. Methods Here Aβ/tau biomarkers were used to distinguish positive (MCI ⁺ - prodromal AD) and MCI ⁻ subjects. Virtual brain models based on high-field MRI data were then developed to determine the inter-node coupling and E/I profile in resting-state networks, while node spectral information was obtained from source analysis of high-density electroencephalography (HD-EEG). Finally, virtual brains and HD-EEG parameters, creating brain digital twins of individual subjects, were correlated with cognitive performance. Results While virtual brain simulations did not reveal E/I differences between MCI ⁺ and MCI ⁻ , a positive correlation emerged between synaptic parameters of the limbic network and verbal episodic memory for both groups. EEG power spectral density revealed a lower high-frequency/low-frequency ratio in MCI ⁺ largely due to a reduced alpha band in the default mode, limbic, attention, frontoparietal, visual and somatomotor networks. The combination of HD-EEG and virtual brain parameters explained up to 90% of patients’ variance in episodic memory scores, going beyond the sensitivity of individual measures alone. Conclusion This multimodal and multiparametric analysis combining virtual brain modelling with MRI, HD-EEG, and molecular data enhances the stratification of MCI patients and could be used to develop digital biomarkers of progression to dementia, opening new perspectives for personalized prognosis and treatment.