Early and accurate detection of Alzheimer's disease (AD) from Magnetic Resonance Imaging (MRI) scans is crucial for clinical intervention. A novel S3Net, a Synthesis–Segmentation–Spiking Network, is proposed for this purpose. It integrates synthetic MRI generation, pathology-aware segmentation, and spike-based classification. The Synthesis Network uses a generative adversarial network framework. In this stage, original MRIs are fused with lesion-only patches from disease-relevant regions. This f