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Human cortical organoids provide an experimentally accessible model of early neural circuit formation, yet whether their activity reflects structured information processing rather than spontaneous synchronization is unclear. We developed a graph-computational framework to quantify stimulus-evoked propagation. This includes stimulus-conditioned functional graphs, a graph-constrained dynamical (graph-neural-network) model used as a system-identification tool, a biological message-passing principle bounding integration depth by observable propagation depth, and a suite of graph-level metrics. We carried this program out in full on longitudinal HD-MEA recordings from three organoids. Once the true acquisition sampling rate and stimulus timing were recovered, the evoked response proved to be a fast, near-synchronous network burst with no measurable outward propagation (peak-latency vs. distance slope = 0). The propagation/integration-depth metrics (Deff ,reachability index, dmax) therefore do not apply, and per-day connectivity graphs were not reliably estimable at the available trial count, a negative result with methodological consequences for applying such metrics to organoid data. Reframing around synchrony, response-population size and shared variability revealed a control-validated phenomenon, i.e., repeated daily stimulation progressively depressed and spatially contracted the evoked response. That repeated stimulation reshapes organoid networks is established, but longitudinal designs in which every preparation is stimulated cannot separate this from developmental maturation. We break that confound with a developmentally-matched, stimulation-naive control, where at day 7, an organoid receiving its first-ever stimulation engaged 93% of the array, whereas organoids with five prior sessions engaged 10%.
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by synaptic dysfunction, protein aggregation, and widespread molecular alterations in the brain. In this study, we applied quantitative mass spectrometry-based proteomics and phosphoproteomics to characterize synaptosomes and sarkosyl-insoluble protein inclusions from the post-mortem frontal lobes of AD and control cases. We identified >3700 proteins across both fractions, revealing AD-associated changes in synaptic composition and phosphorylation patterns. Proteomic analyses indicated mitochondrial deficits and disruptions in vesicle trafficking within synapses, whereas insoluble protein inclusions showed an accumulation of spliceosomal components and glial activation markers as well as an enrichment of N-terminally truncated amyloid beta peptides in AD cases, suggesting involvement of postfibrillar processing events mediated by specific proteases in amyloid plaque pathology. Phosphoproteomic analysis revealed extensive alterations in pathways regulating vesicle trafficking, Golgi homeostasis, and synaptic function. We observed increased tau phosphorylation at AD-associated sites in insoluble inclusions and distinct phosphorylation changes in synaptic tau, particularly at S285 and S305, suggesting altered tau function and aggregation properties. These findings provide new molecular insights into AD-related nerve terminal composition and protein aggregation, advancing our understanding of disease-associated changes at the subcellular level.