The primate visual cortex (V1) and prefrontal cortex (PFC) support distinct computational roles: neurons in V1 respond with high fidelity to synaptic inputs, enabling precise encoding of visual features, whereas PFC neurons integrate and filter information to support higher-order functions such as working memory, cognitive flexibility, and decision-making. A central question is how the intrinsic (in vitro) electrical properties of neurons in these regions shape their circuit dynamics and thereby influence the neural codes engaged during behavior. To address this, our collaborators in the Martinez-Trujillo Lab (Western University) performed whole-cell recordings from marmoset V1 and PFC. We used these datasets to conduct both supervised and unsupervised clustering of neuronal electrophysiological signatures. The supervised approach, based on spike width and spike amplitude, identified broad-spiking (BS) and narrow-spiking (NS) neurons in both regions. Unsupervised clustering, employing the Allen Institute feature-extraction framework, revealed seven distinct electrophysiological clusters. Although the cluster identities were largely conserved across V1 and PFC, the proportion of neurons populating each cluster differed across areas, suggesting that while intrinsic phenotypes are shared, their distributions are region-specific. To examine how these intrinsic features contribute to circuit-level behavior, we developed Hodgkin–Huxley (HH) models of BS and NS neurons in both regions and fit them directly to the key features used for clustering, yielding close quantitative agreement with the empirical data. Bifurcation analyses of these models were then performed to characterize their excitability classes and firing regimes, after which we embedded the HH neurons into networks with different coupling topologies to probe circuit dynamics and synchrony. We are extending this work by incorporating neuronal heterogeneity within and across regions and by developing hybrid models that integrate in vivo recordings with in vitro–derived intrinsic dynamics. As a proof of concept for this hybrid approach, we have conducted a similar hybrid modeling approach in macaques PFC to quantify how intrinsic spike-frequency adaptation contributes to adaptation observed in vivo. In this talk, I will provide an overview of these findings and ongoing efforts.