Nonlinear Dynamical Modeling of Behavior and Multimodal Neural Data
Parastoo Azizeddin, Eray Erturk, Maryam Shanechi · COSYNE 2025
Multimodal data fusion can facilitate a more complete understanding of neural dynamics. In neuroscience, modalities such as neuronal spiking activity, local field potentials (LFPs), and behavioral signals capture various aspects of brain processes. By leveraging the complementary strengths of different modalities, multimodal fusion can not only construct a rich and unified representation of brain processes, but also address the limitations of single-modality analyses---such as incomplete or noisy data. An exciting recent direction has been to build models of simultaneously recorded neural and
ePoster · Neuroscience