1 citations · 1 across the 3 of their papers we have counts for
4 papers
Inferring Multi-Timescale Neural Dynamics with Switching Linear Dynamical Systems
Lulu Gong, Yongxu Zhang, Shreya Saxena
Neural activity often exhibits multiple timescales that can vary with behavioral states and task conditions. Identifying these timescales from neural recordings is important for be…
Integrative neurocybernetic modeling in the era of large-scale neuroscience
Il Memming Park, Ayesha Vermani, Gonzalo G. de Polavieja +12
Large-scale neuroscience is generating rich datasets across animals, brain areas, and behavioral contexts, yet our modeling efforts remain fragmented across isolated experiments. W…
Learning Mixtures of Linear Dynamical Systems via Hybrid Tensor-EM Method
Lulu Gong, Shreya Saxena
Mixtures of linear dynamical systems (MoLDS) provide a path to model time-series data that exhibit diverse temporal dynamics across trajectories. However, its application remains c…
Embodied sensorimotor control: computational modeling of the neural control of movement
Muhammad Noman Almani, John Lazzari, Jeff Walker +1
We review how sensorimotor control is dictated by interacting neural populations, optimal feedback mechanisms, and the biomechanics of bodies. First, we outline the distributed ana…