Understanding the dynamical transformation of neural activity to behavior requires new
capabilities to nonlinearly model, dissociate and prioritize behaviorally relevant neural …

Neuropsychiatric disorders such as major depression are a leading cause of disability
worldwide with standard treatments, including psychotherapy or medication, failing many …

Objective. Investigating neural population dynamics underlying behavior requires learning
accurate models of the recorded spiking activity, which can be modeled with a Poisson …

Objective. Learning dynamical latent state models for multimodal spiking and field potential
activity can reveal their collective low-dimensional dynamics and enable better decoding of …

In the past decades, functional MRI research has investigated task processing in largely
static fashion based on evoked responses during blocked and event-related designs …

Event-related potentials (ERPs) can quantify brain responses to reveal the neural
mechanisms of sensory perception. However, ERPs often reflect nonlinear mixture …

The detection of events in time-series data is a common signal-processing problem. When
the data can be modeled as a known template signal with an unknown delay in Gaussian …

One of the central goals of neuroscience is to gain a mechanistic understanding of how the
dynamics of neural circuits give rise to their observed function. A popular approach towards …

Neural dynamics assumes to reflect computations that relay and transform information in the
brain. Previous studies have identified the neural population dynamics in many individual …

Neural activity in the motor cortex dynamically evolves to plan and generate movement. How
motor cortex adapts to dynamic environments or perturbations remains to be fully explored …