Topic: widefield calcium imaging

Classification of behavior from multi-regional neural data sequentially in time can help in the early detection of behavior, which may provide important ways to provide corrective neural stimulation before the onset of behavior. Recurrent Neural Networks (RNNs) are designed for time-series data: they take in sequential inputs and predict the class of the sequence using recurrent hidden states that are able to retain a memory of previous inputs. However, standard RNNs cannot guarantee the classification at earlier points of the sequence; they are traditionally designed to achieve correct classi

The brain is remarkably flexible, and appears to instantly reconfigure its processing depending on what’s needed to solve a task at hand: fMRI studies indicate that distal brain areas appear to fluidly couple and decouple with one another depending on behavioral context. We investigated how the brain coordinates its activity across areas to inform complex, top-down control behaviors. Animals were trained to perform a novel brain machine interface task to guide a visual cursor to a reward zone, using activity recorded with widefield calcium imaging. This allowed us to screen for cortical areas