A novel statistical algorithm for mining high-dimensional spike train (count) data for significant spatio-temporal patterns reveals new insights into task and brain area dependent functional organization of neural activity.
Neurons in the lateral habenula are activated by pain, bitterness and social defeat, and their responses are dynamically shaped by learning, suggesting a role in experience-dependent selection of behavioral actions to stressors.
Dorsomedial and dorsolateral striatal neural activity differ during early learning of action sequences but do not change with performance improvement across sessions, and become similar after extended training.
Auditory cortical columns contain small subsets of neurons with highly synchronous activity (cNEs) that create robust sequences of coordinated activity suitable for enhanced information processing and signal transmission beyond the capability of individual neurons.
A two-part neural network models reward-based training and provides a unified framework in which to study diverse computations that can be compared to electrophysiological recordings from behaving animals.