Abstract
A modification to the standard estimation–maximization algorithm is presented, that allows the identification of neural ensemble states without predetermination of the number of states. Since the actual number of states a neural ensemble goes through in a given time period may vary from trial to trial, this represents a better description than using a predetermined, fixed number of states. The algorithm is used to identify ensemble states of simultaneously recorded neurons in the prefrontal cortex of behaving monkeys while they were freely viewing scenes containing multiple objects. We demonstrate that state transitions are correlated with behavioral and trial events.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
