Fee, MichalePh.D.Associate Department Head; Glen V. and Phyllis F. Dorflinger Professor of NeuroscienceBrain & Cognitive Sciences InvestigatorMcGovern Institute for Brain Research Building: 46-5133Email: email@example.comPhone: 6173240173Administrative Asst: O'Leary, Margarita Lab websiteProfile BottomAboutFee joined the McGovern Institute in 2003 and is currently the Glen V. and Phyllis F. Dorflinger Professor in the Department of Brain and Cognitive Sciences. He received his PhD in Applied Physics from Stanford University in 1992. Before moving to MIT, he was a principal investigator in the Biological Computation Research Department at Bell Laboratories in New Jersey. ResearchThe research in the Fee Lab has two main themes: To understand the neural and biophysical mechanisms underlying the generation and learning of complex sequences To develop advanced optical and electrical techniques for measurement of brain activity in behaving animals. We study how the brain learns and generates sequential behaviors, with a focus on the songbird as a model system. We are currently trying to understand how circuitry in two forebrain nuclei, RA and HVC, produce the complex sequence of vocal/motor gestures that comprise the song. We have recently found neurons in nucleus HVC that generate only a single brief burst in the sequence, and may form an explicit representation of time in the brain. Young songbirds learn their song by imitating a tutor. Young birds start by babbling, just as humans do, and gradually refine their highly variable juvenile songs to produce a good copy of the adult song. We are trying to understand the brain mechanisms that underlie this vocal imitation, and are focusing on a model called reinforcement learning. Reinforcement learning would suggest that the bird learns its song by ‘trial-and-error' search for the pattern of control parameters that will produce the correct song. We are currently exploring the neural origin of this ‘trial-and-error' search, and have identified a brain area that may be responsible for generating this creative vocal exploration. We are also interested in developing advanced techniques for recording electrical and optical signals from neurons in behaving animals. Recently developed techniques include a 1.5 gram motorized microdrive for chronic recording, an active electrode stabilizer for intracellular recording in awake animals, and a miniature two-photon microscope for intracellular imaging in freely behaving animals. Teaching9.29J Introduction to computational neuroscience 9.40 Introduction to neural computation PublicationsGoldberg JH, Fee MS. Singing-related neural activity distinguishes four classes of putative striatal neurons in the songbird basal ganglia. J Neurophysiol. 2010 Jan 27. [Epub ahead of print] Andalman AS, Fee MS. A basal ganglia-forebrain circuit in the songbird biases motor output to avoid vocal errors. Proc Natl Acad Sci U S A. 2009 Jul 28;106(30):12518-23. Epub 2009 Jul 13. Arfin SK, Long MA, Fee MS, Sarpeshkar R. Wireless neural stimulation in freely behaving small animals. J Neurophysiol. 2009 Jul;102(1):598-605. Epub 2009 Apr 22. Long MA, Fee MS. Using temperature to analyse temporal dynamics in the songbird motor pathway. Nature. 2008 Nov 13;456(7219):189-94.