Brain-related Research

Hand drawing by Ramon Y Cajal of neurons
     found in chick cerebellu Axel figure

On the left: Drawing from Ramon y Cajal's first publication on the central nervous system, showing the five classes of neurons in the cerebellum: A, Purkinje cell; D, stellate cell; F, Golgi cell; H, granule cell; S, basket cell axons., From the Instituto de Neurobiologia "Ramon y Cajal", Madrid, Spain.
On the right: Modern imaging from Richard Axel's lab of neurons in a fly's olfactory system, showing projection neurons labeled in green extending dendrites to glomeruli in the antennal lobe and axons to the mushroom body calyx and lateral horn of the protocerebrum.

Birdsong: My group is currently collaborating with Richard Mooney's birdsong group to understand the neural circuitry of auditory-guided vocal learning in songbirds, since this is a promising experimental paradigm for investigating the neural basis of human speech. Of especial interest is to understand how the nuclei of the premotor pathway (HVc and RA) and of the anterior forebrain pathway (X to DLM to lMAN to X) coordinate their activities so that young songbirds can learn the adult songs appropriate to their species.

Olfaction: A few years ago, I spent a sabbatical year in the laboratory of Dr. Larry Katz, whose group carries out research on mammalian olfaction. Key questions are how do the spatiotemporal electrochemical patterns of the main olfactory bulb and of the accessory olfactory bulb enable an animal to classify odors, to remember odors, and to identify certain mixtures of odors (e.g., pheromone) as a unique perception.

EEG data analysis: I have collaborated with Dr. Andrew Krystal of Duke University's Medical Center on applications of nonlinear dynamics to the analysis of EEG data derived in the context of helping severely depressed patients by electorconvulsive therapy (ECT). While the longer-term clinical goal is to find ways to improve the efficacy of ECT treatments, a shorter term research goal was to understand how to take into account the strongly nonstationary character of a given EEG recording and how to detect and take into account the substantial statistical variability of EEG recordings, even when data from one patient is compared with data of the same patient a week later. Andrew and I are also interested in some of the questions that fascinate many other people about EEG data, e.g,, how much cognitive and clinical information can be extracted from an EEG, which represents a coarse averaging of signals from millions of cortical neurons?

Birdsong links.

Olfaction links.

Neurobiology researchers.

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