Current Projects
dynamics of spontaneous cortical activity
We use a combination of two-photon imaging, whole cell recordings, real-time control, and computational modeling to characterize how the functional connectivity of neural networks leads to emergent network behavior in neocortex.
Computational Neuroscience
We use computational models as detailed, experimentally falsifiable hypotheses of physiological function. Our published models include studies of ion channels, single-neuron computation, self-organization in neural networks, and glial calcium transients.
Neuronal Synchronization
Activity in the brain is noisy but highly organized. Particularly notable are brain “rhythms,” generated by rhythmically modulated activity of neurons and readily detectable in the EEG. Using a combination of electrophysiology, computational modeling and theoretical frameworks, we study the mechanisms underlying theta and gamma oscillations.
Tools for electrophysiology and imaging
Tool-building is an essential part of our efforts. We have developed computer systems for virtual-reality-inspired electrophysiology, mouse lines for calcium imaging, and scanning methods for high-speed imaging of user-identified cells.
Hippocampal population dynamics underlying memory processing
Using electrophysiology, two-photon calcium imaging, and real-time optogenetics, we are studying hippocampal network activity underlying memory processing. Moreover, we are interested in identifying effective stimulation strategies for modulation of memories in animal models.
Effects of anesthesia on neuronal network dynamics
Despite extensive use of anesthesia for research and clinical purposes, the underlying network mechanisms are poorly understood. Using two-photon calcium imaging, voltage indicators, and computational modeling, our lab is investigating network dynamics underlying awake and anesthesized brain states.