Current Projects

 
 
 
 
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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.

 
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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.

 
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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.

 
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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.

 
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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.

 
 
 
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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.