Research focus
Our lab is interested in three main questions:
How is memory encoded as changes to complex networks of synapses and neurons, and how do these representations drift across time?
How do psychedelics change neural activity and synchrony across the brain?
How is brain-wide neural activity disrupted in mouse models of neurological and neurodevelopmental disease?
We employ a wide variety of approaches from systems neuroscience, molecular biology, and computational data science to explore how changes to synaptic plasticity and neural activity encode behavior:
CRISPR/Cas9 gene editing
In vivo two-photon imaging
Silicon probe electrophysiology (Neuropixels)
Optogenetic and pharmacogenetic perturbations
Freely moving and head-fixed behaviors
Molecules
Goal: Track dynamic expression of synaptic proteins in behaving mice
Molecular techniques:
Use CRISPR/Cas9 to label endogenous synaptic proteome
Image of millions of individual synapses in behaving mice
Synaptome imaging in mouse models of Alzheimer's and Autism Spectrum Disorder
Cells
Goal: Explore roles of specific cell types in learning and memory
Cellular techniques:
Activity-based labeling of discrete cell types
In vivo 2p imaging
Patch-clamp (in vivo & in vitro)
Optogenetic and chemogenetic perturbation
Circuits
Goal: Record brain-wide neural activity using Neuropixels probes
Circuit techniques:
Simultaneous whole-brain electrical recordings
Track activity across cortex, hippocampus, and other structures throughout entire process of learning and memory
Behavior
Goal: Observe & perturb learning and memory in behaving mice
Behavioral techniques:
Record brain-wide synaptic and neuronal activity during behavior
Freely moving & head-fixed VR
Behavior in disease models:
AD: Working memory tasks
ASD: social interaction
Current projects in the lab
Neuroscience
Tracking plasticity in millions of synapses in behaving mice
Exploring the neural architecture of psychedelic experience with high-density ephys
Using whole-brain ephys to uncover the spatiotemporal dynamics of memory encoding, storage, and retrieval
Computational
Training machine-learning algorithms to super-resolve synapses in vivo
Improving tissue registration across imaging modalities
Disease models and clinical collaborations
Longitudinal in vivo imaging of synaptic pathologies of Alzheimer’s disease
Using Neuropixels to probe brain-wide changes in activity/synchrony in mouse models of autism