Education & Certifications
Bachelor of Arts, Harvard University, Molecular and Cellular Biology (2011)
Genetically Encoded Voltage Indicators: Opportunities and Challenges.
journal of neuroscience
2016; 36 (39): 9977-9989
A longstanding goal in neuroscience is to understand how spatiotemporal patterns of neuronal electrical activity underlie brain function, from sensory representations to decision making. An emerging technology for monitoring electrical dynamics, voltage imaging using genetically encoded voltage indicators (GEVIs), couples the power of genetics with the advantages of light. Here, we review the properties that determine indicator performance and applicability, discussing both recent progress and technical limitations. We then consider GEVI applications, highlighting studies that have already deployed GEVIs for biological discovery. We also examine which classes of biological questions GEVIs are primed to address and which ones are beyond their current capabilities. As GEVIs are further developed, we anticipate that they will become more broadly used by the neuroscience community to eavesdrop on brain activity with unprecedented spatiotemporal resolution.Genetically encoded voltage indicators are engineered light-emitting protein sensors that typically report neuronal voltage dynamics as changes in brightness. In this review, we systematically discuss the current state of this emerging method, considering both its advantages and limitations for imaging neural activity. We also present recent applications of this technology and discuss what is feasible now and what we anticipate will become possible with future indicator development. This review will inform neuroscientists of recent progress in the field and help potential users critically evaluate the suitability of genetically encoded voltage indicator imaging to answer their specific biological questions.
View details for DOI 10.1523/JNEUROSCI.1095-16.2016
View details for PubMedID 27683896
Subcellular Imaging of Voltage and Calcium Signals Reveals Neural Processing In Vivo
2016; 166 (1): 245-257
A mechanistic understanding of neural computation requires determining how information is processed as it passes through neurons and across synapses. However, it has been challenging to measure membrane potential changes in axons and dendrites in vivo. We use in vivo, two-photon imaging of novel genetically encoded voltage indicators, as well as calcium imaging, to measure sensory stimulus-evoked signals in the Drosophila visual system with subcellular resolution. Across synapses, we find major transformations in the kinetics, amplitude, and sign of voltage responses to light. We also describe distinct relationships between voltage and calcium signals in different neuronal compartments, a substrate for local computation. Finally, we demonstrate that ON and OFF selectivity, a key feature of visual processing across species, emerges through the transformation of membrane potential into intracellular calcium concentration. By imaging voltage and calcium signals to map information flow with subcellular resolution, we illuminate where and how critical computations arise.
View details for DOI 10.1016/j.cell.2016.05.031
View details for Web of Science ID 000380254400025
View details for PubMedID 27264607
- What can fruit flies teach us about karate? eLife 2014; 3
Permanent Genetic Access to Transiently Active Neurons via TRAP: Targeted Recombination in Active Populations
2013; 78 (5): 773-784
Targeting genetically encoded tools for neural circuit dissection to relevant cellular populations is a major challenge in neurobiology. We developed an approach, targeted recombination in active populations (TRAP), to obtain genetic access to neurons that were activated by defined stimuli. This method utilizes mice in which the tamoxifen-dependent recombinase CreER(T2) is expressed in an activity-dependent manner from the loci of the immediate early genes Arc and Fos. Active cells that express CreER(T2) can only undergo recombination when tamoxifen is present, allowing genetic access to neurons that are active during a time window of less than 12 hr. We show that TRAP can provide selective access to neurons activated by specific somatosensory, visual, and auditory stimuli and by experience in a novel environment. When combined with tools for labeling, tracing, recording, and manipulating neurons, TRAP offers a powerful approach for understanding how the brain processes information and generates behavior.
View details for DOI 10.1016/j.neuron.2013.03.025
View details for Web of Science ID 000320743400005