Background:
How does the brain control movement of the body?
In mammals, motor cortex is specialized for the planning, initiation, control, and learning of movements. But the computations performed by this circuit are not known. My long-term research goals are to (a) identify the specific connections of defined cell types in motor cortex, (b) characterize the connections that change strength during learning, and (c) explain how these specific connections drive neuronal firing. Thus, our goal is a circuit diagram of the brain with a functional understanding of how the circuit processes information.
The tools needed to define cortical circuits are being rapidly developed: New transgenic mouse lines (and some viruses with specific promotors, enhancers, and serotypes) label specific sets of excitatory pyramidal neurons and inhibitory interneurons in neocortex, giving us access to defined cell types. We use these to identify cell-type specific inputs and outputs in the motor cortex. Different cell types are believed to play distinct roles in the local circuit, so understanding their specific inputs will help explain the specific response properties of each cell type. New optical and genetic methods for circuit mapping make it possible to independently excite one or more neuron populations, thus quantifying the connectivity of local and long-range inputs to different cortical cell types.
Research Interests:
My near term goals are:
Circuitry of feedforward inhibition:
-Understand how feedforward inhibition is recruited in motor cortex by distinct cortical and thalamic inputs. Specifically, we seek to know whether these inputs recruit the same types of inhibitory interneurons (such as parvalbumin and somatostatin expressing interneurons), whether these inputs excite the same individual cells, and what rules govern the magnitude of feedforward excitation and inhibition from cortical and thalamic inputs to motor cortex.
-Understand the role of inhibitory microcircuits in development and plasticity. In sensory cortex, development of inhibition plays a crucial role in triggering the onset of plasticity and regulating cortical responses. We seek to characterize how inhibitory connections of defined interneuron types develop in motor cortex. We then seek to understand how the development of connections from specific interneuron types regulates motor skill learning. This will require development of a motor skill learning paradigm, assessment of skill learning across development, and implementation of means to label task-related neurons and quantify their inputs in mouse cortex.
Long-range excitatory connections in motor cortex
-Although a lot is known about the area-to-area connectivity of NHP motor cortex, less is known about the specific laminar connectivity of long-range connections in motor areas. These experiments have been done in mice, but it is unknown whether the circuit organization is similar in NHP. We seek to develop methods for optical circuit mapping in NHP motor areas. Thus, we might directly address the question of whether rodent circuitry is homologous to NHP. We expect this will develop additional tools for optical stimulation in new species.
-Long-range corticostriatal output. We are interested in examining functional differences in the synaptic targeting of two major classes of cortical pyramidal neurons, called “IT-type” (for intratelencephalic neurons who only target cortex and straitum) and “PT-type” (for pyramidal tract type neurons whose projections extend to thalamus, pons, and brainstem, with some entering the pyramidal tract). Our recent work has shown that the anatomical projections of these two cell types differ. We now seek to address whether their functional outputs are distinct as well.
Anatomical methods for quantifying cell type specific circuits in whole brain images
-We are collaborating with others to use genetically modified rabies virus (GM-rabies) as a monosynaptic tracing tool to identify inputs to specific cell types in motor cortex. We use cell-type specific approaches to label starter cells and GM-rabies to label putative inputs. We image whole brains (either sectioned or cleared) and align images to a reference space. We are working with MBF Biosciences to improve imaging and alignment tools. We then quantify putative presynaptic cells to identify differences in connectivity of specific cell types.