Staff Profiles

Corinne Teeter, Ph.D.

Scientist II

Corinne Teeter joined the Allen Institute's modeling analysis and theory team in 2012. Her main role is to characterize and build models ranging from simple phenomenological models to more complicated morphologically and biophysically realistic, Hodgkin-Huxley type models of different types of neurons based on intracellular electrophysiological, morphological, and gene expression data. These models will be used to create a large-scale network model of the mouse visual system. Before joining the Allen Institute, Teeter completed two year-long postdoctoral positions at Qualcomm Research and then at Sandia National laboratories. In these positions she worked on parameter estimation techniques for biophysically realistic neurons, and created tools for neuron and network simulation and analysis. Teeter completed her Ph.D. in computational neuroscience at the University of California, San Diego and the Salk Institute for Biological Sciences under the guidance of Charles Stevens, where her research involved understanding the morphology and connectivity of neurons across many different species. Specifically, her dissertation focused on the characterization of a universal function that describes the spatial density function of all neural arbors (axons and dendrites).


Research Interests

Research Interests The brain is an extraordinarily complex system with phenomena that occur across a wide range of temporal and spatial scales. Ultimately my goal is to understand the computations that are performed by neural networks that give rise to cognition and behavior. I am interested in uncovering the basic theoretical and organizational principles that enable neural circuits to perform these computations and the level of abstraction which is needed to describe and recreate network computation.


  • Computational neuroscience

Research Programs

  • Cell types
  • Neural coding

Selected Publications View on PUBMED

Classification of electrophysiological and morphological neuron types in mouse visual cortex

Nature Neuroscience
June 17, 2019

Gouwens NW, Sorensen SA, Berg J, Lee C, Jarsky T, Ting J, Sunkin S, Feng D, Anastassiou C, Barkan E, Bickley K, Blesie N, Braun T, Brouner K, Budzillo A, Caldejon S, Casper T, Castelli D, Chong P, Crichton K, Cuhaciyan C, Daigle T, Dalley R, Dee N, Desta T, Dingman S, Doperalski A, Dotson N, Egdorf T, Fisher M, de Frates RA, Garren E, Garwood M, Gary A, Gaudreault N, Godfrey K, Gorham M, Gu H, Habel C, Hadley K, Harrington J, Harris J, Henry A, Hill D, Josephsen S, Kebede S, Kim L, Kroll M, Lee B, Lemon T, Liu X, Long B, Mann R, McGraw M, Mihalas S, Mukora A, Murphy GJ, Ng L, Ngo K, Nguyen TN, Nicovich PR, Oldre A, Park D, Parry S, Perkins J, Potekhina L, Reid D, Robertson M, Sandman D, Schroedter M, Slaughterbeck C, Soler-Llavina C, Sulc J, Szafer A, Tasic B, Taskin N, Teeter C, Thatra N, Tung H, Wakeman W, Williams G, Young R, Zhou Z, Farrell C, Peng H, Hawrylycz MJ, Lein E, Ng L, Arkhipov A, Bernard A, Phillips J, Zeng H, Koch C

Sparse recurrent excitatory connectivity in the microcircuit of the adult mouse and human cortex

September 26, 2018

Seeman SC, Campagnola L, Davoudian PA, Hoggarth A, Hage TA, Bosma-Moody A, Baker CA, Lee, JH, Mihalas S, Teeter C, Ko AL, Ojemann JG, Gwinn RP, Silbergeld DL, Cobbs C, Phillips J, Lein E, Murphy G, Koch C, Zeng H, Jarsky T

Generalized leaky integrate-and-fire models classify multiple neuron types

Nature Communications
February 19, 2018

Teeter C, Iyer R, Menon V, Gouwens N, Feng D, Berg J, Szafer A, Cain N, Zeng H, Hawrylycz M, Koch C, Mihalas S

A general principle of neural arbor branch density

Current Biology
December 2011

Teeter CM, Stevens CF