• Christina Weaver
Professor of Mathematics

Biography


Professor    Franklin & Marshall College, Lancaster, PA    2022-present
     Department of Mathematics

Department Chair    Franklin & Marshall College, Lancaster, PA    2018-2021
     Department of Mathematics

Associate Professor    Franklin & Marshall College, Lancaster, PA    2015-2022

Assistant Professor    Franklin & Marshall College, Lancaster, PA    2009-2015

Instructor    Mount Sinai School of Medicine, New York, NY.      2007-2009
     Dept. of Neuroscience; Computational Neurobiology and Imaging Center.

Postdoc. Fellow    Mount Sinai School of Medicine, New York, NY.      2003-2007
      Dept. of Biomathematical Sciences; Computational Neurobiology and Imaging Center.  

Education

Ph.D.   Stony Brook University, Stony Brook, NY             2003

            Applied Mathematics & Statistics


B.S.     Mount St. Mary's University, Emmitsburg, MD     1998

            Mathematics

Research

 

I am passionate about mathematical modeling in general, but my research interests focus on computational neuroscience, image analysis, and statistical analyses of biomedical data. Specifically, I use computational modeling to study cellular mechanisms underlying working memory, and how those mechanisms are affected by aging and neurodegenerative disease. The models are constrained by morphologic and electrophysiological data collected by my colleagues at Boston University School of Medicine and the Icahn School of Medicine at Mount Sinai (New York, NY),  resulting in multidisciplinary studies that demonstrate a unique approach to research. This requires methods for automated parameter optimization, a research area that we actively pursue. An intriguing outcome of our research is the application of sensitivity analysis approaches, to predict which electrical parameters to change, and by how much, will to compensate for a given age-, disease-, or development-related morphologic change, to restore normal function. We are extending these methods in new directions, and applying them to our current modeling problems to help us elucidate the mechanisms that shape neuronal function.  

My research is funded currently by the National Institutes of Health, and has been funded in the past by the National Science Foundation and CHDI Foundation.  I have also been an active member of the Organization for Computational Neurosciences.

Publications

 

 
  1. Chang W, Weaver CM, Medalla M, Moore TL, Luebke JI.  Age-related alterations to working memory and to pyramidal neurons in the prefrontal cortex of rhesus monkeys begin in early middle-age and are partially ameliorated by dietary curcumin intervention. Neurobiology of Aging 109: 113-124, (2022).

  2. Ibañez S, Luebke JI, Chang W, Draguljić D, Weaver, CM.  Network models predict that pyramidal neuron hyperexcitability and synapse loss in the dlPFC leads to age-related spatial working memory impairment in rhesus monkeys. Frontiers in Computational Neuroscience, 13: 89, doi:  10.3389/fncom.2019.00089 (2020).  PMID: 32009920.

  3. Goodliffe JW, Song H, Rubakovic A, Chang W, Medalla M, Weaver CM, Luebke JI.  Differential changes to D1 and D2 Medium Spiny Neurons in the 12-month-old Q175+/- mouse model of Huntington’s Disease. PLoS One 13(8):e0200626, (2018).  PMID: 30118496.

  4. Rumbell T, Draguljić D, Yadav A, Luebke JI, Hof PR, Weaver CM.  Automated evolutionary optimization of ion channel conductances and kinetics in models of young and aged rhesus monkey pyramidal neurons. Journal of Computational Neuroscience, 41(1):  65-90, (2016).  PMID: 27106692.

  5. Coskren PJ, Luebke JI, Kabaso D, Wearne SL, Hof PR, Weaver CM.  Functional consequences of age-related morphologic changes in pyramidal cells in the prefrontal cortex of the rhesus monkey.  Journal of Computational Neuroscience 38(2):  263-83, (2015).  PMID:  25527184.

  6. Luebke JI, Medalla M, Amatrudo JA, Weaver CM, Crimins JL, Hunt B, Hof PR, Peters A.  Age-related changes to layer 3 pyramidal cells in the rhesus monkey visual cortex. Cerebral Cortex 25(6):  1454-68, (2015).  PMID:  24323499. 

  7. Steele JW, Brautigam H, Short J, Sowa A, Shi M, Yadav A, Weaver CM, Westaway D, Fraser PE, St George-Hyslop PH, Gandy S, Hof PR, Dickstein DL. Early fear memory defects are associated with altered synaptic plasticity and molecular architecture in the TgCRND8 Alzheimer’s disease mouse model. Journal of Comparative Neurology 522:  2319-35, (2014).  PMID:  24415002.

  8. Dickstein DL, Weaver CM, Luebke JI, Hof PR.  Dendritic spine changes associated with normal aging.  Neuroscience 251: 21-32, (2013).  PMID:  23069756.

  9. Amatrudo J, Weaver CM, Crimins JL, Hof PR, Rosene DL, Luebke JI. Influence of highly distinctive structural properties on the excitability of pyramidal neurons in monkey visual and prefrontal cortices.  (Amatrudo & Weaver are joint first authors.) Journal of Neuroscience 32:  13644-60, (2012). PMID:  23035077.
  10. Yadav A, Gao YZ, Rodriguez A, Dickstein DL, Wearne SL, Luebke JI, Hof PR, Weaver CM. Morphologic evidence for spatially clustered spines in apical dendrites of monkey neocortical pyramidal cells. Journal of Comparative Neurology 520:  2888-902, (2012). PMID:  22315181. 
  11. Luebke JI, Weaver CM, Rocher AB, Rodriguez A, Crimins JL, Dickstein DL, Wearne SL, Hof PR.  Dendritic vulnerability in neurodegenerative disease:  insights from analyses of cortical pyramidal neurons in transgenic mouse models.  Brain Struct Func. 214(2-3): 181-199, (2010).  PMID:  20177698
  12. Weaver CM and Wearne SL.  Neuronal firing sensitivity to morphologic and active membrane parameters.  PLoS Computational Biology 4(1): e11, doi:10.1371/journal.pcbi.0040011 (2008).
  13. Weaver CM and Wearne SL.  The role of action potential shape and parameter constraints in optimization of compartment models.  Neurocomputing 69:  1053-1057, (2006).
  14. Weaver CM, Hof PR, Wearne SL, Lindquist WB.  Automated algorithms for multiscale morphometry of neuronal dendrites.  Neural Comput. 16: 1353-83, (2004).
  15. Weaver CM, Pinezich JD, Lindquist WB, Vazquez ME.  An algorithm for neurite outgrowth reconstruction.  J. Neurosci. Methods. 124: 197-205, (2003).
     

Student Collaborations

 

Sylvia Sun '21, Sherry Ren '22, Maia Lockhart '22, Stheffany Ramos '23.  Fall 2021.  Mathematical modeling of COVID-19 transmission.  (Part of the Diplomath Research Corps.)

Alexa Gordon '20.  Fall 2019-Spring 2020.  Mathematical methods for neuroscience.

Fangzhou Wei '20.  Fall 2019.  Network models of working memory tasks.

Julia Ramsey '18 and Amy Reyes '16.  Spring-Summer 2016:  Simulating young and aged neurons.

Matthew Nadherny '13.  Summer 2012:  Improving detection of spatial clusters of dendritic spines.  Funded by NIA.

Daniel Hass '13.  Spring 2010: Designing fitness functions for the optimization of neuron model parameters.  Summer 2010: The Applications of Neural Modeling in Researching Alzheimer’s Disease.  Funded by HHMI Program in Bioinformatics.

Gregory Schwartz ’11. Summer 2010: The optimization and application of brain metabolite concentration algorithms for clinical use.  Funded by HHMI Program in Bioinformatics.

 

Postdoctoral Fellows 

Dr. Nilapratim Sengupta (2021-present)

Dr. Sara Ibañez (2017-2020), now at Centre de Recerca Mathemática, Barcelona.

Dr. Hanbing Song (2017-2019), now at UCSF.

Dr. Timothy Rumbell (2013-15), now at IBM Watson Research Center.

Dr. Anniruddha Yadav (2009-2012), founder and CEO of Gauge Data Solutions.

 

 

Course Information

Fall 2020

  • MAT339:  Mathematical Models,
  • MAT110:  Calculus II

 

Other courses taught

  • MAT109, Calculus I
  • MAT216, Probability & Statistics I
  • MAT316, Probability & Statistics II
  • MAT/CPS338: Computational Mathematics
  • MAT439:  Nonlinear Dynamics