Anne C Smith

asmith3142 at gmail.com


CV

Anne C Smith


asmith3142-at-gmail.com





Research Interests and Research Experience


I am interested in how mathematics and computer science can be used to understand problems in medicine, neuroscience, and engineering. 


My research experience includes the analysis of electrophysiologic and engineering data using filtering techniques and machine learning, using probability methods to understand neural sequence data, and building software for analysis of imaging and EEG data. 


Recent projects include:

o  pharmacokinetic-pharmacodynamic modeling in drug development (MATLAB Simbiology)

o  analysis of rat and human EEG (Python MNE)

o  development of R Shiny applications for correlation analysis in drug development

o  longitudinal disease modeling




Neuroscience Publications



  1. Smith AC, Wu XB, Levy WB. Controlling activity fluctuations in large,sparsley connected random networks. Network: Computation in Neural Systems 2000; 11:63-81.

  2. Smith AC, Gerrard JL, Barnes CA, McNaughton BL. Effect of age on burst firing characteristics of rat hippocampal cells. NeuroReport 2000; 11:2865-71. 

  3. Smith AC, Brown EN. Estimating a state-space model from point process observations. Neural Computation 2003; 15: 965-991.

  4. Wirth S, Yanike M, Frank LM, Smith AC, Brown EN, Suzuki WA. Single neurons in the monkey hippocampus and learning of new associations. Science 2003; 300: 1578-1581.

  5. Smith AC, Frank LM, Wirth S, Yanike M, Hu D, Kubota Y, Graybiel AM, Suzuki WA, Brown EN. Dynamic analysis of learning in behavioral experiments. Journal of Neuroscience 2004; 24(2): 447-461.   

  6. Smith AC, Stefani MR, Moghaddam B, Brown EN. Analysis and design of behavioral experiments to characterize population learning. J.Neurophysiology (published online Sept. 29, 2004), 2005, 93:1776-1792. 

  7. Prerau MK, Smith AC, Eden UT, Yanike M, Suzuki W, Brown EN. A mixed filter algorithm for simultaneously recorded continuous-valued and binary observations. Biological Cybernetics 2008, 99(1): 1-14. 

  8. Law JR, Flanery MA, Wirth S, Yanike M, Suzuki WA, Smith AC, Frank LM, Brown EN, Stark CEL. fMRI activity during the gradual acquisition and expression of paired-associate memory. Journal of Neuroscience 2005, 25(24): 5720-5729.

  9. Smith AC, Smith P. A set probability technique for detecting relative time order across multiple neurons. Neural Computation 2006, 18(5): 1197-1214. 

  10. Barter LS, Mark LO, Smith AC, Antognini JF. Isoflurane potency in the Northern leopard frog Rana pipiens is similar to that in mammalian species. Vet Res Commun, 2007, 31(6): 757-63.

  11. Smith AC, Wirth S, Suzuki WA, Brown EN. Bayesian analysis of interleaved learning and response bias in behavioral experiments. Journal of Neurophysiology, 2007, 97(3): 2516-24.  

  12. Yanike M, Wirth S, Smith AC, Brown EN, Suzuki WA. Comparison of associative learning-related signals in the macaque perirhinal cortex and hippocampus. Cerebral Cortex, 2008, 19(5):   1064-1078.

  13. Kubota Y, Liu J, Hu D, DeCoteau W, Eden UT, Smith AC, Graybiel AM. Stable encoding of task structure coexists with flexible coding of task events in sensorimotor striatum. J Neurophysiol PMCID2774470, 102: 2142-2160.

  14. Wirth S, Avsar E, Chiu CC, Sharma V, Smith AC, Scalon JD, Brown EN, Suzuki WA. Trial Outcome and Associative Learning Signals in the Monkey Hippocampus.  Neuron 2009,  61( 6):   930-940.

  15. Smith AC, Shah SA, Hudson AE, Purpura KP, Victor JD, Brown EN, Schiff ND. A Bayesian statistical analysis of behavioral facilitation associated with deep brain stimulation. J Neurosci Methods 2009 PMCID2743761, 183(2): 267-76. 

  16. Kubota Y, Liu J, Hu D, DeCoteau WE, Eden UT, Smith AC, Graybiel AM. Stable encoding of task structure coexists with flexible coding of task events in Sensorimotor Striatum. J Neurophysiol 2009 PMCID2774470, 102: 2142-2160.

  17. Prerau MJ, Smith AC, Eden UT, Kubota Y, Yanike M, Suzuki W, Graybiel AM, Brown EN. Characterizing learning by simultaneous analysis of continuous and binary measures of performance. J Neurophysiol 2009, 102: 3060-72.

  18. Smith AC, Scalon JD, Wirth S, Yanike M, Suzuki WA, Brown EN. State-space algorithms for estimating spike rate functions. Computational Intelligence and Neuroscience 2009 PMCID2774470, 2010(Article ID 425639).

  19. McAssey MP, Hsieh F,Smith AC. Coupling among electroencephalogram gamma signals on a short time scale. Computational Intelligence and Neuroscience, 2010,  PMCID2926578.

  20. Smith AC, Nguyen VK, Karlsson MP, Frank LM, Smith P. Probability of repeating patterns in simultaneous neural data. Neural Comput 2010 PMID: 20608872, 22(10): 2522–2536.

  21. Solomon M, Frank MJ, Smith AC, Ly S, Carter CS. Transitive inference in adults with autism spectrum disorders. Cogn Affect Behav Neurosci 2011, 11(3): 437-499.

  22. Solomon M, Smith AC, Frank MJ, Ly S, Carter CS. Probabilistic reinforcement learning in adults with autism spectrum disorders. Autism Res 2011, 4(2): 109-20.

  23. Smith AC, Fall CP, Sornborger AT. Near-real time connectivity estimation for multivariate neural data. Proceedings from the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC '11).   (Software download page

  24. Poulsen C, Smith AC, Tucker D, Mattson C, Luu P. Learning and the Development of Contexts for Action. Frontiers in Human NeurosciencePublished online: 09 December, 2011. Vol 5 Article 159 pp 1-12.

  25. Wong KF, Smith AC, Pierce ET, Harrell PG, Walsh JL, Salazar-Gómez AF, Tavares CL, Purdon PL, Brown EN. Statistical modeling of behavioral dynamics during propofol-induced loss of consciousness. J Neurosci Methods. 2014 Apr 30;227:65-74

  26. Purdon PL, Pavone KJ, Akeju O, Smith AC, Sampson AL, Lee J, Zhou, DW, Solt K, Brown, EN The Ageing Brain: Age-dependent changes in the electroencephalogram during propofol and sevoflurane general anaesthesia. British Journal of Anaesthesia, 2015, Jul. Vol: 115 Special Issue: SI, Supplement: 1: 46-57.

  27. Gray DT, Smith AC, Burke SN, Gazzaley A, Barnes CA. Attentional updating and monitoring and affective shifting are impacted independently by aging in macaque monkeys. Behavioural Brain Research. Available online 28 June 2016.

  28. Comrie AE, Gray DT, Smith AC, Barnes CA. Different macaque models of cognitive aging exhibit task-dependent behavioral disparities. Behav Brain Res. 2018 May 15;344:110-119.

  29. Malem-Shinitski N, Zhang Y, Gray DT, Burke SN, Smith AC, Barnes CA, Ba D. A Separable Two-Dimensional Random Field Model of Binary Response Data from Multi-Day Behavioral Experiments. 2018. Journal of Neuroscience Methods.

    publication datApr 2018  publication descriptionAllsop S, Wichmann R, Mills F, ..., Smith AC, ..., Tye KM ,Corticoamygdala Transfer of Socially Derived Information Gates Observational Learning

  30. Allsop SA, Wichmann R, Mills F, Burgos-Robles A, Chang CJ, Felix-Ortiz AC, Vienne A, Beyeler A, Izadmehr EM, Glober G, Cum MI, Stergiadou J, Anandalingam KK, Farris K, Namburi P, Leppla CA, Weddington JC, Nieh EH, Smith AC, Ba D, Brown EN, Tye KM. Corticoamygdala Transfer of Socially Derived Information Gates Observational Learning. 2018 Cell.

    publication dMay 2018  publication description 

  31.  AJ, Lester AW, Schwartz BA, Smith, AC, Barnes, CA.  Analysis of Learning Deficits in Aged Rats on the W-Track Continuous Spatial Alternation Task 2018. Behavioral Neuroscience 132(6).
  32. Crittenden JR, Sauvage M, Kitsukawa T, Burguière E, Cepeda C, André VM, Canault M , Thomsen M, Zhang H,  Costa C, Martella G, Ghiglieri V, Pescatore KA,  Unterwald EM, Jackson W, Housman DE, Caine SB, Sulzer D, Calabresi P, Levine MS, BrefelCourbon C, Smith AC, Alessi M-C, Azulay J-P, Graybiel AM. Mutations in CalDAG-GEFI Lead to Striatal Signaling Deficits and Psychomotor Symptoms in Multiple Species Including Human 2019. (Bioarchiv).

  33. Antonoudiou P, Colmers PLW, Walton NL, Weiss GL, Smith AC, Nguyen DP, Lewis M, Quirk MC, Barros L, Melon LC,  Maguire JL. Allopregnanolone Mediates Affective Switching Through Modulation of Oscillatory States in the Basolateral Amygdala.  Biol Psychiatry. 2022 Feb 1;91(3):283-293.doi: 10.1016/j.biopsych.2021.07.017. Epub 2021 Jul 27.

    Biol Psychiatry
    . 2022 Feb 1;91(3):283-293. doi: 10.1016/j.biopsych.2021.07.017. Epub 2021 Jul 27.
    Biol Psychiatry
    . 2022 Feb 1;91(3):283-293. doi: 10.1016/j.biopsych.2021.07.017. Epub 2021 Jul 27.
    Biol Psychiatry
    . 2022 Feb 1;91(3):283-293. doi: 10.1016/j.biopsych.2021.07.017. Epub 2021 Jul 27.


Book Chapter


  1. Smith AC. State-space modeling for the analysis of behavior in learning experiments. In "Advanced State-Space Methods for Neural and Clinical Data”, 2015. Cambridge University Press. Z. Chen, editor.


Applied Mathematics Publications


  1. Smith AC, Roberts WW.  Straightening of crimped and hooked fibers in converging transport ducts: Computational modeling. Textile Research Journal 1994; 64(6): 325-334.
  2. Smith AC, Roberts WW. Computational modeling of fiber formation in spunbonding of polypropylene with crystallization: Comparison with experiments. International Nonwovens Journal 1994; 6(1): 31-41.