- Iolov, A, Ditlevsen S and Longtin, A (2014) Fokker-Planck and Fortet equation-based parameter estimation for a leaky integrate-and-fire model with sinusoidal and stochastic forcing. J. Math. Neurosci. 4, 4.
- Seely, AJE, Bravi, A, Herry C, Green G, Longtin A, et al. (2014) Added prognostic accuracy and predictive model of heart and respiratory rate variability to forecast extubation outcomes. Crit. Care 18, R65.
- Bravi, A, Green, G, Herry, C, Wright, HE, Longtin, A, Kenny, GP and Seely, AJE (2013) Do physiological and pathological stresses produce different changes in heart rate variability? Frontiers Physiol. 4, 197.
- Bravi, A, Green, G, Longtin, A and Seely, AJE (2012) Monitoring and identification of sepsis development through a composite measure of heart rate variability. PLoS One 7(9), e45666. (pdf)
- Bravi, A, Longtin, A and Seely, AJE (2011) Review and classification of variability analysis techniques for clinical applications. BMC Biomed. Engin. Online 10: 90 (Oct.10)
- Engbert, R., Longtin, A. and Kliegl, R. (2004) Complexity of eye movements in reading: A theoretical model. Intern. J. Bifurc. Chaos 14, 493-503. (pdf)
- Capurro, A., Longtin, A., Bagarinao, E., Sato, S., Macadar, O. and Pakdaman, K. (2001) Variability of the electric organ discharge interval duration in resting Gymnotus carapo. Biol. Cybern. 84, 309-321. (pdf)
- Racicot, D. and Longtin, A. (1997) Interspike interval attractors from chaotically driven neuron models. Physica D 104, 184-204. (pdf)
- Longtin, A. (1997) Nonlinear prediction of biosignals. Japan Soc. of Med. Electron. and Biol. Engin. BME 11(1), 11-17. (invited review)
- Longtin, A. and Racicot, D.M. (1997) Spike train patterning and forecastability. Biosystems 40, 111-118. (pdf)
- Longtin, A. and D.M. Racicot (1997) Assessment of linear and nonlinear correlations between neural firing events. In: Nonlinear Dynamics and Time Series: Building a Bridge between the Natural and Statistical Sciences, eds. C.D. Cutler and D.T. Kaplan, Fields Institute Communications Vol.11, 223-239.
- Theiler, J., Galdrikian, B., Longtin, A., Eubank, S. and Farmer, J.D. (1992) Testing for nonlinearity in time series: the method of surrogate data. Physica D 58: 77-94. (Reprinted in: Coping with Chaos. Analysis of Chaotic Data and the Exploitation of Chaotic Systems, E. Ott, T. Sauer and J.A. Yorke, eds., Wiley Series in Nonlinear Science, pp.124-141 (1994)). (pdf)
- Theiler, J., Galdrikian, B., Longtin, A., Eubank, S. and Farmer, J.D. (1992) Detecting nonlinear structure in time series. Proceedings, First Experimental Chaos conference, Arlington, Virginia (World Scientific, Singapore) p.47-53.
- Theiler, J., Galdrikian, B., Longtin, A., Eubank, S. and Farmer, J.D. (1991) Using surrogate data to detect nonlinearity in time series. In Nonlinear Prediction and Modeling, M. Casdagli and S. Eubank, eds. (Addison-Wesley, Redwood City, Ca).