Department of Mathematics
University of Utah
155 South 1400 East
Salt Lake City
Tel.: 801 585 1633
Fax.: 801 581 4148
Department of Mathematics
University of Utah
155 South 1400 East
Salt Lake City
Tel.: 801 585 1633
Fax.: 801 581 4148
I am a Professor of Mathematics in the Department of Mathematics at the University of Utah, where I am a faculty member of the Mathematical Biology Group and the Brain Institute. I am also a Visiting Professor at the Mathematical Institute, University of Oxford and INRIA, Sophia-Antipolis.
My main research interests lie in the areas of mathematical neuroscience and theoretical biophysics. The particular focus of my work in neuroscience is to understand how the brain functions as a complex dynamical system at multiple spatial and temporal scales, both in healthy and diseased brains. From the biological perspective, this involves many different levels of description from the molecular basis of memory and learning at an individual synapse to the large-scale structure of cortex responsible for higher cognitive function. From the modeling perspective, the work draws upon a wide range of techniques in applied mathematics and theoretical physics including dynamical systems theory, differential equations, pattern formation and nonlinear wave theory, non-equilibrium statistical physics, biophysics and the theory of self-organizing systems. My interests in theoretical biophysics focus on stochastic models of intracellular transport, including molecular motors, protein receptor trafficking, secretory trafficking, ion channels, and intracellular waves.
|The Journal of Mathematical Neuroscience||The Journal of Mathematical Biology||Physical Review E||Biological Cybernetics|
NEW! Paul C. Bressloff Stochastic Processes in Cell Biology Interdisciplinary Applied Mathematics (Springer) Due: Summer (2014)
Paul C. Bressloff Waves in Neural Media: From Single Neurons to Neural Fields Lecture Notes on Mathematical Modelling in the Life Sciences (Springer) Published (2014)
Stephen Coombes and Paul C. Bressloff(eds.) Bursting: the Genesis of Rhythm in the Nervous System World Scientific (2005)
Paul C. Bressloff and J. Newby. Stochastic models of intracellular transport Rev. Mod. Phys. 85 135-196 (2013)
Paul C. Bressloff. Spatiotemporal Dynamics of Continuum Neural Fields J. Phys. A 45 (2012) 033001
P. C. Bressloff. Lectures in Mathematical Neuroscience In: Mathematical Biology, IAS/Park City Mathematical Series.(M. A. Lewis, M. A. J. Chaplain, J. P. Keener and P. K. Maini (eds) 14 293-398 (American Mathematical Society, 2009).
P. C. Bressloff. Pattern formation in visual cortex. Les Houches Lectures in Neurophysics (2005).
P. C. Bressloff and S. Coombes. Physics of the extended neuron. Int. J. Mod. Phys. B 11:2343-2393 (1997).
P. C. Bressloff and J. M. Newby. Path-integrals and large deviations in stochastic hybrid systems Phys. Rev. E 89 042701 (2014).
P. C. Bressloff and J. M. Newby. Stochastic hybrid model of spontaneous dendritic NMDA spikes.Phys. Biol. 11 016006 (13pp) (2014).
J. M. Newby, P. C. Bressloff and J. P. Keeener. The effect of Potassium channels on spontaneous action potential initiation by stochastic ion channels. Phys. Rev. Lett. 111 128101 (2013).
P. C. Bressloff and J. M. Newby. Metastability in a stochastic neural network modeled as a jump velocity Markov process SIAM J. Appl. Dyn. Syst. 12 1394-1435 (2013).
P. C. Bressloff. Propagation of CaMKII translocation waves in heterogeneous spiny dendrites. J. Math. Biol. 66 1499-1525 (2013).
P. C. Bressloff and J. M. Newby. Filling of a Poisson trap by a population of random intermittent searchers. Phys. Rev. E 85 031909 (2012).
P. C. Bressloff and J. Newby. Quasi-steady state analysis of motor-driven transport on a two-dimensional microtubular network. Phys. Rev. E 83 061139 (2011).
J. Newby and P. C. Bressloff. Local synaptic signalling enhances the stochastic transport of motor-driven cargo in neurons. Phys. Biol. 7 036004 (2010).
J. Newby and P. C. Bressloff. Random intermittent search and the tug-of-war model of motor-driven transport. J. Stat. Mech. P04014 (2010).
J. Newby and P. C. Bressloff. Directed intermittent search for a hidden target on a dendritic tree. Phys. Rev. E 80 021913 (2009).
P. C. Bressloff, B. A. Earnshaw and M. J. Ward. Diffusion of protein receptors on a cylindrical dendritic membrane with partially absorbing traps. SIAM J. Appl. Math. 68 1223-1246 (2008).
B. A. Earnshaw and P. C. Bressloff. Modeling the role of lateral membrane diffusion on AMPA receptor trafficking along a spiny dendrite. J. Comput. Neurosci. 25 366-389 (2008).
B. A. Earnshaw and P. C. Bressloff, A biophysical model of AMPA receptor trafficking and its regulation during LTP/LTD. J. Neurosci. 26 12362-12373 (2006).
P. C. Bressloff, A stochastic model of intraflagellar transport Phys. Rev. E 73 061916 (2006).
P. C. Bressloff, A stochastic model of protein receptor trafficking prior to synaptogenesis Phys. Rev. E 74 031910 (2006).
S. Coombes and P. C. Bressloff, Saltatory waves in the spike-diffuse-spike model of active dendrites. Phys. Rev. Lett. 91:028102 (2003).
P. C. Bressloff. From invasion to extinction in heterogeneous neural fields. J. Math. Neurosci. 2 6 (2012).
M. A. Webber and P. C. Bressloff. The effects of noise on binocular rivalry waves: a stochastic neural field model. J. Stat. Mech. (2012).
P. C. Bressloff and M. A. Webber. Front Propagation in stochastic neural fields SIAM J. Appl. Dyn. Syst. 11 708-740 (2012).
P. C. Bressloff. Metastable states and quasicycles in a stochastic Wilson-Cowan model of neural population dynamics. Phys. Rev. E 82 051903 (2010).
P. C. Bressloff. Stochastic neural field theory and the system-size expansion. SIAM J. Appl. Math 70 1488-1521 (2009).
P. C. Bressloff and M. A. Webber. Neural field model of binocular rivalry waves. J. Comput. Neurosci. 32 233-252 (2012).
Z. P. Kilpatrick and P. C. Bressloff. Binocular rivalry in a competitive neural network with synaptic depression. SIAM J. Appl. Dyn. Syst. 9 1303-1347 (2010).
Z. P. Kilpatrick and P. C. Bressloff. Spatially structured oscillations in a 2D excitatory neuronal network with synaptic depression. J. Comput. Neurosci. 239 1048-1060 (2010).
Z. P. Kilpatrick and P. C. Bressloff. Stability of bumps in piecewise smooth neural fields with nonlinear adaptation. Physica D 239 1048-1060 (2010).
Z. P. Kilpatrick, S. E. Folias and P. C. Bressloff. Traveling pulses and wave propagation failure in an inhomogeneous neural network. SIAM J. Appl. Dyn. Syst. 7 161-185 (2008).
S. E. Folias and P. C. Bressloff, Stimulus-locked waves and breathers in an excitatory neural network.SIAM J. Appl. Math 65:2067-2092 (2005).
S. E. Folias and P. C. Bressloff, Breathing pulses in an excitatory neural network. SIAM J. Appl. Dyn. Syst. 3,: 378-407(2004).
P. C. Bressloff and S. E. Folias, Front bifurcations in an excitatory neural network. SIAM J. Appl. Math. 65: 131-151 (2004).
P. C. Bressloff, Traveling fronts and wave propagation failure in an inhomogeneous neural network Physica D 155 :83-100 (2001).
M. Galtier, O. Faugeras and P. C. Bressloff. Hebbian learning of recurrent connections: a geometrical perspective. Neural Comput. 24 2346-2383 (2012).
P. C. Bressloff and A. M. Oster. A theory for the alignment of cortical feature maps during development. Phys. Rev. E 82 021920 (2010).
A. M. Oster and P. C. Bressloff, A developmental model of ocular dominance formation on a growing cortex Bull. Math. Biol. 68 73-98 (2006).
P. C. Bressloff, Spontaneous symmetry breaking in self-organizing neural fields. Biol. Cybern. 93: 256-274 (2005).
P. C. Bressloff, Spatially periodic modulation of cortical patterns by long-range horizontal connections. Physica D 185:131-157 (2003).
P. C. Bressloff and J. D. Cowan, Spherical model of orientation and spatial frequency tuning in a cortical hypercolumn. Phil. Trans. Roy. Soc. B 358:1643-1667 (2003).
P. C. Bressloff and J. D. Cowan, An amplitude equation approach to contextual effects in primary visual cortex. Neural Comput. 14 :493-525 (2002).
P. C. Bressloff and J. D. Cowan, The visual cortex as a crystal. Physica D 173 :226-258 (2002).
P. C. Bressloff, Bloch waves, periodic feature maps and cortical pattern formation. Phys. Rev. Lett. 89 : 088101 (2002).
P. C. Bressloff, J. D. Cowan, M. Golubitsky, P. J. Thomas and M. Wiener, Geometric visual hallucinations, Euclidean symmetry and the functional architecture of striate cortex Phil. Trans. Roy. Soc. B 40 :299-330 (2001).
Shushruth, P. Mangapathy, J. M. Ichida, P. C. Bressloff, L. Schwabe and A. Angelucci. Strong recurrent networks compute the orientation-tuning of surround modulation in primate V1. J. Neurosci. 32 308-321 (2012).
J. Icheda, L. Schwabe, P. C. Bressloff and A. Angelucci. Response facilitation from the ``suppressive'' surround of V1 neurons. J. Neurophysiol. 98 2168-2181 (2007).
A. Angelucci and P. C. Bressloff. The contribution of feedforward, lateral and feedback connections to the classical receptive field center and extra-classical receptive field surround of primate V1 neurons Prog. Brain Res. 154 93-121 (2006).
L. Schwabe, K. Obermayer, A. Angelucci and P. C. Bressloff. The role of feedback in shaping the extra-classical receptive field of cortical neurons: a recurrent network model J. Neurosci. 26 9117-9129 (2006).
J. S. Lund, A. Angelucci and P. C. Bressloff, Anatomical substrates for the functional column in macaque primary visual cortex. Cerebral Cortex 12:15-24 (2003).
P. C. Bressloff and Yi Ming Lai. Dispersal and noise: Various modes of synchrony in ecological oscillators. J. Math. Biol. 67 1669-1690 (2013).
Y-M Lai, J. Newby and P. C. Bressloff. Effects of demographic noise on the synchronization of metacommunities by a fluctuating environment. Phys. Rev. Lett 107 118102 (2011).
P. C. Bressloff and Y-M Lai. Stochastic synchronization of neuronal populations with intrinsic and extrinsic noise. J. Math. Neurosci. 1 2 (2011).
Sam Carroll (Utah) Neural field theory (2nd year)
Bhargav Karamched (Utah) Axonal transport (3rd year)
Bin Xu (Utah) Cell polarization (3rd year)
Heather Brooks (Utah) Biological oscillators (3rd year)
Matthew Webber (Oxford) Stochastic neural field models of binocular rivalry waves (D. Phil. 2013)
Yi Ming Lai (Oxford) Stochastic population oscillators in ecology and neuroscience (D. Phil. 2013)
Jay Newby (Utah) Molecular motor-based models of random intermittent search in dendrites (Ph. D 2010)
Zachary Kilpatrick (Utah) Spatially structured waves and oscillations in neuronal networks with synaptic depression and adaptation (Ph. D 2010)
William Nesse (Utah) Random fluctuations in dynamical neural networks. (Ph. D 2008)
Berton Earnshaw (Utah) Biophysical models of AMPA receptor trafficking and synaptic plasticity (Ph. D 2007)
Andrew M. Oster (Utah) Models of cortical development (Ph. D 2006)
Stefanos E. Folias (Utah) Stimulus-induced waves and breathers in excitable neural media (Ph. D 2005)
Matthew James Oscillations and waves in IF networks (Ph. D 2002)
Barry de Souza Dynamics of neuronal networks with dendritic interactions (Ph. D 2000)
Peter Roper Noise-induced effects in neural systems (Ph. D 1998)
Jay Newby (2010-2012)
Berton Earnshaw (2007-2009)
Lars Schwabe (2005-2006)
Steve Coombes (1996-1998)
Axonal Transport and Neuronal Mechanics, Mathematical Biosciences Institute, Ohio State, November 3-7, 2014
SIAM Conference on Nonlinear Waves and Coherent Structures, University of Cambridge, August 11-14, 2014
Stochastic Network Models of Neocortex (a Festschrift for Jack Cowan), Banff International research station, July 13-18, 2014
Nonlinear dynamics and stochastic methods: from neuroscience to other biological applications (Bard Ermentrout’s 60th) University of Pittsburgh, March 10-12, 2014
Oxford Conference on Challenges in Applied Mathematics University of Oxford, July 1-5, 2013
Stochastic Modeling of Biological Processes, IMA, University of Minnesota, May 13-17, 2013
Random models in neuroscience Université Pierre et Marie Curie, July 2-6, 2012
Stochastic Modelling in Biological Systems, University of Oxford, March 18-23, 2012
Spatio-Temporal Evolution Equations and Neural Fields, CIRM, Marseilles, October 24-28, 2011
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