Mark A Kramer

Summary

Affiliation: Boston University
Country: USA

Publications

  1. pmc Human seizures self-terminate across spatial scales via a critical transition
    Mark A Kramer
    Department of Mathematics and Statistics, Boston University, Boston, MA 02215, USA
    Proc Natl Acad Sci U S A 109:21116-21. 2012
  2. pmc Emergence of persistent networks in long-term intracranial EEG recordings
    Mark A Kramer
    Department of Mathematics and Statistics, Boston University, Boston, Massachusetts 02215, USA
    J Neurosci 31:15757-67. 2011
  3. ncbi request reprint Network inference with confidence from multivariate time series
    Mark A Kramer
    Department of Mathematics and Statistics, Boston University, Boston, Massachusetts 02215, USA
    Phys Rev E Stat Nonlin Soft Matter Phys 79:061916. 2009
  4. pmc Rhythm generation through period concatenation in rat somatosensory cortex
    Mark A Kramer
    Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States of America
    PLoS Comput Biol 4:e1000169. 2008
  5. pmc Coalescence and fragmentation of cortical networks during focal seizures
    Mark A Kramer
    Department of Mathematics and Statistics, Boston University, 111 Cummington Street, Boston, MA 02215, USA
    J Neurosci 30:10076-85. 2010
  6. ncbi request reprint Emergent network topology at seizure onset in humans
    Mark A Kramer
    Center for BioDynamics, 111 Cummington Street, Boston University, Boston, MA 02215, USA
    Epilepsy Res 79:173-86. 2008
  7. doi request reprint Sharp edge artifacts and spurious coupling in EEG frequency comodulation measures
    Mark A Kramer
    Department of Mathematics and Statistics and Center for BioDynamics, Boston University, Boston, MA 02215, USA
    J Neurosci Methods 170:352-7. 2008
  8. pmc Emergence of stable functional networks in long-term human electroencephalography
    Catherine J Chu
    Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
    J Neurosci 32:2703-13. 2012
  9. pmc A procedure for testing across-condition rhythmic spike-field association change
    Kyle Q Lepage
    Boston University, Department of Mathematics and Statistics, Boston, MA, USA
    J Neurosci Methods 213:43-62. 2013
  10. pmc Epilepsy as a disorder of cortical network organization
    Mark A Kramer
    Department of Mathematics and Statistics, Boston University, Boston, MA 02215, USA
    Neuroscientist 18:360-72. 2012

Detail Information

Publications30

  1. pmc Human seizures self-terminate across spatial scales via a critical transition
    Mark A Kramer
    Department of Mathematics and Statistics, Boston University, Boston, MA 02215, USA
    Proc Natl Acad Sci U S A 109:21116-21. 2012
    ..This description constrains the specific biophysical mechanisms underlying seizure termination, suggests a dynamical understanding of status epilepticus, and demonstrates an accessible system for studying critical transitions in nature...
  2. pmc Emergence of persistent networks in long-term intracranial EEG recordings
    Mark A Kramer
    Department of Mathematics and Statistics, Boston University, Boston, Massachusetts 02215, USA
    J Neurosci 31:15757-67. 2011
    ..These results suggest that a metastable, frequency-band-dependent scaffold of brain connectivity exists from which transient activity emerges and recedes...
  3. ncbi request reprint Network inference with confidence from multivariate time series
    Mark A Kramer
    Department of Mathematics and Statistics, Boston University, Boston, Massachusetts 02215, USA
    Phys Rev E Stat Nonlin Soft Matter Phys 79:061916. 2009
    ..We demonstrate that the procedure is accurate and robust in both the determination of edges and the reporting of uncertainty associated with that determination...
  4. pmc Rhythm generation through period concatenation in rat somatosensory cortex
    Mark A Kramer
    Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States of America
    PLoS Comput Biol 4:e1000169. 2008
    ..We conclude that neural activity in the superficial and deep cortical layers may temporally combine to generate a slower oscillation...
  5. pmc Coalescence and fragmentation of cortical networks during focal seizures
    Mark A Kramer
    Department of Mathematics and Statistics, Boston University, 111 Cummington Street, Boston, MA 02215, USA
    J Neurosci 30:10076-85. 2010
    ..These results suggest that, at the macroscopic spatial scale, epilepsy is not so much a manifestation of hypersynchrony but instead of network reorganization...
  6. ncbi request reprint Emergent network topology at seizure onset in humans
    Mark A Kramer
    Center for BioDynamics, 111 Cummington Street, Boston University, Boston, MA 02215, USA
    Epilepsy Res 79:173-86. 2008
    ..Using these measures, we can identify spatially localized brain regions that may facilitate seizures and may be potential targets for focal therapies...
  7. doi request reprint Sharp edge artifacts and spurious coupling in EEG frequency comodulation measures
    Mark A Kramer
    Department of Mathematics and Statistics and Center for BioDynamics, Boston University, Boston, MA 02215, USA
    J Neurosci Methods 170:352-7. 2008
    ..In this short communication, we describe how abrupt increases or decreases in voltage data may produce spurious coupling in these measures and suggest techniques to detect these effects...
  8. pmc Emergence of stable functional networks in long-term human electroencephalography
    Catherine J Chu
    Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
    J Neurosci 32:2703-13. 2012
    ....
  9. pmc A procedure for testing across-condition rhythmic spike-field association change
    Kyle Q Lepage
    Boston University, Department of Mathematics and Statistics, Boston, MA, USA
    J Neurosci Methods 213:43-62. 2013
    ....
  10. pmc Epilepsy as a disorder of cortical network organization
    Mark A Kramer
    Department of Mathematics and Statistics, Boston University, Boston, MA 02215, USA
    Neuroscientist 18:360-72. 2012
    ..Although the characteristics of functional networks that support the epileptic seizure remain an area of active research, the prevailing trends point to a complex set of network dynamics between, before, and during seizures...
  11. doi request reprint Inferring evoked brain connectivity through adaptive perturbation
    Kyle Q Lepage
    Department of Mathematics and Statistics, Boston University, Boston, MA 02215, USA
    J Comput Neurosci 34:303-18. 2013
    ..The proposed method demonstrates improved accuracy compared to network inference based on passive observation of node dynamics and an increased rate of convergence relative to network estimation employing a naïve stimulation strategy...
  12. pmc Network analysis: applications for the developing brain
    Catherine J Chu-Shore
    Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
    J Child Neurol 26:488-500. 2011
    ....
  13. doi request reprint The dependence of spike field coherence on expected intensity
    Kyle Q Lepage
    Department of Mathematics and Statistics, Boston University, Boston, MA 15213, USA
    Neural Comput 23:2209-41. 2011
    ..Hence, intensity field coherence is a rate-independent measure and a candidate on which to base the appropriate statistical inference of spike field synchrony...
  14. ncbi request reprint Drawing inferences from Fano factor calculations
    Uri T Eden
    Department of Mathematics and Statistics, Boston University, 111 Cummington St, Boston, MA 02215, USA
    J Neurosci Methods 190:149-52. 2010
    ..The analysis provides a simple method to determine how close to 1 the computed Fano factor should be and to formally test whether the observed variability in the spiking is likely to arise in data generated by a Poisson process...
  15. pmc Introduction to focus issue: rhythms and dynamic transitions in neurological disease: modeling, computation, and experiment
    Tasso J Kaper
    Department of Mathematics and Statistics, Boston University, Boston, Massachusetts 02215, USA
    Chaos 23:046001. 2013
    ..This focus issue brings together articles presenting modeling, computational, analytical, and experimental perspectives about rhythms and dynamic transitions between them that are associated to various diseases. ..
  16. pmc Some sampling properties of common phase estimators
    Kyle Q Lepage
    Department of Mathematics, Boston University, Boston, MA 02446, USA
    Neural Comput 25:901-21. 2013
    ..This analysis suggests how prior knowledge about a rhythmic signal can be used to improve the accuracy of phase estimates...
  17. pmc Dynamic cross-frequency couplings of local field potential oscillations in rat striatum and hippocampus during performance of a T-maze task
    Adriano B L Tort
    Department of Mathematics and Center for BioDynamics, Boston University, Boston, MA 02215, USA
    Proc Natl Acad Sci U S A 105:20517-22. 2008
    ..Cross-frequency coupling of multiple neuronal rhythms could be a general mechanism used by the brain to perform network-level dynamical computations underlying voluntary behavior...
  18. pmc A unified approach to linking experimental, statistical and computational analysis of spike train data
    Liang Meng
    Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States of America
    PLoS ONE 9:e85269. 2014
    ..This approach - linking statistical, computational, and experimental neuroscience - provides an effective technique to constrain detailed biophysical models to specific mechanisms consistent with observed spike train data. ..
  19. pmc A showcase of torus canards in neuronal bursters
    John Burke
    Department of Mathematics and Statistics, Center for BioDynamics, Boston University, Boston, MA, 02215, USA
    J Math Neurosci 2:3. 2012
    ..Based on these examples, as well as on emerging theory, we propose that torus canards are a common dynamic phenomenon separating the regimes of spiking and bursting activity...
  20. ncbi request reprint Distributed control in a mean-field cortical network model: implications for seizure suppression
    Shinung Ching
    Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
    Phys Rev E Stat Nonlin Soft Matter Phys 86:021920. 2012
    ..By introducing a mean-field model of neuronal interactions we are able to identify limitations in network controllability based on physiological constraints that suggest the need for more nuanced network control strategies...
  21. pmc A sequential Monte Carlo approach to estimate biophysical neural models from spikes
    Liang Meng
    Department of Mathematics and Statistics, Boston University, Boston, MA, USA
    J Neural Eng 8:065006. 2011
    ..We also address the issues of model identification and misspecification, and show that accurate estimates of model parameters and hidden variables are possible given only spike time data...
  22. pmc New dynamics in cerebellar Purkinje cells: torus canards
    Mark A Kramer
    Department of Mathematics and Statistics, Boston University, Boston, Massachusetts 02215, USA
    Phys Rev Lett 101:068103. 2008
    ..We propose that the system exhibits a dynamical phenomenon new to realistic, biophysical applications: torus canards...
  23. doi request reprint An elementary model of torus canards
    G Nicholas Benes
    Department of Mathematics and Statistics, Center for BioDynamics, Boston University, Boston, Massachusetts 02215, USA
    Chaos 21:023131. 2011
    ..The results of this elementary model provide insight into the torus canards observed in a higher-dimensional neuroscience model...
  24. pmc Are different rhythms good for different functions?
    Nancy Kopell
    Department of Mathematics and Statistics, Boston University Boston, MA, USA
    Front Hum Neurosci 4:187. 2010
    ..We suggest that diverse rhythms, or variations of a rhythm, can support different components of a cognitive act, with multiple rhythms potentially playing multiple roles...
  25. ncbi request reprint Synchronization measures of bursting data: application to the electrocorticogram of an auditory event-related experiment
    Mark A Kramer
    Program in Applied Science and Technology, University of California, Berkeley, California 94720 1708, USA
    Phys Rev E Stat Nonlin Soft Matter Phys 70:011914. 2004
    ..We apply the synchronization measure to human electrocorticogram data collected during an auditory event-related potential experiment. The results suggest a crude model of cortical connectivity...
  26. ncbi request reprint Mechanisms of seizure propagation in a cortical model
    Mark A Kramer
    Applied Science and Technology Graduate Group, University of California, Berkeley, CA 94720 1740, USA
    J Comput Neurosci 22:63-80. 2007
    ..We compare the model results with the disinhibition and 4-AP models of epilepsy and suggest how the model may guide the development of new anticonvulsant therapies...
  27. pmc Pathological pattern formation and cortical propagation of epileptic seizures
    Mark A Kramer
    Program in Applied Science and Technology, University of California, Berkeley, CA 94720 1740, USA
    J R Soc Interface 2:113-27. 2005
    ..This suggests that seizing activity on the human cortex may be understood as an example of pathological pattern formation. Included is a discussion of the applications and limitations of these results...
  28. ncbi request reprint Bifurcation control of a seizing human cortex
    Mark A Kramer
    Program in Applied Science and Technology, University of California, Berkeley, CA 94720, USA
    Phys Rev E Stat Nonlin Soft Matter Phys 73:041928. 2006
    ..We show how bifurcations induced by the linear controller alter those present in the original dynamics...
  29. ncbi request reprint Synchronization measures of the scalp electroencephalogram can discriminate healthy from Alzheimer's subjects
    Mark A Kramer
    Graduate Group in Applied Science and Technology, University of California, Berkeley, Berkeley, CA, USA
    Int J Neural Syst 17:61-9. 2007
    ....
  30. ncbi request reprint Quantitative approximation of the cortical surface potential from EEG and ECoG measurements
    Mark A Kramer
    Graduate Group in Applied Science and Technology, University of California, Berkeley, CA 94720 1708, USA
    IEEE Trans Biomed Eng 51:1358-65. 2004
    ..The inclusion of the biharmonic term, the extension to other geometries, and the application to electrocorticogram measurements are discussed...