Research Topics
| Mark A KramerSummaryAffiliation: Boston University Country: USA Publications
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Detail Information
Publications
Human seizures self-terminate across spatial scales via a critical transitionMark 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...- Emergence of persistent networks in long-term intracranial EEG recordingsMark 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... 
Network inference with confidence from multivariate time seriesMark 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...- Rhythm generation through period concatenation in rat somatosensory cortexMark 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... - Coalescence and fragmentation of cortical networks during focal seizuresMark 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... 
Emergent network topology at seizure onset in humansMark 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...- Sharp edge artifacts and spurious coupling in EEG frequency comodulation measuresMark 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... - Emergence of stable functional networks in long-term human electroencephalographyCatherine J Chu
Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
J Neurosci 32:2703-13. 2012.... - Epilepsy as a disorder of cortical network organizationMark 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... - Network analysis: applications for the developing brainCatherine J Chu-Shore
Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
J Child Neurol 26:488-500. 2011.... - The dependence of spike field coherence on expected intensityKyle 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... - Drawing inferences from Fano factor calculationsUri 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... - Dynamic cross-frequency couplings of local field potential oscillations in rat striatum and hippocampus during performance of a T-maze taskAdriano 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... - A showcase of torus canards in neuronal burstersJohn 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... - Inferring evoked brain connectivity through adaptive perturbationKyle 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... - Some sampling properties of common phase estimatorsKyle 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... - Distributed control in a mean-field cortical network model: implications for seizure suppressionShinung 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... - A procedure for testing across-condition rhythmic spike-field association changeKyle Q Lepage
Boston University, Department of Mathematics and Statistics, Boston, MA, USA
J Neurosci Methods 213:43-62. 2013.... - A sequential Monte Carlo approach to estimate biophysical neural models from spikesLiang 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... - New dynamics in cerebellar Purkinje cells: torus canardsMark 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... - An elementary model of torus canardsG 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... - 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... - Mechanisms of seizure propagation in a cortical modelMark 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... - Pathological pattern formation and cortical propagation of epileptic seizuresMark 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... - Bifurcation control of a seizing human cortexMark 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... - Synchronization measures of bursting data: application to the electrocorticogram of an auditory event-related experimentMark 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... - Synchronization measures of the scalp electroencephalogram can discriminate healthy from Alzheimer's subjectsMark A Kramer
Graduate Group in Applied Science and Technology, University of California, Berkeley, Berkeley, CA, USA
Int J Neural Syst 17:61-9. 2007.... - Quantitative approximation of the cortical surface potential from EEG and ECoG measurementsMark 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...