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Uri Tzvi Eden, Ph.D. Professor
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(617) 353-9553 |
My research focuses on developing mathematical and statistical methods to analyze neural spiking activity. I have worked to integrate methodologies related to model identification, statistical inference, signal processing, and stochastic estimation and control, and expand these methodologies to incorporate point process observation models, making them more appropriate for modeling the dynamics of neural systems observed through spike train data. This research can be divided into two categories; first, a methodological component, focused on developing a statistical framework for relating neural activity to biological and behavioral signals and developing estimation algorithms, goodness-of-fit analyses, and mathematical theory that can be applied to any neural spiking system; second, an application component, wherein these methods are applied to spiking observations in real neural systems to dynamically model the spiking properties of individual neurons, to characterize how ensembles maintain representations of associated biological and behavioral signals, and to reconstruct these signals in real time.
Publications
Original Reports
Meng L, Kramer MA, Middleton SJ, Whittington MA, Eden
UT. A unified approach to linking experimental,
statistical and, computational analysis of spike train data. PLOS One. 9(1): e85269.
Prerau MJ, Purdon
PL, Eden UT. Tracking non-stationary spectral
peak structure in EEG data. Engineering in Medicine and Biology Society,
35th Annual International Conference of the IEEE, 2013, 417-420
Deng X, Eskandar EN, Eden UT. A point process approach to identifying and tracking transitions in
neural spiking dynamics in the subthalamic nucleus of
Parkinson’s patients. Chaos, 2013, 23, 046102
Kramer MA, Eden
UT. Assessment of cross-frequency coupling with confidence using
generalized linear models. Journal of Neuroscience Methods, 2013, 220(1):64-74
Gerhard F, Kispersky T, Gutierrez GJ, Marder
E, Kramer MA, Eden UT. Successful prediction of a physiological
circuit with known connectivity from spiking activity alone. PLOS Computational Biology. 9(7): e1003138, 2013.
Zaydens E, Taylor
A, Cohen M, Eden UT. Characterization and modeling of muscle sympathetic
nerve spiking. IEEE Trans. Biomed. Eng., 2013,
60(10):2914-2924
Lepage KQ, Kramer MA, Eden UT. Some
sampling properties of common phase estimators. Computational
Neuroscience, 2013, 25(4):901-21
Kramer MA, Truccolo W, Eden UT, Lepage
KQ, Hochberg LR, Eskandar EN, Madsen JR, Lee JW, Maheshwari A, Halgren E, Chu CJ,
Cash SS. Human seizures self-terminate across spatial scales via a critical
transition. PNAS, 2012, 109(51):21116-21
Lepage KQ, Gregoriou GG, Kramer
MA, Aoi M, Gotts SJ, Eden
UT, Desimone R. A procedure for
testing across-condition rhythmic spike-field association change.
Journal of Neuroscience Methods, 2013, 213(1):43-62
Sarma SV, Cheng ML, Eden UT, Williams Z, Brown EN,
Eskandar EE. The effects of cues on neurons in the
basal ganglia in Parkinson’s Disease. Frontiers in Neurosci. 2012 6:40
Eden UT, Gale J, Amirnovin R, Eskandar EE. Characterizing the dynamics of subthalamic
nucleus neurons in Parkinson's disease. Frontiers in Neurosci. 2012 6:28
Wagner T,
Rushmore J, Russo CJ, Eden UT, Simon S, Rotman
S, Pitskel NB, Grodzinsky A,
Zahn M, Pascual-Leone A, Valero-Cabre
A. Impact of brain tissue filtering on neurostimulation
fields: a modeling study. Neuroimage. 2013, 85(3):1048-1057
Lepage KQ, MacDonald CJ, Eichenbaum
HB, Eden UT. The statistical analysis of partially
confounded covariates important to neural spiking. J. Neurosci. Methods, 2012, 205: 295–304
MacDonald CJ, Lepage KQ, Eden UT, Eichenbaum HB. Hippocampal “time cells” bridge the gap in memory
for discontiguous events. Neuron,
2011. 71(4):737-749.
Lepage KQ, Kramer MA, Eden UT. The dependence of
spike-field coherence on expected intensity. Neural Computation, 2011,
23(9):2209-2241.
Meng L, Kramer MA, Eden UT. A
sequential Monte Carlo approach to estimate biophysical neural models from
spikes. 2011, Journal of Neural Engineering, 8(6):065006
Prerau MJ, Eden
UT. A General Likelihood Framework for Characterizing the Time Course of
Neural Activity, Neural Computation, 2011, 23(10): 2537-2566.
Eden UT, Kramer MA.
Drawing inferences from Fano factor calculations.
Journal of Neuroscience Methods, 2010, 190(1):149-152.
Kramer MA, Eden
UT, Kolaczyk ED, Zepeda R, Eskandar
EN, Cash SS, Coalescence and Fragmentation of Cortical Architecture During Focal Seizures. Journal of Neuroscience, 2010, 30
(30):10076-10085.
Sarma SV, Eden UT, Cheng M, Williams Z, Eskandar EN, Brown EN.
Using Point Process Models to Determine the Impact of
Visual Cues on Basal Ganglia Activity and Behavior of Parkinson’s Patients.
Proceedings of the 48th IEEE Conference on Decision and Control, 2009,
7716-7722.
Kramer MA, Eden UT, Cash SS, Kolaczyk
ED. Network inference – with confidence - from multivariate time series. Phys. Rev.
E 2009, 79(6):061916.
Koyama S, Eden UT, Brown EN, Kass RE. Bayesian
decoding of neural spike trains. Annals of the Institute of
Statistical Mathematics. 2010, 62(1): 37-59.
Wagner T,
Rushmore J, Eden UT, et al. Biophysical
foundations underlying TMS: Setting the stage for an effective use of neurostimulation in the cognitive neurosciences. Cortex,
2009; 45(9): 1025-1034.
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, 102(4): 2142 – 2160.
Prerau MJ, Smith A, Eden UT, Kubota Y, Yanike M, Suzuki W, Graybiel A,
Brown EN. Characterizing learning by simultaneous analysis of
continuous and binary measures of performance. J. Neurophys. 2009, 102: 3060-3072.
Huang Y,
Brandon MP, Griffin AL, Hasselmo ME, Eden UT. Decoding movement trajectories through a
T-maze using point process filters applied to place field data from rat
Hippocampal region CA1. Neural Computation. 2009,
21(12):3305-3334.
Eden UT, Brown
EN. Mixed observation
filtering for neural data.
Proceedings of the 33rd IEEE International Conference on Acoustics,
Speech, and Signal Processing, 2008, 5201-5203
Czanner G, Eden UT, Wirth S, Yanike
M, Suzuki WA, Brown EN. Analysis of between-trial and
within-trial neural spiking dynamics. J. Neurophys.,
2008; 99:2762-2693.
Wagner T, Eden
UT, Fregni F, Ramos-Estebanez
C, Valero-Cabre A, Pronio-Stelluto
V, Grodzinsky A, Zahn M, Pascual-Leone
A. Transcranial
magnetic stimulation and brain atrophy: a computer-based human brain model
study. Experimental
Brain Research. 2008; 186:539-550.
Prerau MJ, Eden
UT, Smith AC, Yanike M, Suzuki WA, Brown EN. A mixed
filter algorithm for cognitive state estimation from simultaneously recorded
continuous-valued and binary measures of performance. Biological Cybernetics,
2008; 99:1-14.
Czanner G, Dreyer A, Eden UT, Wirth S, Lim HH,
Suzuki WA, Brown EN. Dynamic
models of neural spiking activity.
Proceedings of the 46th IEEE Conference on Decision and Control, 2007,
5812-5817.
Eden UT. Point process adaptive filters for neural
data analysis: theory and applications.
Proceedings of the 46th IEEE Conference on Decision and Control, 2007,
5818-5825
Srinivasan L, Eden UT, Mitter
SK, Brown EN. General purpose filter design for neural
prosthetic devices. Journal of Neurophysiology, 2007; 98:2456-2475.
Eden, UT &
Brown, EN. Continuous-Time Filters for State
Estimation from Point Process Models of Neural Data. Statistica
Sinica, 2008; 18(4):1293-1310.
Ergun A, Barbieri R, Eden UT, Wilson MA,
Brown EN. Construction of point process adaptive filter algorithms for neural
systems using sequential Monte Carlo methods. IEEE Transactions on
Biomedical Engineering, 2007; 54(3):419-428.
Wagner T, Fregni F, Eden UT, Ramos-Estebanez
C, Grodzinsky A, Zahn M, Pascual-Leone
A. Transcranial
magnetic stimulation and stroke: a computer-based human model study. Neuroimage. 2006; 30(3):857-70.
Srinivasan L, Eden
UT, Willsky AS, Brown EN. A state-space analysis for reconstruction of goal-directed
movements using neural signals. Neural Computation, 2006, 18:2465-2494.
Srinivasan L, Eden
UT, Willsky AS, Brown EN. Goal-directed state equation for tracking
reaching movements using neural signals.
Proceedings of the 2nd International IEEE EMBS Conference on Neural
Engineering, 2005, 352-355.
Eden UT, Truccolo W, Fellows MR, Donoghue JP, Brown EN. Reconstruction of Hand
Movement Trajectories from a Dynamic Ensemble of Spiking Motor Cortical
Neurons. Proceedings of the 26th
IEEE International Conference of the Engineering in Medicine and Biology
Society, 2004, 2:4017-4020.
Truccolo W, Eden UT, Fellows MR, Donoghue JP, Brown
EN. A point process
framework for relating neural spiking activity to spiking history, neural
ensemble, and extrinsic covariate effects. Journal of Neurophysiology,
2005, 93(2):1074-1089.
Eden UT, Frank LM,
Solo V, Brown, EN. Dynamic analyses of neural encoding by point process adaptive
filtering. Neural Computation,
2004, 16(5), 971-998.
Frank LM, Eden UT, Solo V, Wilson MA, Brown EN. Contrasting patterns of receptive field
plasticity in the hippocampus and the entorhinal
cortex: an adaptive filtering approach. Journal of Neuroscience 2002, 22:3817-30.
Textbooks
Kass RE, Eden UT, Brown EN.
Analysis of Neural Data. Springer.
2014.
Textbook Chapters
Brown EN, Barbieri R, Eden UT, Frank
LM. Likelihood methods for neural spike
train data analysis, In: Computational neuroscience: a comprehensive
approach. London, CRC Press. 2003; Chapter 9, pp 253-286
Thesis
Eden
UT. Point process filters in the analysis of
neural spiking models. PhD. Thesis in Medical Engineering/Medical Physics. Harvard/MIT Division of
Health Sciences and Technology.
2005
Patents
Eden
UT, Hickerson K.
Accelerated handwritten symbol recognition in a pen based tablet
computer. Patent
number 7,266,236. Granted
September 4, 2007
Wagner
T, Eden UT. Apparatus
and method for stimulation of biological tissue. Filed, June 2007
Srinivasan L, Eden UT, Brown EN & Willsky A. Device and method for providing a combined bioprosthetic specification of goal state and path of
states to goal. Filed, January 27, 2005.