Uri Tzvi Eden, Ph.D.
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.
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.
Kass RE, Eden UT, Brown EN. Analysis of Neural Data. Springer. 2014.
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
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
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.