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Journal of Computational Neuroscience, Volume 29
Volume 29, Numbers 1-2, August 2010
- Robert E. Kass:
Guest editorial: analysis of neural data. 1-2 - Alain Destexhe, Jonathan D. Victor:
Editorial Note. 3 - Patrick J. Drew
, Pablo Blinder
Rapid determination of particle velocity from space-time images using the Radon transform. 5-11 - Joydeep Bhattacharya, Ernesto Pereda
An index of signal mode complexity based on orthogonal transformation. 1-10 - Huixia He, David J. Thomson:
Canonical bicoherence analysis of dynamic EEG data. 23-34 - Atanu Biswas, Apratim Guha:
Time series analysis of hybrid neurophysiological data and application of mutual information. 35-47 - Aman B. Saleem
Methods for predicting cortical UP and DOWN states from the phase of deep layer local field potentials. 49-62 - Catherine Stamoulis, Andrew G. Richardson
Application of matched filtering to identify behavioral modulation of brain oscillations. 63-72 - Shinsuke Koyama, Steven M. Chase
Comparison of brain-computer interface decoding algorithms in open-loop and closed-loop control. 73-87 - Shinsuke Koyama, Liam Paninski:
Efficient computation of the maximum a posteriori path and parameter estimation in integrate-and-fire and more general state-space models. 89-105 - Liam Paninski, Yashar Ahmadian, Daniel Gil Ferreira, Shinsuke Koyama, Kamiar Rahnama Rad, Michael Vidne, Joshua T. Vogelstein
A new look at state-space models for neural data. 107-126 - Felix Franke
An online spike detection and spike classification algorithm capable of instantaneous resolution of overlapping spikes. 127-148 - Dominik Endres, Mike W. Oram:
Feature extraction from spike trains with Bayesian binning: 'Latency is where the signal starts'. 149-169 - Hideaki Shimazaki
Kernel bandwidth optimization in spike rate estimation. 171-182 - Takeaki Shimokawa
A characterization of the time-rescaled gamma process as a model for spike trains. 183-191 - Andrea Trevino, Todd P. Coleman
A dynamical point process model of auditory nerve spiking in response to complex sounds. 193-201 - Surya T. Tokdar, Peiyi Xi, Ryan C. Kelly, Robert E. Kass:
Detection of bursts in extracellular spike trains using hidden semi-Markov point process models. 203-212 - Valentina Pasquale
A self-adapting approach for the detection of bursts and network bursts in neuronal cultures. 213-229 - Christoph Echtermeyer, Tom V. Smulders
Causal pattern recovery from neural spike train data using the Snap Shot Score. 231-252 - Boris Gourévitch
Maximum decoding abilities of temporal patterns and synchronized firings: application to auditory neurons responding to click trains and amplitude modulated white noise. 253-277 - Tayfun Gürel, Stefan Rotter, Ulrich Egert
Functional identification of biological neural networks using reservoir adaptation for point processes. 279-299 - Michael Krumin, Avner Shimron, Shy Shoham
Correlation-distortion based identification of Linear-Nonlinear-Poisson models. 301-308 - Adrien Peyrache
Principal component analysis of ensemble recordings reveals cell assemblies at high temporal resolution. 309-325 - Benjamin Staude, Stefan Rotter, Sonja Grün
CuBIC: cumulant based inference of higher-order correlations in massively parallel spike trains. 327-350 - Adrián Ponce-Alvarez
Comparison of local measures of spike time irregularity and relating variability to firing rate in motor cortical neurons. 351-365
Volume 29, Number 3, December 2010
- Gaute T. Einevoll, Daniel K. Wójcik
Modeling extracellular potentials. 367-369 - Nitin B. Bangera
Experimental validation of the influence of white matter anisotropy on the intracranial EEG forward solution. 371-387 - Claude Bédard, Serafim Rodrigues, Noah Roy, Diego Contreras, Alain Destexhe
Evidence for frequency-dependent extracellular impedance from the transfer function between extracellular and intracellular potentials - Intracellular-LFP transfer function. 389-403 - Nima Dehghani
Comparative power spectral analysis of simultaneous elecroencephalographic and magnetoencephalographic recordings in humans suggests non-resistive extracellular media. 405-421 - Henrik Lindén
Intrinsic dendritic filtering gives low-pass power spectra of local field potentials. 423-444 - Valeri A. Makarov
Disentanglement of local field potential sources by independent component analysis. 445-457 - Szymon Leski, Ewa Kublik
Extracting functional components of neural dynamics with Independent Component Analysis and inverse Current Source Density. 459-473 - Catherine Stamoulis, Andrew G. Richardson
Encoding of brain state changes in local field potentials modulated by motor behaviors. 475-483 - Aleksander Sobolewski, Ewa Kublik
Cross-trial correlation analysis of evoked potentials reveals arousal-related attenuation of thalamo-cortical coupling. 485-493 - Kukjin Kang, Michael J. Shelley
LFP spectral peaks in V1 cortex: network resonance and cortico-cortical feedback. 495-507 - Peter Jedlicka
Computational modeling of GABAA receptor-mediated paired-pulse inhibition in the dentate gyrus. 509-519 - Jesse A. Gillis
Spatial coherence and stationarity of local field potentials in an isolated whole hippocampal preparation in vitro. 521-532 - Andrei Belitski, Stefano Panzeri
Sensory information in local field potentials and spikes from visual and auditory cortices: time scales and frequency bands. 533-545 - Michel Besserve, Bernhard Schölkopf, Nikos K. Logothetis, Stefano Panzeri
Causal relationships between frequency bands of extracellular signals in visual cortex revealed by an information theoretic analysis. 547-566 - Ryan C. Kelly, Matthew A. Smith
Local field potentials indicate network state and account for neuronal response variability. 567-579 - Edgar E. Galindo-Leon, Robert C. Liu:
Predicting stimulus-locked single unit spiking from cortical local field potentials. 581-597 - Michael Denker
Estimating the contribution of assembly activity to cortical dynamics from spike and population measures. 599-613 - Timothy J. Gawne:
The local and non-local components of the local field potential in awake primate visual cortex. 615-623
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