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Journal of Neuroscience Methods|October 28, 2018
A flexible likelihood approach for predicting neural spiking activity from oscillatory phaseTeryn D Johnson, Todd P Coleman, Lara M RangelHippocampus|January 10, 2023
Stimulation-induced entrainment of hippocampal network activity: Identifying optimal input frequenciesTeryn D Johnson, Katherine R Keefe, Lara M RangelScientific Reports|July 22, 2024
Network resonance and the auditory steady state responseTeryn D Johnson, Austin J Gallagher, Seana Coulson, et al.Journal of Neurophysiology|July 20, 2022
Modeling relationships between rhythmic processes and neuronal spike timingPamela D Rivière, Gabriel Schamberg, Todd P Coleman, et al.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|September 10, 2022
Automated classification of sleep and wake from single day triaxial accelerometer dataSandya Subramanian, Todd P ColemanAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|September 10, 2022
A Mutual Information Measure of Phase-Amplitude Coupling using High Dimensional Sparse ModelsAndrew Perley, Todd P ColemanAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 3, 2025
Sequential Probability Assignment for Outlier Detection in Heartbeat TimingsSabrina Liu, Todd P ColemanNeural Computation|May 5, 2010
A computationally efficient method for nonparametric modeling of neural spiking activity with point processesTodd P Coleman, Sridevi S SarmaFrontiers in Computational Neuroscience|June 6, 2024
A mutual information measure of phase-amplitude coupling using gamma generalized linear modelsAndrew S Perley, Todd P ColemanPageof 8