Pages that link to "Item:Q122872"
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The following pages link to The time-rescaling theorem and its application to neural spike train data analysis (Q122872):
Displaying 35 items.
- Decoding Movement Trajectories Through a T-Maze Using Point Process Filters Applied to Place Field Data from Rat Hippocampal Region CA1 (Q3650539) (← links)
- Pattern Filtering for Detection of Neural Activity, with Examples from HVc Activity During Sleep in Zebra Finches (Q4461325) (← links)
- Spatio-temporal patterns of IED usage by the Provisional Irish Republican Army (Q4594589) (← links)
- A non-universal aspect in the temporal occurrence of earthquakes (Q4594892) (← links)
- Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Encoding Model (Q4664510) (← links)
- An Adjustment to the Time-Rescaling Method for Application to Short-Trial Spike Train Data (Q4813873) (← links)
- Estimating a State-Space Model from Point Process Observations (Q4816941) (← links)
- Dynamic Analyses of Information Encoding in Neural Ensembles (Q4819825) (← links)
- Testing for and Estimating Latency Effects for Poisson and Non-Poisson Spike Trains (Q4832454) (← links)
- Dynamic Analysis of Neural Encoding by Point Process Adaptive Filtering (Q4832474) (← links)
- Parameter Estimation in Multiple Dynamic Synaptic Coupling Model Using Bayesian Point Process State-Space Modeling Framework (Q5004352) (← links)
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- Capturing Spike Variability in Noisy Izhikevich Neurons Using Point Process Generalized Linear Models (Q5157108) (← links)
- Optimal Decoding of Dynamic Stimuli by Heterogeneous Populations of Spiking Neurons: A Closed-Form Approximation (Q5157218) (← links)
- Robust Closed-Loop Control of a Cursor in a Person with Tetraplegia using Gaussian Process Regression (Q5157264) (← links)
- Nonlinear Modeling of Neural Interaction for Spike Prediction Using the Staged Point-Process Model (Q5157274) (← links)
- Online Variational Inference for State-Space Models with Point-Process Observations (Q5198612) (← links)
- Decoding Hidden Cognitive States From Behavior and Physiology Using a Bayesian Approach (Q5214369) (← links)
- Direct Estimation of Inhomogeneous Markov Interval Models of Spike Trains (Q5323758) (← links)
- Information Transmission Using Non-Poisson Regular Firing (Q5327193) (← links)
- Likelihood Methods for Point Processes with Refractoriness (Q5378320) (← links)
- On Firing Rate Estimation for Dependent Interspike Intervals (Q5380220) (← links)
- A Novel Nonparametric Approach for Neural Encoding and Decoding Models of Multimodal Receptive Fields (Q5380546) (← links)
- Multiple Tests Based on a Gaussian Approximation of the Unitary Events Method with Delayed Coincidence Count (Q5383784) (← links)
- Valuations for Spike Train Prediction (Q5453532) (← links)
- A Comparison of Descriptive Models of a Single Spike Train by Information-Geometric Measure (Q5469497) (← links)
- Analyzing Functional Connectivity Using a Network Likelihood Model of Ensemble Neural Spiking Activity (Q5706655) (← links)
- Efficient Simulation of Sparse Graphs of Point Processes (Q6108734) (← links)
- A biophysical and statistical modeling paradigm for connecting neural physiology and function (Q6172492) (← links)
- Graph-based mutually exciting point processes for modelling event times in docked bike-sharing systems (Q6548942) (← links)
