Pages that link to "Item:Q3070780"
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The following pages link to Model-Based Decoding, Information Estimation, and Change-Point Detection Techniques for Multineuron Spike Trains (Q3070780):
Displaying 26 items.
- Multi-scale detection of rate changes in spike trains with weak dependencies (Q146398) (← links)
- Estimation bias in maximum entropy models (Q280482) (← links)
- Reconstruction of the input signal of the leaky integrate-and-fire neuronal model from its interspike intervals (Q310131) (← links)
- Demodulation methods for an adaptive neural encoder model (Q792254) (← links)
- Bayesian decoding of neural spike trains (Q904063) (← links)
- Toward statistically valid population decoding models (Q1851626) (← links)
- Information processing in the LGN: a comparison of neural codes and cell types (Q2317476) (← links)
- Techniques for temporal detection of neural sensitivity to external stimulation (Q2376428) (← links)
- Ensembles of change-point detectors: implications for real-time BMI applications (Q2418247) (← links)
- Dynamics and spike trains statistics in conductance-based integrate-and-fire neural networks with chemical and electric synapses (Q2451077) (← links)
- Bivariate cumulative probit model for the comparison of neuronal encoding hypotheses (Q2874291) (← links)
- Efficient Markov Chain Monte Carlo Methods for Decoding Neural Spike Trains (Q3070781) (← links)
- Spatio-temporal spike train analysis for large scale networks using the maximum entropy principle and Monte Carlo method (Q3301544) (← links)
- Information Loss in an Optimal Maximum Likelihood Decoding (Q4330666) (← links)
- Statistical Analysis of Decoding Performances of Diverse Populations of Neurons (Q5004321) (← links)
- A Model for the Study of the Increase in Stimulus and Change Point Detection with Small and Variable Spiking Delays (Q5131147) (← links)
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- A phase transition in the first passage of a Brownian process through a fluctuating boundary with implications for neural coding (Q5171003) (← links)
- Encoding Through Patterns: Regression Tree–Based Neuronal Population Models (Q5378240) (← links)
- Likelihood Methods for Point Processes with Refractoriness (Q5378320) (← links)
- A Computationally Efficient Method for Incorporating Spike Waveform Information into Decoding Algorithms (Q5380236) (← links)
- Neural Decoding with Kernel-Based Metric Learning (Q5383772) (← links)
- Estimating Information Rates with Confidence Intervals in Neural Spike Trains (Q5457581) (← links)
- Hawkes process modelling for chemical reaction networks in a random environment (Q6629677) (← links)
