Statistical models for neural encoding, decoding, and optimal stimulus design.
about
Of toasters and molecular ticker tapesProcessing and Analysis of Multichannel Extracellular Neuronal Signals: State-of-the-Art and ChallengesOptogenetic approaches to retinal prosthesisA virtual retina for studying population codingReceptive Field Vectors of Genetically-Identified Retinal Ganglion Cells Reveal Cell-Type-Dependent Visual FunctionsAnesthetic state modulates excitability but not spectral tuning or neural discrimination in single auditory midbrain neurons.Input-Specific Gain Modulation by Local Sensory Context Shapes Cortical and Thalamic Responses to Complex Sounds.Neuron-specific stimulus masking reveals interference in spike timing at the cortical level.Online stimulus optimization rapidly reveals multidimensional selectivity in auditory cortical neurons.Encoding of ultrasonic vocalizations in the auditory cortex.A point process framework for modeling electrical stimulation of the auditory nerve.Automating the design of informative sequences of sensory stimuliBiophysical information representation in temporally correlated spike trains.A generalized linear model for estimating spectrotemporal receptive fields from responses to natural sounds.Model-based feature construction for multivariate decoding.Determining the role of correlated firing in large populations of neurons using white noise and natural scene stimuliA unified approach to linking experimental, statistical and computational analysis of spike train data.Intrinsic gain modulation and adaptive neural codingAutomatic fitting of spiking neuron models to electrophysiological recordingsCollective dynamics in human and monkey sensorimotor cortex: predicting single neuron spikesHow advances in neural recording affect data analysisAn Adaptation-Induced Repulsion Illusion in Tactile Spatial PerceptionFitting neuron models to spike trains.Modulation of temporal precision in thalamic population responses to natural visual stimuliCoding and decoding with adapting neurons: a population approach to the peri-stimulus time histogram.Temporal precision in the visual pathway through the interplay of excitation and stimulus-driven suppressionSparse decoding of multiple spike trains for brain-machine interfaces.A generalized linear model of the impact of direct and indirect inputs to the lateral geniculate nucleusUsing Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains.Retinal prosthetic strategy with the capacity to restore normal visionPostnatal development attunes olfactory bulb mitral cells to high-frequency signalingPrediction of primary somatosensory neuron activity during active tactile exploration.Local field potentials indicate network state and account for neuronal response variabilityComputational identification of receptive fields.Interacting linear and nonlinear characteristics produce population coding asymmetries between ON and OFF cells in the retina.Spike inference from calcium imaging using sequential Monte Carlo methods.An overview of Bayesian methods for neural spike train analysis.Divisive suppression explains high-precision firing and contrast adaptation in retinal ganglion cells.The science of neural interface systems.Bayesian decoding using unsorted spikes in the rat hippocampus.
P2860
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P2860
Statistical models for neural encoding, decoding, and optimal stimulus design.
description
2007 nî lūn-bûn
@nan
2007年の論文
@ja
2007年論文
@yue
2007年論文
@zh-hant
2007年論文
@zh-hk
2007年論文
@zh-mo
2007年論文
@zh-tw
2007年论文
@wuu
2007年论文
@zh
2007年论文
@zh-cn
name
Statistical models for neural encoding, decoding, and optimal stimulus design.
@en
type
label
Statistical models for neural encoding, decoding, and optimal stimulus design.
@en
prefLabel
Statistical models for neural encoding, decoding, and optimal stimulus design.
@en
P1476
Statistical models for neural encoding, decoding, and optimal stimulus design.
@en
P2093
Jeremy Lewi
Jonathan Pillow
P304
P356
10.1016/S0079-6123(06)65031-0
P577
2007-01-01T00:00:00Z