ArticleBiological cybernetics1994
Analysis, classification, and coding of multielectrode spike trains with hidden Markov models.
Article in Biological cybernetics, 1994. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Exploiting correlations across trials and behavioral sessions to improve neural decoding.Neuron · 2026Article
- Exploiting correlations across trials and behavioral sessions to improve neural decoding.bioRxiv : the preprint server for biology · 2025Article
- A sticky Poisson Hidden Markov Model for solving the problem of over-segmentation and rapid state switching in cortical datasets.bioRxiv : the preprint server for biology · 2025Article
- A sticky Poisson Hidden Markov Model for solving the problem of over-segmentation and rapid state switching in cortical datasets.PloS one · 2025Article
- Latent dynamics of primary sensory cortical population activity structured by fluctuations in the local field potential.Frontiers in computational neuroscience · 2024Article
- Temporal progression along discrete coding states during decision-making in the mouse gustatory cortex.PLoS computational biology · 2023Article
- Metastable dynamics of neural circuits and networks.Applied physics reviews · 2022Review
- A novel approach to teaching Hidden Markov Models to a diverse undergraduate population.Heliyon · 2021Article
- Signal Fluctuations and the Information Transmission Rates in Binary Communication Channels.Entropy (Basel, Switzerland) · 2021Article
- Attractor-state itinerancy in neural circuits with synaptic depression.Journal of mathematical neuroscience · 2020Article
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- Closed-Loop Deep Brain Stimulation for Refractory Chronic Pain.Frontiers in computational neuroscience · 2018Article
- Itinerancy between attractor states in neural systems.Current opinion in neurobiology · 2016Review
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- High Accuracy Decoding of Dynamical Motion from a Large Retinal Population.PLoS computational biology · 2015Article
- Dynamic alignment models for neural coding.PLoS computational biology · 2014Article
- Compositionality in neural control: an interdisciplinary study of scribbling movements in primates.Frontiers in computational neuroscience · 2013Article
- Abrupt changes in the patterns and complexity of anterior cingulate cortex activity when food is introduced into an environment.Frontiers in neuroscience · 2013Article
- Neural dynamics of choice: single-trial analysis of decision-related activity in parietal cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2012Article
- Timescales of multineuronal activity patterns reflect temporal structure of visual stimuli.PloS one · 2011Article
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4 authors.
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Abstract
It is shown that hidden Markov models (HMMs) are a powerful tool in the analysis of multielectrode data. This is demonstrated for a 30-electrode measurement of neuronal spike activity in the monkey's visual cortex during the application of different visual stimuli. HMMs with optimized parameters code the information contained in the spatiotemporal discharge patterns as a probabilistic function of a Markov process and thus provide abstract dynamical models of the pattern-generating process. We compare HMMs obtained from vector-quantized data with models in which parametrized output processes such as multivariate Poisson or binomial distributions are assumed. In the latter cases the visual stimuli are recognized at rates of more than 90% from the neuronal spike patterns. An analysis of the models obtained reveals important aspects of the coding of information in the brain. For example, we identify relevant time scales and characterize the degree and nature of the spatiotemporal variations on these scales.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.