Cargando…
An Information-Theoretic Approach for Evaluating Probabilistic Tuning Functions of Single Neurons
Neuronal tuning functions can be expressed by the conditional probability of observing a spike given any combination of explanatory variables. However, accurately determining such probabilistic tuning functions from experimental data poses several challenges such as finding the right combination of...
Autores principales: | Brostek, Lukas, Eggert, Thomas, Ono, Seiji, Mustari, Michael J., Büttner, Ulrich, Glasauer, Stefan |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
Frontiers Research Foundation
2011
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3071493/ https://www.ncbi.nlm.nih.gov/pubmed/21503137 http://dx.doi.org/10.3389/fncom.2011.00015 |
Ejemplares similares
-
Gain Control in Predictive Smooth Pursuit Eye Movements: Evidence for an Acceleration-Based Predictive Mechanism
por: Brostek, Lukas, et al.
Publicado: (2017) -
Smooth Pursuit–Related Information Processing in Frontal Eye Field Neurons that Project to the NRTP
por: Ono, Seiji, et al.
Publicado: (2009) -
Emerging Artificial Neuron Devices for Probabilistic Computing
por: Li, Zong-xiao, et al.
Publicado: (2021) -
Frequency-Domain Analysis of Intrinsic Neuronal Properties using High-Resistant Electrodes
por: Rössert, Christian, et al.
Publicado: (2009) -
An Information Theoretic Approach to Reveal the Formation of Shared Representations
por: Eguchi, Akihiro, et al.
Publicado: (2020)