J 2008

Classification of stimuli based on stimulus-response curves and their variability

LÁNSKÝ, Petr, Ondřej POKORA a Jean-Pierre ROSPARS

Základní údaje

Originální název

Classification of stimuli based on stimulus-response curves and their variability

Název česky

Klasifikace stimulů podle křivek stimulus-odpověď a jejich variabilitě

Autoři

LÁNSKÝ, Petr (203 Česká republika, domácí), Ondřej POKORA (203 Česká republika, garant, domácí) a Jean-Pierre ROSPARS (250 Francie)

Vydání

Brain Research, Amsterdam, Elsevier, 2008, 0006-8993

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10000 1. Natural Sciences

Stát vydavatele

Nizozemské království

Utajení

není předmětem státního či obchodního tajemství

Impakt faktor

Impact factor: 2.494

Kód RIV

RIV/00216224:14310/08:00024208

Organizační jednotka

Přírodovědecká fakulta

UT WoS

000258954600007

Klíčová slova anglicky

Fisher information; Information theory; Noise; Response curve; Sensory neurons; Stimulus identification

Příznaky

Mezinárodní význam, Recenzováno
Změněno: 13. 1. 2015 23:09, Mgr. Ondřej Pokora, Ph.D.

Anotace

V originále

Neuronal responses evoked in sensory neurons by static stimuli of various intensities are usually characterized by their input-output transfer function, i.e. by plotting the firing frequency (or any other measurable neuron response) versus the corresponding stimulus intensity. The aim of the present article is to determine the stimulus intensities which can be considered as "the most important" from two different points of view: transferring as much information as possible and coding the intensity as precisely as possible. These two problems are very different because, for example, an informative signal may be difficult to identify. We show that the role of noise is crucial in both problems. To obtain the range of stimuli which are the best identified, we propose to use measures based on Fisher information as known from the theory of statistical inference. To classify the most important stimuli from the point of view of information transfer, we suggest methods based on information theory. We show that both the most identifiable signal and the most informative signal are not unique. To study this, a generic model of input-output transfer function is analyzed under the influence of several different types of noise. Finally, the methods are illustrated on a model and data pertaining to olfactory sensory neurons.

Česky

Neuronal responses evoked in sensory neurons by static stimuli of various intensities are usually characterized by their input-output transfer function, i.e. by plotting the firing frequency (or any other measurable neuron response) versus the corresponding stimulus intensity. The aim of the present article is to determine the stimulus intensities which can be considered as "the most important" from two different points of view: transferring as much information as possible and coding the intensity as precisely as possible. These two problems are very different because, for example, an informative signal may be difficult to identify. We show that the role of noise is crucial in both problems. To obtain the range of stimuli which are the best identified, we propose to use measures based on Fisher information as known from the theory of statistical inference. To classify the most important stimuli from the point of view of information transfer, we suggest methods based on information theory. We show that both the most identifiable signal and the most informative signal are not unique. To study this, a generic model of input-output transfer function is analyzed under the influence of several different types of noise. Finally, the methods are illustrated on a model and data pertaining to olfactory sensory neurons.

Návaznosti

GD201/05/H007, projekt VaV
Název: Statistické dynamické modely a jejich aplikace v ekonomických, přírodovědných a technických oborech
Investor: Grantová agentura ČR, Statistické dynamické modely a jejich aplikace v ekonomických, přírodovědných a technických oborech
LC06024, projekt VaV
Název: Centrum Jaroslava Hájka pro teoretickou a aplikovanou statistiku
Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, Centrum Jaroslava Hájka pro teoretickou a aplikovanou statistiku