Modeling self-organized emergence of perspective in/variant mirror neurons in a robotic system

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F19%3A00337693" target="_blank" >RIV/68407700:21730/19:00337693 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/DEVLRN.2019.8850692" target="_blank" >https://doi.org/10.1109/DEVLRN.2019.8850692</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/DEVLRN.2019.8850692" target="_blank" >10.1109/DEVLRN.2019.8850692</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Modeling self-organized emergence of perspective in/variant mirror neurons in a robotic system

Popis výsledku v původním jazyce

A major role attributed to mirror neurons, according to the direct matching hypothesis, is to mediate the link between an observed action and agent's own motor repertoire, to provide understanding STS from inside. The mirror neurons gave rise to various models but one of the issues not tackled by them is the perspective in/variance. Neurons in STS visual areas can be either perspective selective or invariant and the same variability was later also discovered in premotor F5 area in macaques, showing the existence of different types of mirror neurons regarding their perspective selectivity. We model this as an emergent phenomenom using the data from the simulated iCub robot, that learns to reach for objects with three types of grasp. The neural network model learns in two phases. First, the motor (F5) and visual (STS) modules are trained in parallel to self-organize modal maps using the corresponding data sequences from the self-perspective. Then, F5 area is retrained using the output from the pretrained STS module, to acquire the mirroring property. Using the optimized model hyperparameters found by grid search, we show that our model fits very well empirical observations, by showing how neurons with various degrees of perspective selectivity emerge in the F5 map.

Název v anglickém jazyce

Modeling self-organized emergence of perspective in/variant mirror neurons in a robotic system

Popis výsledku anglicky

A major role attributed to mirror neurons, according to the direct matching hypothesis, is to mediate the link between an observed action and agent's own motor repertoire, to provide understanding STS from inside. The mirror neurons gave rise to various models but one of the issues not tackled by them is the perspective in/variance. Neurons in STS visual areas can be either perspective selective or invariant and the same variability was later also discovered in premotor F5 area in macaques, showing the existence of different types of mirror neurons regarding their perspective selectivity. We model this as an emergent phenomenom using the data from the simulated iCub robot, that learns to reach for objects with three types of grasp. The neural network model learns in two phases. First, the motor (F5) and visual (STS) modules are trained in parallel to self-organize modal maps using the corresponding data sequences from the self-perspective. Then, F5 area is retrained using the output from the pretrained STS module, to acquire the mirroring property. Using the optimized model hyperparameters found by grid search, we show that our model fits very well empirical observations, by showing how neurons with various degrees of perspective selectivity emerge in the F5 map.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20204 - Robotics and automatic control

Projekt

<a href="/cs/project/VI20172019082" target="_blank" >VI20172019082: Smart Camera - Dohledové centrum nové generace</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob)

ISBN

978-1-5386-8128-2

ISSN

2161-9484

e-ISSN

2161-9484

Počet stran výsledku

6

Strana od-do

278-283

Název nakladatele

IEEE

Místo vydání

Anchorage, Alaska

Místo konání akce

Oslo

Datum konání akce

19. 8. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000564518200042