Trabajo de InvestigaciónEl presente estudio tuvo como objetivo evaluar el desempeño de 24 ratas Wistar en una tarea de memoria espacial, según las características de sexo y edad (ratas jóvenes y ratas adultas). Para este fin, se llevó a cabo una fase inicial de habituación de 10 minuto diarios en el laberinto radial de Olton, y una fase de entrenamiento de una tarea de memoria espacial durante 27 sesiones.INTRODUCCIÓN Y ASPECTOS GENERALES
1. RESUMEN
2. JUSTIFICACIÓN
3. MARCO TEÓRICO
4. MÉTODO
5. RESULTADOS 6. DISCUSIÓN Y CONCLUSIONES
BIBLIOGRAFÍA
ANEXOSPregradoPsicólog

Honda Naoki (59683)

Ikue Mori (221423)

Muneki Ikeda (5166362)

Shin Ishii (1617)

Shoichiro Yamaguchi (5166356)

Shunji Nakano (5166359)

Yuki Tsukada (221420)

Spanish

Shoichiro Yamaguchi

Honda Naoki

Muneki Ikeda

Yuki Tsukada

Shunji Nakano

Ikue Mori

Shin Ishii

Crossref

PLoS Computational Biology

Identification of animal behavioral strategies by inverse reinforcement learning

Trabajo de InvestigaciónEl presente estudio tuvo como objetivo evaluar el desempeño de 24 ratas Wistar en una tarea de memoria espacial, según las características de sexo y edad (ratas jóvenes y ratas adultas). Para este fin, se llevó a cabo una fase inicial de habituación de 10 minuto diarios en el laberinto radial de Olton, y una fase de entrenamiento de una tarea de memoria espacial durante 27 sesiones.PregradoPsicólogoINTRODUCCIÓN Y ASPECTOS GENERALES
1. RESUMEN
2. JUSTIFICACIÓN
3. MARCO TEÓRICO
4. MÉTODO
5. RESULTADOS 6. DISCUSIÓN Y CONCLUSIONES
BIBLIOGRAFÍA
ANEXO

Arévalo-Contreras, Daniela Alejandra

Durán-Jacobo, Carol Johanna

González-González, Carol Zolangie

Repositorio Institucional Universidad Católica de Colombia

Efectos de la edad y el sexo sobre la memoria espacial de ratas Wistar en el laberinto radial de 8 brazos

Animals are able to reach a desired state in an environment by controlling various behavioral patterns. Identification of the behavioral strategy used for this control is important for understanding animals’ decision-making and is fundamental to dissect information processing done by the nervous system. However, methods for quantifying such behavioral strategies have not been fully established. In this study, we developed an inverse reinforcement-learning (IRL) framework to identify an animal’s behavioral strategy from behavioral time-series data. We applied this framework to C. elegans thermotactic behavior; after cultivation at a constant temperature with or without food, fed worms prefer, while starved worms avoid the cultivation temperature on a thermal gradient. Our IRL approach revealed that the fed worms used both the absolute temperature and its temporal derivative and that their behavior involved two strategies: directed migration (DM) and isothermal migration (IM). With DM, worms efficiently reached specific temperatures, which explains their thermotactic behavior when fed. With IM, worms moved along a constant temperature, which reflects isothermal tracking, well-observed in previous studies. In contrast to fed animals, starved worms escaped the cultivation temperature using only the absolute, but not the temporal derivative of temperature. We also investigated the neural basis underlying these strategies, by applying our method to thermosensory neuron-deficient worms. Thus, our IRL-based approach is useful in identifying animal strategies from behavioral time-series data and could be applied to a wide range of behavioral studies, including decision-making, in other organisms.</div

The Francis Crick Institute

機械学習により「動物の行動戦略」を解読 --動物は何を報酬として行動しているのか--. 京都大学プレスリリース. 2018-05-18.Animals are able to reach a desired state in an environment by controlling various behavioral patterns. Identification of the behavioral strategy used for this control is important for understanding animals’ decision-making and is fundamental to dissect information processing done by the nervous system. However, methods for quantifying such behavioral strategies have not been fully established. In this study, we developed an inverse reinforcement-learning (IRL) framework to identify an animal’s behavioral strategy from behavioral time-series data. We applied this framework to C. elegans thermotactic behavior; after cultivation at a constant temperature with or without food, fed worms prefer, while starved worms avoid the cultivation temperature on a thermal gradient. Our IRL approach revealed that the fed worms used both the absolute temperature and its temporal derivative and that their behavior involved two strategies: directed migration (DM) and isothermal migration (IM). With DM, worms efficiently reached specific temperatures, which explains their thermotactic behavior when fed. With IM, worms moved along a constant temperature, which reflects isothermal tracking, well-observed in previous studies. In contrast to fed animals, starved worms escaped the cultivation temperature using only the absolute, but not the temporal derivative of temperature. We also investigated the neural basis underlying these strategies, by applying our method to thermosensory neuron-deficient worms. Thus, our IRL-based approach is useful in identifying animal strategies from behavioral time-series data and could be applied to a wide range of behavioral studies, including decision-making, in other organisms

Yamaguchi, Shoichiro

Naoki, Honda

Ikeda, Muneki

Tsukada, Yuki

Nakano, Shunji

Mori, Ikue

Ishii, Shin

Kyoto University Research Information Repository

Animals are able to reach a desired state in an environment by controlling various behavioral patterns. Identification of the behavioral strategy used for this control is important for understanding animals' decision-making and is fundamental to dissect information processing done by the nervous system. However, methods for quantifying such behavioral strategies have not been fully established. In this study, we developed an inverse reinforcement-learning (IRL) framework to identify an animal's behavioral strategy from behavioral time-series data. We applied this framework to C. elegans thermotactic behavior; after cultivation at a constant temperature with or without food, fed worms prefer, while starved worms avoid the cultivation temperature on a thermal gradient. Our IRL approach revealed that the fed worms used both the absolute temperature and its temporal derivative and that their behavior involved two strategies: directed migration (DM) and isothermal migration (IM). With DM, worms efficiently reached specific temperatures, which explains their thermotactic behavior when fed. With IM, worms moved along a constant temperature, which reflects isothermal tracking, well-observed in previous studies. In contrast to fed animals, starved worms escaped the cultivation temperature using only the absolute, but not the temporal derivative of temperature. We also investigated the neural basis underlying these strategies, by applying our method to thermosensory neuron-deficient worms. Thus, our IRL-based approach is useful in identifying animal strategies from behavioral time-series data and could be applied to a wide range of behavioral studies, including decision-making, in other organisms

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Identification of animal behavioral strategies by inverse reinforcement learning.

Efectos de la edad y el sexo sobre la memoria espacial de ratas Wistar en el laberinto radial de 8 brazos

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Repositorio Institucional Universidad Católica de Colombia

The Francis Crick Institute

Kyoto University Research Information Repository

Directory of Open Access Journals