ID Consecutivo : 1975

Titulo

serie

Editorial

 

ISBN

Año de publicación Edición Primera Segunda Tercera Cuarta Quita Sexta Septima Octava Novena Decima Selecione una

Paginas Existencias 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Resumen
The development and application of concepts is a critical component of cognition. Although concepts can be formed on the basis of simple perceptual or semantic features, conceptual representations can also capitalize on similarities across feature relationships. By representing these types of higher-order relationships, concepts can simplify the learning problem and facilitate decisions. Despite this, little is known about the neural mechanisms that support the construction and deployment of these kinds of higher-order concepts during learning. To address this question, we combined a carefully designed associative learning task with computational model-based functional magnetic resonance imaging (fMRI). Participants were scanned as they learned and made decisions about sixteen pairs of cues and associated outcomes. Associations were structured such that individual cues shared feature relationships, operationalized as shared patterns of cue pair-outcome associations. In order to capture the large number of possible conceptual representational structures that participants might employ and to evaluate how conceptual representations are used during learning, we leveraged a well-specified Bayesian computational model of category learning [1]. Behavioral and model-based results revealed that participants who displayed a tendency to link experiences in memory benefitted from faster learning rates, suggesting that the use of the conceptual structure in the task facilitated decisions about cue pair-outcome associations. Model-based fMRI analyses revealed that trial-by-trial integration of cue information into higher-order conceptual representations was supported by an anterior temporal (AT) network of regions previously implicated in representing complex conjunctions of features and meaning-based information.

 

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Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Evaluacion Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

Disponibilidad:	Digital	Físico	Físico y Digital	Link Externo

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Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores

 

Signatura topografica:

ID Consecutivo : 1975

Titulo

Editorial

 

Año de publicación Edición Primera Segunda Tercera Cuarta Quita Sexta Septima Octava Novena Decima Selecione una

Paginas Existencias 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Resumen
The development and application of concepts is a critical component of cognition. Although concepts can be formed on the basis of simple perceptual or semantic features, conceptual representations can also capitalize on similarities across feature relationships. By representing these types of higher-order relationships, concepts can simplify the learning problem and facilitate decisions. Despite this, little is known about the neural mechanisms that support the construction and deployment of these kinds of higher-order concepts during learning. To address this question, we combined a carefully designed associative learning task with computational model-based functional magnetic resonance imaging (fMRI). Participants were scanned as they learned and made decisions about sixteen pairs of cues and associated outcomes. Associations were structured such that individual cues shared feature relationships, operationalized as shared patterns of cue pair-outcome associations. In order to capture the large number of possible conceptual representational structures that participants might employ and to evaluate how conceptual representations are used during learning, we leveraged a well-specified Bayesian computational model of category learning [1]. Behavioral and model-based results revealed that participants who displayed a tendency to link experiences in memory benefitted from faster learning rates, suggesting that the use of the conceptual structure in the task facilitated decisions about cue pair-outcome associations. Model-based fMRI analyses revealed that trial-by-trial integration of cue information into higher-order conceptual representations was supported by an anterior temporal (AT) network of regions previously implicated in representing complex conjunctions of features and meaning-based information.

 

Adjunte la portada del libro Si no tiene una imagen, descargue aqui la imagen de Ascofame

Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Evaluacion Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

Disponibilidad:	Digital	Físico	Físico y Digital	Link Externo

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Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores

 

Signatura topografica:

ID Consecutivo : 1975

Titulo

Tipo : Ley Decreto Norma Resolucion Circular Directiva

 

Año de publicación

Resumen
The development and application of concepts is a critical component of cognition. Although concepts can be formed on the basis of simple perceptual or semantic features, conceptual representations can also capitalize on similarities across feature relationships. By representing these types of higher-order relationships, concepts can simplify the learning problem and facilitate decisions. Despite this, little is known about the neural mechanisms that support the construction and deployment of these kinds of higher-order concepts during learning. To address this question, we combined a carefully designed associative learning task with computational model-based functional magnetic resonance imaging (fMRI). Participants were scanned as they learned and made decisions about sixteen pairs of cues and associated outcomes. Associations were structured such that individual cues shared feature relationships, operationalized as shared patterns of cue pair-outcome associations. In order to capture the large number of possible conceptual representational structures that participants might employ and to evaluate how conceptual representations are used during learning, we leveraged a well-specified Bayesian computational model of category learning [1]. Behavioral and model-based results revealed that participants who displayed a tendency to link experiences in memory benefitted from faster learning rates, suggesting that the use of the conceptual structure in the task facilitated decisions about cue pair-outcome associations. Model-based fMRI analyses revealed that trial-by-trial integration of cue information into higher-order conceptual representations was supported by an anterior temporal (AT) network of regions previously implicated in representing complex conjunctions of features and meaning-based information.

 

Adjunte la portada del libro Si no tiene una imagen, descargue aqui la imagen de Ascofame

Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Evaluacion Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

Disponibilidad:	Digital	Físico	Físico y Digital	Link Externo

Cargue el Documento

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Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores

 

ID Consecutivo : 1975

Titulo

Autor como conferencia

Paginas

 

Año de publicación

Resumen
The development and application of concepts is a critical component of cognition. Although concepts can be formed on the basis of simple perceptual or semantic features, conceptual representations can also capitalize on similarities across feature relationships. By representing these types of higher-order relationships, concepts can simplify the learning problem and facilitate decisions. Despite this, little is known about the neural mechanisms that support the construction and deployment of these kinds of higher-order concepts during learning. To address this question, we combined a carefully designed associative learning task with computational model-based functional magnetic resonance imaging (fMRI). Participants were scanned as they learned and made decisions about sixteen pairs of cues and associated outcomes. Associations were structured such that individual cues shared feature relationships, operationalized as shared patterns of cue pair-outcome associations. In order to capture the large number of possible conceptual representational structures that participants might employ and to evaluate how conceptual representations are used during learning, we leveraged a well-specified Bayesian computational model of category learning [1]. Behavioral and model-based results revealed that participants who displayed a tendency to link experiences in memory benefitted from faster learning rates, suggesting that the use of the conceptual structure in the task facilitated decisions about cue pair-outcome associations. Model-based fMRI analyses revealed that trial-by-trial integration of cue information into higher-order conceptual representations was supported by an anterior temporal (AT) network of regions previously implicated in representing complex conjunctions of features and meaning-based information.

 

Adjunte la portada del libro Si no tiene una imagen, descargue aqui la imagen de Ascofame

Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Evaluacion Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

Disponibilidad:	Digital	Físico	Físico y Digital	Link Externo

Cargue el Documento

Ingrese el Link: ejemplo: http://www.google.com.co

 

Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores

 

ID Consecutivo : 1975

Titulo

 

Año de publicación

Producción de publicación

Volumen

ISBN

Frecuencia

Resumen
The development and application of concepts is a critical component of cognition. Although concepts can be formed on the basis of simple perceptual or semantic features, conceptual representations can also capitalize on similarities across feature relationships. By representing these types of higher-order relationships, concepts can simplify the learning problem and facilitate decisions. Despite this, little is known about the neural mechanisms that support the construction and deployment of these kinds of higher-order concepts during learning. To address this question, we combined a carefully designed associative learning task with computational model-based functional magnetic resonance imaging (fMRI). Participants were scanned as they learned and made decisions about sixteen pairs of cues and associated outcomes. Associations were structured such that individual cues shared feature relationships, operationalized as shared patterns of cue pair-outcome associations. In order to capture the large number of possible conceptual representational structures that participants might employ and to evaluate how conceptual representations are used during learning, we leveraged a well-specified Bayesian computational model of category learning [1]. Behavioral and model-based results revealed that participants who displayed a tendency to link experiences in memory benefitted from faster learning rates, suggesting that the use of the conceptual structure in the task facilitated decisions about cue pair-outcome associations. Model-based fMRI analyses revealed that trial-by-trial integration of cue information into higher-order conceptual representations was supported by an anterior temporal (AT) network of regions previously implicated in representing complex conjunctions of features and meaning-based information.

 

Adjunte la portada del libro Si no tiene una imagen, descargue aqui la imagen de Ascofame

Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Evaluacion Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

Disponibilidad:	Digital	Físico	Físico y Digital	Link Externo

Cargue el Documento

Ingrese el Link: ejemplo: http://www.google.com.co

 

Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores

 

ID Consecutivo : 1975

Titulo videos

Año de publicación

Resumen
The development and application of concepts is a critical component of cognition. Although concepts can be formed on the basis of simple perceptual or semantic features, conceptual representations can also capitalize on similarities across feature relationships. By representing these types of higher-order relationships, concepts can simplify the learning problem and facilitate decisions. Despite this, little is known about the neural mechanisms that support the construction and deployment of these kinds of higher-order concepts during learning. To address this question, we combined a carefully designed associative learning task with computational model-based functional magnetic resonance imaging (fMRI). Participants were scanned as they learned and made decisions about sixteen pairs of cues and associated outcomes. Associations were structured such that individual cues shared feature relationships, operationalized as shared patterns of cue pair-outcome associations. In order to capture the large number of possible conceptual representational structures that participants might employ and to evaluate how conceptual representations are used during learning, we leveraged a well-specified Bayesian computational model of category learning [1]. Behavioral and model-based results revealed that participants who displayed a tendency to link experiences in memory benefitted from faster learning rates, suggesting that the use of the conceptual structure in the task facilitated decisions about cue pair-outcome associations. Model-based fMRI analyses revealed that trial-by-trial integration of cue information into higher-order conceptual representations was supported by an anterior temporal (AT) network of regions previously implicated in representing complex conjunctions of features and meaning-based information.

 

Adjunte la Imagen del Video

 

Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Evaluacion Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

https://pesquisa.bvsalud.org/portal/resource/es/mdl-30427917

Ingrese el Link: ejemplo: http://www.google.com.co

 

Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores

 

ID Consecutivo : 1975

Titulo

Titulo Revista

ISSN

Año de publicación Suplemento

Numero: Volumen

Pagina Inicial Pagina Final

Resumen
The development and application of concepts is a critical component of cognition. Although concepts can be formed on the basis of simple perceptual or semantic features, conceptual representations can also capitalize on similarities across feature relationships. By representing these types of higher-order relationships, concepts can simplify the learning problem and facilitate decisions. Despite this, little is known about the neural mechanisms that support the construction and deployment of these kinds of higher-order concepts during learning. To address this question, we combined a carefully designed associative learning task with computational model-based functional magnetic resonance imaging (fMRI). Participants were scanned as they learned and made decisions about sixteen pairs of cues and associated outcomes. Associations were structured such that individual cues shared feature relationships, operationalized as shared patterns of cue pair-outcome associations. In order to capture the large number of possible conceptual representational structures that participants might employ and to evaluate how conceptual representations are used during learning, we leveraged a well-specified Bayesian computational model of category learning [1]. Behavioral and model-based results revealed that participants who displayed a tendency to link experiences in memory benefitted from faster learning rates, suggesting that the use of the conceptual structure in the task facilitated decisions about cue pair-outcome associations. Model-based fMRI analyses revealed that trial-by-trial integration of cue information into higher-order conceptual representations was supported by an anterior temporal (AT) network of regions previously implicated in representing complex conjunctions of features and meaning-based information.

 

Base de datos bibliográfica Base de datos bibliográfica Seleccione una Access Medicine Biblioteca VirtualenSalud(BVS) Cochrane Central Dialnet Lilacs-Literatura Latinoamericana en Ciencias de la Salud Medline-PubMed Redalyc ScienceDirect SciELO-Scientific Electronic Library Online WHOLIS Otra

Imagen de portada

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Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Evaluacion Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

Disponibilidad:	Digital	Físico	Físico y Digital	Link Externo

Cargue el Documento

Ingrese el Link: ejemplo: http://www.google.com.co

 

Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores