Cortical thickness and age-related thinning jointly reveal spatial patterns of granularity (2018)
- Authors:
- USP affiliated authors: SALMON, CARLOS ERNESTO GARRIDO - FFCLRP ; VIEIRA, BRUNO HEBLING - FFCLRP
- Unidade: FFCLRP
- Assunto: CÉREBRO
- Language: Inglês
- Imprenta:
- Publisher: Sociedade Brasileira de Física - SBF
- Publisher place: São Paulo
- Date published: 2018
- Source:
- Título: Resumos
- Conference titles: Encontro de Outono da Sociedade Brasileira de Física - EOSBF
-
ABNT
VIEIRA, Bruno Hebling e SALMON, Carlos Ernesto Garrido. Cortical thickness and age-related thinning jointly reveal spatial patterns of granularity. 2018, Anais.. São Paulo: Sociedade Brasileira de Física - SBF, 2018. Disponível em: https://sec.sbfisica.org.br/eventos/enfmc/xli/prog/trabalhos.asp?sesId=105. Acesso em: 31 dez. 2025. -
APA
Vieira, B. H., & Salmon, C. E. G. (2018). Cortical thickness and age-related thinning jointly reveal spatial patterns of granularity. In Resumos. São Paulo: Sociedade Brasileira de Física - SBF. Recuperado de https://sec.sbfisica.org.br/eventos/enfmc/xli/prog/trabalhos.asp?sesId=105 -
NLM
Vieira BH, Salmon CEG. Cortical thickness and age-related thinning jointly reveal spatial patterns of granularity [Internet]. Resumos. 2018 ;[citado 2025 dez. 31 ] Available from: https://sec.sbfisica.org.br/eventos/enfmc/xli/prog/trabalhos.asp?sesId=105 -
Vancouver
Vieira BH, Salmon CEG. Cortical thickness and age-related thinning jointly reveal spatial patterns of granularity [Internet]. Resumos. 2018 ;[citado 2025 dez. 31 ] Available from: https://sec.sbfisica.org.br/eventos/enfmc/xli/prog/trabalhos.asp?sesId=105 - A deep learning based approach identifies regions more relevant than resting‐state networks to the prediction of general intelligence from resting‐state fMRI
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