Evaluating the evolution and inter-individual variability of infant functional module development from 0 to 5 yr old

Lingbin Bian; Nizhuan Wang; Yuanning Li; Adeel Razi; Qian Wang; Han Zhang; Dinggang Shen

doi:10.1093/cercor/bhaf071

Evaluating the evolution and inter-individual variability of infant functional module development from 0 to 5 yr old

Lingbin Bian, Nizhuan Wang, Yuanning Li, Adeel Razi, Qian Wang, Han Zhang, Dinggang Shen (Corresponding Author)

Research output: Journal article publication › Journal article › Academic research › peer-review

Abstract

The segregation and integration of infant brain networks undergo tremendous changes due to the rapid development of brain function and organization. In this paper, we introduce a novel approach utilizing Bayesian modeling to analyze the dynamic development of functional modules in infants over time. This method retains inter-individual variability and, in comparison with conventional group averaging techniques, more effectively detects modules, taking into account the stationarity of module evolution. Furthermore, we explore gender differences in module development under awake and sleep conditions by assessing modular similarities. Our results show that female infants demonstrate more distinct modular structures between these 2 conditions, possibly implying relative quiet and restful sleep compared with male infants.

Original language	English
Article number	bhaf071
Pages (from-to)	1-14
Number of pages	14
Journal	Cerebral Cortex
Volume	35
Issue number	4
DOIs	https://doi.org/10.1093/cercor/bhaf071
Publication status	Published - 25 Apr 2025
Externally published	Yes

Keywords

fMRI
brain development
modularity
Bayesian inference

More information

10.1093/cercor/bhaf071

Cite this

@article{011d5222b23d4ce18b00e894d824e3de,

title = "Evaluating the evolution and inter-individual variability of infant functional module development from 0 to 5 yr old",

abstract = "The segregation and integration of infant brain networks undergo tremendous changes due to the rapid development of brain function and organization. In this paper, we introduce a novel approach utilizing Bayesian modeling to analyze the dynamic development of functional modules in infants over time. This method retains inter-individual variability and, in comparison with conventional group averaging techniques, more effectively detects modules, taking into account the stationarity of module evolution. Furthermore, we explore gender differences in module development under awake and sleep conditions by assessing modular similarities. Our results show that female infants demonstrate more distinct modular structures between these 2 conditions, possibly implying relative quiet and restful sleep compared with male infants.",

keywords = "fMRI, brain development, modularity, Bayesian inference",

author = "Lingbin Bian and Nizhuan Wang and Yuanning Li and Adeel Razi and Qian Wang and Han Zhang and Dinggang Shen",

year = "2025",

month = apr,

day = "25",

doi = "10.1093/cercor/bhaf071",

language = "English",

volume = "35",

pages = "1--14",

journal = "Cerebral Cortex",

issn = "1047-3211",

publisher = "Oxford University Press",

number = "4",

}

TY - JOUR

T1 - Evaluating the evolution and inter-individual variability of infant functional module development from 0 to 5 yr old

AU - Bian, Lingbin

AU - Wang, Nizhuan

AU - Li, Yuanning

AU - Razi, Adeel

AU - Wang, Qian

AU - Zhang, Han

AU - Shen, Dinggang

PY - 2025/4/25

Y1 - 2025/4/25

N2 - The segregation and integration of infant brain networks undergo tremendous changes due to the rapid development of brain function and organization. In this paper, we introduce a novel approach utilizing Bayesian modeling to analyze the dynamic development of functional modules in infants over time. This method retains inter-individual variability and, in comparison with conventional group averaging techniques, more effectively detects modules, taking into account the stationarity of module evolution. Furthermore, we explore gender differences in module development under awake and sleep conditions by assessing modular similarities. Our results show that female infants demonstrate more distinct modular structures between these 2 conditions, possibly implying relative quiet and restful sleep compared with male infants.

AB - The segregation and integration of infant brain networks undergo tremendous changes due to the rapid development of brain function and organization. In this paper, we introduce a novel approach utilizing Bayesian modeling to analyze the dynamic development of functional modules in infants over time. This method retains inter-individual variability and, in comparison with conventional group averaging techniques, more effectively detects modules, taking into account the stationarity of module evolution. Furthermore, we explore gender differences in module development under awake and sleep conditions by assessing modular similarities. Our results show that female infants demonstrate more distinct modular structures between these 2 conditions, possibly implying relative quiet and restful sleep compared with male infants.

KW - fMRI

KW - brain development

KW - modularity

KW - Bayesian inference

UR - https://academic.oup.com/cercor/article/35/4/bhaf071/8119856?searchresult=1

UR - http://www.scopus.com/inward/record.url?scp=105003780184&partnerID=8YFLogxK

U2 - 10.1093/cercor/bhaf071

DO - 10.1093/cercor/bhaf071

M3 - Journal article

SN - 1047-3211

VL - 35

SP - 1

EP - 14

JO - Cerebral Cortex

JF - Cerebral Cortex

IS - 4

M1 - bhaf071

ER -

Evaluating the evolution and inter-individual variability of infant functional module development from 0 to 5 yr old

Abstract

Keywords

More information

Other files and links

Fingerprint

Cite this