Developmental Shifts in Neurobehavioral Substrates of Attentional Networks:A Longitudinal fMRI Study
Poster No:
1306
Submission Type:
Abstract Submission
Authors:
Siya Peng1, Rui Ding1, Yuyao Zhao1, Lei Hao1, Shaozheng Qin1
Institutions:
1Beijing Normal University, Beijing, Beiijng
First Author:
Co-Author(s):
Introduction:
Human brain undergoes a prolonged maturation process to support nuanced cognitive functions, wherein developmental shifts may occur, giving rise to sensitive periods of development. However, hindered by small sample sizes, cross-sectional designs, and limited age range distribution, the impact of age maturation on the neurobehavioral substrates of attention networks, and dynamic shifts in these substrates during development, still remain elusive. Utilizing longitudinal data to capture developmental changes in attention can contribute to early clinical detection.
Methods:
This study is part of the Beijing Cohort of the Children School Functions and Brain Development Project. A total of 846 scans were completed, spanning over ages 6 to 16, at an interval of one year for three years, with 400, 281, and 165 scans per year. An additional fMRI dataset from 84 healthy young adults (final sample of 73) was used for comparative purposes. Based on the neural specialization perspective, we investigated changes in brain systems involved in three attentional components (i.e., alerting, orienting, and executive attention). The child-friendly version of the Attention Network Test (ANT) developed by Fan et al., (2002) was used. This version includes four cue-prompt conditions and two target-response flanker tasks to measure alerting, orienting, and executive attention processes.
In order to investigate the developmental trajectories of behavioral indices for three attentional processes with age, we analyzed behavioral performance in the ANT by calculating the average reaction times (RTs) for different cue and target conditions, and fitted the developmental trajectories using linear mixed-effects (LME) models. In terms of neural activity, we used voxel-based linear mixed-effects models to analyze the interaction between age and behavior during attention using the 3dLMEr in AFNI. We also extracted regions of interest (ROIs) and studied the activation patterns of these regions. Finally, we performed a generalized psychophysiological interaction (gPPI) analysis to explore the functional connectivity patterns that support differences in attentional behaviors.
In order to investigate the developmental trajectories of behavioral indices for three attentional processes with age, we analyzed behavioral performance in the ANT by calculating the average reaction times (RTs) for different cue and target conditions, and fitted the developmental trajectories using linear mixed-effects (LME) models. In terms of neural activity, we used voxel-based linear mixed-effects models to analyze the interaction between age and behavior during attention using the 3dLMEr in AFNI. We also extracted regions of interest (ROIs) and studied the activation patterns of these regions. Finally, we performed a generalized psychophysiological interaction (gPPI) analysis to explore the functional connectivity patterns that support differences in attentional behaviors.
Results:
Behaviorally, the three attention processes-alerting, orienting, and executive control-follow distinct age-related developmental paths, ultimately converging towards adult proficiency, indicative of attentional maturation. The alerting network's efficiency demonstrates an inverted U-shaped trajectory, while the orienting network's efficiency marginally declines, and the executive control network's efficiency consistently enhances with age.
Neurally, there is a shifting point from 9 to 10 in age by performance interactions. Specifically, in alerting and orienting networks, an interaction between age and behavioral performance was observed in the activation of the frontal eye fields (FEF) and supplementary motor area (SMA). Younger children show better performance with higher activation, a trend that reverses in older children. Furthermore, children with poorer attention performance relied on functional connectivity between the SMA and other brain regions like the thalamus and precuneus to maintain attention efficiency, a dependency that diminishes with age. Similarly, stronger activation of the right rostrolateral prefrontal cortex (RLPFC) and temporoparietal junction (TPJ), along with higher levels of ventral striatum-dorsomedial prefrontal cortex (VS-dmPFC) functional connectivity, support the development of children with poorer executive attention performance.
Neurally, there is a shifting point from 9 to 10 in age by performance interactions. Specifically, in alerting and orienting networks, an interaction between age and behavioral performance was observed in the activation of the frontal eye fields (FEF) and supplementary motor area (SMA). Younger children show better performance with higher activation, a trend that reverses in older children. Furthermore, children with poorer attention performance relied on functional connectivity between the SMA and other brain regions like the thalamus and precuneus to maintain attention efficiency, a dependency that diminishes with age. Similarly, stronger activation of the right rostrolateral prefrontal cortex (RLPFC) and temporoparietal junction (TPJ), along with higher levels of ventral striatum-dorsomedial prefrontal cortex (VS-dmPFC) functional connectivity, support the development of children with poorer executive attention performance.
Conclusions:
Overall, brain regions that facilitate the transition of higher cognitive functions and their co-activation patterns with other cortical/subcortical regions play a central role throughout development. And children with lower executive attention performance demonstrate an increased reliance on the functional connectivity of prefrontal-striatal pathway, indicating impairments related to goal-directed processes.
Disorders of the Nervous System:
Neurodevelopmental/ Early Life (eg. ADHD, autism) 2
Lifespan Development:
Normal Brain Development: Fetus to Adolescence 1
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI)
Novel Imaging Acquisition Methods:
BOLD fMRI
Perception, Attention and Motor Behavior:
Attention: Visual
Keywords:
Attention Deficit Disorder
Cognition
Development
FUNCTIONAL MRI
1|2Indicates the priority used for review
Provide references using author date format
Fan, J. (2002). Testing the Efficiency and Independence of Attentional Networks. Journal of Cognitive Neuroscience, vol. 14, no. 3, pp. 340–347.
Petersen, S.E., & Posner, M.I. (2012). The Attention System of the Human Brain: 20 Years After. Annual review of neuroscience, vol. 35, pp. 73–89.
Raz, A., & Buhle, J. (2006). Typologies of attentional networks. Nature Reviews Neuroscience, vol. 7, no. 5, pp. 367–379.