Alterations in DLPFC Activation during the Willingness-to-pay Task in Individuals with Obesity

Poster No:

712 

Submission Type:

Abstract Submission 

Authors:

Shilong Yu1,2, Guanya Li1,2, Wenchao Zhang1,2, Yang Hu1,2, Jinxu Zhang1,2, Weibin Ji1,2, Yufei Dong1,2, Yang Liu1,2, Hailin Huang1,2, Yi Zhang1,2

Institutions:

1Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China, 2International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China

First Author:

Shilong Yu  
Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education|International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University
Xi'an, Shaanxi 710126, China|Xi'an, Shaanxi 710126, China

Co-Author(s):

Guanya Li  
Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education|International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University
Xi'an, Shaanxi 710126, China|Xi'an, Shaanxi 710126, China
Wenchao Zhang  
Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education|International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University
Xi'an, Shaanxi 710126, China|Xi'an, Shaanxi 710126, China
Yang Hu  
Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education|International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University
Xi'an, Shaanxi 710126, China|Xi'an, Shaanxi 710126, China
Jinxu Zhang  
Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education|International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University
Xi'an, Shaanxi 710126, China|Xi'an, Shaanxi 710126, China
Weibin Ji  
Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education|International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University
Xi'an, Shaanxi 710126, China|Xi'an, Shaanxi 710126, China
Yufei Dong  
Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education|International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University
Xi'an, Shaanxi 710126, China|Xi'an, Shaanxi 710126, China
Yang Liu  
Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education|International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University
Xi'an, Shaanxi 710126, China|Xi'an, Shaanxi 710126, China
Hailin Huang  
Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education|International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University
Xi'an, Shaanxi 710126, China|Xi'an, Shaanxi 710126, China
Yi Zhang  
Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education|International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University
Xi'an, Shaanxi 710126, China|Xi'an, Shaanxi 710126, China

Introduction:

Individuals with obesity tend to make food choices based on food reward rather than energy demand, suggesting the dysfunction of brain regions involved with cognitive decision-making (Cosme, 2019; Zhang, 2022) . Previous studies showed that brain regions, including the orbital frontal cortex (OFC), ventral striatum (VS), Ventromedial prefrontal cortex (VMPFC) and anterior cingulate cortex (ACC), played important roles in encoding the subjective value of rewards (Verdejo-Roman, 2017; Smith, 2018; Mackey, 2016) , which also have closely connections with the dorsolateral prefrontal cortex (DLPFC), one of the key nodes of the executive control network (ECN) (Hare, 2009) . However, it remains unclear how these regions interact during the food decision making. Thus, the current study employed a willingness-to-pay (WTP) fMRI task with high- (HC) and low-caloric (LC) food cues to investigate differences in brain activation during food cue and decision-making between obese participants (OB) and normal weight (NW) controls.

Methods:

A total of 51 NW and 62 OB adults, aged 18 to 45 years, were recruited at Xijing Gastrointestinal Hospital affiliated to the Air Force Medical University in Xi'an, China, and they all completed a WTP fMRI task scan with 3.0-T GE scanner. A gradient-echo T2*-weighted echo planar sequence was used for acquiring functional images with the following parameters: TR = 2 sec, TE = 30 ms, matrix size = 64×64, FOV = 256×256 mm2, flip angle = 90º, in-plane resolution of 4 mm2, and 32 axial slices3. The WTP task trial consisted of two stages: including stimulus and choice (Fig 1a). The food stimuli were categorized into HC and LC, the task was divided into two runs, each consisting of 40 trials. Two-sample t-tests were performed to compare behavioral and demographic data (Table 1). Functional imaging data were preprocessed and analyzed using SPM12, and first-level analyses using the General Linear Model (GLM) then individual beta images to food and choice responses were calculated and submitted to the second-level random-effects analysis by calculating a flexible-factorial model with group (OB, NW), Results were corrected for multiple comparisons using family wise error (FWE) corrections at the cluster-level correction approach (PFWE < 0.05) with a minimum cluster size of k = 50 voxels and a cluster defining threshold of p < 0.001 (at the voxel level). Clusters showing significant group or interaction effects were selected as ROIs. Pearson correlation was employed to assess the associations between changes in activation in these ROIs and changes in behavioral measurements.

Results:

There were no significant differences in age and gender between OB and NW. OB were significant higher in BMI, HAMA, HAMD, Depression and Hunger than NW. For the task measures, OB exhibited significantly lower WTP for LC food, mean WTP and significantly higher WTP difference between HC and LC food compared with NW (Table 2). In addition, there were significant interaction effects (Group × Condition) in the right DLPFC and right supplementary motor area (SMA) between food contrast and choice contrast, and in the right DMPFC between food stimulus and choice stage (Fig 1c). Main effects of group showed significantly increased activation in the left DLPFC, left inferior parietal (IPL) and right angular gyrus (ANG) during food stimuli in OB compared with NW (Fig 1b). Activations in the right DMPFC, right ANG were positively correlated with body mass index (BMI) in OB. (Fig 1d)
Supporting Image: Fig1.jpg
Supporting Image: Fig2.jpg
 

Conclusions:

These findings reveal hyperactivation of DLPFC and its close association with decision-making behaviors during WTP task in OB, suggesting the impaired executive control functions during decision-making contribute to maladaptive eating behaviors.

Higher Cognitive Functions:

Decision Making 1

Modeling and Analysis Methods:

Activation (eg. BOLD task-fMRI)

Novel Imaging Acquisition Methods:

BOLD fMRI 2

Keywords:

Eating Disorders
FUNCTIONAL MRI

1|2Indicates the priority used for review

Abstract Information

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Please indicate below if your study was a "resting state" or "task-activation” study.

Task-activation

Healthy subjects only or patients (note that patient studies may also involve healthy subjects):

Patients

Was this research conducted in the United States?

No

Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.

Yes

Were any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.

Not applicable

Please indicate which methods were used in your research:

Functional MRI

For human MRI, what field strength scanner do you use?

3.0T

Which processing packages did you use for your study?

SPM

Provide references using APA citation style.

Cosme, D. (2019). Comparing two neurocognitive models of self-control during dietary decisions. Soc Cogn Affect Neurosci, 14(9), 957-966.
Hare, T. A. (2009). Self-control in decision-making involves modulation of the vmPFC valuation system. Science, 324(5927), 646-648.
Mackey, S. (2016). Greater preference consistency during the Willingness-to-Pay task is related to higher resting state connectivity between the ventromedial prefrontal cortex and the ventral striatum. Brain Imaging and Behavior, 10(3), 730-738.
Smith, R. (2018). Conflict-related dorsomedial frontal cortex activation during healthy food decisions is associated with increased cravings for high-fat foods. Brain Imaging and Behavior, 12(3), 685-696.
Verdejo-Roman, J. (2017). Brain reward system's alterations in response to food and monetary stimuli in overweight and obese individuals. Human Brain Mapping, 38(2), 666-677.
Zhang, W. (2022). Functional Abnormality of the Executive Control Network in Individuals With Obesity During Delay Discounting. Cerebral Cortex, 32(9), 2013-2021.

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No