The conjunction analysis suggested that viewing high-calorie food cues activated the OFC in both normal-weight people and people with obesity.
1. Introduction
The prevalence of obesity is problematic and rising in both developed and developing nations
[1]. This fact has far-reaching and costly implications, because obesity contributes to the development of numerous diseases (e.g., diabetes, some cancers)
[2][3][4][2,3,4], and it is a risk factor for psychiatric disorders (e.g., depression, anxiety)
[5]. Not surprisingly, excessive weight has become an increasing threat to healthcare systems
[6], and accounts for an estimated 2.8 million deaths per annum worldwide
[7]. These statistics have prompted a plethora of research aimed at understanding factors that contribute to the development or maintenance of obesity
[8][9][10][11][12][8,9,10,11,12].
One contributing factor is the overconsumption of high-calorie or unhealthy foods (e.g., chocolate cake), and underconsumption of low-calorie or healthy foods (e.g., salad), which leads to a positive energy balance and, subsequently, weight gain
[13][14][15][13,14,15]. We are currently facing the rise of the ‘obesogenic’ environment
[16] where the exposure to food advertisements, and availability of cheap, unhealthy, and energy dense foods has dramatically increased
[17][18][17,18]. The constant exposure to high-calorie foods and food cues may promote overconsumption by stimulating brain reward and motivation pathways
[19][20][19,20]. In this vein, using techniques such as functional magnetic resonance imaging (
fMRI), a growing number of research has been conducted to investigate neural responses to various forms of food stimuli
[21], such as liquid tastants, food odors
[22], or visual food cues
[23][24][23,24]. Moreover, recent reviews have used
fMRI-based meta-analysis such as Activation Likelihood Estimation (ALE)
[25][26][25,26] to evaluate the consistency of findings across these studies
[23][24][27][28][29][30][31][32][23,24,27,28,29,30,31,32]. For instance, Chen and Zeffiro meta-analyzed 39 experiments with 995 participants and found that taste (e.g, insula), sensory integration (e.g., postcentral gyrus), and reward processing (e.g., amygdala) regions were involved in processing sweet food cues (one kind of high-calorie foods)
[30]. With regard to visual food cues, several
fMRI-based meta-analyses have also been conducted
[18][24][27][28][18,24,27,28]. For example, an ALE meta-analysis including 12 experiments and 201 participants reported that visual food cues were reliably associated with increased blood oxygen level dependent (BOLD) response in the visual system proper (e.g., the occipital lobe) rather than reward-related brain network (e.g., the orbitofrontal cortex)
[28].
None of the aforementioned meta-analyses, however, have investigated which brain regions are concurrently activated in response to viewing high-calorie food cues specifically. Furthermore, most of these meta-analyses only included participants with normal-weight and did not consider individuals with obesity (i.e., body mass index ≥30. A meta-analysis pooling data across relevant fMRI studies would therefore be warranted, as it may help to understand neural responses of viewing high-calorie food cues among people with various weight-status categories (e.g., normal-weight, obesity) and develop better interventions for preventing or reducing overeating and obesity.
2. Brain Response to High-Calorie Visual Food Cues in People with Normal-Weight
For brain activations of viewing high-calorie food cues in participants with normal-weight, the meta-analysis of 39 independent samples (493 foci) identified seven significant clusters (total volume of activation of 10,680 mm3 and maximum ALE value of 0.0713) that covered regions of the bilateral fusiform gyrus, OFC, insula, as well as the right lingual gyrus (Table 1, Figure 1).
Figure 1. Significant clusters for of viewing high-calorie food cues in samples of individuals with normal-weight.
Table 1. Separate meta-analytic results of significant clusters in individuals with normal-weight or obesity.
Cluster |
Cluster Size (mm3) |
Brain Region |
Peak Voxel MNI Coordinates |
ALE Value (×10−2) |
Z |
Contributing Samples |
X |
Y |
Z |
No. |
% |
|
Normal weight |
|
1 |
2080 |
L Orbitofrontal Cortex |
−24 |
32 |
−14 |
4.01 |
6.56 |
9 |
23% |
2 |
1600 |
R Lingual Gyrus |
20 |
−96 |
4 |
2.92 |
5.36 |
8 |
21% |
3 |
1568 |
L Fusiform Gyrus |
−46 |
−68 |
−6 |
2.73 |
5.02 |
8 |
21% |
4 |
1568 |
L Insula |
−38 |
−6 |
6 |
4.53 |
7.13 |
9 |
23% |
5 |
1560 |
R Fusiform Gyrus |
50 |
−60 |
−12 |
3.23 |
5.65 |
7 |
18% |
6 |
1160 |
R Insula |
40 |
−4 |
4 |
3.62 |
6.11 |
8 |
21% |
7 |
1144 |
R Orbitofrontal Cortex |
28 |
32 |
−16 |
2.24 |
4.37 |
8 |
21% |
|
Obesity |
|
1 |
1680 |
L Orbitofrontal Cortex |
−26 |
34 |
−16 |
2.56 |
5.33 |
6 |
35% |
2 |
1344 |
L Lingual Gyrus |
−16 |
−100 |
−4 |
1.96 |
4.47 |
6 |
35% |
3 |
1000 |
R Orbitofrontal Cortex |
32 |
28 |
−14 |
1.96 |
4.48 |
4 |
24% |
4 |
928 |
Anterior Cingulate Cortex |
0 |
36 |
14 |
2.15 |
4.75 |
5 |
29% |