Summary: Weight loss isn’t simply a matter of willpower, it’s actually connected to basic visual and olfactory cues.
Source: Ben-Gurion University of the Negev
What if an MRI scan could determine whether a weight loss program was likely to be effective? Ben-Gurion University of the Negev (BGU) researchers have discovered a neural subnetwork of connected regions between the brain and gastric basal electric frequency that correlates with future weight loss based on connectivity patterns.
BGU’s multidisciplinary team’s findings, published in the journal NeuroImage, support a prevalent neural theory that people with an increased neural response to seeing and smelling food consistently overeat and gain weight.
“To our surprise, we discovered that while higher executive functions, as measured behaviorally, were dominant factors in weight loss, this was not reflected in patterns of brain connectivity,” says Gidon Levakov, a graduate student, who led the study from the BGU Department of Brain and Cognitive Sciences.
“Consequently, we found that weight loss is not merely a matter of willpower, but is actually connected to much more basic visual and olfactory cues.”
The researchers identified a connection between the stomach basal electric rhythm within the subnetwork and weight loss. That rhythm governs the gastric waves that are associated with hunger and satiety. They also found that the brain’s pericalcarine sulcus, the anatomical location of the primary visual cortex, was the most active node in this subnetwork.
The team assessed 92 people during an 18-month lifestyle weight loss intervention led by Prof. Iris Shai, of BGU’s Department of Epidemiology. The participants were selected based on large waist circumference, abnormal blood lipid levels and age.
Before the intervention, the participants underwent a battery of brain imaging scans and behavioral executive function tests. The participants’ weight loss was measured after six months of dieting, in which, according to Prof. Shai, the maximum weight loss is generally achieved.
The team found that the subnetwork of brain regions corresponded more closely to basic sensory and motor regions rather than higher, multi-modal regions.
“It appears that visual information may be an important factor triggering eating,” says principal investigator Prof. Galia Avidan, from the BGU Departments of Brain and Cognitive Sciences and Psychology. “This is reasonable, given that vision is the primary sense in humans.”
The researchers note that these results may have significant implications toward understanding the cause of obesity and the mechanism of response to dieting.
Funding: This research was supported by grants from: The Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Projektnummer 209933838 – SFB 1052; the DFG, Obesity Mechanisms; Israel Ministry of Health (grant no. 87472511), Israel Ministry of Science and Technology (grant 3-13604), and the California Walnuts Commission.
Neural correlates of future weight loss reveal a possible role for brain-gastric interactions
Lifestyle dietary interventions are an essential practice in treating obesity, hence neural factors that may assist in predicting individual treatment success are of great significance. Here, in a prospective, open-label, three arms study, we examined the correlation between brain resting-state functional connectivity measured at baseline and weight loss following 6 months of lifestyle intervention in 92 overweight participants. We report a robust subnetwork composed mainly of sensory and motor cortical regions, whose edges correlated with future weight loss. This effect was found regardless of intervention group. Importantly, this main finding was further corroborated using a stringent connectivity-based prediction model assessed with cross-validation thus attesting to its robustness. The engagement of senso-motor regions in this subnetwork is consistent with the over-sensitivity to food cues theory of weight regulation. Finally, we tested an additional hypothesis regarding the role of brain-gastric interaction in this subnetwork, considering recent findings of a cortical network synchronized with gastric activity. Accordingly, we found a significant spatial overlap with the subnetwork reported in the present study. Moreover, power in the gastric basal electric frequency within our reported subnetwork negatively correlated with future weight loss. This finding was specific to the weight loss related subnetwork and to the gastric basal frequency. These findings should be further corroborated by combining direct recordings of gastric activity in future studies. Taken together, these intriguing results may have important implications for our understanding of the etiology of obesity and the mechanism of response to dietary intervention.