In a recent study published in the journal PNAS, researchers used a gradient approach to examine how changes in brain state during routine (natural) and regulated dietary decision-making processes influence the success of diet modification efforts. They further investigate the role of body mass indices (BMI) and the extent of brain activity modifications in this success. Their findings reveal that BMI plays an important role in observed dietary outcomes, with higher BMI resulting in lower success rates. The number and extent of brain modifications was also found to be substantial, with fewer and smaller remodeling showing better results than more extensive changes.
Study: Body mass index-dependent shifts along large-scale gradients in human cortical organization explain nutritional regulatory success. Image credit: Simple Line / Shutterstock
The role of mind and body in adherence to dietary patterns
Chronic diseases, including cancers and cardiovascular diseases (CVDs), are some of the most persistent healthcare challenges in the world today, with their increasing prevalence largely attributable to poor health behaviors such as inconsistent sleep and suboptimal diets. Obesity and overweight are of particular concern, with reports estimating more than one billion sufferers worldwide, with projections predicting that 18% of the world’s population will suffer from the condition by 2025.
Encouragingly, the global human population appears to have awakened to these pressing issues, promoting the growing popularity of healthy, mostly vegetarian diets (eg, the Mediterranean Dietary Pattern and DASH) and exercise routines. In America alone, more than 40% of the population is said to be actively engaged in weight loss efforts. Unfortunately, the results of these diet and fitness interventions remain surprisingly heterogeneous – some people experience significant weight loss, while others’ efforts are met with failure.
Recent neuroimaging studies have attempted to shed light on these inconsistencies and have so far identified several brain regions that are consistently activated during eating regulation efforts, including the supplementary motor cortex, the dorsolateral prefrontal cortex, and the anterior insula. However, efforts to establish reproducible associations between these activation centers and individual differences in regulatory successes remain confounded. The complexity of food choices and their relationships with individuals’ preferences has been suggested as a possible reason for these observations. However, this remains to be tested within the scientific context.
About the study
In the present study, the researchers aim to determine whether measuring the dynamic remodeling of large-scale neural networks embedded in cortical organization can help predict the success of dietary regulation. Specifically, they test whether measures of weight (such as body mass indices [BMIs]) and the magnitude of neural network remodeling required (number and extent) could determine whether a person is more or less likely to succeed when trying to lose weight through dieting.
The study sample cohort included data from 137 volunteers with a BMI < 35 enrolled in three previous food choice studies. Exclusions of subjects with missing BMI data (N = 4) and outliers (N = 10) resulted in a final data set of 123 participants (84 women) between 20 and 33 years of age. Data collection included sociodemographic, anthropometric and medical data of the enrolled participants. The experimental design of the study involved the presentation and performance of a “well-established laboratory food choice task” involving individual preference for food photographs. The data of interest included functional magnetic resonance imaging (fMRI) of the participants' brains during feeding.
“Participants made food choices under three different conditions implemented in separate task blocks. In Studies 1 and 3, participants made choices while being asked to focus on the palatability of the food (taste-focus condition, TC), the healthiness (taste-focus condition, TC health focus, HC), or as they would naturally do (natural condition, NC served as a baseline that represented the natural eating processes of study 2 participants but were instructed to distance themselves from food cravings in a third condition (distance, DC)’.
To compare and contrast brain images during natural (NC) and health-focused (HC) conditions, neural general linear models (GLMs) were developed. These GLMs were coded to identify brain states associated with either condition (NC or HC). They included two regressors of interest per functional run (one run for each of the three studies) and eight regressors of no interest. The resulting output represents participants’ brain states in different dietary contexts (natural vs. regulated).
“Gradients quantify basic topographic principles of macroscale brain organization (12). Brain regions that are most similar with respect to the feature of interest occupy similar positions along a major axis of variation (gradient).”
Finally, the researchers created and tested brain gradient maps (basic dimensions of brain change) for each participant and then projected task-based brain states onto this gradient space, thus elucidating the intrinsic coordinate system of neural organization.
Study findings and conclusions
The present study revealed three new insights into the associations between a person’s weight and their neural predisposition and the success of dietary interventions for weight loss. First, people who need smaller
