Inhibitory Brain Circuitry and Food Intake

Introduction

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The Well-Stocked Kitchen - Joachim Beuckelaer (circa 1533–1575)
Image source: http://commons.wikimedia.org/wiki/File:Joachim_Beuckelaer_003.jpg

Evolutionary perspectives of the current obesity epidemic suggest that the overconsumption of food in modern society is the consequence of our formerly adaptive behaviour to overeat when the supply was available [1] . This evolved overeating behaviour would help to ensure one would be sufficiently sustained during periods when food was scarce [1]. However, the conditions of the industrialized world now provide an overabundance of food that makes this proposed inherent drive to overeat and underdeveloped inhibitory control of food intake maladaptive [1]. The neurobiological differences between individuals that are able to effectively control their food intake in an environment that provides an excessive food supply and individuals who are overweight as a result of lacking dietary self-constraint has important implications for understanding obesity and its possible risk factors [2]. Moreover, the investigation of the neural mechanisms behind the inhibitory control of food intake has been proposed as a critical area of research for methods of prevention and treatment of obesity [2]. Findings from both functional and structural neuroimaging studies have been key in analyzing the differences in brain regions that control food intake between obese and non-obese individuals. Specific areas of research include what areas of the brain are activated during self restraint from eating [3] and the structural brain differences between those of normal and high BMIs such as grey matter regions involved in inhibitory control and white matter regions implicated in food cues and reward [4].

1. Brain Regions Activated with Self-Restraint of Eating

In addition to involuntary homeostatic mechanisms, food intake can be regulated through conscious cognitive control [3]. Current research has shown that consciously inhibiting eating correlates with distinct cortical brain activation [3]. Consciously regulating the desire to eat involves both the brain valuation systems required in making evaluative judgments and top-down control systems involved in inhibiting behaviour [3]. It has been proposed that connections between these two systems allow top-down control signals to modulate the perceived value of food computed in brain valuation regions which ultimately enables individuals to regulate their food consumption [5].

1.1 Brain Valuation System

The Orbitofrontal Cortex
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The OFC is involved in representing reward value
Image source: http://brmlab.cz/project/brain_hacking/tdcs/pfc

The brain valuation system is a circuit of frontal, striatal and limbic brain regions that been has been implicated in the appraisal of objects in terms of their perceived reward or punishment [6]. Neuroimaging studies have identified the orbitofrontal cortex (OFC) as a part of the brain valuation system that is strongly associated with assessing food reward value [7]. Differential activation of the OFC has been found between individuals who consciously regulated their desire to eat foods that were subjectively rated as palatable but unhealthy compared to those that admitted their desire their to consume such foods [3]. Participants that regulated their desire to eat unhealthy foods performed a cognitive reappraisal strategy that required considering the long-term health and social consequences of consuming the desired unhealthy food, while participants in the admit condition were instructed to admit their desire without considering the disadvantages. Greater neural activation indicated by functional magnetic resonance imaging (fMRI) hemodynamic responses was found in the OFC of individuals in the regulate condition that performed conscious evaluation of the negative consequences of consuming unhealthy food items. These findings suggest that as a part of the brain valuation system the OFC is implicated in evaluating the punishment associated with eating unhealthy but hedonically rewarding foods [3].
The ventromedial prefrontal cortex (vmPFC) is another area of the brain valuation system that has been proposed to encode the subjective value of food stimuli [5]. Dieters rated as either self-controllers that based their food choices on healthiness and taste and non-self controllers that based their food choices only on taste showed increased hemodynamic responses in the vmPFC when decision making about what foods to eat. Based on these results it has been proposed that the vmPFC is involved in computing the subjective value of a food stimulus regardless of whether an individual employs cognitive control over their desire for unhealthy foods [5]. Moreover, the incorporation of the valuation processes generated in the brain valuation system with top-down control signals is a currently suggested mechanism for individuals to exercise self-control when eating [3] [5].

Prefrontal Top-Down Control Network
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The Prefrontal cortex is important in response inhibition and has been implicated in regulating feeding
Image adapted from Arnsten & Rubia (2012). [9]
http://www.sciencedirect.com/science/article/pii/S0890856712000433

1.2 Top-Down Control System

The top-down control system of the brain is a network of frontal brain regions involved in executive control, goal directed behaviour and response inhibition [8] (Fig.1 [9]). The dorsolateral prefrontal cortex (dlPFC) and inferior frontal gyrus (IFG) are regions of the brain's top-down control system that have been shown to produce significant activation when individuals are consciously regulating their desire to consume subjectively palatable but unhealthy foods as indicated by fMRI hemodynamic responses [3] . The role of the dlPFC and IFG in inhibiting food desire is further supported by research that shows greater cortical activation in these areas when individuals successfully exert self-control when making food choices between healthy and unhealthy foods in comparison to when self-control is not employed successfully [5]. Additionally, individuals with Prader-Willi syndrome, a genetic disorder that is phenotypically expressed as hyperphagia which results in food consumption beyond that of obese individuals have shown reduced activation in the dlPFC post-meal compared to obese individuals [10]. Collectively, these findings provide evidence that the inhibitory control of food intake is contingent on the ability of the brain's top-down control systems to modulate the subjective value of food derived by the brain valuation system. Individual differences in the ability to regulate food intake may result from structural differences of the dlPFC or its connectivity with brain valuation regions [5].

2. Volumetric Measures of Brain Regions and Relation to BMI

There is increasing evidence to suggest that obesity is associated with structural variations in the brain [4]. Structural MRI has been used to investigate the differences in grey matter and white matter volumes between individuals with high BMIs compared to those with normal BMIs. Some of the more consistent findings across studies are that obese individuals have a reduced volume of overall grey matter and reduced grey matter volumes in areas of inhibitory control compared to controls [4]. The direction of causation of this relationship has yet to be established. There is evidence to suggest that increased BMI and adipose tissue mass may result in decreased grey matter volumes. Moreover, increased adiposity is correlated with elevated inflammatory cytokines such as C-reactive protein, tumor necrosis factor-α and interleukin-6 [11] that have shown to be associated with total brain volume [12] and may be a mechanism of brain atrophy in obese individuals [4]. In addition, obesity has been linked to neurodegenerative disorders such as Alzheimer's Disease and dementia [13] supporting the hypothesis that obesity may result in brain atrophy. In contrast, individuals with low grey matter volumes especially in prefrontal brain regions associated with cognitive control and response inhibition may lack the ability to regulate their food intake and therefore be predisposed to obesity [4].

2.1 Overall Grey Matter

Reduced overall volumes of grey matter consisting of the neuronal cell bodies that carry out synaptic transmission of information throughout the nervous system, the dendrites of neurons, glia and supporting cells [14] have been found to be reduced in obese individuals [4] [15] [16]. A recent study by Yokum et. al (2012) using structural MRI voxel-based morphometry found that obese female adolescents had less overall grey matter compared with female adolescents who were categorized with a overweight BMI or lean BMI, providing converging evidence for findings found in obese middle-aged adults [15] [16]. In addition, there were no significant differences in overall grey matter between individuals with overweight and lean BMIs [4]. This suggests that reduced grey matter is associated with the higher levels adiposity in individuals with an obese BMI and perhaps related to the increased severity of metabolic dysfunction that obese individuals experience such as heightened insulin resistance [4].

2.2 Regional Grey Matter in Inhibitory Control Regions

Figure 2. Decreased Grey Matter in the Superior Frontal
Gyrus and Future Weight Gain
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Reduced regional grey matter volume of the SFG is
related to increases in BMI after a one-year follow-up.
image adapted from Yokum et al. 2012 [4]

Regional analysis of grey matter volumes with structural MRI voxel based-morphometry has revealed that obese middle-aged adults have significant reductions in prefrontal brain regions implicated in inhibitory control [17] [18]. Inconsistent with findings in obese middle-aged adults, Yokum et al. (2012) did not find significant differences in regional grey matter volumes between female adolescents with obese, overweight and lean BMIs. A proposed explanation for this result was that the female adolescents were less obese and younger than the middle-aged adults in previous studies which may suggest that regional differences in grey matter result from more chronic and severe obesity [4]. Despite the initial lack evidence supporting the relationship between reduced regional grey matter and obesity, Yokum et al. (2012) found that after a one-year follow up their obese subjects with reduced grey matter volume in brain regions involved in inhibitory control had significant increases in BMI (Fig. 2). Specifically, future increases in BMI were correlated with reduced grey matter volumes in the prefrontal cortex including regions such as the superior frontal gyrus and middle frontal gyrus. In addition, these results support the hypothesis that reductions of grey matter in brain regions implicated in inhibitory control lead to failures in self-control and the ability to regulate food intake and thus result in overeating and increases in BMI [4].

Prefrontal-Striatal Circuitry
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Top down control signals from the prefrontal cortex (dlPFC)
modulate reward signals generated by the dorsal striatum (dSTr) to inhibit behaviour
Image source: http://brmlab.cz/project/brain_hacking/tdcs/pfc

2.3 White Matter Involved in Food Cues and Reward

Structural MRI findings also indicate that obese individuals have variations in white matter which is composed of the myelinated axons of neurons that allow connectivity between different brain regions [14]. Increased white matter has been detected in brain regions related to food cues and reward such as the striatum, middle temporal gyrus, parahippocampal gyrus, fusiform gyrus, and Rolandic operculum [4] [19]. Specifically, larger white matter volumes in areas such as the dorsal striatum that is known for its significant involvement in reward anticipation and reward-based learning [20], have been found in obese individuals [4]. The abnormalities in white matter of regions involved in reward processing detected in obese individuals is consistent with the hypothesis that obese individuals have increased sensitivity for food reward cues [4]. Moreover, it has been proposed that self-restraint from food intake involves the active regulation of top-down control signals to modulate competing striatal reward signals through prefrontal-striatal circuitry [21].

3.1 Self-regulation failure

The regulation of feeding evidently requires top-down control of the prefrontal cortex in order to modulate impulses to consume food and failures of self-control likely result when top-down control is compromised [22]. An interesting example of self-regulation failure is observed in dieters when they indulge in some food that breaks their diet and then consequently engage in a period of unregulated eating [23] . In addition, dieters that broke their diet after being instructed to drink a large milkshake produced greater activation in the nucleus accumbens of the striatum in response to visual food cues compared to dieters that were not instructed to drink the milkshake and break their diet [24]. These results support the hypothesis that exposure to hedonically rewarding foods that are perceived as dietary violations may lead to overactive responses in reward regions that top-down control signals from the prefrontal cortex are insufficient to inhibit, thereby leading to overeating [22]. It has also been proposed that stress or negative emotional arousal likely attributes to failures in self-control by causing activation of subcortical regions such the amygdala involved in emotional processing that then impair prefrontal functioning [22].

3.2 Methods of Increasing Self-Regulation

Increasing the strength of top-down control signals in order to modulate the reward signals generated in subcortical regions by food cues has been proposed as being crucial in controlling impulses to overeat [25]. A recent study by Siep et al. (2012) provides evidence that by employing cognitive control strategies individuals can alter subcortical reward activity and increase prefrontal top-down control in response to food cues. Subjects that engaged in the practice of suppression, which involves inhibiting cognitions and emotions related to food cravings, showed decreased activation in the reward processing regions of the ventral tegmental area and ventral striatum, and increased activation in the dorsolateral prefrontal cortex as indicated by fMRI hemodynamic responses compared to controls. Contrary to the researchers' hypothesis, the suppression strategy was more successful at regulating reward activation and increasing prefrontal control than the strategy of cognitive reappraisal which involves considering the long-term health and social consequences of consuming hedonically rewarding food. This was attributed to the fact that the suppression strategy is more cognitively demanding by requiring more self-regulatory effort. Nevertheless, both strategies of suppression and cognitive reappraisal were successful in down-regulating reward motivation and up-regulating prefrontal control and provide promising directions for techniques of therapeutic intervention [25].

Related Neurowiki Links
Food Addiction
Anti-Obesity Drugs
Eating Disorders
Genetics of Obesity
Self-control and Moral Judgment
Reward Pathway and Behavior in Addiction
Circadian Rhythms: Food, Sleep and Stress
Food Intake and the Vagus Nerve
Hormonal Regulation of Feeding Behaviour

External Links
It’s All in the Brain: Unlocking the Secrets of Overeating With Neuroscience

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