Hostname: page-component-76fb5796d-9pm4c Total loading time: 0 Render date: 2024-04-26T08:22:27.732Z Has data issue: false hasContentIssue false

Adverse effects of consuming high fat–sugar diets on cognition: implications for understanding obesity

Published online by Cambridge University Press:  18 May 2017

Martin R. Yeomans*
Affiliation:
School of Psychology, University of Sussex, Brighton BN1 9QH, UK
*
*Corresponding author: Professor M. R. Yeomans, email martin@sussex.ac.uk
Rights & Permissions [Opens in a new window]

Abstract

There is increasing evidence for important roles of key cognitive processes, including attention, memory and learning, in the short-term decision making about eating. There is parallel evidence that people who are overweight or obese tend to perform worse on a variety of cognitive tasks. In this review, the evidence for these two ideas is summarised and then the idea that overconsumption of Western-style high-fat (HF)–high-sugar diets may underlie the association between obesity and poorer cognitive performance is explored. In particular, evidence in animals and human subjects that repeated consumption of HF or HF and sugar (HFS) diets leads to specific impairments in the functioning of the hippocampus, which underpin the consequent changes in cognition is summarised. These findings lead into the vicious cycle model (VCM), which suggests that these cognitive changes have knock-on negative effects for future appetite control, and evidence that altered hippocampal function is also associated with impaired appetite control is explored. The review concludes that there is consistent evidence in the animal literature and emerging evidence from human studies that supports this VCM. It is also noted, however, that to date studies lack the nutritional specificity needed to be able to translate these basic research findings into clear nutritional effects, and concludes that there is an urgent need for additional research to clarify the precise nature of the apparent effects of consuming HFS diets on cognition.

Type
Conference on ‘Diet, nutrition and mental health and wellbeing’
Copyright
Copyright © The Author 2017 

Historically, the study of human appetite control has been dominated by theories based about the sensing of nutritional status and the use of these sensed signals to either promote a desire to eat (hunger signals) or suppress that desire (satiety signals). There is a great deal of evidence confirming that such signals play an important role in appetite control, and the underlying peripheral and neural signals that influence eating have been well characterised( Reference Hellström 1 Reference Finlayson, Halford, King and Matthias 3 ). However, homeostatic models are increasingly recognised as inadequate explanations of everyday eating behaviour, particularly because of the worldwide increase in incidence of obesity driven by overconsumption. The prevailing view is that short-term appetite control involves a balance between responding to homeostatic controls arising from internal nutrient-derived signals and external signals that can over-ride homeostatic control( Reference Stroebe, Papies and Aarts 4 Reference Lowe and Butryn 6 ). Eating can thus be viewed as decision making about food based on a balance between immediate rewards and homeostatic needs.

Ultimately starting or stopping eating is a decision, and these decisions are informed by a wide range of factors, certainly including physiological cues arising from detection of signals arising from sensing of nutrient status (interoceptive signals), but also by external factors, including the social context of eating( Reference Herman 7 , Reference Cruwys, Bevelander and Hermans 8 ), the palatability of the food on offer( Reference Yeomans, Blundell and Lesham 9 Reference Johnson and Wardle 11 ), the served portion size( Reference Almiron-Roig, Tsiountsioura and Lewis 12 Reference Livingstone and Pourshahidi 15 ) etc. Thus, understanding the cognitive processes that underlie the decision making about meal initiation, meal size, etc. offers the potential for new insights into human appetite control, and consequently the potential to develop more effective treatment approaches for those who struggle to regulate their appetite. But our cognitive functioning is in turn influenced by nutritional status, and in this review, the focus is on one such influence, the growing evidence that repeated consumption of diets with higher levels of fat (HF), or fat and sugar (HFS) alter specific functioning in key areas of the brain involved in memory, and that consequently HFS diets lead to impaired cognition, which in turn leads to poor decision making about eating. To date, however, the evidence for the effects of HFS diets has largely come from animal models( Reference Hargrave, Jones and Davidson 16 , Reference Kanoski and Davidson 17 ). Here, the focus is primarily on growing evidence for similar effects in studies with human volunteers.

Role of cognition in appetite control

To set the potential impact of HFS diets on cognition and appetite into context, first it is important to consider the wider role of cognition in appetite control. Many cognitive processes are involved in decision making about meals. The extent to which we are aware of food cues in the environment (attention) has long been hypothesised as a key component of our sensitivity to external drivers of ingestion( Reference Schachter 18 ). More recent work( Reference Robinson, Aveyard and Daley 19 ) has focused on our ability to recall in the short term what we have recently eaten and to adjust our subsequent eating accordingly (memory). Memory is also key to how we identify the foods we consume( Reference Prescott, Taylor, Roberts, Taylor and Roberts 20 ), and even modifies our perception of flavour( Reference Small and Prescott 21 ). These memories are laid down through learning processes which integrate sensory and nutrient information through experience( Reference Yeomans, Shepherd and Raats 22 , Reference Havermans, Jansen, Preedy, Watson and martin 23 ). Each of these four aspects of cognition are reviewed here in brief to set the broader context for the potential way HFS diet consumption may impact on cognitive controls of ingestion.

Role of memory in appetite control

The idea that memory for recent eating events was a critical determinant of the decision to start and end a meal came to the fore with the Rozin et al.( Reference Rozin, Dow and Moscovitch 24 ) seminal study of eating in two amnesic patients. These patients failed to remember they had just eaten, and so accepted and consumed a second lunch served soon after a first lunch. An elegant series of studies led by Higgs has demonstrated that this is not as a result of aberrant appetite in amnesia: healthy volunteers who are directed to recall the lunch they had earlier reliably eat less in a mid-afternoon snack intake test than do controls in other recall conditions( Reference Higgs and Donohoe 25 Reference Higgs 28 ). It is also well established that people consume more when distracted than when their attention is on eating( Reference Robinson, Aveyard and Daley 19 ). Notably, recall of intake is poorer for food consumed under distraction( Reference Higgs and Woodward 27 ), while focusing on eating during lunch increases memory and reduces later intake( Reference Higgs and Donohoe 25 ). Taken together, these lines of evidence provide strong evidence for an important role for memory in short-term intake regulation.

Attention to food cues as clues to underlying eating motivation

Since human subjects are born with no innate attraction to any specific foods beyond a tendency to like those with sweet tastes, our preferences develop through learning about the short-term effects of consuming different items( Reference Yeomans, Shepherd and Raats 22 ). Once we have acquired these associations, cues which predict the presence of foods in our environment are more likely to attract attention. Consequently, the study of the extent to which we attend to food cues can give insights into underlying eating motivation. For example, it has been repeatedly shown that healthy normal-weight participants pay greater attention to food cues when hungry than when sated( Reference Piech, Pastorino and Zald 29 Reference Siep, Roefs and Roebroeck 32 ). Overweight and/or obesity individuals, however, have been shown to attend more strongly to food-related cues (typically pictures of foodReference Castellanos, Charboneau and Dietrich 33 Reference Deluchi, Costa and Friedman 41 ) than do normal-weight controls. Moreover, studies have suggested attention to food is maintained even when sated in obese individuals( Reference Nijs, Muris and Euser 36 ). These effects of weight status on attention to foods are further complicated by effects of dieting and weight dissatisfaction, with individuals with a history of dieting or weight dissatisfaction also showing greater attention to food cues( Reference Gao, Wang and Jackson 42 , Reference Werthmann, Roefs and Nederkoorn 43 ). Taken together, these data suggest that cognitive systems involved in selective and sustained attention play a key role in both normal appetite control and overeating. They also demonstrate how our individual attention to food reflects a balance of motives for eating, partly derived from homeostatic signalling, but also influenced by both the rewarding consequences of eating and weight-related concerns about the effects of eating. Thus, attention may reflect the momentary integration of eating motivation derived from the processing of multiple signals.

Role of learning in development of food preferences and the control of appetite

Attention to food cues involves recognition of external cues that map onto our individual memories. These memories are acquired through a lifetime of exposure to foods and learning of what items are safe to eat or not, and what nutritional value we obtain from consumption. There is neither scope nor relevance to fully explore the mechanisms of learning underpinning the development of our food preferences, which have been reviewed elsewhere( Reference Yeomans, Shepherd and Raats 22 , Reference Gibson, Brunstrom, Kirkham and Cooper 44 ), but it is important to remember that these learning processes are likely to be impaired by changes to the neural systems, which subserve learning and memory, including the hippocampus. In particular, animal studies strongly suggest that the hippocampus plays a key role in detection and integration of interoceptive signals into learned responses( Reference Benoit, Davis and Davidson 45 ), an idea developed more fully later in this review. It is also notable that the expression of learned preferences is sensitive to acute hunger state in healthy normal-weight individuals( Reference Yeomans and Mobini 46 , Reference Mobini, Chambers and Yeomans 47 ), but these types of learning may be disrupted by dieting( Reference Brunstrom, Downes and Higgs 48 , Reference Brunstrom and Mitchell 49 ). The dependence of learning on memory for interoceptive experience post-ingestion( Reference Yeomans, Shepherd and Raats 22 ) also suggests that impaired memory will interfere with these learning processes, suggesting that flavour preference acquisition may be less regulated by post-ingestive experience in obesity.

Obesity, memory and cognition

The previous section highlights, in brief, the importance of three aspects of cognition in control of appetite. Critical to the present review, however, is the idea that overconsumption of HFS diets can impact on brain function and so alter cognition. The argument then follows that these nutritionally derived changes in brain function in turn impair short-term appetite control through the consequent changes in cognition: a vicious cycle model (VCM)( Reference Hargrave, Jones and Davidson 16 , Reference Kanoski and Davidson 17 ) described later in more detail. For such a model to have any explanatory power for human overeating, there has to be evidence that people who overeat show power memory, and there is growing evidence that this is so. Firstly, there are specific cognitive impairments associated with obesity. This has been found both in cross-sectional studies( Reference Gunstad, Paul and Cohen 50 , Reference Cournot, Marquie and Ansiau 51 ), and more crucially in longitudinal studies( Reference Gunstad, Lhotsky and Wendell 52 ). For example, a recent study showed that performance on a novel visual episodic memory task decreased as a function of BMI( Reference Cheke, Simons and Clayton 53 ), with significant impairments on all aspects of this novel memory task with increasing BMI (Fig. 1). It is notable that this study only measured overall BMI, and whether the reported memory impairment was more associated with weight or overall fat content cannot be determined, and warrants further investigation. Other studies report explicit memory deficits in obese populations: for example, explicit memory deficits were found in one-quarter of obese participants who were about to undergo bariatric surgery, with memory improving post-surgery( Reference Miller, Crosby and Galioto 54 ). Recovery in this context could be due to altered diet, reduced weight or reduced body fat. Further evidence for a specific memory impairment associated with obesity came from a more recent study that contrasted a variety of measures of cognitive performance, including working memory, between obese and normal-weight groups( Reference Coppin, Nolan-Poupart and Jones-Gotman 55 ). The outcome suggested impaired working memory associated with obesity, but also found evidence of impairments in learning, particularly for negative outcomes. Some studies have found more general impaired cognitive function or impaired executive function associated with increased body weight, BMI or obesity( Reference Sabia, Kivimaki and Shipley 56 , Reference Barkin 57 ), although one study found that obesity was associated with improved overall cognitive function in older adults( Reference Kuo, Jones and Milberg 58 ). The current consensus however is that overweight and obesity tend to be associated with poorer memory performance, consistent with the idea that overconsuming HFS diets impairs memory, but not providing direct evidence for the HFS association per se.

Fig. 1. Associations between BMI and performance on a novel spatial test of episodic memory (the what, where, when task), redrawn from Cheke, Simons( Reference Cheke, Simons and Clayton 53 ), with permission.

Evidence for specific effects of diets high in fat and sugar on memory

Animal studies

The clearest evidence for an effect of consuming HFS diets and impaired memory comes from studies with non-human animals. A full review of this literature is beyond the scope of the present paper, and has been subject to several recent critical reviews( Reference Hargrave, Jones and Davidson 16 , Reference Kanoski and Davidson 17 ). In brief, the basic design of studies in this area involves measuring different aspects of memory performance for rodents who are fed either a HFS or control diet. Using this approach, extended exposure to HFS diets has been shown to impair performance on tasks which have been implicated in hippocampal-dependent spatial memory, such as the Radial Arm Maze or the Morris water bath( Reference Molteni, Barnard and Ying 59 Reference Valladolid-Acebes, Stucchi and Cano 64 ). What is striking in these animal studies is that the impairment in memory is specific to spatial tasks, whereas other measures such as object recognition remain relatively unimpaired( Reference Tran and Westbrook 65 ). This can be seen in Fig. 2: performance (measured as exploration time) is impaired for rats placed on a HFS diet on a spatial (Fig. 2(a)) but not object recognition (Fig. 2(b)) task. These spatial memory deficits also emerge rapidly, with recent studies finding deficits emerging soon after being placed on the HFS diet( Reference Kanoski and Davidson 61 , Reference Tran and Westbrook 65 Reference Murray, Knight and Cochlin 67 ), as can be seen in Fig. 2. Thus, the evidence that consuming Western-style HFS diets impair hippocampal-dependent memory tasks in animals is strong, and is further backed up by evidence of changes to the hippocampus itself, described in detail in several recent reviews( Reference Hargrave, Jones and Davidson 16 , Reference Kanoski and Davidson 17 , Reference Francis and Stevenson 68 , Reference Kanoski, Hsu, Pennell, Watson and De Meester 69 ), but beyond the scope of this review.

Fig. 2. Performance on (a) a spatial (place recognition) and (b) non-spatial (object recognition) task for rats fed a chow () or high-fat–high-sugar diet (). Higher exploration proportion values reflect better memory. Figure adapted from data in( Reference Tran and Westbrook 65 ) with permission.

Human studies

Most studies of effects of consuming a Western-style HFS diet on memory and broader cognitive performance have tended to rely on associations in cross-sectional studies. Studies of this kind have provided evidence consistent with the idea that consuming a HFS diet impairs memory, but because of the cross-sectional nature of the data, these studies do not provide the same strong test of causation that is seen in the rodent literature. That said, the evidence is largely in line with what would be predicted from the animal findings. In terms of effects of high intake of saturated fat (SF), a cross-sectional study of middle-aged adults (45–60-year old) using an extensive cognitive battery as part of a larger cohort study found an association between SF intake and increased risk of impaired cognitive functions, including memory, speed and flexibility( Reference Kalmijn, Van Boxtel and Ocke 70 ). Notably, that study was conducted in the context of examining potential beneficial effects of intake of n-3 fatty acids, an issue discussed in greater detail later. A similar study which examined effects of intake of different types of fat on cognitive performance in an older cohort (65 years +) also reported greater cognitive decline over time in participants with higher SF intake( Reference Morris, Evans and Bienias 71 ). These large cohort data are further supported by a more recent but smaller study contrasting effects of fat intake on memory in younger women( Reference Gibson, Barr and Jeanes 72 ). Again, habitual fat intake was associated with specific memory impairments (poorer word recall and recognition, impaired performance on a visuospatial task).

More in line with the animal approach was a study which contrasted cognitive performance between individuals classified as having whole-food or processed-food diets based on the analysis of 4693 participants from the Whitehall cohort study( Reference Akbaraly, Singh-Manoux and Marmot 73 ). The processed-food group had increased risk of cognitive deficit, including poorer memory, whereas the whole-food group had reduced risk, although controlling for potential confounders (socioeconomic status, education, etc.) reduced the significance. In a different approach, Francis and Stevenson( Reference Francis and Stevenson 74 ) developed a modified FFQ to estimate HFS diet intake, and then examined how performance on standardised memory tasks (verbal paired associates and the logical memory subtests from the Wechsler Memory Scale) varied as a function of HFS. The Dietary Fat and Free Sugar Questionnaire (DFS) assesses frequency of consumption of twenty-six foods and drinks that are high in SF and/or added sugar, and has been shown to be a fairly reliable measure of actual intake of HF and sweetened products( Reference Francis and Stevenson 75 ). In line with animal data, higher HFS intake was associated with poorer performance on these memory tasks, but not on other tasks (the Trail Making Test and the Wisconsin Card Sort Test). Since both verbal paired associates and logical memory subtests from the Wechsler Memory Scale tasks have been shown to be impaired in patients with hippocampal damage, whereas the other tasks measure frontal executive function, these associations provide support for the idea that HFS intake is associated with impaired memory through an impact on the hippocampus, although they are again based on an association rather than a clear causal test. These findings were replicated in a follow-up study( Reference Brannigan, Stevenson and Francis 76 ), again with higher HFS intake correlating with poorer performance on the logical memory subtests from the Wechsler Memory Scale. A more recent study by the same group provided further evidence of effects of HFS on memory( Reference Attuquayefio, Stevenson and Boakes 77 ). Here, healthy volunteers who varied in their habitual HFS consumption measured using the DFS completed the verbal paired associate test, which is well established to involve the hippocampus. In line with previous findings, performance on the verbal paired associates decreased as a function of HFS score. Thus, there is a growing body of evidence from cross-sectional studies relating HFS diets to impaired memory. The idea that HFS diets directly impact on hippocampal function was further supported by the finding that a standardised measure of consumption of a Western-style diet was associated with decreased overall volume of the left hippocampus in a sample of 255 middle-aged men( Reference Jacka, Cherbuin and Anstey 78 ). However, all the studies discussed so far report associations between HFS or Western-style diets and memory or hippocampal function: thus, these studies are consistent with the broader idea that these diets impair hippocampal function but cannot establish causation.

The most convincing test for the theory that intake of HFS diets impairs hippocampal function would be to examine changes in hippocampal-sensitive memory tasks before and after an intervention where the proportion of HFS in the diet was artificially increased or decreased. Such tests raise obvious ethical issues, and there have been few studies which have attempted to do so to date. One study that used this approach( Reference Edwards, Murray and Holloway 79 ) did find impaired cognitive function (increased reaction time and impaired attention) after placing twenty healthy volunteers on a HF diet for 7 d, although they did not include any specific hippocampal-dependent memory tests. Placing healthy young men on a HF, low-carbohydrate diet for 5 d not only impaired attention, but also showed a deterioration in speed of retrieval from short-term memory( Reference Holloway, Cochlin and Emmanuel 80 ). Thus, both studies suggest similarly acute effects of consuming HF diets on cognitive performance that has been reported in animal studies, although some caution is needed in interpretation since both studies were small.

Overall current human data are consistent with the broader idea that repeated consumption of Western-style HFS diets may impair cognitive function, possibly through a particular action on the hippocampus, but more studies are needed to fully characterise these effects and establish greater specificity and causation.

Vicious cycle model

The argument that changes in function of the hippocampus brought about by habitual overconsumption of Western-style HFS diets promotes unhealthy diet choice has been encapsulated in the VCM developed by Davidson and co-workers( Reference Hargrave, Jones and Davidson 16 , Reference Davidson, Tracy and Schier 81 Reference Davidson, Kanoski and Walls 83 ). The essential argument underlying the VCM (Fig. 3) is that the hippocampus plays a key role in the decisions to start and end meals. Feeding on HFS diets is then hypothesised to promote overconsumption and consequent weight gain, and also leads to alterations in hippocampal function. It is then argued that these changes in the hippocampus disrupt normal controls of ingestion, so promoting continued overconsumption, leading to a vicious cycle of further overeating. The implication is that once an individual has overconsumed sufficient HFS diet to impair hippocampal functioning, the resulting damage to the hippocampus and consequent alterations in cognitive functions make it harder to make the necessary changes in behaviour to reduce intake and adopt a healthier diet. Critical to the VCM is the idea that the hippocampus plays a key role in control of normal food intake( Reference Parent, Darling and Henderson 82 , Reference Davidson, Kanoski and Schier 84 Reference Hannapel, Henderson and Nalloor 88 ) as well as its more widely known role in memory( Reference Preston and Eichenbaum 89 Reference Zeidman and Maguire 91 ). The evidence for a role of the hippocampus in control of feeding comes largely from animal studies. For example, rats with lesions to the hippocampus took smaller more frequent meals than do normal rats( Reference Clifton, Vickers and Somerville 92 ), while temporary inactivation of the hippocampus also reduced the intermeal interval( Reference Henderson, Smith and Parent 93 ). But the evidence reviewed earlier of a key role of short-term memory in normal control of appetite in human subjects is consistent with this. What is now needed is a critical evaluation of the extent to which the key changes in behaviour proposed by the VCM, and evidenced in animals, is also seen in studies with human subjects.

Fig. 3. A schematic summary of the vicious cycle model proposed by Davidson and co-workers, adapted from( Reference Kanoski and Davidson 17 ).

Vicious cycle model: evidence from studies of human eating behaviour

The evidence of impaired memory associated with HFS diet consumption reviewed earlier implicates the hippocampus in short-term memory impairment. However, the VCM suggests that these apparent changes to hippocampal function then alter key aspects of appetite control. Of these, two aspects have been examined in recent studies: decreased sensitivity to interoceptive cues and reduced inhibitory control. While current evidence is still limited, these recent studies provide some support for what is proposed in the VCM.

The first aspect of the VCM that has been looked at is the extent to which the effects of HFS on memory also impacts on awareness of interoceptive cues associated with eating. Studies in animals have shown a critical role for the hippocampus in integrating the use of interoceptive cues in control of feeding( Reference Sample, Jones and Hargrave 94 , Reference Sample, Martin and Jones 95 ). In human subjects, high scores on the DFS in a normal-weight population were associated with reduced sensitivity to internal hunger/satiety cues, evidenced by altered effects of ingestion on the experience of appetite in those with high HFS intake( Reference Francis and Stevenson 74 ). Similarly, DFS scores were associated with smaller reductions in ratings of incentive but not hedonic motivations to eat in a state of satiety( Reference Attuquayefio, Stevenson and Boakes 77 ). These measures were derived from ratings of food liking and desire to eat at the start and end of lunch: both ratings declined overall, but the rate of decrease for the desire to eat measure was markedly slower for those with high HFS intake. These results are further supported in a study which tested the extent to which habitual HFS intake in a healthy normal-weight population were related to sensitivity to thirst-related interoceptive cues( Reference Brannigan, Stevenson and Francis 76 ). Here, changes in thirst sensations after a thirst-inducing challenge (eating salty crisps) decreased as a function of increased HFS intake, interpreted as further evidence of poorer interoceptive awareness in HFS consumers.

A second key prediction from the VCM is that people who habitually consume excessive amounts of HFS diets will also display poorer impulse control. In parallel to the development of the VCM here has been a large increase in interest in the role of impulsivity as a risk factor for development of obesity, based on the idea that the risky decision making and emphasis on short-term rewards, which are key features of impulsivity could contribute to the poor dietary choices that underlie overeating and HFS consumption. There is now a wealth of studies reporting that higher measures of impulsivity are associated with obesity( Reference Batterink, Yokum and Stice 96 Reference Schag, Schonleber and Teufel 100 ) and uncontrolled eating( Reference Yeomans, Leitch and Mobini 101 ). None of those studies specifically assessed habitual HFS intake; however, a recent study reported an association between HFS intake measured using the DFS ( Reference Lumley, Stevenson and Oaten 102 ). They reported that HFS intake was associated with higher scores on two standardised measures of impulsivity: overall scores on the Barratt Impulsivity Scale and the Urgency measure from the Urgency, Premeditation, Perseverance and Sensation Seeking questionnaire.

The VCM also has other testable implications for human ingestion, which remain largely unexplored. There is now considerable scope for new research to clarify the full extent to which habitual dietary patterns about HFS consumption do cause long-term changes in cognitive function which in turn makes it harder to self-regulate appetite and food choice.

Brief word on mechanism

How then might excessive intake of HFS diets alter hippocampal function? Based on extensive research in animals, evidence of three potential mechanisms has emerged and these have been reviewed in detail elsewhere( Reference Hargrave, Jones and Davidson 16 , Reference Kanoski and Davidson 17 , Reference Francis and Stevenson 68 ). A number of potential mechanisms have been identified, and here the three where there appears to strongest evidence is briefly summarised: neuroinflammation, effects on the blood–brain barrier and altered levels of brain-derived neurotrophic factor (BDNF).

The idea that specific responses to diet can lead to an inflammatory response is well established: inflammatory responses, particularly chronic low-grade inflammation, have been implicated in many diet-related diseases, including heart disease( Reference Yudkin, Kumari and Humphries 103 Reference Halaris 105 ), diabetes( Reference Figaro, Kritchevsky and Resnick 106 , Reference Wellen and Hotamisligil 107 ) and depression( Reference Dantzer, O'Connor and Freund 108 ). Many studies have found higher levels of inflammatory markers in obese than normal-weight participants( Reference Wang, Lam and Kraegen 109 Reference Spyridaki, Avgoustinaki and Margioris 111 ). It has also been argued, with considerable evidence, that inflammation may be a key link between obesity and diabetes( Reference Esser, Legrand-Poels and Piette 112 ), and that this damage in turn alters subsequent food intake regulation( Reference Hargrave, Jones and Davidson 16 , Reference Cazettes, Cohen and Yau 113 ). In the present context, the key findings come principally from studies with animals that show increased levels of inflammatory markers for rats placed on HFS diets( Reference Pistell, Morrison and Gupta 63 ), and particularly evidence of specific neuroinflammatory responses in the hippocampus( Reference Sobesky, Barrientos and Henning 114 Reference Castanon, Luheshi and Layé 116 ). Thus, diet-induced inflammation provides a potential explanation for the specific impact of HF and HFS diets on hippocampal-dependent cognitive processes.

One of the potential explanations for how neuroinflammation alters hippocampal function might be through changes in the levels of BDNF. BDNF acts to support the differentiation of neurons, and crucially is abundant in the hippocampus. BDNF plays a key role in long-term memory( Reference Cunha, Brambilla and Thomas 117 , Reference Lu, Christian and Lu 118 ), and so any changes in BDNF are likely to also affect memory and so appear a prime candidate as a link between the diet-induced changes in hippocampal function and memory highlighted in this review. There is now considerable evidence for alterations in hippocampal BDNF in animals fed HF or HFS diets( Reference Hargrave, Jones and Davidson 16 ). For example, rats consuming a HFS diet had reduced BDNF in the ventral hippocampus, alongside hippocampal-dependent changes in cognitive performance( Reference Kanoski, Meisel and Mullins 119 ). Other studies also found reduced hippocampal BDNF in animals consuming HF or HFS diets( Reference Molteni, Barnard and Ying 59 , Reference Lee, Duan and Mattson 120 ). Together, these studies clearly implicate changes in BDNF in diet-induced hippocampal dysfunction, although what causes the changes in BDNF needs to be clarified.

The selectivity of the semipermeable blood–brain barrier separates the brain from circulating blood, so protecting the brain from circulating pathogens. It is then surprising that the effectiveness of the blood–brain barrier can be affected by diet. For example, mid-life BMI predicted the integrity of the blood–brain barrier 24 years later, with higher BMI associated with less effective blood–brain barriers in these women( Reference Gustafson, Karlsson and Skoog 121 ). That study does not directly implicate diet, although higher BMI would be expected to relate to higher intake. Animal studies have however reported specific deficits in the blood–brain barrier for rats maintained on HFS( Reference Kanoski, Zhang and Zheng 122 ) or HF high-cholesterol( Reference Freeman and Granholm 123 ) diets. Thus, repeated consumption of these types of diet do appear to impair the effectiveness of the blood–brain barrier.

So far, there is evidence for three potential explanations for the effects of Western-style HF or HFS diets on hippocampal function: whether these act independently or are related (e.g. reduced effectiveness of the blood–brain barrier contributing to local inflammation which might reduce BDNF production) remains unknown. But they do offer plausible and testable mechanisms that could underpin the cognitive deficits.

Cause of hippocampal changes: diets, nutrients or adiposity?

A weakness in this research area to date is the poor specification of what dietary changes are involved. Animal studies use diets with high levels of added (typically saturated) fat and/or sugar: whether it is the effects of overconsuming the enhanced elements of these diets or consequent dilution of other features of the diet that are key to the observed effects needs to be clarified. Of particular relevance is the nature of the fats in the diet, since there is evidence that n-3 fats in particular may act to reduce inflammation( Reference Flock, Rogers and Prabhu 124 , Reference Lorente-Cebrián, Costa and Navas-Carretero 125 ), and increasing SF content of a diet may act to alter the proportion of n-3 indirectly, for example. Thus, there is urgent need to examine the specificity of the dietary changes observed in the animal studies that largely underpin this research area. A further issue in interpretation of the animal studies is that these diets also lead to increased body weight, and determining whether the inflammatory responses etc. are then a direct consequence of the diet or adiposity cannot be easily determined.

Human studies to date are essentially based on the relative proportion of HFS foods in an individual's diet estimated from self-report food frequency measures. That replicable behavioural findings emerge from this simple measure implies that more highly specified dietary analyses may be able to identify more specifically what dietary features are critical. A key feature of the main human studies( Reference Francis and Stevenson 74 , Reference Brannigan, Stevenson and Francis 76 , Reference Attuquayefio, Stevenson and Boakes 77 ), however, is that they are able to dissociate the effects of diet from the potential confound of adiposity, since all of these studies were in normal-weight volunteers and the critical relationships between behavioural measures and HFS intake were still evident once BMI had been controlled for.

Future directions

This short review highlights the current state of knowledge of the potential impact of Western diets on cognition and consequently on appetite. But it also highlights major shortcomings in our current understanding. Most critical is the lack of dietary specificity in the studies underpinning research findings in this area to date. There is now a real opportunity to data-mine existing longitudinal studies, which hold nutritional and cognitive measures to test the hypotheses generated from the current findings in a more representative large population. Such analyses could potentially dissociate more fully effects of diet per se from weight gain, and identify whether it is excess of certain food types or nutrients that are the key risks for cognitive impairment. There is also a need to test in human subjects more of the predictions from the VCM: what is the impact of HFS consumption on food-related reward and attention, for example. The ideas and hypotheses in this area are intriguing, and have the potential to make major advances in our understanding of causes and consequences of overeating, and warrant urgent further investigation.

Conclusion

This brief review summarised the importance of cognitive factors in human appetite control and then speculated how changes in a core brain area associated with cognition, and particularly memory, may be disrupted by habitual overconsumption of energy-dense HFS diets. The animal research in this area is persuasive in terms of the specificity of the effects on the hippocampus, but is less impressive in considering the nutritional specification of the diets that have these effects. Human research in this area is emerging, and is consistent with the broad findings from the animal models, however. The overall conclusion would be that excessive intake of readily metabolised nutrients may lead to a subclinical inflammatory response which in turn may impair performance of key areas of the brain. The consequent changes in cognition in turn impair the ability to engage with the healthy lifestyle needed to reverse the effects. Research is now needed to test these ideas more broadly, and consider how these ideas may be valuable in novel approaches to countering the obesity crisis.

Financial Support

Some of the reported work was supported by a grant from the Australian Research Council (grant number DP150100105).

Conflicts of Interest

None.

Authorship

The author had sole responsibility for all aspects of preparation of this paper.

References

1. Hellström, PM (2013) Satiety signals and obesity. Curr Opin Gastroenterol 29, 222227.Google Scholar
2. Hussain, S & Bloom, S (2013) The regulation of food intake by the gut-brain axis: implications for obesity. Int J Obes 37, 625633.Google Scholar
3. Finlayson, G, Halford, JC, King, NA et al. (2007) The regulation of food intake in humans. In Obesitext - The Source [Matthias, T, editor] Endotext. com.Google Scholar
4. Stroebe, W, Papies, EK & Aarts, H (2008) From homeostatic to hedonic theories of eating: self-regulatory failure in food-rich environments. Appl Psychol 57, 172193.Google Scholar
5. Hess, ME & Brüning, JC (2014) Obesity: the need to eat [mdash] overruling the homeostatic control of feeding. Nat Rev Endocrinol 10, 56.CrossRefGoogle ScholarPubMed
6. Lowe, MR & Butryn, ML (2007) Hedonic hunger: a new dimension of appetite? Physiol Behav 91, 432439.Google Scholar
7. Herman, CP (2015) The social facilitation of eating. A review. Appetite 86, 6173.Google Scholar
8. Cruwys, T, Bevelander, KE & Hermans, RC (2015) Social modeling of eating: a review of when and why social influence affects food intake and choice. Appetite 86, 318.CrossRefGoogle ScholarPubMed
9. Yeomans, MR, Blundell, JE & Lesham, M (2004) Palatability: response to nutritional need or need-free stimulation of appetite? Br J Nutr 92, Suppl. 3, S3S14.CrossRefGoogle ScholarPubMed
10. Yeomans, MR (2007) The role of palatability in control of food intake: implications for understanding and treating obesity. In Appetite and Body Weight: Integrative systems and the Development of Anti-Obesity Drugs, pp. 247269 [Cooper, SJ and Kirkham, TC, editors]. London: Academic Press.CrossRefGoogle Scholar
11. Johnson, F & Wardle, J (2014) Variety, palatability, and obesity. Adv. Nutr 5, 851859.Google Scholar
12. Almiron-Roig, E, Tsiountsioura, M, Lewis, HB et al. (2015) Large portion sizes increase bite size and eating rate in overweight women. Physiol Behav 139, 297302.Google Scholar
13. Zlatevska, N, Dubelaar, C & Holden, SS (2014) Sizing up the effect of portion size on consumption: a meta-analytic review. J Mark. 78, 140154.Google Scholar
14. Wansink, B & Van Ittersum, K (2013) Portion size me: plate-size induced consumption norms and win-win solutions for reducing food intake and waste. J Exp Psychol Appl 19, 320.Google Scholar
15. Livingstone, MBE & Pourshahidi, LK (2014) Portion size and obesity. Adv. Nutr 5, 829834.Google Scholar
16. Hargrave, SL, Jones, S & Davidson, TL (2016) The outward spiral: a vicious cycle model of obesity and cognitive dysfunction. Curr Opin Behav Sci 9, 4046.Google Scholar
17. Kanoski, SE & Davidson, TL (2011) Western diet consumption and cognitive impairment: links to hippocampal dysfunction and obesity. Physiol Behav 103, 5968.Google Scholar
18. Schachter, S (1968) Obesity and eating. Science 161, 751756.Google Scholar
19. Robinson, E, Aveyard, P, Daley, A et al. (2013) Eating attentively: a systematic review and meta-analysis of the effect of food intake memory and awareness on eating. Am J Clin Nutr, 92, 728742.CrossRefGoogle Scholar
20. Prescott, J, Taylor, A & Roberts, D (2004) Psychological processes in flavour perception. In Flav Percept pp. 256277 [Taylor, AJ and Roberts, D, editors] London: Blackwell Publishing.CrossRefGoogle Scholar
21. Small, DM & Prescott, J (2005) Odor/taste integration and the perception of flavor. Exp Brain Res 166, 345357.CrossRefGoogle ScholarPubMed
22. Yeomans, MR (2006) The role of learning in development of food preferences. In Psychology of Food Choice, pp. 93112 [Shepherd, R and Raats, M, editors]. Wallingford, Oxford: CABI.CrossRefGoogle Scholar
23. Havermans, RC & Jansen, A (2011) Acquired tastes: establishing food (dis-) likes by flavour–flavour learning. In Handbook of Behavior, Food and Nutrition, pp. 7384 [Preedy, VR, Watson, RR and martin, CR, editors]. New York: Springer.CrossRefGoogle Scholar
24. Rozin, P, Dow, S, Moscovitch, M et al. (1998) What causes humans to begin and end a meal? A role for memory for what has been eaten, as evidenced by a study of multiple meal eating in amnesic patients. Psychol Sci 9, 392396.Google Scholar
25. Higgs, S & Donohoe, JE (2011) Focusing on food during lunch enhances lunch memory and decreases later snack intake. Appetite 57, 202206.Google Scholar
26. Higgs, S, Williamson, AC & Attwood, AS (2008) Recall of recent lunch and its effect on subsequent snack intake. Physiol Behav 94, 454462.CrossRefGoogle ScholarPubMed
27. Higgs, S & Woodward, M (2009) Television watching during lunch increases afternoon snack intake of young women. Appetite 52, 3943.Google Scholar
28. Higgs, S (2008) Cognitive influences on food intake: the effects of manipulating memory for recent eating. Physiol Behav 94, 734739.CrossRefGoogle ScholarPubMed
29. Piech, RM, Pastorino, MT & Zald, DH (2010) All I saw was the cake. Hunger effects on attentional capture by visual food cues. Appetite 54, 579582.Google Scholar
30. Tapper, K, Pothos, EM & Lawrence, AD (2010) Feast your eyes: hunger and trait reward drive predict attentional bias for food cues. Emotion 10, 949.Google Scholar
31. Mogg, K, Bradley, BP, Hyare, H et al. (1998) Selective attention to food-related stimuli in hunger: are attentional biases specific to emotional and psychopathological states, or are they also found in normal drive states? Behav Res Ther 36, 227237.CrossRefGoogle ScholarPubMed
32. Siep, N, Roefs, A, Roebroeck, A et al. (2009) Hunger is the best spice: an fMRI study of the effects of attention, hunger and calorie content on food reward processing in the amygdala and orbitofrontal cortex. Behav Brain Res 198, 149158.CrossRefGoogle ScholarPubMed
33. Castellanos, EH, Charboneau, E, Dietrich, MS et al. (2009) Obese adults have visual attention bias for food cue images: evidence for altered reward system function. Int J Obes (Lond) 33, 10631073.Google Scholar
34. Braet, C & Crombez, G (2003) Cognitive interference due to food cues in childhood obesity. J Clin Child Adolesc 32, 3239.Google Scholar
35. Nijs, IM, Franken, IH & Muris, P (2010) Food-related Stroop interference in obese and normal-weight individuals: behavioral and electrophysiological indices. Eat Behav 11, 258265.CrossRefGoogle ScholarPubMed
36. Nijs, IM, Muris, P, Euser, AS et al. (2010) Differences in attention to food and food intake between overweight/obese and normal-weight females under conditions of hunger and satiety. Appetite 54, 243254.Google Scholar
37. Yokum, S, Ng, J & Stice, E (2011) Attentional bias to food images associated with elevated weight and future weight gain: an fMRI study. Obesity 19, 17751783.CrossRefGoogle ScholarPubMed
38. Werthmann, J, Roefs, A, Nederkoorn, C et al. (2011) Can (not) take my eyes off it: attention bias for food in overweight participants. Health Psychol 30, 561.CrossRefGoogle ScholarPubMed
39. Kemps, E, Tiggemann, M & Hollitt, S (2014) Biased attentional processing of food cues and modification in obese individuals. Health Psychol 33, 1391.CrossRefGoogle ScholarPubMed
40. Doolan, KJ, Breslin, G, Hanna, D et al. (2014) Visual attention to food cues in obesity: an eye-tracking study. Obesity 22, 25012507.Google ScholarPubMed
41. Deluchi, M, Costa, FS, Friedman, R et al. (2017) Attentional bias to unhealthy food in individuals with severe obesity and binge eating. Appetite 108, 471476.Google Scholar
42. Gao, X, Wang, Q, Jackson, T et al. (2011) Biases in orienting and maintenance of attention among weight dissatisfied women: an eye-movement study. Behav Res Ther 49, 252259.Google Scholar
43. Werthmann, J, Roefs, A, Nederkoorn, C et al. (2013) Attention bias for food is independent of restraint in healthy weight individuals – an eye tracking study. Eat Behav 14, 397400.Google Scholar
44. Gibson, EL & Brunstrom, JM (2007) Learned influences on appetite, food choice and intake: evidence in human beings. In Appetite and Body Weight: Integrative Systems and the Development of Anti-Obesity Drugs, pp. 271300 [Kirkham, TC and Cooper, SJ, editors] London: Academic Press.CrossRefGoogle Scholar
45. Benoit, SC, Davis, JF & Davidson, T (2010) Learned and cognitive controls of food intake. Brain Res 1350, 7176.CrossRefGoogle ScholarPubMed
46. Yeomans, MR & Mobini, S (2006) Hunger alters the expression of acquired hedonic but not sensory qualities of food-paired odors in humans. J Exp Psychol Anim Behav Proc 32, 460466.CrossRefGoogle Scholar
47. Mobini, S, Chambers, LC & Yeomans, MR (2007) Effects of hunger state on flavour pleasantness conditioning at home: flavour-nutrient learning versus flavour-flavour learning. Appetite 48, 2028.CrossRefGoogle Scholar
48. Brunstrom, JM, Downes, CR & Higgs, S (2001) Effects of dietary restraint on flavour-flavour learning. Appetite 37, 197206.CrossRefGoogle ScholarPubMed
49. Brunstrom, JM & Mitchell, GL (2007) Flavor-nutrient learning in restrained and unrestrained eaters. Physiol Behav 90, 133141.CrossRefGoogle ScholarPubMed
50. Gunstad, J, Paul, R, Cohen, R et al. (2006) Obesity is associated with memory deficits in young and middle-aged adults. Eat Weight DisordStud Anorexia Bulimia Obes 11, e15e19.CrossRefGoogle Scholar
51. Cournot, M, Marquie, J, Ansiau, D et al. (2006) Relation between body mass index and cognitive function in healthy middle-aged men and women. Neurology 67, 12081214.CrossRefGoogle ScholarPubMed
52. Gunstad, J, Lhotsky, A, Wendell, CR et al. (2010) Longitudinal examination of obesity and cognitive function: results from the Baltimore longitudinal study of aging. Neuroepidemiology 34, 222229.CrossRefGoogle ScholarPubMed
53. Cheke, LG, Simons, JS & Clayton, NS (2016) Higher body mass index is associated with episodic memory deficits in young adults. Q J Exp Psychol 69, 23052316.Google Scholar
54. Miller, LA, Crosby, RD, Galioto, R et al. (2013) Bariatric surgery patients exhibit improved memory function 12 months postoperatively. Obes Surg 23, 15271535.Google Scholar
55. Coppin, G, Nolan-Poupart, S, Jones-Gotman, M et al. (2014) Working memory and reward association learning impairments in obesity. Neuropsychologia 65, 146155.CrossRefGoogle ScholarPubMed
56. Sabia, S, Kivimaki, M, Shipley, MJ et al. (2009) Body mass index over the adult life course and cognition in late midlife: the Whitehall II Cohort Study. Am J Clin Nutr 89, 601607.Google Scholar
57. Barkin, SL (2013) The relationship between executive function and obesity in children and adolescents: a systematic literature review. J Obes 2013. http://dx.doi.org/10.1155/2013/820956.Google Scholar
58. Kuo, HK, Jones, RN, Milberg, WP et al. (2006) Cognitive function in normal-weight, overweight, and obese older adults: an analysis of the advanced cognitive training for independent and vital elderly cohort. J Am Geriatr Soc 54, 97103.Google Scholar
59. Molteni, R, Barnard, R, Ying, Z et al. (2002) A high-fat, refined sugar diet reduces hippocampal brain-derived neurotrophic factor, neuronal plasticity, and learning. Neuroscience 112, 803814.Google Scholar
60. Stranahan, AM, Norman, ED, Lee, K et al. (2008) Diet-induced insulin resistance impairs hippocampal synaptic plasticity and cognition in middle-aged rats. Hippocampus 18, 10851088.Google Scholar
61. Kanoski, SE & Davidson, TL (2010) Different patterns of memory impairments accompany short-and longer-term maintenance on a high-energy diet. J Exp Psychol Anim Behav Proc 36, 313.CrossRefGoogle ScholarPubMed
62. Jurdak, N, Lichtenstein, AH & Kanarek, RB (2008) Diet-induced obesity and spatial cognition in young male rats. Nutr Neurosci 11, 4854.Google Scholar
63. Pistell, PJ, Morrison, CD, Gupta, S et al. (2010) Cognitive impairment following high fat diet consumption is associated with brain inflammation. J Neuroimmunol 219, 2532.Google Scholar
64. Valladolid-Acebes, I, Stucchi, P, Cano, V et al. (2011) High-fat diets impair spatial learning in the radial-arm maze in mice. Neurobiol Learn Mem 95, 8085.Google Scholar
65. Tran, DM & Westbrook, RF (2015) Rats fed a diet rich in fats and sugars are impaired in the use of spatial geometry. Psychol Sci, 26, 19471957.Google Scholar
66. Beilharz, JE, Maniam, J & Morris, MJ (2014) Short exposure to a diet rich in both fat and sugar or sugar alone impairs place, but not object recognition memory in rats. Brain Behav Immun 37, 134141.CrossRefGoogle Scholar
67. Murray, AJ, Knight, NS, Cochlin, LE et al. (2009) Deterioration of physical performance and cognitive function in rats with short-term high-fat feeding. FASEB J 23, 43534360.Google Scholar
68. Francis, H & Stevenson, R (2013) The longer-term impacts of Western diet on human cognition and the brain. Appetite 63, 119128.Google Scholar
69. Kanoski, SE, Hsu, TM & Pennell, S (2014) Obesity, Western diet intake, and cognitive impairment. In Omega-3 Fatty Acids in Brain and Neurological Health, pp. 5762 [Watson, RR and De Meester, F, editors]. New York: Academic Press.Google Scholar
70. Kalmijn, S, Van Boxtel, M, Ocke, M et al. (2004) Dietary intake of fatty acids and fish in relation to cognitive performance at middle age. Neurology 62, 275280.Google Scholar
71. Morris, M, Evans, D, Bienias, J et al. (2004) Dietary fat intake and 6-year cognitive change in an older biracial community population. Neurology 62, 15731579.CrossRefGoogle Scholar
72. Gibson, EL, Barr, S & Jeanes, YM (2013) Habitual fat intake predicts memory function in younger women. Front Hum Neurosci 7, 838.Google Scholar
73. Akbaraly, TN, Singh-Manoux, A, Marmot, MG et al. (2009) Education attenuates the association between dietary patterns and cognition. Dement Geriatr Cogn 27, 147154.Google Scholar
74. Francis, HM & Stevenson, RJ (2011) Higher reported saturated fat and refined sugar intake is associated with reduced hippocampal-dependent memory and sensitivity to interoceptive signals. Behav Neurosci 125, 943955.Google Scholar
75. Francis, H & Stevenson, R (2013) Validity and test–retest reliability of a short dietary questionnaire to assess intake of saturated fat and free sugars: a preliminary study. J Hum Nutr Dietet 26, 234242.Google Scholar
76. Brannigan, M, Stevenson, RJ & Francis, H (2015) Thirst interoception and its relationship to a Western-style diet. Physiol Behav 139, 423429.CrossRefGoogle ScholarPubMed
77. Attuquayefio, T, Stevenson, RJ, Boakes, RA et al. (2016) A high-fat high-sugar diet predicts poorer hippocampal-related memory and a reduced ability to suppress wanting under satiety. J Exp Psychol Animal Learn Cogn 42, 415428.Google Scholar
78. Jacka, FN, Cherbuin, N, Anstey, KJ et al. (2015) Western diet is associated with a smaller hippocampus: a longitudinal investigation. BMC Med 13, 215.Google Scholar
79. Edwards, LM, Murray, AJ, Holloway, CJ et al. (2011) Short-term consumption of a high-fat diet impairs whole-body efficiency and cognitive function in sedentary men. FASEB J 25, 10881096.CrossRefGoogle ScholarPubMed
80. Holloway, CJ, Cochlin, LE, Emmanuel, Y et al. (2011) A high-fat diet impairs cardiac high-energy phosphate metabolism and cognitive function in healthy human subjects. Am J Clin Nutr 93, 748755.Google Scholar
81. Davidson, TL, Tracy, AL, Schier, LA et al. (2014) A view of obesity as a learning and memory disorder. J Exp Psychol Animal Learn Cogn 40, 261279.CrossRefGoogle ScholarPubMed
82. Parent, MB, Darling, JN & Henderson, YO (2014) Remembering to eat: hippocampal regulation of meal onset. Am J Physiol Regul Integr Comp Physiol 306, R701R713.CrossRefGoogle ScholarPubMed
83. Davidson, T, Kanoski, SE, Walls, EK et al. (2005) Memory inhibition and energy regulation. Physiol Behav 86, 731746.Google Scholar
84. Davidson, TL, Kanoski, SE, Schier, LA et al. (2007) A potential role for the hippocampus in energy intake and body weight regulation. Curr Opp Pharmacol 7, 613616.Google Scholar
85. Berthoud, H-R & Morrison, C (2008) The brain, appetite, and obesity. Ann Rev Psychol 59, 5592.CrossRefGoogle ScholarPubMed
86. Cota, D, Proulx, K, Smith, KAB et al. (2006) Hypothalamic mTOR signaling regulates food intake. Science 312, 927930.Google Scholar
87. Kanoski, SE & Grill, HJ (2017) Hippocampus contributions to food intake control: mnemonic, neuroanatomical, and endocrine mechanisms. Biol Psychiatr, 81, 748756.Google Scholar
88. Hannapel, RC, Henderson, YH, Nalloor, R et al. (2017) Ventral hippocampal neurons inhibit postprandial energy intake. Hippocampus, 27, 274284.Google Scholar
89. Preston, AR & Eichenbaum, H (2013) Interplay of hippocampus and prefrontal cortex in memory. Curr Biol 23, R764R773.CrossRefGoogle ScholarPubMed
90. Schiller, D, Eichenbaum, H, Buffalo, EA et al. (2015) Memory and space: towards an understanding of the cognitive map. J Neurosci 35, 1390413911.Google Scholar
91. Zeidman, P & Maguire, EA (2016) Anterior hippocampus: the anatomy of perception, imagination and episodic memory. Nat Rev Neurosci 17, 173182.Google Scholar
92. Clifton, PG, Vickers, SP & Somerville, EM (1998) Little and often: ingestive behavior patterns following hippocampal lesions in rats. Behav Neurosci 112, 502.Google Scholar
93. Henderson, YO, Smith, GP & Parent, MB (2013) Hippocampal neurons inhibit meal onset. Hippocampus 23, 100107.Google Scholar
94. Sample, CH, Jones, S, Hargrave, SL et al. (2016) Western diet and the weakening of the interoceptive stimulus control of appetitive behavior. Behav Brain Res 312, 219230.Google Scholar
95. Sample, CH, Martin, AA, Jones, S et al. (2015) Western-style diet impairs stimulus control by food deprivation state cues: implications for obesogenic environments. Appetite 93, 1323.Google Scholar
96. Batterink, L, Yokum, S & Stice, E (2010) Body mass correlates inversely with inhibitory control in response to food among adolescent girls: an fMRI study. Neuroimage 52, 16961703.Google Scholar
97. Epstein, LH, Dearing, KK, Temple, JL et al. (2008) Food reinforcement and impulsivity in overweight children and their parents. Eat Behav 9, 319327.Google Scholar
98. Mobbs, O, Crepin, C, Thiery, C et al. (2010) Obesity and the four facets of impulsivity. Patient Educ Couns 79, 372377.Google Scholar
99. Nederkoorn, C, Braet, C, Van Eijs, Y et al. (2006) Why obese children cannot resist food: the role of impulsivity. Eat Behav 7, 315322.Google Scholar
100. Schag, K, Schonleber, J, Teufel, M et al. (2013) Food-related impulsivity in obesity and binge eating disorder – a systematic review. Obes Rev 14, 477495.Google Scholar
101. Yeomans, MR, Leitch, M & Mobini, S (2008) Impulsivity is associated with the disinhibition but not restraint factor from the Three Factor Eating Questionnaire. Appetite 50, 469476.Google Scholar
102. Lumley, J, Stevenson, RJ, Oaten, MJ et al. (2016) Individual differences in impulsivity and their relationship to a Western-style diet. Pers Indiv Differ 97, 178185.Google Scholar
103. Yudkin, JS, Kumari, M, Humphries, SE et al. (2000) Inflammation, obesity, stress and coronary heart disease: is interleukin-6 the link? Atherosclerosis 148, 209214.Google Scholar
104. Danesh, J, Whincup, P, Walker, M et al. (2000) Low grade inflammation and coronary heart disease: prospective study and updated meta-analyses. BMJ 321, 199204.CrossRefGoogle ScholarPubMed
105. Halaris, A (2013) Inflammation, heart disease, and depression. Curr Psychiatr Rep 15, 400.Google Scholar
106. Figaro, MK, Kritchevsky, SB, Resnick, HE et al. (2006) Diabetes, inflammation, and functional decline in older adults. Diabetes Care 29, 20392045.Google Scholar
107. Wellen, KE & Hotamisligil, GS (2005) Inflammation, stress, and diabetes. J Clin Invest 115, 11111119.CrossRefGoogle ScholarPubMed
108. Dantzer, R, O'Connor, JC, Freund, GG et al. (2008) From inflammation to sickness and depression: when the immune system subjugates the brain. Nat Rev Neurosci 9, 4656.Google Scholar
109. Wang, Y, Lam, KS, Kraegen, EW et al. (2007) Lipocalin-2 is an inflammatory marker closely associated with obesity, insulin resistance, and hyperglycemia in humans. Clin Chem 53, 3441.Google Scholar
110. Shoelson, SE, Herrero, L & Naaz, A (2007) Obesity, inflammation, and insulin resistance. Gastroenterology 132, 21692180.Google Scholar
111. Spyridaki, EC, Avgoustinaki, PD & Margioris, AN (2016) Obesity, inflammation and cognition. Curr Opin Behav Sci 9, 169175.CrossRefGoogle Scholar
112. Esser, N, Legrand-Poels, S, Piette, J et al. (2014) Inflammation as a link between obesity, metabolic syndrome and type 2 diabetes. Diab Res Clin Pract 105, 141150.Google Scholar
113. Cazettes, F, Cohen, JI, Yau, PL et al. (2011) Obesity-mediated inflammation may damage the brain circuit that regulates food intake. Brain Res 1373, 101109.Google Scholar
114. Sobesky, JL, Barrientos, RM, Henning, S et al. (2014) High-fat diet consumption disrupts memory and primes elevations in hippocampal IL-1β, an effect that can be prevented with dietary reversal or IL-1 receptor antagonism. Brain Behav Immun 42, 2232.CrossRefGoogle ScholarPubMed
115. Boitard, C, Cavaroc, A, Sauvant, J et al. (2014) Impairment of hippocampal-dependent memory induced by juvenile high-fat diet intake is associated with enhanced hippocampal inflammation in rats. Brain Behav Immun 40, 917.Google Scholar
116. Castanon, N, Luheshi, G & Layé, S (2015) Role of neuroinflammation in the emotional and cognitive alterations displayed by animal models of obesity. Front Neurosci 9, 229.Google Scholar
117. Cunha, C, Brambilla, R & Thomas, KL (2010) A simple role for BDNF in learning and memory? Front Mol Neurosci 3, 1.Google Scholar
118. Lu, Y, Christian, K & Lu, B (2008) BDNF: a key regulator for protein synthesis-dependent LTP and long-term memory? Neurobiol Learn Mem 89, 312323.Google Scholar
119. Kanoski, SE, Meisel, RL, Mullins, AJ et al. (2007) The effects of energy-rich diets on discrimination reversal learning and on BDNF in the hippocampus and prefrontal cortex of the rat. Behav Brain Res 182, 5766.Google Scholar
120. Lee, J, Duan, W & Mattson, MP (2002) Evidence that brain-derived neurotrophic factor is required for basal neurogenesis and mediates, in part, the enhancement of neurogenesis by dietary restriction in the hippocampus of adult mice. J Neurochem 82, 13671375.Google Scholar
121. Gustafson, D, Karlsson, C, Skoog, I et al. (2007) Mid-life adiposity factors relate to blood–brain barrier integrity in late life. J Int Med 262, 643650.Google Scholar
122. Kanoski, SE, Zhang, Y, Zheng, W et al. (2010) The effects of a high-energy diet on hippocampal function and blood-brain barrier integrity in the rat. J Alzheimers Dis 21, 207219.Google Scholar
123. Freeman, LR & Granholm, A-CE (2012) Vascular changes in rat hippocampus following a high saturated fat and cholesterol diet. J Cereb Blood Flow Metab 32, 643653.Google Scholar
124. Flock, MR, Rogers, CJ, Prabhu, KS et al. (2013) Immunometabolic role of long-chain omega-3 fatty acids in obesity-induced inflammation. Diab Metab Res Rev 29, 431445.Google Scholar
125. Lorente-Cebrián, S, Costa, AG, Navas-Carretero, S et al. (2015) An update on the role of omega-3 fatty acids on inflammatory and degenerative diseases. J Physiol Biochem 71, 341349.Google Scholar
Figure 0

Fig. 1. Associations between BMI and performance on a novel spatial test of episodic memory (the what, where, when task), redrawn from Cheke, Simons(53), with permission.

Figure 1

Fig. 2. Performance on (a) a spatial (place recognition) and (b) non-spatial (object recognition) task for rats fed a chow () or high-fat–high-sugar diet (). Higher exploration proportion values reflect better memory. Figure adapted from data in(65) with permission.

Figure 2

Fig. 3. A schematic summary of the vicious cycle model proposed by Davidson and co-workers, adapted from(17).