PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Int J Obes (Lond). Author manuscript; available in PMC Jul 1, 2009.
Published in final edited form as:
PMCID: PMC2667112
NIHMSID: NIHMS101294
Differences in response to food stimuli in a rat model of obesity: in-vivo assessment of brain glucose metabolism
PK Thanos,1,2,3 M Michaelides,1,2,3 J-D Gispert,4 J Pascau,5 ML Soto-Montenegro,5 M Desco,5 R Wang,1 G-J Wang,1 and ND Volkow2
1Department of Medicine, Behavioral Neuropharmacology and Neuroimaging Laboratory, Brookhaven National Laboratory, Upton, NY, USA
2Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Department of Health and Human Services, Bethesda, MD, USA
3Department of Psychology, Stony Brook University, Stony Brook, NY, USA
4Institut d’Alta Tecnologia Parc de Recerca Biomeèdica de Barcelona, Passeig Marítim, Barcelona, Spain
5Unidad de Medicina y Cirugía Experimental Hospital General Universitario Gregorio Maranñón, Madrid, Spain
Correspondence: Dr PK Thanos, Department of Medicine, Brookhaven National Laboratory, 30 Bell Avenue, Upton, NY 11973-5000, USA. E-mail: thanos/at/bnl.gov
Objective
Food intake is regulated by factors that modulate caloric requirements as well as food’s reinforcing properties. In this study, we measured brain glucose utilization to an olfactory stimulus (bacon scent), and we examined the role of food restriction and genetic predisposition to obesity on such brain metabolic activity.
Methods
Zucker obese (Ob) and lean (Le) rats were divided into four groups: (1) Ob ad-libitum fed, (2) Ob food restricted (70% of ad libitum), (3) Le ad-libitum fed and (4) Le food restricted. Rats were scanned using µ-positron emission tomography and 2-[18F]-fluoro-2-deoxy-d-glucose under two conditions: (1) baseline scan (no stimulation) and (2) challenge scan (food stimulation, FS).
Results
FS resulted in deactivation of the right and left hippocampus. Ob rats showed greater changes with FS than Le rats (deactivation of hippocampus and activation of the medial thalamus) and Ob but not Le animals deactivated the frontal cortex and activated the superior colliculus. Access to food resulted in an opposite pattern of metabolic changes to the food stimuli in olfactory nucleus (deactivated in unrestricted and activated in restricted) and in right insular/parietal cortex (activated in unrestricted and deactivated in restricted). In addition, restricted but not unrestricted animals activated the medial thalamus.
Conclusions
The greater changes in the Ob rats suggest that leptin modulates the regional brain responses to a familiar food stimulus. Similarly, the differences in the pattern of responses with food restriction suggest that FS is influenced by access to food conditions. The main changes with FS occurred in the hippocampus, a region involved in memory, the insular cortex, a region involved with interoception (perception of internal sensations), the medial thalamus (region involved in alertness) and in regions involved with sensory perception (olfactory bulb, olfactory nucleus, occipital cortex, superior colliculus and parietal cortex), which corroborates their relevance in the perception of food.
Keywords: 18FDG-craving-Zucker-food restriction, ingestive behavior, positron emission tomography-hippocampus
The importance of the internal environment in part via the hypothalamus in the regulation of body weight is well recognized.1 There is also increasing interest on the importance of the external environment in modulating food intake as well as its contribution to the dramatic increases in obesity.2 Food intake is regulated by multiple factors that modulate not only nutrient and caloric requirements but also food’s reinforcing properties, and thus changes in food palatability and availability are expected to affect its rate of consumption.3 Thus, environmental factors that have been associated with the increase in obesity include a wide expansion in food variety, increased food palatability, low cost and availability (particularly from energy-dense foods), larger food portions and finally increases in the exposure to food cues.4 It is also recognized that emotional variables such as stress and depression can also contribute to over-eating. 5 Of these, the contribution that the plethora of sensory cues (that are conditioned to elicit powerful responses involved in food craving) have on overeating is poorly understood.
Measurements of regional brain glucose metabolism have been done with positron emission tomography (PET) and 2-[18F]-flouro-2-deoxy-d-glucose (FDG) to investigate the regions of the brain that are involved in processing food stimuli in the human brain. One such study showed that visual and chemosensory exposure to an appetitive food stimulus led to significant whole brain activation that was most accentuated in the left parietal somatosensory cortex, left and right insula and left orbitofrontal cortex in food deprived subjects.4 In satiated subjects exposure to descriptors of highly desirable foods led to activation of the amygdala and orbitofrontal cortex when compared to activation with descriptors of neutral foods.6 A baseline comparison of regional brain glucose metabolism between obese (Ob) and normal weight subjects revealed that even without FS, Ob subjects had significantly higher metabolism in the parietal somatosensory cortex where the lips and tongue are represented, which was interpreted to reflect increased sensitivity of the regions that process food palatability.7
Studies in laboratory animals have also identified regional activation of the prefrontal cortex,8 amygdala9 and nucleus accumbens10 upon exposure to rewarding food stimuli. Here, we evaluate the regional brain metabolic responses to a food stimulus to assess the brain response to food reinforcers. In parallel, we also evaluated the effects of food restriction and genotype (Zucker Ob vs Zucker lean, Le) to evaluate the interaction between deficits in leptin receptor function and access to food in the response to FS. The Ob Zucker rat (fa/fa) has a leptin receptor deficiency (mutation in the leptin receptor gene) that prevents the expression of the long form of the leptin receptor11 that is mainly responsible for its Ob phenotype. Leptin is an anorexigenic peptide involved in the modulation of food intake and energy balance and as these rats show impaired leptin signaling they become severely Ob by adolescence.12
For this purpose, we used small animal PET (µPET) and FDG and a recently developed automatic method that applies the statistical parametric mapping (SPM) techniques traditionally used to analyze images of the human and the rat brains.13
We hypothesized that (1) the hippocampus and the prefrontal cortex would be engaged in the response to the food stimuli, (2) Ob rats would show a greater activation when exposed to the FS than Le rats and (3) food-restricted animals would have greater activation to the FS than unrestricted animals.
Animals
Male adult Ob Zucker (fa/fa) (N = 20) and Le (N = 20) rats were purchased from Harlan (Indianapolis, IN, USA) and maintained on a 12 h dark/light cycle. Rats were divided into four groups consisting of 10 rats in each group. Specifically (1) Ob rats with unrestricted (U) ad-libitum food access, (2) Ob rats with restricted (R) food access (70% of ad libitum), (3) Le U rats and (4) Le R rats. Rats were housed on a reverse 12 h light/dark cycle with lights off at 0700. All experiments were conducted in conformity with the National Academy of Sciences Guide for the Care and Use of Laboratory Animals14 and Brookhaven National Laboratory Institutional Animal Care and Use Committee protocols.
Behavior assessment: food intake and weight
Rats placed on restricted food access were given a daily amount of food limited to 70% of food levels consumed by similarly aged ad-libitum fed animals. Rats were fed a standard (Purina) laboratory rat chow and food intake was monitored daily at 1500. All rats were weighed every other day.
[18F] FDG scanning protocol
All animals were scanned at 6–7 months of age using FDG, which was synthesized at the Brookhaven National Laboratory Cyclotron. Each animal was fasted for 24 h before the scan. Blood was sampled from either the left or right lateral tail vein and glucose strip measurements were taken (True-Track smart system, CVS) before administration of FDG to ensure expected fasting blood glucose levels. Each animal was scanned twice and each scan was performed 2 weeks apart. Scan 1 was used as a control scan during which each animal received an intraperitoneal injection of approximately 0.8 mCi FDG and was immediately placed in a custom-built cage (50 × 30 × 30 cm), representing a novel environment. The floor and ceiling of the cage were made out of steel mesh. The floor was elevated three inches above the ground so that the olfactory stimulus (5 × 5 cm cotton gauze with bacon scent) could be placed underneath. Each rat was awake during the presentation of the olfactory stimulus for a period of 40 min during the FDG uptake. Rats were then anesthetized with a mixture of ketamine (100 mg kg−1) and xylazine (10 mg kg−1) and placed in a stereotaxic head holder (David Kopf Instruments, Tujunga, CA, USA) in a prone position on the bed of the scanner. Scan 2 occurred 2 weeks later and was the same as scan 1 except that this time each animal was given daily 5 g of cooked bacon for 5 consecutive days prior to the 24 h fasting period. Figure 1 illustrates the sequence of the procedures. Rats in the restricted diet groups were also given the bacon but had this amount subtracted from their daily food amount.
Figure 1
Figure 1
Experimental timeline. Animals were scanned at two time points: (1) before and (2) after exposure to a highly palatable food stimulus (bacon).
MicroPET image acquisition
An R4 µPET tomograph (Concorde CTI, Siemens, Knoxville, TN, USA) was used for FDG µPET imaging. The µPET R4 has a transaxial resolution of 2.0 mm full-width at half maximum, with a field-of-view (FOV) of 11.5 cm. Animals were placed in the center of the FOV and were scanned under a static imaging protocol for 80 min using a ramp filter with cutoff at Nyquist frequency. After scanning, all images were corrected for photon emission. Initially, images were reconstructed using filtered back projection; however, to achieve higher pixel resolution, they were later reconstructed using the OSEM3D/MAP algorithm provided by Concorde CTI.
MRI image acquisitions
Four magnetic resonance imaging (MRI) brain images, (one from each group) were obtained on a 4 T Superconducting Magnet System using the proton-density pulse sequence with TE/TR = 20/2000 ms at 1mm slice thickness (37 total slices). The matrix size was 256 × 256 points at a FOV of 4.0 × 4.0 cm2. Rats were anesthetized with a mixture of ketamine (100 mg kg−1) and xylazine (10 mg kg−1) and placed in a custom in-house designed volume coil.
MicroPET image analysis
To obtain statistical parametric maps from different animals, these studies must be properly co-registered. For this purpose, all the images in the dataset were co-registered to a reference image (manually selected by the user). The registration algorithm makes use of normalized mutual information to find the rigid transformation that co-registers both images, and works in two multiresolution steps: At the first step (lower resolution), the whole reference image is used, whereas at the second step (higher resolution) the reference image is masked in such a way that only those pixels inside the brain are used to compute the cost function. To minimize registration errors, this process was repeated three times, selecting different reference images in every repetition. These three reference images are also registered against each other. Finally, by combining all these geometrical transformations, we can automatically detect any incorrect registration making use of consistency measures.15 Once the whole dataset is properly registered, an FDG PET template image is created by averaging all co-registered images. Ob and Le Zucker rats have very different metabolisms and such differences in metabolism could underlie observed glucose uptake levels. As this posed a potential confound in data interpretation, we assessed the regional metabolic change of each animal relative to its global activity. This prevented the characterization of metabolic changes being attributed to differences in animal metabolism. It also prevented misleading glucose uptake effects due to injected dose and weight differences between animals.
Images were analyzed using the SPM2 software package. Two separate analysis of variance (ANOVA) models were used. The first defined four different groups that corresponded to Ob and Le rats with and without food restriction (U and R) during the baseline condition, and thus examined differences in metabolism between these groups prior to bacon exposure. The second defined the same four groups, examining the difference in the activation patterns between the images obtained prior to and after FS (Scans 2 and 1). Images were subtracted after intensity normalization to 100 by the proportional scaling method. After estimation of the statistical model, an F contrast was applied to reveal the effects of interest. These effects were overlaid on the previously generated MRI brain images to get a more accurate representation of the areas of activation. An uncorrected P-value of 0.001 was used as threshold to determine statistical significance for both ANOVA models.
Body weight and food intake
A one-way ANOVA revealed significant main effects in body weight (F = 24.44; DF = 3, 99; P < 0.004). Ob U rats showed significantly greater weight than Le R (t = 8.42; P < 0.001), Le U (t = 5.57; P < 0.001) and Ob R (t = 4.69; P < 0.001). Similarly, Le U and Ob R showed significantly greater weight compared to Le R, (t = 2.85; P = 0.0054) and (t = 3.72; P < 0.001), respectively). Mean weights for all groups were Ob U, 725.02 ± 13.7 g; Le U, 470.66 ± 4.09 g; Ob R, 527.15 ± 15.5 g; Le R, 326.36 ± 4.31 g) (Figure 2a).
Figure 2
Figure 2
(a) Weekly mean (±s.e.m.) body weight (g) in obese unrestricted (Ob U), lean unrestricted (Le U), obese restricted (Ob R) and lean restricted (Le R) rats from 4 to 28 weeks of age. (b) Weekly mean (±s.e.m.) food intake (g) in Ob U and (more ...)
A one-way ANOVA showed significant main effects (F = 96.97; DF = 1, 49; P < 0.001) for food intake. Ob rats had higher food intake levels compared to Le (t = 9.85; P < 0.001). Ob rats consumed on average an additional 8 g of food per day than Le U rats (34% more) (Figure 2b).
FDG brain µPET image analysis
Differences in metabolism prior to FS between obese and lean and restricted and unrestricted
Le U rats showed the greater metabolic activation in the occipital cortex when compared to the other groups (Figure 3a; Table 1). No significant differences were found between the other groups.
Figure 3
Figure 3
Representative statistical parametric mapping (SPM) images co-registered to magnetic resonance imaging (MRI) and generated with the two analysis of variance (ANOVA) models described above. Images were fused using the Amide v. 0.8.15 software package. (more ...)
Table 1
Table 1
Greatest regional brain metabolic activation: baseline effects
Differences in metabolism induced by FS across the groups
The SPM activation results for the two-way ANOVA are shown in Figure 3b. FS resulted in significant deactivation of right and left hippocampus and of a region where the superior colliculus is located. These effects were significant in the Ob R and in the Le U animals but not in the Ob U and in the Le R (Table 2, Figure 4a).
Table 2
Table 2
Greatest regional brain metabolic activation: interaction effects of strain and diet
Figure 4
Figure 4
(a) Two-way analysis of variance (ANOVA) pair-wise interaction effects. Regional percent metabolic change (food stimulation-baseline scan) relative to the global value. The y axis shows the difference between food stimulation and the baseline scan in (more ...)
Overall the magnitude of the changes was greater in Ob than in lean subjects (Figure 4b). The effects were significant in left hippocampus, frontal cortex, medial thalamus and in a region where the superior colliculus is located (Table 3, Figure 4b). In Ob animals, deactivation of the left hippocampus and activation of the medial thalamus were significantly greater than in lean animals. Also Ob animals but not the lean animals showed deactivation in the frontal cortex whereas the Ob animals showed activation in the area of the superior colliculus, the lean ones showed deactivation.
Table 3
Table 3
Greatest regional brain metabolic activation: effects of strain
Differences in the changes induced by FS between restricted and unrestricted animals
Overall, the magnitude of the changes was greater in restricted than in unrestricted animals. The restricted animals had significantly greater activation in right and left olfactory nucleus, medial thalamus and right hippocampus. In contrast, unrestricted animals showed greater activation in the insular/parietal cortex and in the olfactory bulb (Table 4, Figure 4c). The interaction by food access conditions revealed an opposite pattern of metabolic changes in these regions. The left and right olfactory nucleus were deactivated in the unrestricted but activated in the restricted animals; the olfactory bulb, the right insular cortex and the right parietal cortex were activated in the unrestricted but deactivated in the restricted animals. In addition in restricted but not in unrestricted conditioning activated medial thalamus and right hippocampus (Figure 4c).
Table 4
Table 4
Greatest regional brain metabolic activation: effects of diet
Brain glucose utilization
Our results showed significant changes in several brain regions that have been associated with responses to food or food-related stimuli in clinical and preclinical studies upon exposure to a familiar olfactory food stimulus (Figures 4a, b and c). Among these, the hippocampus, superior colliculus and occipital cortex showed the most significant metabolic change. Other regions that showed significant changes included the olfactory bulb, anterior olfactory nucleus, medial thalamus, frontal cortex, insula and somatosensory parietal cortex. Overall, the lateralized response to the food stimuli in the Le U rats (right > deactivation than left) is reminiscent of the lateralized responses to food stimuli reported in the human brain.16 Both, food access and genotype significantly affected pattern of responses to the conditioned food stimulus, and greatest differences were observed in hippocampus, superior colliculus and occipital cortex.
Hippocampus
Exposure to the bacon stimulus resulted in a significant decrease in metabolism in the hippocampus in Ob U (26 and 27% in right and left hippocampus, respectively) and an even greater response in Le U rats (74 and 38% in right and left hippocampus, respectively) when compared with the baseline condition. The greater response of the hippocampus in the Le U than in the Ob U may possibly reflect the effects of leptin in modulating responses to familiar food stimuli. Indeed, the hippocampus expresses large concentrations of leptin receptors17 and leptin modulates the excitability of hippocampal neurons18 facilitating learning.19 There are several reports of volumetric and cell density differences between the left and right hippocampus (reviewed in Lister et al.20) but the significance of this lateralization as it relates to food stimuli is unclear.
Food restriction in the Ob rats accentuated the decrease in hippocampal metabolism between the two scans. Specifically, Ob R rats showed a respective decrease of 95 and 110% in right and left hippocampus (compared to 26 and 27% in Ob U) (Figure 4a). The accentuated decrease in hippocampal activity observed in Ob R rats compared to their ad-libitum counterparts may reflect an adaptation to compensate for unmet food intake requirements imposed by the food restriction. In contrast in the Le rats, food restriction decreased the differences between FS and baseline showing a 2% increase and a 10% decrease in right and left hippocampus (compared to decreases of 74 and 38% in Le U) (Figure 4a; Table 2). The small difference in the hippocampal response between FS and baseline in the Le R rats in contrast to the large response in the Ob R suggests that the hippocampus is a key structure in processing food stimuli and that leptin is one of the signals that modulates this response as a function of access to food. Therefore, there is increasing evidence of importance of leptin in processing food stimuli.21 Evidence of hippocampal involvement in food-related behaviors has also been reported. To start with, the neuroanatomical connections of the hippocampus allow it to receive information from areas of the brain involved in satiety and hunger signals including the arcuate nucleus in the hypothalamus,22 the nucleus tractus solitarius, which receives afferents from the vagus23 that are thought to regulate food intake24 and from the insula, which processes internal perception of hunger signals25 and in concert with the hippocampus is thought to be involved in novel taste learning.26 Furthermore, the hippocampus is directly linked to the nucleus accumbens which is a brain region involved in reward.27 The hippocampus in addition to leptin receptors also expresses receptors for other neuropeptides involved in regulating food intake such as insulin and cholecystokinin,28 and finally, two recent clinical studies showed that gastric stimulation and distention activated the hippocampus.29,30 This suggests the possibility of functionally relevant connections between peripheral organs that is important in food-intake regulation such as the stomach and the hippocampus.
In birds, hippocampal size is positively correlated with food-hoarding behavior,31 possibly through spatial memory function (remembering the location of food hoards).31 In humans and rodents, normal hippocampal function is implicated in memories of food or of the rewarding consequences of eating.32 If this function is disturbed, these memories and the environmental cues that retrieve them, may have increased power to evoke appetitive responses that are instrumental in obtaining and consuming food.32 Indeed, impaired hippocampal functioning in rats has been linked to a reduction in the ability to use information provided by interoceptive energy state signals, an increase in appetitive behavior, food intake, weight gain, as well as heightened general behavioral activity in environments that are strongly associated with food.32 Leptin receptors in the hippocampus appear to be involved in memory function;17 direct administration of leptin into the hippocampus facilitates long-term potentiation and improves memory processing in mice.33 Insulin receptors are also expressed in large concentrations in the hippocampus and are believed to be involved in memory function, possibly through their regulation of glucose transport.34 Accordingly, glucose administration improves memory in both humans and animals.35 Finally, obesity and obesity-related diabetes mellitus are both associated with leptin and insulin resistance as well as memory impairment,36 and Ob Zucker rats, which are both leptin receptor deficient and insulin resistant, have been found to have impaired spatial learning and memory.36 Our results suggest that the Ob Zucker rat in addition to impairment of spatial memory36 may also have impairments in conditioned learning, which involves a different type of memory.37 The responses to FS in the Ob Zucker rats differed in hippocampus, which suggests that abnormal leptin receptor function underlie these changes. To our knowledge, there are no published behavioral studies on conditioning responses in Zucker rats. On the basis of our findings, we hypothesize that conditioning responses to food and also others reinforcers may be disrupted in Ob Zucker rats.
Superior colliculus
There were significant differences in metabolism between FS and baseline in the superior colliculus between the groups. Specifically, Ob U and Le R rats showed a respective decrease of 5 and 10% of global activity between FS and baseline conditions whereas Ob R and Le U rats showed a decrease of 67 and 70%, respectively (Figure 4a; Table 2). In Ob rats, food restriction accentuated the decrease in the superior colliculus observed in adlibitum-fed Ob rats, while in Le rats the metabolic response was attenuated by food restriction. It is unclear as to why we see such a differential pattern in the response of the superior colliculus between the two strains. The superior colliculus receives projections from retinal ganglion cells, the primary visual cortex and also shares a direct projection with the substantia nigra.38 Some have argued that the superior colliculus is the decision center for reactions to novel, salient and/or moving stimuli in the peripheral visual field.38 Specifically, its functions have been described to include the detection and localization of stimuli,39 as well as the organization of orienting reactions toward or away from such stimuli.39 Other studies point to an involvement of the superior colliculus in multisensory integration.40 That is, the outer layers of the superior colliculus are primarily associated with the detection of visual stimuli while deeper layers involve the detection of combinations of visual, tactile and auditory stimuli.40 Thus, the limited spatial memory performance reported in Ob Zucker rats could reflect not only deficits in learning and memory (hippocampus) but also impaired visuospatial detection and disrupted ability for detecting salient stimuli (superior colliculus).
The following are limitations of this study: (1) here we report on relative and not on absolute metabolic measures. This precludes us from assessing potential differences in regional metabolism at baseline between strains. Nonetheless, this method highlights regional differences in brain responses. (2) The limited spatial resolution of our in-vivo imaging approach does not allow us to assess within the hippocampus the regions that may be most affected by food deprivation condition or genotype. (3) In this study, we did not evaluate brain activation in response to unconditioned FS (rats receiving the olfactory stimulus for the first time) and therefore we cannot exclude the possibility that the difference in the responses between the experimental groups are affected by this.
Here we show that food stimuli generate robust activation responses in the rodent brain that are influenced by access to food and leptin receptor function. The differences were most prominent in the hippocampus, a brain region that is increasingly being recognized important in food behaviors, and the superior colliculus that appears to modulate the saliency value of reinforcers and is therefore likely to mediate the enhanced value of food reinforcers as a function of deprivation. These findings have therapeutic implications as they suggest that interventions to restrict food access are likely to have different responses as functions of genetic diversity and that a better understanding of this interaction is likely to lead to tailored interventions that maximize success in weight gain regimes.
Acknowledgements
This work was supported by the NIAAA Intramural Research Program (AA 11034 and AA07574, AA07611) and by the US Department of Energy under contract DE-AC02-98CH10886.
1. Rohner-Jeanrenaud F, Jeanrenaud B. The discovery of leptin and its impact in the understanding of obesity. Eur J Endocrinol. 1996;135:649–650. [PubMed]
2. Levitsky DA. The non-regulation of food intake in humans: hope for reversing the epidemic of obesity. Physiol Behav. 2005;86:623–632. [PubMed]
3. Schwartz M, Woods S, Porte DJ, Seeley R, Baskin D. Central nervous system control of food intake. Nature. 2000;404:661–671. [PubMed]
4. Wang GJ, Volkow ND, Thanos PK, Fowler JS. Similarity between obesity and drug addiction as assessed by neurofunctional imaging: a concept review. J Addict Dis. 2004;23:39–53. [PubMed]
5. Patel KA, Schlundt DG. Impact of moods and social context on eating behavior. Appetite. 2001;36:111–118. [PubMed]
6. Arana FS, Parkinson JA, Hinton E, Holland AJ, Owen AM, Roberts AC. Dissociable contributions of the human amygdala and orbitofrontal cortex to incentive motivation and goal selection. J Neurosci. 2003;23:9632–9638. [PubMed]
7. Wang GJ, Volkow ND, Felder C, Fowler JS, Levy AV, Pappas NR, et al. Enhanced resting activity of the oral somatosensory cortex in obese subjects. Neuroreport. 2002;13:1151–1155. [PubMed]
8. Bassareo V, Di Chiara G. Differential responsiveness of dopamine transmission to food-stimuli in nucleus accumbens shell/core compartments. Neuroscience. 1999;89:637–641. [PubMed]
9. Pomonis JD, Jewett DC, Kotz CM, Briggs JE, Billington CJ, Levine AS. Sucrose consumption increases naloxone-induced c-Fos immunoreactivity in limbic forebrain. Am J Physiol Regul Integr Comp Physiol. 2000;278:R712–R719. [PubMed]
10. Berridge KC, Robinson TE. Parsing reward. Trends Neurosci. 2003;26:507–513. [PubMed]
11. Phillips MS, Liu Q, Hammond HA, Dugan V, Hey PJ, Caskey CJ, et al. Leptin receptor missense mutation in the fatty Zucker rat. Nat Genet. 1996;13:18–19. [PubMed]
12. York DA, Godbole V. Effect of adrenalectomy on obese ‘fatty’ rats. Horm Metab Res. 1979;11:646. [PubMed]
13. Soto M, Vaquero J, Pascau J, Gispert J, Desco M. Validation of SPM analysis of visual activation in rat brain PET studies. Mol Imaging Biol. 2004;6:78.
14. NAS, NRC. Guide for the Care and Use of Laboratory Animals. Washington DC: National Academy Press; 1996.
15. Woods RP, Grafton ST, Holmes CJ, Cherry SR, Mazziotta JC. Automated image registration: I. general methods and intrasubject, intramodality validation. J Comput Assist Tomogr. 1998;22:139–152. [PubMed]
16. Wang GJ, Volkow ND, Telang F, Jayne M, Ma J, Rao M, et al. Exposure to appetitive food stimuli markedly activates the human brain. Neuroimage. 2004;21:1790–1797. [PubMed]
17. Li XL, Aou S, Oomura Y, Hori N, Fukunaga K, Hori T. Impairment of long-term potentiation and spatial memory in leptin receptor-deficient rodents. Neuroscience. 2002;113:607–615. [PubMed]
18. Harvey J. Leptin: a diverse regulator of neuronal function. J Neurochem. 2007;100:307–313. [PMC free article] [PubMed]
19. Oomura Y, Hori N, Shiraishi T, Fukunaga K, Takeda H, Tsuji M, et al. Leptin facilitates learning and memory performance and enhances hippocampal CA1 long-term potentiation and CaMK II phosphorylation in rats. Peptides. 2006;27:2738–2749. [PubMed]
20. Lister JP, Tonkiss J, Blatt GJ, Kemper TL, DeBassio WA, Galler JR, et al. Asymmetry of neuron numbers in the hippocampal formation of prenatally malnourished and normally nourished rats: a stereological investigation. Hippocampus. 2006;16:946–958. [PubMed]
21. Baicy K, London ED, Monterosso J, Wong ML, Delibasi T, Sharma A, et al. Leptin replacement alters brain response to food cues in genetically leptin-deficient adults. Proc Natl Acad Sci USA. 2007;104:18276–18279. [PubMed]
22. Hoebel BG. Neuroscience and appetitive behavior research: 25 years. Appetite. 1997;29:119–133. [PubMed]
23. Ritter S. Multiple metabolic controls of feeding. Appetite. 1994;23:199. [PubMed]
24. Travers JB, Travers SP, Norgren R. Gustatory neural processing in the hindbrain. Annu Rev Neurosci. 1987;10:595–632. [PubMed]
25. Cameron OG. Interoception: the inside story—a model for psychosomatic processes. Psychosom Med. 2001;63:697–710. [PubMed]
26. Yefet K, Merhav M, Kuulmann-Vander S, Elkobi A, Belelovsky K, Jacobson-Pick S, et al. Different signal transduction cascades are activated simultaneously in the rat insular cortex and hippocampus following novel taste learning. Eur J Neurosci. 2006;24:1434–1442. [PubMed]
27. Berthoud HR. Neural systems controlling food intake and energy balance in the modern world. Curr Opin Clin Nutr Metab Care. 2003;6:615–620. [PubMed]
28. Benedict L, Nelson CA, Schunk E, Sullwold K, Seaquist ER. Effect of insulin on the brain activity obtained during visual and memory tasks in healthy human subjects. Neuroendocrinology. 2006;83:20–26. [PubMed]
29. Wang GJ, Yang J, Volkow ND, Telang F, Ma Y, Zhu W, et al. Gastric stimulation in obese subjects activates the hippocampus and other regions involved in brain reward circuitry. Proc Natl Acad Sci USA. 2006;103:15641–15645. [PubMed]
30. Wang GJ, Tomasi D, Backus W, Wang R, Telang F, Geliebter A, et al. Gastric distention activates satiety circuitry in the human brain. Neuroimage. 2008;39:1824–1831. [PubMed]
31. Healy SD, de Kort SR, Clayton NS. The hippocampus, spatial memory and food hoarding: a puzzle revisited. Trends Ecol Evol. 2005;20:17–22. [PubMed]
32. Davidson TL, Kanoski SE, Walls EK, Jarrard LE. Memory inhibition and energy regulation. Physiol Behav. 2005;86:731–746. [PubMed]
33. Farr SA, Banks WA, Uezu K, Gaskin FS, Morley JE. DHEAS improves learning and memory in aged SAMP8 mice but not in diabetic mice. Life Sci. 2004;75:2775–2785. [PubMed]
34. Biessels GJ, Bravenboer B, Gispen WH. Glucose, insulin and the brain: modulation of cognition and synaptic plasticity in health and disease: a preface. Eur J Pharmacol. 2004;490:1–4. [PubMed]
35. Messier C. Glucose improvement of memory: a review. Eur J Pharmacol. 2004;490:33–57. [PubMed]
36. Winocur G, Greenwood CE, Piroli GG, Grillo CA, Reznikov LR, Reagan LP, et al. Memory impairment in obese Zucker rats: an investigation of cognitive function in an animal model of insulin resistance and obesity. Behav Neurosci. 2005;119:1389–1395. [PubMed]
37. Shen F, Meredith GE, Napier TC. Amphetamine-induced place preference and conditioned motor sensitization requires activation of tyrosine kinase receptors in the hippocampus. J Neurosci. 2006;26:11041–11051. [PubMed]
38. Comoli E, Coizet V, Boyes J, Bolam JP, Canteras NS, Quirk RH, et al. A direct projection from superior colliculus to substantia nigra for detecting salient visual events. Nat Neurosci. 2003;6:974–980. [PubMed]
39. Boulenguez P, Foreman N, Chauveau J, Segu L, Buhot MC. Distractibility and locomotor activity in rat following intra-collicular injection of a serotonin 1B-1D agonist. Behav brain res. 1995;67:229–239. [PubMed]
40. Holmes NP, Spence C. Multisensory integration: space, time and superadditivity. Curr Biol. 2005;15:R762–R764. [PMC free article] [PubMed]