INTRODUCTION

The mammalian gustatory system participates in the detection and discrimination of intraoral stimuli, allowing for the selection of nutrients and rejection of toxic compounds. However, the sensory percept of a substance that is placed in the mouth does not depend solely on its taste. The olfactory and somatosensory systems discriminate odor, texture, and temperature, which participate, with taste, in the unitary perception of flavor (Small and Prescott 2005). Flavor is a central contributor in the decision making relative to ingestive behavior. However, feeding decisions are made in specific physiological contexts and, therefore, are not entirely dependent on sensory experience. We know today that the central nervous system (CNS) detects a multitude of peripheral neural and humoral signals that reflect gastrointestinal status and current energy needs, availability, and stores (Broberger 2005). The regulation of energy homeostasis and maintenance of stable body weight depend on the integration of these signals and the ability to respond adequately through the modulation of both energy expenditure and food intake (Schwartz and Porte 2005).

The appearance and familiarity of a particular food, given the memory of the orosensory, olfactory, and postingestive (Garcia, Kimeldorf et al. 1955; Sclafani 2004) effects of previously encountered identical or similar substances, will also influence the decision of ingestion, as will emotional, cognitive, and social factors (Wilson 2002). These observations underline that, when trying to understand food seeking, one should consider not only sensory and homeostatic factors but others such as emotional processing, learning and decision making (Balleine 2005; Kelley, Baldo et al. 2005).

Data obtained by recording neural ensemble activity in awake animals has demonstrated not only that neural populations distributed across several cortical and subcortical brain areas can encode the multisensory properties of intraoral stimuli but also that this coding is modulated by physiological state (de Araujo, Gutierrez et al. 2006; Fontanini and Katz 2006; Gutierrez, Carmena et al. 2006; Stapleton, Lavine et al. 2006). Consequently, it has been proposed that gustatory processing must be considered in a multimodal perspective, combining taste with the several other sensory and homeostatic processes that occur in association with taste receptor activation (Jones, Fontanini et al. 2006; Simon, de Araujo et al. 2006). According to this view, gustation results from a distributed neural process by which information conveyed to the brain through specialized taste, and oral somatosensory, olfactory, and gastrointestinal fibers is integrated with humoral signals, allowing the organism to feed in accordance with the maintenance of adequate energy homeostasis, and participating with complex neural circuits of affective and cognitive processing to organize ingestive behavior.

In our laboratories at Duke University, experimental work is directed to further understand the neural mechanisms of gustation in order to contribute towards a better comprehension of dysfunctional feeding behavior, especially as it relates to hyperphagia and obesity. In this chapter we will describe the methodology currently in use in our laboratories to perform neural ensemble recordings from the gustatory-reward system of awake and freely licking mice and rats, as well as other associated measures performed simultaneously or in parallel to neural recordings.

BACKGROUND: PERIPHERAL GUSTATORY SYSTEM

The peripheral gustatory system extracts multisensory information from foods placed in the mouth, and conveys this information through multiple neural pathways to brainstem structures (Kawamura, Okamoto et al. 1968). Taste receptor cells (TRCs) are responsive to the type and quantity of chemicals dissolved in saliva and allow for the detection of the five primary taste qualities: salt, sweet, bitter, umami (savory taste of amino acids), and sour (acidic) (Spector and Travers 2005). Information about most relatively water-insoluble compounds, as well as food texture, weight and temperature, is primarily transduced by specialized somatosensory neurons with endings distributed throughout the oral epithelia (Halata and Munger 1983).

In vertebrates, TRCs are found in specialized microscopic taste receptor organs—the taste buds (Figure 10.1B). Mammalian taste buds are onion-shaped cell clusters that are embedded at the surface of several intraoral structures, mainly the palate and tongue, where they cluster at macroscopic structures named gustatory papillae (Miller 1995).

FIGURE 10.1

(see facing page) (See color insert following page 140.) Illustration of a taste bud, taste receptor cell, and associated neurons. A. Diagram of a TRC and respective synapse with a primary gustatory neuron. Several receptors and transduction pathways (more...)

TRCs extend towards the bud pore where they present microvillar processes to contact with sapid chemical stimuli in the oral cavity. Taste receptors are transmembrane structures found on these microvilli and are the basis for the chemosensory properties of TRCs since, upon detection of a specific stimulus, they will activate intracellular transduction cascades to initiate the process of gustatory neural signaling (Margolskee 2002; Scott 2005) (Figure 10.1A).

Proteins belonging to the G-protein-coupled receptor (GPCR) superfamily have been established as receptors for sweet tastants (heterodimeric T1R2/T1R3 receptors), amino acids (heterodimeric T1R1/T1R3 receptors), and bitter (T2R receptors) tastants (Chandrashekar, Hoon et al. 2006). The predominant downstream signaling pathways for these receptors require two common elements: TRPM5, a transient receptor potential ion channel, and PLCß2, a phospholipase C (Zhang, Hoon et al. 2003). Sour and salt taste qualities seem to rely on a different set of receptors and signaling pathways (Zhang, Hoon et al. 2003; Chandrashekar, Hoon et al. 2006). Recently, a member of the TRP ion channel family, the polycystic-kidney-disease-like ion channel PKD2L1, was shown to be necessary for sour taste transduction (Huang, Chen et al. 2006; Ishimaru, Inada et al. 2006; LopezJimenez, Cavenagh et al. 2006). Although the molecular mechanisms for salt taste are more controversial (Chandrashekar, Hoon et al. 2006), in rodents, an amiloride-sensitive sodium channel, ENaC, accounts for part of the transduction of salt (NaCl) (Heck, Mierson et al. 1984).

In regard to sweet, bitter, umami, and sour, recent evidence has suggested that the taste receptors for each of these four taste qualities are present in largely segregated populations of cells (Nelson, Hoon et al. 2001; Zhang, Hoon et al. 2003; Huang, Chen et al. 2006). Additionally, perception of a particular taste quality, more than the property of a specific tastant–taste receptor interaction, seems to reflect the selective activation of the TRC population expressing a particular taste receptor that is, in itself, sufficient to generate specific behavioral programs (Zhao, Zhang et al. 2003; Mueller, Hoon et al. 2005). It therefore seems clear that, at the TRC level, sweet, bitter, umami, and sour taste pathways are segregated (Figure 10.1B). This does not imply that this labeled-line model is also true for the CNS, where most data supports the occurrence of multisensory and distributed gustatory processing.

TRCs are not neurons and do not have specialized processes for signal transmission to the CNS. The TRC generates action potentials in response to tastant detection, and this activity is transmitted to primary sensory neurons that innervate taste buds and transmit information centrally to the solitary tract nucleus (NTS) of the medulla (Scott 2005) (Figure 10.1B). Taste buds are innervated by primary sensory neurons from branches of the facial (VII), glossopharyngeal (IX), and vagal (X) cranial nerves. The chorda tympani and greater superior petrosal branches of the facial nerve carry sensory axons of cells in the geniculate ganglion and innervate taste buds, respectively, in the anterior tongue and palate. Sensory axons of the glossopharyngeal nerve, with cell bodies in the petrosal ganglion, terminate in taste buds in the posterior tongue (lingual branch) and pharynx (pharyngeal branch). The nodose ganglion of the vagus nerve contains primary gustatory neurons with axons that integrate the pharyngeal, superior laryngeal, and internal laryngeal branch of the vagus nerve to innervate taste buds in the epiglottis, larynx, and esophagus (Miller 1995).

The glossopharyngeal and vagal nerves also carry general sensory nerve fibers for the oral and upper digestive mucosa, as does the trigeminal (V) cranial nerve (Matsumoto, Emori et al. 2001; Grundy 2006), allowing for the transduction of information relating to the temperature and texture of ingested stimuli (Halata and Munger 1983). Some intraoral somatosensory nerve endings can also be activated by high concentrations of the same chemical stimuli that define some primary tastants, such as NaCl (Wang, Erickson et al. 1993; Carstens, Kuenzler et al. 1998), usually producing irritating sensations. Oral mucosa nerve endings may also have other chemosensing properties, as exemplified by the responses of the thermosensitive TRPV1 and TRPM8 channels, respectively, to capsaicin (found in chilli peppers) (Liu and Simon 1996), producing a burning sensation, and menthol (Chuang, Neuhausser et al. 2004), producing a cooling sensation. It thus becomes clear that, even at the periphery, input to the gustatory system is inherently multisensory.

CENTRAL GUSTATORY-REWARD NEURAL PATHWAYS

Chemosensory information, derived from all taste-responsive cranial nerves, converges on the rostral division of the nucleus tractus solitarius (rNTS) (Hamilton and Norgren 1984). Trigeminal somatosensory inputs from oral branches of the fifth nerve also project to regions of NTS innervated by gustatory nerves (Hamilton and Norgren 1984). A second subdivision of the nucleus, the caudal NTS (cNTS), is the main target of visceral (vagal) afferent inputs that convey information on the physiological status of the gastrointestinal (GI) system (Travagli, Hermann et al. 2006). Trigeminal stimulants with irritating effects can modulate taste responses in the rNTS (Simons, Boucher et al. 2003; Simons, Boucher et al. 2006), as does afferent vagal activity, such as that produced by gastric distention (Glenn and Erickson 1976). The rNTS is also a target of descending forebrain projections from the gustatory cortex (GC), prefrontal cortex, central nucleus of the amygdala (AMYce), lateral hypothalamus (LH), bed nucleus of the stria terminalis and substancia innominata (van der Kooy, Koda et al. 1984; Di Lorenzo and Monroe 1995; Smith and Li 2000; Whitehead, Bergula et al. 2000). The NTS thus offers the first opportunity for neural signals derived from the somatosensory and GI systems and other CNS nuclei to modulate incoming taste information.

In rodents, ascending neural pathways from the NTS include an obligatory synapse in the ipsilateral pontine parabrachial nucleus (PBN) (Norgren 1984). Similarly to the rNTS, the PBN is a target of descending forebrain projections, and taste-responsive neurons in this location have been shown to be modulated by electrical stimulation of forebrain sites (Di Lorenzo 1990; Lundy and Norgren 2004; Tokita, Karadi et al. 2004; Li, Cho et al. 2005).

From the PBN, third-order neurons project to several forebrain systems, forming two gustatory projection systems (Norgren and Leonard 1973). The thalamocortical system, with synapse in the parvicellular part of the ventral posteromedial (VPMpc) nucleus of the thalamus, terminates in the GC. The ventral forebrain system includes PBN projections to several structures in the limbic forebrain, namely the LH and AMYce (Norgren and Leonard 1973; Norgren 1976), thus establishing a subcortical loop between brainstem primary gustatory areas and motivational and reinforcement-related areas in the ventral forebrain, such as the mesolimbic dopaminergic system (Norgren, Hajnal et al. 2006). Note that, in primates, including humans, rNTS projection fibers have not been shown to terminate in the PBN and synapse directly in the VMPpc (Pritchard, Hamilton et al. 2000).

In macaques the primary GC, as defined by VPMpc efferent projections (Scott and Plata-Salaman 1999), corresponds to the frontal operculum and adjoining insula (Pritchard, Hamilton et al. 1986). VPMpc also projects to the primary somatosensory cortex (Jain, Qi et al. 2001), suggesting a further point of convergence between taste and somatosensory stimuli. The caudolateral orbitofrontal cortex (OFC), sometimes defined as a secondary taste cortical area (Rolls, Yaxley et al. 1990), receives converging projections from the GC and primary olfactory cortex, relevant to the perception of flavor (Small and Prescott 2005) (Figure 10.2).

FIGURE 10.2

(See color insert following page 140.) Anatomy of the principal central gustatory pathways. Taste-specific information is conveyed by cranial nerves VII, IX, and X (blue lines) to the rNTS (rostral division of the nucleus tractus solitarius) in the medulla. (more...)

SIMULTANEOUS RECORDINGS OF MULTIPLE SINGLE NEURONS IN AWAKE AND BEHAVING RODENTS

From the previous discussion, it is evident that eating is an active and multisensory process that involves the integration of sensory, hedonic, and motor pathways. Despite this knowledge, most studies of gustatory processing from animals, especially rodents, have used recordings from anesthetized preparations in which tastants are delivered for several seconds. In such preparations, motor, motivational, and postingestive effects are avoided and, if there is continuous stimulus flow, somatosensory input of mechanical and thermal input is adapted and hence controlled. At higher multisensory cortical and subcortical structures, these inputs contribute significantly to the neural events associated with eating and, to adequately understand the distributed neural processes involved in the control of ingestive behavior, they must be considered (Simon, de Araujo et al. 2006). Additionally, most anesthetics depress cortical neurons (Burke, Bartley et al. 2000), and their administration is accompanied by hyperglycemia (Taylor and Howard 1971), which has been shown to have an effect on neural responses to tastants (Rolls, Sienkiewicz et al. 1989). The use of anesthetized preparations is therefore an important limitation, especially because certain findings have been shown to differ from observations in awake animals (Nishijo, Uwano et al. 1998).

Throughout the development of electrophysiological techniques to probe the CNS, recording single units has yielded valuable information for all sensory systems, including taste (Rolls 2006). However, single unit recordings are of limited duration (up to hours), are confined to a single area, and allow for the recording of only a small sample of single neurons in each session. Even if multiple neurons are recorded in every animal, they are never recorded simultaneously. Consequently, the concatenation of neurons to form ensembles that, as we shall see, provide more information than single neurons, cannot readily be constructed, and conclusions about distributed coding processes are highly limited (Super and Roelfsema 2005).

The limitations just mentioned in the study of CNS neurophysiology motivated efforts towards the development of techniques that would allow simultaneous recordings of multiple single neurons in awake and behaving animals, chronically implanted in one or more brain areas. Indeed this has been shown to be possible in rats (Nicolelis, Lin et al. 1993; Nicolelis, Baccala et al. 1995; Nicolelis, Fanselow et al. 1997), nonhuman primates (Nicolelis, Ghazanfar et al. 1998; Kralik, Dimitrov et al. 2001; Nicolelis, Dimitrov et al. 2003), and mice (Costa, Cohen et al. 2004; Costa, Lin et al. 2006; Dzirasa, Ribeiro et al. 2006).

In the gustatory system, the first application of these techniques to the study of gustatory processing was performed at Duke University by Katz et al (Katz, Simon et al. 2001). In this initial study, ensembles of neurons were recorded from the GC of rats trained to press a lever in order to receive tastants through an intraoral cannula. As will be described bellow, over the past five years, the techniques used in this initial study have been revised and refined in our laboratories. Thus, we are currently capable of recording from neuronal ensembles in multiple areas of the brains of both rats and mice while they freely lick a sipper to obtain a liquid stimulus (de Araujo, Gutierrez et al. 2006; Gutierrez, Carmena et al. 2006; Stapleton, Lavine et al. 2006).

Methods for Chronic Implantation of Multiple Microwires

Initially, mice are anesthetized using 5% isoflurane, followed by an intramuscular injection of a mixture of xylazine and ketamine (5 mg/kg and 75 mg/kg). In rats, following isoflurane, an intraperitoneal injection of sodium pentobarbital (50 mg/kg) or xylazine and ketamine (10 mg/kg and 100 mg/kg, respectively) is administered, and 0.1 mL atropine sulfate (0.4 mg/mL) is given subcutaneously. Supplemental doses are administered throughout surgery whenever necessary.

Following adequate anesthesia, the animals are placed in a standard stereotaxic frame (David Kopf Instruments, Tujunga, California) and surgery is initiated, using approved aseptic techniques. One or more craniotomies are drilled, according to the desired target sites, as defined by available brain stereotaxic atlases (Paxinos and Watson 1998; Paxinos and Franklin 2001) and other supporting literature. Three or four stainless steel support screws are also secured to the skull, and the electrode ground wire is soldered to at least one of the screws. Microwires are then lowered to the desired position at a 100–200 μm/min rate to minimize damage to brain tissue. Once electrodes are in place, areas of exposed cortex or microwire arrays are protected with antibiotic cream, and dental cement is applied to seal the exposed skull surface, supporting screws, and microwire array or bundle.

Multiple microwires are assembled in our laboratory (see chapter 1), in accordance with designs that vary to target the desired structures in either the mouse or rat (Figure 10.3). The S-isonel-coated tungsten microwire electrodes (15, 35, or 50 μm diameter) are connected to a printed circuit board (PCB) and assembled into 16- or 32-wire microarrays or bundles (groups of electrodes in a guiding cannula). A miniature connector is attached to the side of the PCB opposite to the wires. Up to two microwire assemblies have been implanted in both mice and rats. In rats, a maximum of 64 microwires have been implanted in four ipsilateral brain structures in the same rat (GC, OFC, LH, and AMY) (de Araujo, Gutierrez et al. 2006), whereas in other designs, the GC or OFC was targeted bilaterally (Gutierrez, Carmena et al. 2006; Stapleton, Lavine et al. 2006). Simultaneous GC/OFC and GC/OFC/AMY/NucAcb recordings have also been pursued. We have only recently initiated recordings in the mouse and have implanted a maximum of 32 microwires in up to two ipsilateral brain structures (OFC/NucAcb). In most cases, each mouse has been implanted with a single 16-channel microarray in the GC.

FIGURE 10.3

Multiple microwire bundles and arrays and plan for stereotaxic implantation of electrodes. A and B. Magnified photographs of a movable 16-microwire bundle in a cannula, designed for deep structures such as the AMY or LH (A), and a 32-channel microarray, (more...)

Most microwire arrays and bundles implanted in the rat are movable. They are glued to a small microdrive that allows for further dorsoventral electrode mobility after implantation (See chapter 1). This will permit refinement of electrode placement according to neural activity observed in the awake animal (e.g., chemosensory responses) and, furthermore, the recording from several ensembles of neurons across multiple recording sessions in the same animal (previous to each experimental session, arrays and bundles are advanced ~100 to 150 μm into the recorded areas such that a new ensemble will be recorded).

Methods for Histological Confirmation of Electrode’s Tip Placement

In implanted animals, once experiments are completed, the location of microwire implantation is confirmed histologically. The animals are anesthetized with intra-peritoneal sodium pentobarbital (100 mg/kg) and then perfused through the heart with 10% formalin. Once perfused, the animals are decapitated, and their heads, still with electrode arrays, are fixed in a 10% formalin/30% sucrose solution for up to 3 days. This fixation period, particularly important for cortical implants in mice, will prevent large areas of tissue to be lost when the brain is isolated from the skull and electrode arrays are removed. The brain is then cut serially in a cryostat into 60-μm-thick sections that are mounted onto gel-coated slides for cresyl-violet staining and inspection under a microscope. Location of electrode tracts are photographed (Figure 10.4) or mapped on images from reference mouse or rat brain atlases (Paxinos and Watson 1998; Paxinos and Franklin 2001). Data from arrays that are not correctly implanted is excluded from the analyses.

FIGURE 10.4

Histological confirmation of electrode tip placement. 50-μm-thick coronal section taken through the gustatory cortex and stained with cresyl violet. A cannula track, indicated by two arrows, is visible. Terminations of electrodes in dysgranular (more...)

NEURAL ENSEMBLE RECORDINGS IN FREELY LICKING RODENTS

Some bitter tastants, such as strychnine, are poisons and can be lethal if ingested. The decision to ingest or reject a substance that is placed in the mouth must therefore rely on fast mechanisms of stimulus detection and discrimination. Indeed, trained rats have been shown to identify tastants in the timeframe of a single lick cycle (~200 ms) (Halpern and Tapper 1971; Travers, Dinardo et al. 1997). However, most studies of CNS gustatory coding have measured neuronal responses to specific tastants or taste qualities based on average firing rate across several seconds after intraoral stimulus delivery. Such long averages of neuronal firing modulation (in the order of seconds) will probably represent many other parameters, such as hedonics and mouth movements (Katz, Simon et al. 2002). Recently, electrophysiological data collected in freely behaving animals has shed new light on this issue. In accordance with the timing of licking, we have shown that chemosensory-specific information is conveyed by taste-responsive GC neurons within 150 ms of stimulus delivery (Stapleton, Lavine et al. 2006) (Figure 10.5).

FIGURE 10.5

Rapid chemosensitive neuronal responses in the gustatory cortex. Raster plots and peri-stimulus-time histograms (PSTHs) for the responses to multiple stimuli of four different neurons obtained from the same ensemble. Zero on the x-axis denotes the time (more...)

Our current research into gustatory-reward coding in the CNS has been done using neural ensembles recorded from rodents that are freely licking for various tastants (Figure 10.6). We believe that it is important to incorporate the use of licking into studies of gustatory physiology for several reasons:

FIGURE 10.6

Neural ensemble recordings in freely licking rats and mice. A. Design for a custom-made beam lickometer for the mouse. A very thin photo-beam (black dot) is placed between a rectangular aperture, through which the mice can lick, and the sipper such that (more...)

• Licking is a highly rhythmic and stereotypic behavior, during which tastants are most often presented to the same areas of the oral cavity, making responses reproducible across events and sessions. On the contrary, when tastants are delivered through intraoral cannula, the oral surface of exposure to the presented liquid stimulus may vary not only due to differences in the site of cannula placement between animals but also due to lack of control of active oral movements even across events and sessions in the same animal. Thus, the reproducibility of chemosensory and somatosensory responses is lessened.
• Licking allows for a unique methodology of controlling oral somatosensory stimulation: given its stereotypic nature, by having an animal first lick a dry sipper and then lick the same sipper to receive water and/or other tastants, somatosensory responses can be controlled and disambiguated from taste responses (Figure 10.5).
• During tastant delivery through intraoral cannula, time of contact with the oral mucosa is somewhat uncertain. However, when rodents lick a sipper tube, the time of each lick can be accurately measured with 10 ms resolution. Temporal accuracy is important in elucidating gustatory processing because, as already mentioned, animals can detect and identify tastants in a very short time frame and, as we have shown (Stapleton, Lavine et al. 2006), neural responses are both sparse and time locked (Figure 10.7).

FIGURE 10.7

Gustatory cortex neuronal responses are sparse and time locked. Tuning profile of a GC neuron, across several concentrations of five different tastants (see Figure 10.5 for details on symbols). The firing rate of the cell is sparse, and spike trains exhibit (more...)

• Licking is a behavior in which animals engage naturally when they are motivated to drink. This implies that, when licking, the animal is actively focusing on this consummatory activity, an entirely different process than having food delivered to the mouth, as is done when liquids are delivered via intraoral cannula or in anesthetized preparations.
• Measurements of licking can be used as an indirect behavioral index of preference and hunger/satiety. Therefore, when recording licking and electrophysiological events simultaneously and synchronously, neural activity can be correlated not only to purely sensory aspects of the licking task but also to the mentioned hedonic and motivation-related measurements.
• Only small amounts of tastants are delivered in each single-lick cycle. Thus, many behavioral events, each representing a trial, can be obtained such that statistical inferences will have more weight than when only a few trials are obtained for each tastant.

NEURAL CORRELATES OF PREFERENCE, HUNGER, AND SATIETY IN FREELY LICKING RODENTS

In most societies the prevalence of obesity has risen dramatically to reach epidemic proportions. The World Health Organization (http://www.who.int) estimates figures of 1 billion overweight (BMI>25 kg/m²) adults, 30% of these being considered clinically obese (BMI > 30 kg/m²). In the United States alone, a staggering 30% of all adults are obese (Stein and Colditz 2004). Increase in adiposity leads to significant metabolic disregulation (Muoio and Newgard 2006), with important health and economic consequences (Stein and Colditz 2004). Understanding the central mechanisms of food reward and appetite regulation is therefore an important objective in neuroscience research, hopefully allowing a deeper comprehension of obesity and other eating disorders such as anorexia nervosa and bulimia nervosa.

Neural Ensemble Recordings in Taste-Reward Pathways

When a rodent licks for a natural reward, such as water or a palatable and nutritive solution, the licking activity is not continuous, resulting in a temporal distribution of licks into clusters (at least three rhythmic licks with interlick interval <500 ms) separated by pauses in licking 500 ms or longer (Davis and Smith 1992). Unlike licking, which in itself is highly stereotyped and stable, licking clusters reflect the animal’s motivational status such that their number and duration have been shown to vary in accordance with factors such as tastant palatability and satiety onset. In rats freely licking for sucrose and water, we have shown that inactivation of the OFC, a cortical area known to be involved in chemosensory and reward processing, modifies both cluster number and duration (Gutierrez, Carmena et al. 2006). Furthermore, we found that OFC neuronal ensembles can discriminate cluster onset from termination, predict cluster initiation, and distinguish and anticipate between natural rewards (Figure 10.8).

FIGURE 10.8

(See color insert following page 140.) Ensemble activity of OFC neurons discriminates and anticipates natural rewards in the rat. A and B. Color-coded peristimulus time histograms of activity from eight simultaneously recorded orbitofrontal cortex (OFC) (more...)

In another study relating to the characterization of motivational states such as hunger and satiety, we have shown that, by analyzing the activity of neurons recorded simultaneously in the GC, OFC, LH, and AMY (Figure 10.9), the animal’s motivational state, as measured by behavioral parameters obtained from licking bouts, can be accurately predicted (de Araujo, Gutierrez et al. 2006). This work was performed by using food-deprived rats given intermittent access to a high-concentration sucrose solution. We used the latency between self-initiated licking bouts as a measure of the motivation to consume sucrose, thus defining the boundaries between hunger and satiety phases. When the animals were hungry, interbout intervals were short, increasing with the transition to satiety. Blood sampling from rats placed in this paradigm demonstrated that plasma glucose and insulin levels vary significantly across different phases of the feeding cycle (hunger1–satiety1–hunger2, see the following text for details). As expected, both glucose and insulin levels are higher in satiety than in any of the hunger phases, and higher in hunger 2 (when rats return to drinking sucrose after a satiety phase) than hunger 1 (when rats are first exposed to sucrose after a long period of food deprivation) (Figure 10.10). Neural activity was recorded in rats performing this task. A proportion of the single neurons recorded were shown to be satiety modulated, and the majority of these changed their firing rate in a specific single phase of the feeding cycle. These specific responses likely reflect the unique metabolic characteristics of each of the phases, as described in terms of glycemia and insulinemia, but in all probability also integrating variation of other circulating factors, such as cholecystokinin, leptin, and ghrelin. Importantly, we found that neural populations are better at predicting the different internal states of the animal than individual neurons, whose activity may reflect only one phase of the feeding cycle (Figure 10.11).

FIGURE 10.9

Simultaneous multiple single-neuron recordings from the gustatory-reward pathways of awake, behaving, and freely licking rats. Representation of four recording sites and examples of units recorded simultaneously from them during sucrose intake. The upper (more...)

FIGURE 10.10

Behavioral and metabolic analysis of hunger/satiety states. A. Scheme illustrating structure of intermittent sucrose access task. D. Vertical dashed lines—sliding doors are open, giving access to sucrose. Solid vertical lines—doors are (more...)

FIGURE 10.11

(see facing page) (See color insert following page 140.) Coding of hunger and satiety states by neuronal ensembles and single cells. A and B. Example of an experimental session where the population mean firing rate correlated significantly with ITIs. (more...)

CONCLUSIONS

Both environmental (Keith, Redden et al. 2006) and genetic (Mutch and Clement 2006) factors are usually pointed out as culprits of the obesity epidemic. Furthermore, current data suggest that individual susceptibility for the occurrence of obesity is determined not solely by factors influencing metabolic rate or the partitioning of excess calories into fat but also by others related to the neural regulation of hunger, satiety, and food intake (O’Rahilly and Farooqi 2006). Understanding how the CNS regulates feeding behaviors is therefore a central theme in neuroscience research. The central gustatory system, viewed as a distributed brain circuit that integrates peripheral sensory information from multiple sensory modalities with neuroendocrine and gastrointestinal homeostasis-related signals, is a central concept in ingestive behavior research. Thus, we propose that a systems-level approach, integrating neurophysiology from multiple brain areas in awake and freely licking animals with complementary neurochemical or metabolic measurements, is essential to allow for further advances in this field, especially when this approach is used in conjunction with genetic or pharmacologic manipulations.

ACKNOWLEDGMENTS

This work was supported in part by grants DC-01065, and from Philip Morris USA and Philip Morris International Inc., to SAS. AJO-M is a recipient of a GABBA fellowship from FCT (Portugal).

REFERENCES

1. Balleine BW. Neural bases of food-seeking: affect, arousal and reward in corticostriatolimbic circuits. Physiol Behav. 2005;86(5):717–30. [PubMed: 16257019]
2. Broberger C. Brain regulation of food intake and appetite: molecules and networks. J Intern Med. 2005;258(4):301–27. [PubMed: 16164570]
3. Burke D, Bartley K, et al. The effects of a volatile anaesthetic on the excitability of human corticospinal axons. Brain. 2000;123 (Pt. 5):992–1000. [PubMed: 10775543]
4. Carstens E, Kuenzler N, et al. Activation of neurons in rat trigeminal subnucleus caudalis by different irritant chemicals applied to oral or ocular mucosa. J Neurophysiol. 1998;80(2):465–92. [PubMed: 9705444]
5. Chandrashekar J, Hoon MA, et al. The receptors and cells for mammalian taste. Nature. 2006;444(7117):288–94. [PubMed: 17108952]
6. Chuang HH, Neuhausser WM, et al. The super-cooling agent icilin reveals a mechanism of coincidence detection by a temperature-sensitive TRP channel. Neuron. 2004;43(6):859–69. [PubMed: 15363396]
7. Costa RM, Cohen D, et al. Differential corticostriatal plasticity during fast and slow motor skill learning in mice. Curr Biol. 2004;14(13):1124–34. [PubMed: 15242609]
8. Costa RM, Gutierrez R, et al. Dopamine levels modulate the updating of tastant values. Genes Brain Behav. 2007;6(4):314–20. [PubMed: 16848782]
9. Costa RM, Lin SC, et al. Rapid alterations in corticostriatal ensemble coordination during acute dopamine-dependent motor dysfunction. Neuron. 2006;52(2):359–69. [PubMed: 17046697]
10. Davis JD, Smith GP. Analysis of the microstructure of the rhythmic tongue movements of rats ingesting maltose and sucrose solutions. Behav Neurosci. 1992;106(1):217–28. [PubMed: 1554433]
11. de Araujo IE, Gutierrez R, et al. Neural ensemble coding of satiety States. Neuron. 2006;51(4):483–94. [PubMed: 16908413]
12. Di Lorenzo PM. Corticofugal influence on taste responses in the parabrachial pons of the rat. Brain Res. 1990;530(1):73–84. [PubMed: 2271954]
13. Di Lorenzo PM, Hallock RM, et al. Temporal coding of sensation: mimicking taste quality with electrical stimulation of the brain. Behav Neurosci. 2003;117(6):1423–33. [PubMed: 14674860]
14. Di Lorenzo PM, Monroe S. Corticofugal influence on taste responses in the nucleus of the solitary tract in the rat. J Neurophysiol. 1995;74(1):258–72. [PubMed: 7472329]
15. Dzirasa K, Ribeiro S, et al. Dopaminergic control of sleep-wake states. J Neurosci. 2006;26(41):10577–89. [PMC free article: PMC6674686] [PubMed: 17035544]
16. Erlanson-Albertsson C. How palatable food disrupts appetite regulation. Basic Clin Pharmacol Toxicol. 2005;97(2):61–73. [PubMed: 15998351]
17. Fontanini A, Katz DB. State-dependent modulation of time-varying gustatory responses. J Neurophysiol. 2006;96(6):3183–93. [PubMed: 16928791]
18. Fudge JL, Haber SN. The central nucleus of the amygdala projection to dopamine subpopulations in primates. Neuroscience. 2000;97(3):479–94. [PubMed: 10828531]
19. Gainetdinov RR, Fumagalli F, et al. Dopamine transporter is required for in vivo MPTP neurotoxicity: evidence from mice lacking the transporter. J Neurochem. 1997;69(3):1322–5. [PubMed: 9282960]
20. Garcia J, Kimeldorf DJ, et al. Conditioned aversion to saccharin resulting from exposure to gamma radiation. Science. 1955;122(3160):157–8. [PubMed: 14396377]
21. Glendinning JI, Gresack J, et al. A high-throughput screening procedure for identifying mice with aberrant taste and oromotor function. Chem Senses. 2002;27(5):461–74. [PubMed: 12052783]
22. Glenn JF, Erickson RP. Gastric modulation of gustatory afferent activity. Physiol Behav. 1976;(16):561–568. [PubMed: 972948]
23. Grundy D. Signalling the state of the digestive tract. Auton Neurosci. 2006;125(1 and 2):76–80. [PubMed: 16473562]
24. Gutierrez R, Carmena JM, et al. Orbitofrontal ensemble activity monitors licking and distinguishes among natural rewards. J Neurophysiol. 2006;95(1):119–33. [PubMed: 16120664]
25. Hajnal A, Smith GP, et al. Oral sucrose stimulation increases accumbens dopamine in the rat. Am J Physiol Regul Integr Comp Physiol. 2004;286(1):R31–7. [PubMed: 12933362]
26. Halata Z, Munger BL. The sensory innervation of primate facial skin. II Vermilion border and mucosa of lip. Brain Res. 1983;286(1):81–107. [PubMed: 6824957]
27. Halpern BP, Tapper DN. Taste stimuli: quality coding time. Science. 1971;171(977):1256–8. [PubMed: 5545205]
28. Hamilton RB, Norgren R. Central projections of gustatory nerves in the rat. J Comp Neurol. 1984;222(4):560–77. [PubMed: 6199385]
29. Heck GL, Mierson S, et al. Salt taste transduction occurs through an amiloride-sensitive sodium transport pathway. Science. 1984;223(4634):403–5. [PubMed: 6691151]
30. Huang AL, Chen X, et al. The cells and logic for mammalian sour taste detection. Nature. 2006;442(7105):934–8. [PMC free article: PMC1571047] [PubMed: 16929298]
31. Ishimaru Y, Inada H, et al. Transient receptor potential family members PKD1L3 and PKD2L1 form a candidate sour taste receptor. Proc Natl Acad Sci USA. 2006;103(33):12569–74. [PMC free article: PMC1531643] [PubMed: 16891422]
32. Jain N, Qi HX, et al. Anatomic correlates of the face and oral cavity representations in the somatosensory cortical area 3b of monkeys. J Comp Neurol. 2001;429(3):455–68. [PubMed: 11116231]
33. Jones LM, Fontanini A, et al. Gustatory processing: a dynamic systems approach. Curr Opin Neurobiol. 2006;16(4):420–8. [PubMed: 16842991]
34. Jones SR, Gainetdinov RR, et al. Loss of autoreceptor functions in mice lacking the dopamine transporter. Nat Neurosci. 1999;2(7):649–55. [PubMed: 10404198]
35. Katz DB, Simon SA, et al. Dynamic and multimodal responses of gustatory cortical neurons in awake rats. J Neurosci. 2001;21(12):4478–89. [PMC free article: PMC6762775] [PubMed: 11404435]
36. Katz DB, Simon SA, et al. Taste-specific neuronal ensembles in the gustatory cortex of awake rats. J Neurosci. 2002;22(5):1850–7. [PMC free article: PMC6758892] [PubMed: 11880514]
37. Kawamura Y, Okamoto J, et al. A role of oral afferents in aversion to taste solutions. Physiol Behav. 1968;(3):537–542.
38. Keith SW, Redden DT, et al. Putative contributors to the secular increase in obesity: exploring the roads less traveled. Int J Obes (Lond). 2006;30(11):1585–94. [PubMed: 16801930]
39. Kelley AE, Baldo BA, et al. Corticostriatal-hypothalamic circuitry and food motivation: integration of energy, action and reward. Physiol Behav. 2005;86(5):773–95. [PubMed: 16289609]
40. Kralik JD, Dimitrov DF, et al. Techniques for long-term multisite neuronal ensemble recordings in behaving animals. Methods. 2001;25(2):121–50. [PubMed: 11812202]
41. Li CS, Cho YK, et al. Modulation of parabrachial taste neurons by electrical and chemical stimulation of the lateral hypothalamus and amygdala. J Neurophysiol. 2005;93(3):1183–96. [PubMed: 15483060]
42. Liu L, Simon SA. Capsaicin-induced currents with distinct desensitization and Ca2+ dependence in rat trigeminal ganglion cells. J Neurophysiol. 1996;75(4):1503–14. [PubMed: 8727394]
43. LopezJimenez ND, Cavenagh MM, et al. Two members of the TRPP family of ion channels, Pkd1l3 and Pkd2l1, are co-expressed in a subset of taste receptor cells. J Neurochem. 2006;98(1):68–77. [PubMed: 16805797]
44. Lundy RF Jr, Norgren R. Activity in the hypothalamus, amygdala, and cortex generates bilateral and convergent modulation of pontine gustatory neurons. J Neurophysiol. 2004;91(3):1143–57. [PubMed: 14627662]
45. Margolskee RF. Molecular mechanisms of bitter and sweet taste transduction. J Biol Chem. 2002;277(1):1–4. [PubMed: 11696554]
46. Matsumoto I, Emori Y, et al. A comparative study of three cranial sensory ganglia projecting into the oral cavity: in situ hybridization analyses of neurotrophin receptors and thermosensitive cation channels. Brain Res Mol Brain Res. 2001;93(2):105–12. [PubMed: 11589988]
47. Miller IJ Jr. Anatomy of the peripheral taste system. In: Doty RL, editor. Handbook of olfaction and gustation. New York: Marcel Dekker; 1995. pp. 521–547.
48. Mueller KL, Hoon MA, et al. The receptors and coding logic for bitter taste. Nature. 2005;434(7030):225–9. [PubMed: 15759003]
49. Muoio DM, Newgard CB. Obesity-related derangements in metabolic regulation. Annu Rev Biochem. 2006;75:367–401. [PubMed: 16756496]
50. Mutch DM, Clement K. Unraveling the genetics of human obesity. PLoS Genet. 2006;2(12):e188. [PMC free article: PMC1756898] [PubMed: 17196040]
51. Nelson G, Hoon MA, et al. Mammalian sweet taste receptors. Cell. 2001;106(3):381–90. [PubMed: 11509186]
52. Nicolelis MA, Baccala LA, et al. Sensorimotor encoding by synchronous neural ensemble activity at multiple levels of the somatosensory system. Science. 1995;268(5215):1353–8. [PubMed: 7761855]
53. Nicolelis MA, Dimitrov D, et al. Chronic, multisite, multielectrode recordings in macaque monkeys. Proc Natl Acad Sci USA. 2003;100(19):11041–6. [PMC free article: PMC196923] [PubMed: 12960378]
54. Nicolelis MA, Fanselow EE, et al. Hebb’s dream: the resurgence of cell assemblies. Neuron. 1997;19(2):219–21. [PubMed: 9292712]
55. Nicolelis MA, Ghazanfar AA, et al. Simultaneous encoding of tactile information by three primate cortical areas. Nat Neurosci. 1998;1(7):621–30. [PubMed: 10196571]
56. Nicolelis MA, Lin RC, et al. Induction of immediate spatiotemporal changes in thalamic networks by peripheral block of ascending cutaneous information. Nature. 1993;361(6412):533–6. [PubMed: 8429906]
57. Nishijo H, Uwano T, et al. Gustatory and multimodal neuronal responses in the amygdala during licking and discrimination of sensory stimuli in awake rats. J Neurophysiol. 1998;79(1):21–36. [PubMed: 9425173]
58. Norgren R. Taste pathways to hypothalamus and amygdala. J Comp Neurol. 1976;166:17–30. [PubMed: 1262547]
59. Norgren R. Central neural mechanisms of taste. In: Darien-Smith I, editor. Handbook of Physiology—The Nervous System III. Sensory Processes 1. Washington, D.C: American Physiological Society; 1984. pp. 1087–1128.
60. Norgren R, Hajnal A, et al. Gustatory reward and the nucleus accumbens. Physiol Behav. 2006;89(4):531–5. [PMC free article: PMC3114426] [PubMed: 16822531]
61. Norgren R, Leonard CM. Ascending central gustatory pathways. J Comp Neurol. 1973;150(2):217–37. [PubMed: 4723066]
62. O’Rahilly S, Farooqi IS. Genetics of obesity. Philos Trans R Soc Lond B Biol Sci. 2006;361(1471):1095–105. [PMC free article: PMC1642700] [PubMed: 16815794]
63. Öngür D, Price JL. Prefrontal cortical projections to the hypothalamus in macaque monkeys. J Comp Neurol. 1998;401:480–505. [PubMed: 9826274]
64. Paxinos G, Franklin KBJ. The mouse brain in stereotaxic coordinates. New York: Academic Press; 2001.
65. Paxinos G, Watson C. The rat brain in stereotaxic coordinates. New York: Academic Press; 1998.
66. Pritchard TC, Hamilton RB, et al. Projections of thalamic gustatory and lingual areas in the monkey, Macaca fascicularis. J Comp Neurol. 1986;244(2):213–228. [PubMed: 3950095]
67. Pritchard TC, Hamilton RB, et al. Projections of the parabrachial nucleus in the old world monkey. Exp Neurol. 2000;165(1):101–17. [PubMed: 10964489]
68. Rolls ET. Brain mechanisms underlying flavour and appetite. Philos Trans R Soc Lond B Biol Sci. 2006;361(1471):1123–36. [PMC free article: PMC1642694] [PubMed: 16815796]
69. Rolls ET, Baylis LL. Gustatory, olfactory, and visual convergence within the primate orbitofrontal cortex. J Neurosci. 1994;14:5437–5452. [PMC free article: PMC6577073] [PubMed: 8083747]
70. Rolls ET, Critchley HD, et al. Responses to the sensory properties of fat of neurons in the primate orbitofrontal cortex. J Neurosci. 1999;19:1532–1540. [PMC free article: PMC6786033] [PubMed: 9952429]
71. Rolls ET, Sienkiewicz ZJ, et al. Hunger modulates the responses to gustatory stimuli of single neurons in the caudolateral orbitofrontal cortex of the Macaque monkey. Eur J Neurosci. 1989;1(1):53–60. [PubMed: 12106174]
72. Rolls ET, Yaxley S, et al. Gustatory responses of single neurons in the caudo-lateral orbitofrontal cortex of the macaque monkey. J Neurophysiol. 1990;64(4):1055–66. [PubMed: 2258734]
73. Schwartz MW, Porte D Jr. Diabetes, obesity, and the brain. Science. 2005;307(5708):375–9. [PubMed: 15662002]
74. Sclafani A. Oral and postoral determinants of food reward. Physiol Behav. 2004;81(5):773–9. [PubMed: 15234183]
75. Scott K. Taste recognition: food for thought. Neuron. 2005;48(3):455–64. [PubMed: 16269362]
76. Scott TR, Plata-Salaman CR. Taste in the monkey cortex. Physiol Behav. 1999;67(4):489–511. [PubMed: 10549886]
77. Shi CJ, Cassell MD. Cortical, thalamic, and amygdaloid connections of the anterior and posterior insular cortices. J Comp Neurol. 1998;399(4):440–68. [PubMed: 9741477]
78. Simon SA, de Araujo IE, et al. The neural mechanisms of gustation: a distributed processing code. Nat Rev Neurosci. 2006;7(11):890–901. [PubMed: 17053812]
79. Simons CT, Boucher Y, et al. Suppression of central taste transmission by oral capsaicin. J Neurosci. 2003;23(3):978–85. [PMC free article: PMC6741918] [PubMed: 12574427]
80. Simons CT, Boucher Y, et al. Nicotine suppression of gustatory responses of neurons in the nucleus of the solitary tract. J Neurophysiol. 2006;96(4):1877–86. [PubMed: 16837661]
81. Small DM, Prescott J. Odor/taste integration and the perception of flavor. Exp Brain Res. 2005;166(3–4):345–57. [PubMed: 16028032]
82. Smith DV, Li CS. GABA-mediated corticofugal inhibition of taste-responsive neurons in the nucleus of the solitary tract. Brain Res. 2000;858(2):408–15. [PubMed: 10708694]
83. Spector AC, Travers SP. The representation of taste quality in the mammalian nervous system. Behav Cogn Neurosci Rev. 2005;4(3):143–91. [PubMed: 16510892]
84. Stapleton JR, Lavine ML, et al. Rapid taste responses in the gustatory cortex during licking. J Neurosci. 2006;26(15):4126–38. [PMC free article: PMC6673900] [PubMed: 16611830]
85. Stein CJ, Colditz GA. The epidemic of obesity. J Clin Endocrinol Metab. 2004;89(6):2522–5. [PubMed: 15181019]
86. Super H, Roelfsema PR. Chronic multiunit recordings in behaving animals: advantages and limitations. Prog Brain Res. 2005;147:263–82. [PubMed: 15581712]
87. Taylor MH, Howard E. Impaired glucose homeostasis in adult rats after corticosterone treatment in infancy. Endocrinology. 1971;88(5):1190–202. [PubMed: 5547241]
88. Tokita K, Karadi Z, et al. Centrifugal inputs modulate taste aversion learning associated parabrachial neuronal activities. J Neurophysiol. 2004;92(1):265–79. [PubMed: 14973323]
89. Travagli RA, Hermann GE, et al. Brainstem circuits regulating gastric function. Annu Rev Physiol. 2006;68:279–305. [PMC free article: PMC3062484] [PubMed: 16460274]
90. Travers JB, Dinardo LA, et al. Motor and premotor mechanisms of licking. Neurosci Biobehav Rev. 1997;21(5):631–47. [PubMed: 9353796]
91. van der Kooy D, Koda LY, et al. The organization of projections from the cortex, amygdala, and hypothalamus to the nucleus of the solitary tract in rat. J Comp Neurol. 1984;224(1):1–24. [PubMed: 6715573]
92. Wang Y, Erickson RP, et al. Selectivity of lingual nerve fibers to chemical stimuli. J Gen Physiol. 1993;101(6):843–66. [PMC free article: PMC2216747] [PubMed: 8331321]
93. Wang YM, Gainetdinov RR, et al. Knockout of the vesicular monoamine transporter 2 gene results in neonatal death and supersensitivity to cocaine and amphetamine. Neuron. 1997;19(6):1285–96. [PubMed: 9427251]
94. Whitehead MC, Bergula A, et al. Forebrain projections to the rostral nucleus of the solitary tract in the hamster. J Comp Neurol. 2000;422(3):429–47. [PubMed: 10861518]
95. Wilson CS. Reasons for eating: personal experiences in nutrition and anthropology. Appetite. 2002;38(1):63–7. [PubMed: 11883919]
96. Wise RA. Role of brain dopamine in food reward and reinforcement. Philos Trans R Soc Lond B Biol Sci. 2006;361(1471):1149–58. [PMC free article: PMC1642703] [PubMed: 16874930]
97. Zhang Y, Hoon MA, et al. Coding of sweet, bitter, and umami tastes: different receptor cells sharing similar signaling pathways. Cell. 2003;112(3):293–301. [PubMed: 12581520]
98. Zhao GQ, Zhang Y, et al. The receptors for mammalian sweet and umami taste. Cell. 2003;115(3):255–66. [PubMed: 14636554]