Feeding Behavior

Feeding behavior in the marine mollusk Aplysia californica20 is a useful model system to overcome the previously mentioned limitations and conduct a comparative analysis of the mechanisms of classical and operant conditioning.

From: Handbook of Behavioral Neuroscience , 2013

Molecular Mechanisms of Memory

F.D. Lorenzetti , J.H. Byrne , in Learning and Memory: A Comprehensive Reference, 2008

4.10.3.1 Behavioral Studies

Feeding behavior in Aplysia can be modified by pairing feeding with an aversive stimulus. If food is wrapped in a tough plastic net, Aplysia bite and attempt to swallow the food. However, netted food cannot be swallowed, and so it is rejected. The inability to consume the food appeared to be an aversive stimulus that modified the feeding behavior, because the trained animals no longer attempted to bite the netted food (Susswein et al., 1986).

Feeding behavior can also be operantly conditioned with an appetitive stimulus (Brembs et al., 2002). The reinforcement signal for the in vivo training protocol was a brief shock to the esophageal nerve. The esophageal nerve is believed to be part of the pathway mediating food reward because bursts of activity in this nerve occur when the animal successfully ingests food (Brembs et al., 2002). In addition, lesions to this nerve blocked in vivo appetitive classical conditioning (Lechner et al., 2000a). Also, the in vitro analog of classical conditioning discussed earlier successfully increased the number of CS-elicited motor patterns when esophageal nerve shock was used as the US (Mozzachiodi et al., 2003). In the operant conditioning paradigm, the contingent reinforcement of biting behavior by a shock to the esophageal nerve produced an increase in the frequency of biting, when measured both immediately after training and 24   h after training, as compared to animals trained with a yoke-control procedure (Brembs et al., 2002).

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Neuropeptides: Food Intake

S.F. Leibowitz , K.E. Wortley , in Encyclopedia of Neuroscience, 2009

Feeding behavior and body weight are controlled by a rich network of interrelated factors. These include the orexigenic peptides in the hypothalamus and forebrain, which stimulate feeding and are regulated by neurohumoral signals and dietary nutrients such as triglycerides and glucose. They are inhibited by signals of energy abundance to prevent further consummatory behavior or are stimulated by signals of energy deficiency to promote feeding. These orexigenic systems exhibit considerable diversity and redundancy in their actions. In addition to the stimulation of food intake, these involve effects on more intricate behavioral, endocrine, and metabolic processes. These may be related to the circadian rhythm of meals, arousal of food-seeking behavior, and diet palatability, in addition to energy expenditure, nutrient metabolism, and adiposity.

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Orexins and Control of Feeding by Learned Cues

Gorica D. Petrovich , in The Orexin/Hypocretin System, 2019

Abstract

Feeding behavior is essential for survival and is physiologically controlled through processes associated with energy and nutrient needs. In addition, environmental signals can drive appetite and eating through hedonic and cognitive processes in the absence of hunger. Cognitive cues, such as food-associated cues are powerful appetite stimulants. These cues are abundant in our environment and their stimulatory effects, together with easily accessible and affordable palatable foods, make us vulnerable to overeating. Deciphering the neural mechanisms underlying this cognitive motivation to eat is crucial for potential therapeutic interventions for those who suffer from insatiable appetites. This chapter provides an overview of the role of the neuropeptide orexin/hypocretin in the control of feeding by learned cues. The orexin system is an integral part of the feeding neural network and is critical for cue-mediated food seeking and consumption. Its dysregulation maybe be an important cause of vulnerability to enhanced cognitive motivation to eat.

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Invertebrate Learning and Memory

Riccardo Mozzachiodi , ... John H. Byrne , in Handbook of Behavioral Neuroscience, 2013

Conclusions

Feeding behavior in Aplysia has proven to be an excellent model system for comparing and contrasting the cellular and molecular mechanisms of associative learning. This chapter focused on the changes produced by appetitive operant and classical conditioning on B51 activity. However, modifications have been identified in other neurons of the feeding neural circuit following operant (B30, B63, and B65) 56,57 and classical conditioning (CBI-2 and B31/32). 39,55 Synergism among different neuronal elements modified by conditioning has emerged as a general principle for the associative storage of information in both vertebrate 7,71 and invertebrate animals. 72–74

Because of the distributed cellular substrates underlying associative learning, it is important to determine the contribution of each locus of plasticity to the expression of the learned behavioral changes. The presence of multiple sites underlying associative plasticity also raises the issue regarding to what extent the cellular mechanisms for plasticity at each site are conserved. For example, is the convergence of Ca2+ entry and activation of DA receptors observed in B51 following operant conditioning also used to bring about the contingent-dependent changes in B63? Continued analysis of the cellular and molecular mechanisms underlying appetitive classical and appetitive operant conditioning of feeding in Aplysia will provide important insights into the similarities and differences between these two main forms of associative learning.

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Invertebrate Learning and Memory

Douglas A. Baxter , ... John H. Byrne , in Handbook of Behavioral Neuroscience, 2013

Classical Conditioning of Feeding Behavior in Lymnaea

Feeding behavior of the pond snail Lymnaea stagnalis can be modified by classical conditioning (for review, see 63 ). This behavior is controlled by a central pattern generator (CPG), and the neurons and synaptic connections in the CPG are well-characterized (for review, see 64 ). Moreover, neuronal correlates of learning are known. Thus, Lymnaea is an excellent candidate for system-level analysis of learning. As a first step toward simulating learning in Lymnaea, Vavoulis et al. 46 developed a four-cell model of the feeding CPG (Figure 7.2B2). The neural network included cells N1, N2, and N3, which mediate the rhythmic neural activity underlying feeding movements, and cell SO, which is a modulatory neuron. Individual neurons in the neural network were represented by two-compartment models (Figure 7.2B1). The axonal compartment includes a fast, transient Na+ current (I NA) and a delayed-like K+ current (I K), which mediate spike activity. The somatic compartment includes currents (I ACh, I NaL, or I T), which mediate slowly developing, long-lasting changes of the membrane potential, such as plateau potentials in N1 and N2 and postinhibitory rebound in N3. The model simulates the rhythmic neural activity that mediates feeding behavior.

As a second step in modeling learning in Lymnaea, Vavoulis et al. 45 modeled the cerebral giant cells (CGCs). The CGCs are modulatory interneurons and are a locus of plasticity following appetitive classical conditioning. 65 The CGC is modeled as a single compartment, which includes (1) transient and persistent Na+ currents (I NaT and I NaP, respectively), (2) an A-type and a delayed-type K+ current (I A and I D, respectively), and (3) low- and high-voltage-activated Ca2+ currents (I LVA and I HVA, respectively). Two of the currents, I NaP and I D, are increased following conditioning. 45,65 Thus, the effects of conditioning are simulated by increasing the maximal conductances of I NaP and I D. Simulations reproduce some of the previously identified neuronal changes following conditioning, including a depolarization in CGC without a change in tonic firing in CGC. To maintain the spike waveform in CGC, however, it is necessary to hypothesize an increase in I HVA. The effects of conditioning on I HVA have yet to be examined empirically. Thus, the possible role of I HVA represents an important prediction of the model. An important next step will be to combine the CPG and CGC models and examine the extent to which the currently identified cellular correlates of conditioning can reproduce learning-induced changes in behavior.

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Motor Control of Feeding and Drinking

J.B. Travers , in Encyclopedia of Neuroscience, 2009

Organization of Feeding

Feeding behavior is commonly divided into appetitive and consummatory phases. The appetitive phase of feeding, seeking out and finding food, is highly variable. We can, for example, make elaborate dinner plans and travel great distances to find our favorite restaurant, or simply stumble into the kitchen and open a can of soup. Equally diverse are the antecedents or coincidents of appetitive behavior, which involve a vast array of neural and hormonal signals reflecting metabolic need or surfeit, and the subsequent activation of hypothalamic pathways that lead to the search for food. Habits, time of day, and social pressure further induce one to eat. However, once food is in the mouth, the behaviors exhibited are far less variable, as one need only reduce the food to a size commensurate with swallowing, perhaps pausing long enough to enjoy the flavor, before propelling it toward the stomach. In comparison to the vast array of sensory and regulatory signals associated with body weight regulation or appetitive behavior, the highly stereotyped motor actions of mastication, licking, suckling, and swallowing are guided by a considerably more restricted set of gustatory and orotactile receptors.

Consummatory behavior can be subdivided based on behavioral, cinefluorographic, and electromyographic analyses. Although highly species specific, there are behavioral commonalities. Thus, the consummatory phase of eating begins with ingestion (putting food in the mouth), followed by transport of the bolus to an interdental position for mastication, and followed by a further transport phase to the back of the tongue for swallowing. Mastication can be further subdivided into a fast-closing phase that ceases when food makes contact with the bolus, at which point there is a slow-closing phase. Subsequent jaw opening begins with a slow jaw-opening phase followed by a fast jaw-opening phase. The act of swallowing is subdivided into oral, pharyngeal, and esophageal phases.

The seemingly simple motor problem of transporting food from the front of the mouth to the stomach belies an underlying complexity of coordination among a large number of muscles. Although mastication/licking and swallowing are inextricably linked during eating, sharing muscles of the tongue and jaws, historically they have been studied largely independently. This view is beginning to change as it is recognized that the generation of these behaviors does not derive from entirely dedicated circuits, but rather from multifunctional networks coordinating other oral motor behaviors, including respiration and, perhaps, even vocalization. Nevertheless, herein, the discussion will proceed from the perspective of acute neurophysiological studies in which mastication/licking and swallowing appear to have relatively distinct, spatially separate brain stem circuitry.

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Neurobiology of Cytokines

Carlos R. Plata-Salamán , in Methods in Neurosciences, 1993

Publisher Summary

Ingestive behavior—feeding and drinking— is a complex process that involves a variety of psychological factors, neuronal mechanisms, metabolic processes, and gastrointestinal mechanisms that convey neural and humoral signals to the central nervous system (CNS). Acute and chronic pathological processes stimulate the synthesis and release of cytokines. During these processes, cooperation of cytokines is essential for the coordination of immune and other host responses. Cytokines released during disease also participate in the mediation of endocrinological, metabolic, and neurological responses. These neurological responses include fever, somnolence, and appetite suppression that frequently accompany acute and chronic disease. Monitoring of cytokines by the CNS is one of the regulatory factors that induce appetite suppression during disease. This chapter discusses the methods that are used to study the effects of cytokines on feeding and drinking under a variety of experimental conditions. It explains the participation of single or multiple cytokines in the suppression of feeding and drinking during pathological processes. The chapter describes the peripheral and/or central target sites responsible for the feeding and drinking suppression induced by cytokines.

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Treatment Components

Jonathan Tarbox , Taira Lanagan Bermudez , in Treating Feeding Challenges in Autism, 2017

5.4 Bite Requirement/Demand Fading

When beginning treatment or introducing a new food, acceptance of nonpreferred foods may be more likely if the feeding task is smaller or easier. One option is to begin intervention with only one or a few bites required per meal, then increasing the bite requirement once the client is consistently consuming bites of nonpreferred foods. For example, on the first day of feeding intervention, Johnny is presented with one bite of each target food: chicken, apple, broccoli, and spaghetti. On day 2, he is presented with two bites of each food; day 3, he is presented with five bites, and so on. There are no black and white rules for how quickly to increase the number of bites per meal. All other things being equal, fading slowly is more likely to be successful but may hold the client back from progressing as fast as he could.

5.4.1 Advantages

For escape maintained feeding behaviors, decreasing the motivation to escape will reduce the occurrence of problem behavior to gain escape. Demand fading is a simple variable to manipulate because you are not changing the content or format of the demand, just the amount of demands. It is also a very common sense approach: Just don't make the client eat so much!

5.4.2 Disadvantages

Because demand fading involves presenting much smaller meals at first, treatment sessions might not include ample bites of food or variety of foods. Put another way, staff and parents may be highly skeptical of an approach that only requires the client to eat a few bites at first. Of course, very small meals will not provide the client with enough calories. You may need to present a larger number of small meals per day, rather than fewer larger meals. Another option is for the parents to provide the client with an additional meal of preferred foods later that is not considered a treatment meal. If this option is used, be very careful that the additional meal is not presented soon after a treatment meal where the client has failed to eat the prescribed amount of nonpreferred foods. Even for clients with minimal verbal repertoires, it is possible that getting preferred foods soon after refusing nonpreferred foods during treatment meals will reinforce the refusal behavior that occurred during the intervention. Therefore, we often recommend that if parents need to provide supplemental meals outside of treatment meals, they wait at least an hour after a treatment meal if the client had not eaten the expected amount of target nonpreferred foods during the treatment meal.

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The Human Hypothalamus

Anna Maria van Opstal , in Handbook of Clinical Neurology, 2021

Introduction

The regulation of feeding behavior and energy balance is crucial for maintaining health. Energy balance is maintained when the energy that is taken in is balanced by the energy that is expended. A negative energy balance is countered by increasing energy intake by an increase in appetite and decreasing energy expenditure by decreasing movement and metabolic rate ( Schwartz et al., 2000). Common health problems such as obesity, metabolic syndrome, and diabetes type 2 are all caused by a combination of disrupted feeding behavior that leads to increased energy intake and decreased energy expenditure, which together leads to a disrupted energy balance. In addition to the well-known endocrinological aspects of energy balance, the importance of the regulatory role of the brain in maintaining energy balance, glucose homeostasis, and eating behavior is increasingly being recognized (Schwartz et al., 2000; Morton et al., 2006; Deem et al., 2017).

The brain regulates energy balance through several interacting neuronal systems that use external, peripheral, and central factors within the brain as input. The homeostatic system regulates energy intake according to caloric need by combining satiety signals with other metabolic and hormonal cues (Morton et al., 2014; Kim et al., 2018). Homeostatic regulation of feeding behavior has been proposed as the most important aspect in regulating energy balance (Araujo et al., 2020). In the homeostatic system, the hypothalamus is the central structure that regulates energy balance as it is the primary site of convergence and integration for nutrient-related signals (Lam et al., 2009; Blouet and Schwartz, 2010; Jordan et al., 2010; Cornejo et al., 2016; Rogers and Brunstrom, 2016; Kim et al., 2018).

Endocrine signals from the periphery that are related to the energy status of the body, such as ghrelin, leptin, and insulin, all influence the homeostatic regulation by the hypothalamus by initiating signals of hunger and satiety (Schwartz and Porte, 2005; Lam et al., 2009; Mergenthaler et al., 2013; Cornejo et al., 2016). Additionally, neuroendocrine signals within the brain influence energy balance regulation by the hypothalamus. The peptide transmitters proopiomelanocortin (POMC) and its downstream peptide products melanocyte-stimulating hormones are important anorectic regulators of energy balance that suppress energy intake Neuropeptide Y (NPY) and agouti-related peptide have an opposing role as orexigenic regulators stimulating food intake (Jordan et al., 2010; Mercer et al., 2013). These endocrine and neuroendocrine signals are combined with central neuronal signals from the limbic and executive control system (Berthoud and Morrison, 2008). Through integrating signals from these systems, the regulation of food intake by the hypothalamus also relies on the reward and motivational neurocircuitry signaling via neurotransmitters such as dopamine to modify (acute) eating behaviors and long-term energy homeostasis (Volkow et al., 2011; Kim et al., 2018). After receiving and integrating this input, the hypothalamus then sends downstream signals to the periphery to regulate energy balance. This output is conveyed via the autonomic nervous system (ANS). The ANS plays a key role in the physiological responses to the signals received by the hypothalamus by innervating peripheral metabolic tissues, including brown and white adipose tissue (BAT and WAT), the liver, pancreas, and skeletal muscle (Seoane-Collazo et al., 2015). These tissues are involved in glucose homeostasis, energy expenditure, and storage and thermoregulation, and thus all play an active role in the maintenance of energy balance. The hypothalamus is thus at the heart of a complex system that regulates energy balance; a graphic summary of this system is depicted in Fig. 24.1.

Fig. 24.1

Fig. 24.1. Hypothalamic regulation of energy balance. Various external, central, and peripheral signals influence the nutrient sensing and homeostatic regulation by the hypothalamus. After integrating these input signals combined with neuronal input from the executive control and limbic system, the hypothalamus signals to several peripheral tissues via the autonomic nervous system (ANS) innervation to regulate energy balance. AgRP: agouti-related peptide, MSH: melanocyte-stimulating hormones, NPY: neuropeptide Y, POMC: proopiomelanocortin.

Nutrient sensing by the hypothalamus is very important to determine the availability of energy to body and the brain as it represents the first step in the regulation of energy balance. The most important nutrients used for energy by the body and the brain are glucose and fats, with the first being used as a direct source of energy and the latter as a more longer-term stored energy supply. Therefore, in this review, we will focus on glucose and fat sensing in the human hypothalamus on both a neuronal level and a systemic level. We will discuss the hypothalamic structures involved in nutrient sensing, the specific nutrient-sensing pathways of both glucose and fats, and how these two pathways intertwine and influence one another. Also, as various common health problems and chronic diseases can be led back to a disrupted hypothalamic function, we will discuss hypothalamic sensing of glucose and fats in these pathologies. Finally, we will summarize the current knowledge to determine how this can be applied clinically and for future research perspectives.

Much work on the detailed function of the hypothalamus on a neuronal level has been done in vivo or in rodents. Although very informative, due to technical restraints similar work cannot be done in vivo in humans. Therefore, in addition to discussing fundamental work on hypothalamic nutrient sensing, we aim to focus on the sensing of glucose and fats and the reaction of the hypothalamus in humans, although the body of this work is much more limited. Most of the work that has been done in this field uses functional magnetic resonance imaging (MRI) of the brain. Functional MRI is the designated method to investigate in vivo functional brain responses in humans and has been extensively used to visualize and quantify brain function to determine the immediate or longer-term effects of nutrient ingestion on either specific brain areas or throughout the brain as a whole (Smeets et al., 2005a,b; Vidarsdottir et al., 2007; Haase et al., 2009; van Opstal et al., 2015, 2018a,b,c, 2019a,b).

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Anatomy and Physiology, Systems

T.C. Pritchard , in Brain Mapping, 2015

Taste Processing in the Hypothalamus and Amygdala

The gustatory system guides feeding behavior through its projections to the hypothalamus and the amygdala. In rodents, gustatory projections to the hypothalamus and amygdala arise from the PBN; in monkeys and presumably humans, the routes are less certain but they appear to originate in the insula. The hypothalamus and the amygdala, rather than contributing to sensory coding per se, are more heavily invested in feeding behavior, broadly defined.

Hypothalamic neurons that respond to the gustatory, olfactory, and visual attributes of food are in close proximity to cells that respond to fluctuating blood glucose levels. Their proximity to one another enables the hypothalamus to monitor the chemosensory nature of food in the context of the animal's internal milieu, in general, and their hunger/satiety status, in particular. Not surprisingly, the activity of some hypothalamic neurons is modulated by the animal's level of hunger/satiety.

The amygdala also monitors the internal and external worlds so that need-driven behaviors, such as feeding, are managed in the context of emotional and motivational states. Through its connections with other areas of the limbic system and the OFC, the amygdala contributes to the emotive aspects of taste and feeding.

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