The neural control of appetite is important for understanding motivated behavior as well as the present rising prevalence of obesity. Over the past several years, new tools for cell type-specific neuron activity monitoring and perturbation have enabled increasingly detailed analyses of the mechanisms underlying appetite-control systems. Three major neural circuits strongly and acutely influence appetite but with notably different characteristics. Although these circuits interact, they have distinct properties and thus appear to contribute to separate but interlinked processes influencing appetite, thereby forming three pillars of appetite control. Here, we summarize some of the key characteristics of appetite circuits that are emerging from recent work and synthesize the findings into a provisional framework that can guide future studies.

Processing quantity information based on abstract principles is central to intelligent behavior. Neural correlates of quantitative rule selectivity have been identified previously in the prefrontal cortex (PFC). However, whether individual neurons represent rules applied to multiple magnitude types is unknown. We recorded from PFC neurons while monkeys switched between "greater than/less than" rules applied to spatial and numerical magnitudes. A majority of rule-selective neurons responded only to the quantitative rules applied to one specific magnitude type. However, another population of neurons generalized the magnitude principle and represented the quantitative rules related to both magnitudes. This indicates that the primate brain uses rule-selective neurons specialized in guiding decisions related to a specific magnitude type only, as well as generalizing neurons that respond abstractly to the overarching concept "magnitude rules."

R. Sekuler, P. Tynan, and E. Levinson (1973) found that when 2 characters are presented side-by-side with a short onset asynchrony, subjectively they often appear in a "first-left, then-right" order. The authors of this article conducted 6 experiments in which observers judged the temporal order (TOJs) in which 2 digits were presented. They found a consistent TOJ benefit (larger d;) when the numerically smaller digit was presented first, even though this semantic information was irrelevant to the task and unrelated to the correct response. They concluded that digits located to the left of the mental number line are transmitted faster to a central comparison stage, which represents an "internal counterpart" to the Sekuler et al. (1973) finding regarding external locations. A corresponding benefit is found for letters pairs (e.g., A-Z) and also for mixed digit-letter pairs (e.g., 1-Z).

Physiological need states direct decision-making towards re-establishing homeostasis. Using a two-alternative-forced-choice task for mice that models elements of human decisions, we found that varying hunger and thirst states caused need-inappropriate choices, such as food-seeking when thirsty. These results show limits on interoceptive knowledge of hunger and thirst states to guide decision-making. Instead, need states were identified after food and water consumption by outcome evaluation, which depended on medial prefrontal cortex.

The representation of magnitude information enables humans and animal species alike to successfully interact with the external environment. However, how various types of magnitudes are processed by single neurons to guide goal-directed behavior remains elusive. Here, we recorded single-cell activity from the dorsolateral prefrontal (PFC), dorsal premotor (PMd) and cingulate motor (CMA) cortices in monkeys discriminating discrete numerical (numerosity), continuous spatial (line length) and basic sensory (spatial frequency) stimuli. We found that almost exclusively PFC neurons represented the different magnitude types during sample presentation and working memory periods. The frequency of magnitude-selective cells in PMd and CMA did not exceed chance level. The proportion of PFC neurons selectively tuned to each of the three magnitude types were comparable. Magnitude coding was mainly dissociated at the single-neuron level, with individual neurons representing only one of the three tested magnitude types. Neuronal magnitude discriminability, coding strength and temporal evolution were comparable between magnitude types encoded by PFC neuron populations. Our data highlight the importance of PFC neurons in representing various magnitude categories. Such magnitude representations are based on largely distributed coding by single neurons that are anatomically intermingled within the same cortical area.

We present three experiments in which observers searched for a target digit among distractor digits in displays in which the mean numerical target-distractor distance was varied. Search speed and accuracy increased with numerical distance in both target-present and target-absent trials (Exp. 1A). In Experiment 1B, the target 5 was replaced with the letter S. The results suggest that the findings of Experiment 1A do not simply reflect the fact that digits that were numerically closer to the target coincidentally also shared more physical features with it. In Experiment 2, the numerical distance effect increased with set size in both target-present and target-absent trials. These findings are consistent with the view that increasing numerical target-distractor distance affords faster nontarget rejection and target identification times. Recent neurobiological findings (e.g., Nieder, 2011) on the neuronal coding of numerosity have reported a width of tuning curves of numerosity-selective neurons that suggests graded, distance-dependent coactivation of the representations of adjacent numbers, which in visual search would make it harder to reject numerically closer distractors as nontargets.

In everyday situations, quantitative rules, such as "greater than/less than," need to be applied to a multitude of magnitude comparisons, be they sensory, spatial, temporal, or numerical. We have previously shown that rules applied to different magnitudes are encoded in the lateral PFC. To investigate if and how other frontal lobe areas also contribute to the encoding of quantitative rules applied to multiple magnitudes, we trained monkeys to switch between "greater than/less than" rules applied to either line lengths (spatial magnitudes) or dot numerosities (discrete numerical magnitudes). We recorded single-cell activity from the dorsal premotor cortex (dPMC) and cingulate motor cortex (CMA) and compared it with PFC activity. We found the largest proportion of quantitative rule-selective cells in PFC (24% of randomly selected cells), whereas neurons in dPMC and CMA rarely encoded the rule (6% of the cells). In addition, rule selectivity of individual cells was highest in PFC neurons compared with dPMC and CMA neurons. Rule-selective neurons that simultaneously represented the "greater than/less than" rules applied to line lengths and numerosities ("rule generalists") were exclusively present in PFC. In dPMC and CMA, however, neurons primarily encoded rules applied to only one of the two magnitude types ("rule specialists"). Our data suggest a special involvement of PFC in representing quantitative rules at an abstract level, both in terms of the proportion of neurons engaged and the coding capacities.

Awake, behaving rhesus monkeys are widely used in neurophysiological research. Neural signals are typically measured from monkeys trained with operant conditioning techniques to perform a variety of behavioral tasks in exchange for rewards. Over the past years, monkeys' psychological well-being during experimentation has become an increasingly important concern. We suggest objective criteria to explore whether training sessions during which the monkeys work under controlled water intake over many days might affect their behavior. With that aim, we analyzed a broad range of species-specific behaviors over several months ('ethogram') and used these ethograms as a proxy for the monkeys' well-being. Our results show that monkeys' behavior during training sessions is unaffected by the duration of training-free days in-between. Independently of the number of training-free days (two or nine days) with ad libitum food and water supply, the monkeys were equally active and alert in their home group cages during training phases. This indicates that the monkeys were well habituated to prolonged working schedules and that their well-being was stably ensured during the training sessions.