Despite widespread neural activity related to reward values, signals related to upcoming choice have not been clearly identified in the rodent brain. Here, we examined neuronal activity in the lateral (AGl) and medial (AGm) agranular cortex, corresponding to the primary and secondary motor cortex, respectively, in rats performing a dynamic foraging task. Choice signals arose in the AGm before behavioral manifestation of the animal’s choice earlier than in any other areas of the rat brain previously studied under free-choice conditions. The AGm also conveyed significant neural signals for decision value and chosen value. In contrast, upcoming choice signals arose later and value signals were weaker in the AGl. We also found that AGm lesions made the animal’s choices less dependent on dynamically updated values. These results suggest that rodent secondary motor cortex might be uniquely involved in both representing and reading out value signals for flexible action selection.

Several lines of evidence suggest the involvement of prefrontal cortex in time interval estimation. The underlying neural processes are poorly understood, however, in part because of the paucity of physiological studies. The goal of this study was to establish an interval timing task for physiological recordings in rats, and test the requirement of intact medial prefrontal cortex (mPFC) for performing the task. We established a temporal bisection procedure using six different time intervals ranging from 3018 to 4784 ms that needed to be discriminated as either long or short. Bilateral infusions of muscimol (GABAA receptor agonist) into the mPFC significantly impaired animal's performance in this task, even when the animals were required to discriminate between only the longest and shortest time intervals. These results show the requirement of intact mPFC in rats for time interval discrimination in the range of a few seconds.

1 Amitriptyline has been known to induce QT prolongation and torsades de pointes which causes sudden death. We studied the e ects of amitriptyline on the human ether-a-go-go-related gene (HERG) channel expressed in Xenopus oocytes and on the rapidly activating delayed recti®er K + current (I Kr ) in rat atrial myocytes. 2 The amplitudes of steady-state currents and tail currents of HERG were decreased by amitriptyline dose-dependently. The decrease became more pronounced at more positive potential, suggesting that the block of HERG by amitriptyline is voltage dependent. IC 50 for amitriptyline block of HERG current was progressively decreased according to depolarization: IC 50 values at 730, 710, +10 and +30 mV were 23.0, 8.71, 5.96 and 4.66 mM, respectively. 3 Block of HERG by amitriptyline was use dependent: exhibiting a much faster block at higher activation frequency. Subsequent decrease in frequency after high activation frequency resulted in a partial relief of HERG blockade. 4 Steady-state block by amitriptyline was obtained while depolarization to +20 mV for 0.5 s was applied at 0.5 Hz: IC 50 was 3.26 mM in 2 mM [K + ] o . It was increased to 4.78 mM in 4 mM [K + ] o , suggesting that the a nity of amitriptyline on HERG was decreased by external K + . 5 In rat atrial myocytes bathed in 358C, 5 mM amitriptyline blocked I Kr by 55%. However, transient outward K + current (I to ) was not signi®cantly a ected. 6 In summary, the data suggest that the block of HERG currents may contribute to arrhythmogenic side e ects of amitriptyline.

Reinforcement learning theories postulate that actions are chosen to maximize a long-term sum of positive outcomes based on value functions, which are subjective estimates of future rewards. In simple reinforcement learning algorithms, value functions are updated only by trial-and-error, whereas they are updated according to the decision-maker's knowledge or model of the environment in model-based reinforcement learning algorithms. To investigate how animals update value functions, we trained rats under two different free-choice tasks. The reward probability of the unchosen target remained unchanged in one task, whereas it increased over time since the target was last chosen in the other task. The results show that goal choice probability increased as a function of the number of consecutive alternative choices in the latter, but not the former task, indicating that the animals were aware of time-dependent increases in arming probability and used this information in choosing goals. In addition, the choice behavior in the latter task was better accounted for by a model-based reinforcement learning algorithm. Our results show that rats adopt a decision-making process that cannot be accounted for by simple reinforcement learning models even in a relatively simple binary choice task, suggesting that rats can readily improve their decision-making strategy through the knowledge of their environments.Animals must continually update their behavioral strategies according to changes in an environment in order to optimize their choices. Reinforcement learning (RL) models (Sutton and Barto 1998) provide a powerful theoretical framework for understanding choice behavior in humans and animals in a dynamic environment. In theories of RL, future actions are chosen so as to maximize a long-term sum of positive outcomes, and this can be accomplished by a set of value functions that represent the amount of expected reward that is associated with particular states or actions. The value functions are continually updated based on the reward prediction error, which is the difference between the expected and actual rewards. This way, even without prior knowledge about an uncertain and dynamically changing environment, an animal can discover the structure of the environment that can be exploited for optimal choice by trial-and-error. Not surprisingly, human and monkey choice behaviors in various tasks are well described by reinforcement learning algorithms (e.g., O'Doherty et al. 2003;Barraclough et al. 2004;Lee et al. 2004;Samejima et al. 2005;Daw et al. 2006;Pessiglione et al. 2006).The updating of value functions can be achieved in two fundamentally different ways. In simple or direct RL algorithms, value functions are updated only by trial-and-error. In other words, only the value function that is associated with the chosen action is updated, and those that are associated with uncommitted actions remain unchanged. On the other hand, in indirect or model-based RL algorithms, the value functions might also change according to the decis...

One of the common side effects of antihistamine medicines is xerostomia (dry mouth). The current consensus is that antihistamine-induced xerostomia comes from an antimuscarinic effect. Although the effect of antihistamines on salivary secretion is both obvious and significant, the cellular mechanism whereby this happens is still unclear because of the lack of knowledge of histamine signaling in human salivary glands. Here, we have studied histamine receptors and the effect of antihistamines on human submandibular acinar cells. In primary cultured human submandibular gland and a HSG cell line, histamine increased the intracellular Ca 2ϩ concentration. The histamine-induced cytosolic free Ca 2ϩ concentration ([Ca 2ϩ ] i ) increase was inhibited by histamine H1 receptor-specific antagonists, and the expression of the functional histamine H1 receptor was confirmed by reverse transcription-polymerase chain reaction. Interestingly, histamine pretreatment did not inhibit a subsequent carbachol-induced [Ca 2ϩ ] i rise without "heterologous desensitization." Chlorpheniramine inhibited a carbachol-induced [Ca 2ϩ ] i increase at a 100-fold greater concentration than histamine receptor antagonism, whereas astemizole and cetrizine showed more than 1000-fold difference, which in part explains the xerostomia-inducing potency among the antihistamines. Notably, histamine resulted in translocation of aquaporin-5 to the plasma membrane in human submandibular gland cells and green fluorescent proteintagged aquaporin-5 expressing HSG cells. We found that histidine decarboxylase and the histamine H1 receptor are broadly distributed in submandibular gland cells, whereas choline acetyltransferase is localized only at the parasympathetic terminals. Our results suggest that human salivary gland cells express histamine H1 receptors and histamine-synthesizing enzymes, revealing the cellular mechanism of antihistamineinduced xerostomia.