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Uchida, Naoshige

Decision making requires an actor to not only steer behavior towards specific goals, but also determine the optimal vigor of performance. Current research and models have largely focused on the former problem of how actions are directed, while overlooking the latter problem of how they are energized. Here, we designed a self-paced decision-making paradigm that showed that rats' performance vigor globally fluctuates with the net value of their options, suggesting that they maintain long-term estimates of the value of their current state. Lesions of the dorsomedial (DMS), and to a lesser degree, in the ventral striatum (VS) impaired such state-dependent modulation of vigor, rendering vigor to depend more exclusively on the outcomes of immediately preceding trials. The lesions, however, spared choice biases. Neuronal recordings showed that the DMS is enriched with net-value-coding neurons. In sum, the DMS encodes one's net expected return, which drives the general motivation to perform.

Recent studies indicate that dopamine neurons in the ventral tegmental area (VTA) and substantia nigra pars compacta (SNc) convey distinct signals. To explore this difference, we comprehensively identified each area's monosynaptic inputs using the rabies virus. We show that dopamine neurons in both areas integrate inputs from a more diverse collection of areas than previously thought, including autonomic, motor, and somatosensory areas. SNc and VTA dopamine neurons receive contrasting excitatory inputs: the former from the somatosensory/motor cortex and subthalamic nucleus, which may explain their short-latency responses to salient events; and the latter from the lateral hypothalamus, which may explain their involvement in value coding. We demonstrate that neurons in the striatum that project directly to dopamine neurons form patches in both the dorsal and ventral striatum, whereas those projecting to GABAergic neurons are distributed in the matrix compartment. Neuron-type-specific connectivity lays a foundation for studying how dopamine neurons compute outputs.

Dopamine has a central role in motivation and reward. Dopaminergic neurons in the ventral tegmental area (VTA) signal the discrepancy between expected and actual rewards (that is, reward prediction error)1–3, but how they compute such signals is unknown. We recorded the activity of VTA neurons while mice associated different odour cues with appetitive and aversive outcomes. We found three types of neuron based on responses to odours and outcomes: approximately half of the neurons (type I, 52%) showed phasic excitation after reward-predicting odours and rewards in a manner consistent with reward prediction error coding; the other half of neurons showed persistent activity during the delay between odour and outcome that was modulated positively (type II, 31%) or negatively (type III, 18%) by the value of outcomes. Whereas the activity of type I neurons was sensitive to actual outcomes (that is, when the reward was delivered as expected compared to when it was unexpectedly omitted), the activity of type II and type III neurons was determined predominantly by reward-predicting odours. We ‘tagged’ dopaminergic and GABAergic neurons with the light-sensitive protein channelrhodopsin-2 and identified them based on their responses to optical stimulation while recording. All identified dopaminergic neurons were of type I and all GABAergic neurons were of type II. These results show that VTA GABAergic neurons signal expected reward, a key variable for dopaminergic neurons to calculate reward prediction error.

The olfactory system encodes information about molecules by spatiotemporal patterns of activity across distributed populations of neurons and extracts information from these patterns to control specific behaviors. Recent studies used in vivo recordings, optogenetics, and other methods to analyze the mechanisms by which odor information is encoded and processed in the olfactory system, the functional connectivity within and between olfactory brain areas, and the impact of spatiotemporal patterning of neuronal activity on higher-order neurons and behavioral outputs. The results give rise to a faceted picture of olfactory processing and provide insights into fundamental mechanisms underlying neuronal computations. This review focuses on some of this work presented in a Mini-Symposium at the Annual Meeting of the Society for Neuroscience in 2012.

How information encoded in neuronal spike trains is used to guide sensory decisions is a fundamental question. In olfaction, a single sniff is sufficient for fine odor discrimination but the neural representations on which olfactory decisions are based are unclear. Here, we recorded neural ensemble activity in the anterior piriformcortex (aPC) of rats performing an odor mixture categorization task. We show that odors evoke transient bursts locked to sniff onset and that odor identity can be better decoded using burst spike counts than by spike latencies or temporal patterns. Surprisingly, aPC ensembles also exhibited near-zero noise correlations during odor stimulation. Consequently, fewer than 100 aPC neurons provided sufficient information to account for behavioral speed and accuracy, suggesting that behavioral performance limits arise downstream of aPC. These findings demonstrate profound transformations in the dynamics of odor representations from the olfactory bulb to cortex and reveal likely substrates for odor-guided decisions.

Summary Hunger is a hard-wired motivational state essential for survival. Agouti-related peptide (AgRP)-expressing neurons in the arcuate nucleus (ARC) at the base of the hypothalamus are crucial to its control. They are activated by caloric deficiency and, when naturally or artificially stimulated, they potently induce intense hunger and subsequent food intake1-5. Consistent with their obligatory role in regulating appetite, genetic ablation or pharmacogenetic inhibition of AgRP neurons decreases feeding3,6,7. Excitatory input to AgRP neurons is key in caloric-deficiency-induced activation, and is notable for its remarkable degree of caloric state-dependent synaptic plasticity8-10. Despite the important role of excitatory input, its source(s) has been unknown. Here, through the use of Cre-recombinase-enabled, cell-specific neuron mapping techniques, we have discovered strong excitatory drive that, unexpectedly, emanates from the hypothalamic paraventricular nucleus, specifically from subsets of neurons expressing Thyrotropin-releasing hormone (TRH) and Pituitary adenylate cyclase-activating polypeptide (PACAP). Pharmaco-genetic stimulation of these afferent neurons in sated mice markedly activates AgRP neurons and induces intense feeding. Conversely, acute inhibition in mice with caloric deficiency-induced hunger decreases feeding. Discovery of these afferent neurons capable of triggering hunger advances understanding of how this intense motivational state is regulated.

It has been proposed that a single sniff generates a “snapshot” of the olfactory world. However, odor coding on this timescale is poorly understood, and it is not known whether coding is invariant to changes in respiration frequency. We investigated this by recording spike trains from the olfactory bulb in awake, behaving rats. During rapid sniffing, odor inhalation triggered rapid and reliable cell- and odor-specific temporal spike patterns. These fine temporal responses conveyed substantial odor information within the first ∼100 ms, and correlated with behavioral discrimination time on a trial-by-trial basis. Surprisingly, the initial transient portions of responses were highly conserved between rapid sniffing and slow breathing. Firing rates over the entire respiration cycle carried less odor information, did not correlate with behavior, and were poorly conserved across respiration frequency. These results suggest that inhalation-coupled transient activity forms a robust neural code that is invariant to changes in respiration behavior.

Although higher-order statistics of neuronal firing have been characterized in neuroscience, many analyses ignore the nonstationarity of the background firing rate. We discuss how to measure the irregularity of interspike intervals in a rate-independent manner. Under the framework of semiparametric statistical models, we develop an estimator of firing irregularity which remains after the effects of rate modulations are removed. We found that firing irregularity is robust and reproducible in neurons in olfactory cortex irrespective of the rate modulation during the task period. As the level of irregularity varies among neurons, we classified neurons in olfactory cortex by using the proposed measure as a feature.

Orbitofrontal cortex (OFC) is a region of prefrontal cortex implicated in the motivational control of behavior and in related abnormalities seen in psychosis and depression. It has been hypothesized that a critical mechanism in these disorders is the dysfunction of GABAergic interneurons that normally regulate prefrontal information processing. Here, we studied a subclass of interneurons isolated in rat OFC using extracellular waveform and spike train analysis. During performance of a goal-directed behavioral task, the firing of this class of putative fast-spiking (FS) interneurons showed robust temporal correlations indicative of a functionally coherent network. FS cell activity also co-varied with behavioral response latency, a key indicator of motivational state. Systemic administration of ketamine, a drug that can mimic psychosis, preferentially inhibited this cell class. Together, these results support the idea that OFC–FS interneurons form a critical link in the regulation of motivation by prefrontal circuits during normal and abnormal brain and behavioral states.

Humans and other animals must often make decisions on the basis of imperfect evidence. Statisticians use measures such as P values to assign degrees of confidence to propositions, but little is known about how the brain computes confidence estimates about decisions. We explored this issue using behavioural analysis and neural recordings in rats in combination with computational modelling. Subjects were trained to perform an odour categorization task that allowed decision confidence to be manipulated by varying the distance of the test stimulus to the category boundary. To understand how confidence could be computed along with the choice itself, using standard models of decision-making, we defined a simple measure that quantified the quality of the evidence contributing to a particular decision. Here we show that the firing rates of many single neurons in the orbitofrontal cortex match closely to the predictions of confidence models and cannot be readily explained by alternative mechanisms, such as learning stimulus–outcome associations. Moreover, when tested using a delayed reward version of the task, we found that rats' willingness to wait for rewards increased with confidence, as predicted by the theoretical model. These results indicate that confidence estimates, previously suggested to require 'metacognition' and conscious awareness, are available even in the rodent brain, can be computed with relatively simple operations, and can drive adaptive behaviour. We suggest that confidence estimation may be a fundamental and ubiquitous component of decision-making.