Humans often rank craniofacial pain as more severe than body pain. Evidence suggests that a stimulus of the same intensity induces stronger pain in the face than in the body. However, the underlying neural circuitry for the differential processing of facial versus bodily pain remains unknown. Interestingly, the lateral parabrachial nucleus (PB_L), a critical node in the affective pain circuit, is activated more strongly by noxious stimulation of the face than of the hindpaw. Using a novel activity-dependent technology called CANE developed in our laboratory, we identified and selectively labeled noxious-stimulus-activated PB_L neurons and performed comprehensive anatomical input–output mapping. Surprisingly, we uncovered a hitherto uncharacterized monosynaptic connection between cranial sensory neurons and the PB_L-nociceptive neurons. Optogenetic activation of this monosynaptic craniofacial-to-PB_L projection induced robust escape and avoidance behaviors and stress calls, whereas optogenetic silencing specifically reduced facial nociception. The monosynaptic circuit revealed here provides a neural substrate for heightened craniofacial affective pain.

Pupils can signify various internal processes and states, such as attention, arousal, and working memory. Changes in pupil size have been associated with learning speed, prediction of future events, and deviations from the prediction in human studies. However, the detailed relationships between pupil size changes and prediction are unclear. We explored pupil size dynamics in mice performing a Pavlovian delay conditioning task. A head-fixed experimental setup combined with deep-learning-based image analysis enabled us to reduce spontaneous locomotor activity and to track the precise dynamics of pupil size of behaving mice. By setting up two experimental groups, one for which mice were able to predict reward in the Pavlovian delay conditioning task and the other for which mice were not, we demonstrated that the pupil size of mice is modulated by reward prediction and consumption, as well as body movements, but not by unpredicted reward delivery. Furthermore, we clarified that pupil size is still modulated by reward prediction even after the disruption of body movements by intraperitoneal injection of haloperidol, a dopamine D2 receptor antagonist. These results suggest that changes in pupil size reflect reward prediction signals. Thus, we provide important evidence to reconsider the neuronal circuit involved in computing reward prediction error. This integrative approach of behavioral analysis, image analysis, pupillometry, and pharmacological manipulation will pave the way for understanding the psychological and neurobiological mechanisms of reward prediction and the prediction errors essential to learning and behavior.

Habit formation is a process in which an action becomes involuntary. While goal-directed behavior is driven by its consequences, habits are elicited by a situation rather than its consequences. Existing theories have proposed that actions are controlled by corresponding two distinct systems. Although canonical theories based on such distinctions are starting to be challenged, there are a few theoretical frameworks that implement goal-directed behavior and habits within a single system. Here, we propose a novel theoretical framework by hypothesizing that behavior is a network composed of several responses. With this framework, we have shown that the transition of goal-directed actions to habits is caused by a change in a single network structure. Furthermore, we confirmed that the proposed network model behaves in a manner consistent with the existing experimental results reported in animal behavioral studies. Our results revealed that habit could be formed under the control of a single system rather than two distinct systems. By capturing the behavior as a single network change, this framework provides a new perspective on studying the structure of the behavior for experimental and theoretical research.

Nicotinic acetylcholine receptors are thought to be associated with a wide range of phenomena, such as movement, learning, memory, attention, and addiction. However, the causal relationship between nicotinic receptor activity and behavior remains unclear. Contrary to the studies that examined the functions of muscarinic acetylcholine receptors, the role of the nicotinic acetylcholine receptors on behavior has not been examined as extensively. Here, we examined the effects of intraperitoneal injection of mecamylamine, a nicotinic acetylcholine receptor antagonist, on the performance of male mice in a head-fixed temporal conditioning task and a free-moving open-field task. The head-fixed experimental setup allowed us to record and precisely quantify the licking response while the mice performed the behavioral task with no external cues. In addition, by combining the utility of the head-fixed experimental design with computer vision analysis based on deep learning algorithms, we succeeded in quantifying the eyelid size of awake mice. In the temporal conditioning task, we delivered a 10% sucrose solution every 10 s using a blunt-tipped needle placed within the licking distance of the mice. After the training, the mice showed increased anticipatory licking toward the timing of sucrose delivery, suggesting that the mice could predict the timing of the reward. Systemic injection of mecamylamine decreased licking behavior and caused eye closure but had no effect on learned conditioned predictive behavior in the head-fixed temporal conditioning task. In addition, the injection of mecamylamine decreased spontaneous locomotor activity in a dose-dependent manner in the free-moving open-field task. The results in the open-field experiments further revealed that the effect of mecamylamine on fecal output and urination, suggesting the effects on autonomic activities. Our achievement of successful eyelid size recording has potential as a useful approach in initial screening for drug discovery. Our study paves a way forward to understanding the role of nicotinic acetylcholine receptors on learning and behavior.

Major depressive disorder is a highly prevalent psychiatric condition that can affect individuals across the lifespan, yet its pathophysiology remains incompletely understood. Classical hypotheses, informed by preclinical and clinical studies, emphasized dysregulated monoaminergic neurotransmission and guided the development of widely prescribed antidepressants, including selective serotonin reuptake inhibitors and serotonin–noradrenaline reuptake inhibitors. Although these agents improved treatment outcomes, they typically require weeks to achieve therapeutic effects, must be taken continuously, and fail to produce adequate responses in nearly one-third of patients. In addition, adverse effects, such as increased suicidal ideation in some populations, highlight the need for safer and more effective therapies. Recent discoveries of rapid-acting antidepressant effects of ketamine and psychedelic compounds have challenged traditional monoaminergic models and highlighted alternative mechanisms involving glutamatergic signaling, synaptic plasticity, and immune–brain interactions. At the same time, long-standing assumptions about neurotransmitter abnormalities are being re-examined, reinvigorating interest in mechanistic and circuit-level models. This review summarizes historical and emerging perspectives on antidepressant development, outlines major animal models of depression, and highlights recent advances in translational research that are redefining therapeutic strategies.