Goal-directed actions and habits in head-fixed mice

Background: Behavioral control is fundamentally governed by a dynamic balance between flexible, goal-directed actions and efficient but highly automated habits. While the transition to habitual control can be adaptive, an imbalance favoring rigid habits over flexible control is thought to contribute significantly to the core pathology of many neuropsychiatric disorders. Despite their pervasiveness, the precise neural circuits that govern this critical balance remain poorly characterized. A major barrier to progress lies in the technical challenge of tracking single neurons in relevant circuits as goal-directed behavior becomes habitual. Methods: neural interrogation. To functionally validate the behavioral paradigm, we employed chemogenetic inhibition of the dorsolateral striatum (DLS) in limited-trained and overtrained mice. Results: Our findings demonstrate that mice rapidly acquire lever pressing, exhibiting robust active/inactive lever discrimination, and comparable initial learning between limited and overtrained cohorts. Crucially, while mice with limited training readily reduced their lever-press behavior when the resulting outcome was devalued or omitted, overtrained mice displayed characteristic insensitivity to outcome devaluation and omission. Furthermore, chemogenetic inhibition of the DLS in overtrained mice restored sensitivity to both devaluation and contingency reversal, blocking habit expression and preserving goal-directed control. Conclusion: These results establish a paradigm for studying both goal-directed actions and habits in head-fixed mice and validate the DLS as a key neuronal substrate as previously demonstrated in freely moving models. This paradigm represents a vital methodological advancement that overcomes the technical barriers to longitudinal, cellular-level interrogation. By providing the optical stability necessary to track the same neuronal ensembles across acquisition and expression of habits, this platform enables investigations into the computational neural dynamics underlying goal-directed and habitual behaviors.