Preclinical computational psychiatry: Linking formal and quantitative models, behavior, and neural circuits

Computational psychiatry has emerged as a powerful framework for understanding the mechanistic foundations of psychiatric disorders by bridging mathematical models of decision-making, learning, and reward processing with clinical observations. However, most computational approaches remain descriptive, capturing behavioral patterns without elucidating the underlying neural substrates. Preclinical research uniquely enables direct investigation of neural circuits while maintaining controlled behavioral paradigms and quantifiable metrics. By combining formal computational models with animal behavior and circuit-level neuroscience, we can identify the specific neurobiological mechanisms disrupted in psychiatric conditions. This integrative approach provides crucial mechanistic insights that cannot be obtained through clinical studies alone, offering a pathway to understand how dysfunctional neural computations translate to pathological behavior.This Research Topic addresses a critical gap: the lack of integrated frameworks connecting computational models, behavioral phenotypes, and neural circuit function in preclinical psychiatry research. Current studies often operate in silos, with computational modelers, behavioral neuroscientists, and neurophysiologists working independently. We aim to foster collaboration that bridges these domains to establish a coherent understanding of how disrupted computation at the circuit level manifests as psychiatric symptoms.The Research Topic will showcase work that:- Develops and validates formal/quantitative models using preclinical behavioral data- Identifies the neural circuit mechanisms implementing these computational processes- Links circuit dysfunction to psychiatric-like behaviors in animal models- Translates preclinical insights toward predicting clinical phenotypes and treatment responsesBy integrating these perspectives, contributors will advance our ability to identify therapeutic targets and accelerate the development of mechanism-based interventions for psychiatric disorders. We welcome articles addressing the intersection of computational modeling, behavior, and neural circuits in preclinical psychiatry. Specific themes include:- Computational models of psychiatric-relevant behaviors: decision-making, risk assessment, social cognition, addiction, anxiety, and reward processing- Circuit dissection of computational processes: using optogenetics, chemogenetics, electrophysiology, and imaging to map neural implementations of formal models- Behavioral phenotyping: establishing quantifiable behavioral readouts that reflect computational dysfunction- Translational links: connecting preclinical findings to clinical biomarkers and psychiatric conditions- Cross-species validation: extending preclinical insights toward clinical predictions- Methodological innovations: novel approaches for integrating computational, behavioral, and neurobiological data- Specific psychiatric models: depression, anxiety, schizophrenia, addiction, autism spectrum disorders, and other conditionsContributions should demonstrate rigorous experimental design, clear mechanistic insights, and explicit connections between computation, behavior, and neural circuits. Topic editors: Peter Erdi, Ido Maor, Saranya Jayapalan, Giulia Battilotti, Syeda Shamaila Zareen Source: https://www.frontiersin.org/research-topics/85322/preclinical-computational-psychiatry-linking-formal-and-quantitative-models-behavior-and-neural-circuits