Cognition, learning and memory in the invertebrate brain

Invertebrate nervous systems have played a foundational role in establishing cellular and circuit-level mechanisms of learning and memory, from habituation and sensitization in Aplysia to associative learning circuits in the Drosophila mushroom body.Whole-brain connectomes for Drosophila now reveal how connectivity motifs within the mushroom body shape learning hierarchies, while macroscale connectivity mapping and immediate early gene profiling in cephalopods are beginning to resolve how the octopus vertical lobe supports associative and non-associative memory.Behavioral studies further show that cephalopods and arthropods including insects and spiders, exhibit capacities such as reversal learning, social transmission of novel behaviors, numerosity discrimination, and working-memory-dependent route planning, enabling flexible, context-dependent behavioral updating.These advances establish invertebrates as powerful comparative systems for investigating how learning and memory are implemented across evolutionarily distinct neural architectures.This Research Topic aims to identify the neural, cellular, and molecular mechanisms of learning and memory across invertebrate taxa, by integrating well-defined behavioral paradigms with circuit-level and computational analyses.We encourage contributions applying connectomics, in vivo calcium imaging, voltammetric neuromodulator measurement, and automated behavioral analysis to link circuit structure to function.Emphasis is placed on cephalopods and arthropods, including insects and spiders, where higher-order neuropils, the vertical lobe in cephalopods, the arcuate body in spiders, and the mushroom body and central complex in insects, provide comparative frameworks for understanding memory system organization.At the circuit and systems levels, we seek studies that characterize identified cell types, synaptic connectivity, and neuromodulatory regulation, including dopaminergic, octopaminergic, serotonergic, and peptidergic signaling, during reinforcement and conditioning.We welcome investigations of synaptic plasticity and cell-intrinsic memory mechanisms, including activity-dependent signaling, gene expression, intrinsic excitability, and long-term memory stabilization, as well as studies of multimodal sensory integration in context- and state-dependent recall.Beyond core mechanisms, contributions addressing individual variability in learning performance, developmental and experience-dependent plasticity, and evolutionary analyses of convergent and divergent circuit solutions are encouraged. Computational models that link circuit architecture to learning dynamics and generate testable predictions are also within scope. By integrating behavioral, circuit-level, molecular, and computational approaches, this Research Topic aims to define generalizable principles of learning and memory while accounting for diversity in invertebrate neural organization.Topics of Interest· Behavioral paradigms for associative and non-associative learning, including habituation, sensitization, reversal learning, and flexible updating of learned associations.· Circuit-level organization of learning and memory systems, with emphasis on identified cell types and connectivity motifs revealed by electrophysiology and connectomics.· Functional contributions of specialized neuropils, mushroom bodies, vertical lobes, arcuate bodies, and central complex, to memory encoding, consolidation, and retrieval.· Neuromodulatory control of learning dynamics, including dopaminergic, octopaminergic, serotonergic, and peptidergic signaling during reinforcement and conditioning.· Cellular and molecular mechanisms of synaptic plasticity, including activity-dependent signaling, gene expression, intrinsic excitability, and long-term memory stabilization.· Integration of multimodal sensory inputs in memory-guided behavior, including context-dependent and state-dependent modulation of recall.· Individual variability in learning performance and its neural and circuit-level determinants.· Developmental and experience-dependent plasticity shaping circuit architecture and learning capacity.· Evolutionary and comparative organization of memory systems across invertebrate lineages, including convergent and divergent circuit solutions.· Computational and theoretical models linking circuit architecture to learning dynamics, memory capacity, and decision-making. Topic editors: Clare C Rittschof, Eirik Søvik, Jennifer Ann Mather Source: https://www.frontiersin.org/research-topics/84360/cognition-learning-and-memory-in-the-invertebrate-brain