Advancing methods in learning and memory neurophysiology

Memory is classically defined as a complex cognitive process that involves multiple stages, including learning, memory consolidation and storage, retrieval, reconsolidation, and forgetting. As described by Eric Kandel, neurobiological research in this field over the past four decades has progressed through phases of increasing complexity, starting with the cellular biology of synaptic plasticity, advancing to the molecular mechanisms, then exploring genetic regulation in mammals, and culminating in systems-level approaches that integrate circuits and behavior. In recent years, the field has undergone another important transition. Beyond neurons and synapses, non-neuronal cell types, including astrocytes, oligodendrocytes, microglia, and pericytes, have emerged as critical contributors to learning and memory processes. At the same time, emphasis has increasingly shifted away from isolated cellular players toward their dynamic interactions, embracing a systems-centered view in which activity-dependent gene expression, molecular signaling cascades, and structural remodeling converge to drive circuit reorganization and memory function.

Advances in the memory field over recent years have been closely paralleled and supported by remarkable methodological innovations. New recording techniques, molecular tools, computational analyses, and experimental designs have not only increased the resolution of scientific findings and expanded the range of questions that can be addressed but have also enabled researchers to pose more challenging questions and test bold ideas. This Research Topic aims to bring together contributions that showcase novel methods, refined protocols, technological developments, and analytical frameworks that allow for a deeper and more precise investigation of learning and memory mechanisms across species and levels of analysis.

We welcome submissions presenting innovative experimental tools, methodological approaches, refined protocols, integrated multimodal techniques, and open, reproducible workflows specifically applied to the study of learning and memory. Contributions are encouraged from all species and experimental models, and across both healthy and pathological conditions, with no restrictions on animal models or disease states. Methods of interest include, but are not limited to:

1. Methods for assessing learning and memory in animal models
• Standardized cross-assay behavioral testing (olfactory conditioning, reward learning, aversive learning)
• Machine-learning-based scoring of fly behavior
• High-throughput genetic screening for memory phenotypes
• Open-source tools for automated tracking and stimulus delivery

2. Neurostimulation and neuromodulation methods for memory research
• Closed-loop deep brain stimulation platforms
• Non-invasive stimulation (tES, TMS) combined with behavioral memory tasks
• Stimulation-triggered plasticity mapping
• Standardization of stimulation parameters relevant to memory improvement
• Multimodal recording during neuromodulation (LFP, calcium imaging, fMRI)

3. Neurovascular imaging and perfusion-based methods for studying memory
• Advanced MRI techniques (ASL, DCE-MRI) to monitor perfusion–memory relationships
• Microvascular imaging of hippocampal function
• Standardized ischemic injury memory paradigms (MCAO, reperfusion models)
• Quantitative mapping of neurovascular recovery during learning tasks

4. New analytical methods for multi-pathway mechanisms of memory
• High-sensitivity quantification of synaptic remodeling (spine imaging, 3D reconstructions)
• Novel assays for microglial/macrophage polarization states
• High-throughput screening for learning-associated molecular signatures
• Integrated molecular/behavioral phenotyping workflows

5. Epigenomic and single-cell multi-region methods for memory research
• Single-cell ATAC-seq and multi-omics approaches for memory circuits
• Multi-region epigenomic mapping (hippocampus, cortex, amygdala)
• Chromatin accessibility profiling during learning tasks
• Computational pipelines for epigenetic data integration
• Methods to study epigenetic plasticity during memory formation or impairment

6. Organoid, microphysiological, and bioengineered models of learning and memory
• Brain organoids as models for synaptic plasticity
• Microphysiological chip systems mimicking circuit-level learning
• Synthetic materials exhibiting “memory-like” behavior for neuromorphic modeling
• Methods to stimulate, record, and analyze organoid learning activity

7. Methods to study metabolism–memory links
• Metabolomics combined with memory behavior assays
• Hormonal and circulation-based biomarkers of memory function
• Nutritional intervention protocols for learning and memory studies
• Standardized stress, sleep-deprivation, and metabolic-challenge paradigms

8. Advanced functional connectivity imaging and analysis for memory
• fMRI and mesoscopic imaging pipelines optimized for memory tasks
• Longitudinal tracking of functional connectivity during learning stages
• Neural network modeling of memory circuits
• Machine-learning classifiers for detecting memory impairment from imaging data

9. Behavioral methodology innovation in memory testing
• High-throughput behavioral tracking using neural networks
• VR-based spatial learning tasks
• Automated versions of Morris water maze, object recognition, and avoidance learning
• Sensor-rich cages for continuous cognitive and behavioral monitoring