From womb to world: The development of learning, memory, and predictive adaptation from fetal life through the neonatal period
Abstract
Background: The developing fetus is increasingly recognized as an active participant in its own development rather than a passive recipient of sensory stimulation. Advances in fetal behavioral assessment, neuroimaging, electrophysiology, and developmental neuroscience have substantially expanded understanding of learning and memory before and immediately after birth.
Objective: To provide a comprehensive review of current evidence regarding fetal and neonatal learning and to examine the neural, behavioral, and developmental mechanisms that support the emergence of learning during the prenatal and early postnatal periods.
Methods: Findings from human and animal research were reviewed across multiple domains of learning, including habituation, sensitization, classical conditioning, exposure learning, sensory adaptation, memory formation, multisensory integration, and early predictive processes. Evidence from behavioral, physiological, and neurodevelopmental studies was integrated to provide a developmental framework for understanding early learning.
Results: Convergent evidence indicates that multiple forms of learning emerge during fetal life and continue into the neonatal period. Fetuses demonstrate habituation, auditory recognition, chemosensory learning, sensorimotor adaptation, and memory for repeated experiences. Prenatal exposure influences neonatal responses to voices, language, music, odors, tastes, and patterns of sensory stimulation. These capacities develop…
Read the paper
Related studies
- Diarylethenes for Memories and Switches
- Long-Term Potentiation and Memory
- Social Memory Studies: From “Collective Memory” to the Historical Sociology of Mnemonic Practices
- The Cognitive Neuroscience of Working Memory
- Memory aging and brain maintenance
- Effector and Memory CTL Differentiation
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.