Learning and Synaptic Plasticity in 3D Bioengineered Neural Tissues

Learning is integral to an organism's capacity to adapt to complex changes within its environment. Our understanding of the fundamental mechanisms that underlie learning within biological systems has historically been reliant upon the measurement of established nervous systems and their dissociated parts. However, advances in biomaterials and tissue engineering have made it possible to design and construct artificial neural substrates de novo , building iterative brain models to identify functional cause‐effect relationships in vitro . And with the emergence of increasingly complex physiological response patterns among organoids and other laboratory‐grown neural tissues, it has become relevant to ask what minimal features of cognition, if any, might be present within said substrates. One approach toward a study of minimal cognition in vitro is to operationalize a basic form of learning and assess information‐processing features associated with the system under study. In the present work, we demonstrate that a 3D bioengineered neural tissue model can be habituated with patterned injections of current. Evoked‐potentials following injections displayed features of non‐associative learning including spontaneous recovery which was transient and reversible. Massed and distributed applications of current contributed to differential effects upon the expression of immediate early genes (IEGs) and, in particular, those regulating early growth response (EGR) transcriptional factors. These are known to facilitate synaptic plasticity and govern memory formation. We conclude that this experimental demonstration of rudimentary stimulus‐response patterns represents a first step toward a study of minimal cognition in bioengineered 3D neural tissues. Next steps are discussed with an emphasis on current challenges and limitations to in vivo approaches in the cognitive sciences.