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Alzheimer's disease (AD) is an incurable neurodegenerative disorder and the leading cause of death among older individuals. Available treatment strategies only temporarily mitigate symptoms without modifying disease progression. Recent studies revealed the multifaceted neurobiology of AD and shifted the target of drug development. Established animal models of AD are mostly tailored to yield a subset of disease phenotypes, which do not recapitulate the complexity of sporadic late-onset AD, the most common form of the disease. The use of human induced pluripotent stem cells (HiPSCs) offers unique opportunities to fill these gaps. Emerging technology allows the development of disease models that recapitulate a brain-like microenvironment using patient-derived cells. These models retain the individual's unraveled genetic background, yielding clinically relevant disease phenotypes and enabling cost-effective, high-throughput studies for drug discovery. Here, we review the development of various HiPSC-based models to study AD mechanisms and their application in drug discovery.

Neural circuits are responsible for the brain's ability to process and store information. Reductionist approaches to understanding the brain include isolation of individual neurons for detailed characterization. When maintained in vitro for several days or weeks, dissociated neurons self-assemble into randomly connected networks that produce synchronized activity and are capable of learning. This review focuses on efforts to control neuronal connectivity in vitro and construct living neural circuits of increasing complexity and precision. Microfabrication-based methods have been developed to guide network self-assembly, accomplishing control over in vitro circuit size and connectivity. The ability to control neural connectivity and synchronized activity led to the implementation of logic functions using living neurons. Techniques to construct and control three-dimensional circuits have also been established. Advances in multiple electrode arrays as well as genetically encoded, optical activity sensors and transducers enabled highly specific interfaces to circuits composed of thousands of neurons. Further advances in on-chip neural circuits may lead to better understanding of the brain.