Information processing-like phenotype of human brain organoids

Human brain organoids recapitulate key physiological features and functions of the human brain and hold remarkable potential for studying neurological diseases. Despite clinical evidence suggesting that neurodegenerative diseases impair the information-processing ability of the human brain, the capacity of brain organoids for information processing and its relationship to neural network function remain largely unexplored. Here, we test and quantify information-processing-like properties of human cortical organoids using a task-based functional phenotyping framework (Brainopheno). We demonstrate the pattern-processing-like phenotype of cortical organoids through the representation and classification of evoked neural activities in response to distinct spatial input stimulation patterns via a microelectrode array (MEA) system. Moreover, this functional phenotype emerges with network maturation and is disrupted by pharmacological perturbations, linking classification performance to the functional integrity of organoid neural networks (ONNs). Importantly, this functional phenotype also reveals functional deficits in ONNs altered by a familial Alzheimer's disease (AD)-associated gene mutation (APP) and by monocytes from patients with sporadic AD. This work may establish a new quantifiable functional phenotype of neural organoids and provide a framework to bridge molecular and cellular profiles with neural circuit function for basic neurology, disease phenotyping, and therapeutic development.