Search

The brain is arguably the most powerful computation system known. It is extremely efficient in processing large amounts of information and can discern signals from noise, adapt, and filter faulty information all while running on only 20 watts of power. The human brain's processing efficiency, progressive learning, and plasticity are unmatched by any computer system. Recent advances in stem cell technology have elevated the field of cell culture to higher levels of complexity, such as the development of three-dimensional (3D) brain organoids that recapitulate human brain functionality better than traditional monolayer cell systems. Organoid Intelligence (OI) aims to harness the innate biological capabilities of brain organoids for biocomputing and synthetic intelligence by interfacing them with computer technology. With the latest strides in stem cell technology, bioengineering, and machine learning, we can explore the ability of brain organoids to compute, and store given information (input), execute a task (output), and study how this affects the structural and functional connections in the organoids themselves. Furthermore, understanding how learning generates and changes patterns of connectivity in organoids can shed light on the early stages of cognition in the human brain. Investigating and understanding these concepts is an enormous, multidisciplinary endeavor that necessitates the engagement of both the scientific community and the public. Thus, on Feb 22-24 of 2022, the Johns Hopkins University held the first Organoid Intelligence Workshop to form an OI Community and to lay out the groundwork for the establishment of OI as a new scientific discipline. The potential of OI to revolutionize computing, neurological research, and drug development was discussed, along with a vision and roadmap for its development over the coming decade.

The brain is arguably the most powerful computation system known. It is extremely efficient in processing large amounts of information and can discern signals from noise, adapt, and filter faulty information all while running on only 20 watts of power. The human brain's processing efficiency, progressive learning, and plasticity are unmatched by any computer system. Recent advances in stem cell technology have elevated the field of cell culture to higher levels of complexity, such as the development of three-dimensional (3D) brain organoids that recapitulate human brain functionality better than traditional monolayer cell systems. Organoid Intelligence (OI) aims to harness the innate biological capabilities of brain organoids for biocomputing and synthetic intelligence by interfacing them with computer technology. With the latest strides in stem cell technology, bioengineering, and machine learning, we can explore the ability of brain organoids to compute, and store given information (input), execute a task (output), and study how this affects the structural and functional connections in the organoids themselves. Furthermore, understanding how learning generates and changes patterns of connectivity in organoids can shed light on the early stages of cognition in the human brain. Investigating and understanding these concepts is an enormous, multidisciplinary endeavor that necessitates the engagement of both the scientific community and the public. Thus, on Feb 22–24 of 2022, the Johns Hopkins University held the first Organoid Intelligence Workshop to form an OI Community and to lay out the groundwork for the establishment of OI as a new scientific discipline. The potential of OI to revolutionize computing, neurological research, and drug development was discussed, along with a vision and roadmap for its development over the coming decade.

Improvements in medical science have drastically increased survival for infants suffering from neonatal arterial ischemic stroke (NAIS). However, the failure to reverse the associated injuries has resulted in increased numbers of patients suffering from chronic neurodevelopmental disability. Potentially, stem cell-based therapy offers the greatest potential as a viable therapeutic tool not only for neuro-protection but importantly also for neural repair and restabilising lost connections. However, there is still vital investigations to be performed in the optimisation of cellular therapy as a medically effective tool, along with gaining a more comprehensive understanding of the mechanisms of actions and difference utility between different cell types. This research firstly aimed to develop a technically simple, high-throughput rodent model of NAIS affecting the cortex to be able to effectively test cellular therapy. Refined behavioural and cognitive testing procedures were also required to test the functional recovery offered by this therapy and this work aimed to develop and assess the validity of these methods. Ultimately, this work aimed to test the therapeutic efficacy human pluripotent cells differentiated to a cortical progenitor cells as a method of directly replacing damaged tissue. Moreover, this therapy was directly compared to the use of human umbilical cord blood cells (hUCBCs) as a therapy, with the aim of determining the relative value each of these therapies as potential treatments following NAIS. A technically simple, high-throughput rodent model of NAIS was developed. Utilising this model, two separate studies were conducted testing the therapeutic efficacy of pluripotent cells differentiated to cortical progenitor cells vs multipotent UBCs as a treatment of neonatal ischemic stroke. Holistically, the data indicated that grafts of cortical progenitors but not hUCBCs improved behavioural outcomes compared to ischemia alone. Moreover, a comparable lev