Unraveling the Potential of Brain-Organoid Learning Capabilities through Computational Models-Mental health AI
- Viora-AI
- Dec 12, 2024
- 4 min read
Maria Jahnert, MSc¹˒³; Ayman Anika²˒³; Kerem Jumalyyev³;
¹ The Rhenish Friedrich Wilhelm University of Bonn, Bonn, Germany
² Independent University, Bangladesh (IUB), Dhaka, Bangladesh
³ Viora-AI: Mental Health AI Co; Berlin, Germany
Abstract
Brain organoids refer to miniature models of human brain tissues grown in vitro. These three-dimensional (3D) neural tissues are grown from stem cells and can be used to study the early stages of development of the human brain, test drugs – and by extension, learning capabilities – as organoids are essentially made from living cells. Developments in computational modelling have made it feasible to examine and stimulate brain organoid activity. Therefore, by utilising computational modelling, we can understand the learning capabilities of brain organoids. The article details the creation of computational models designed precisely for brain organoids. By analysing the challenges and future implications, the study discusses how computer models can bridge the gap between experimental biology and theoretical neuroscience.
Introduction
Often, many experts have described the human brain as the most complex of the universe. It is a labyrinth of neurons and made up of countless synaptic connections. Though researchers have been trying to understand its learning mechanism for years now, much remains to be understood and discovered. In this regard, brain organoids have displayed the potential to replicate the synaptic connections and neural activity of the human brain.
One research study, published in Nature Reviews Neurology, detailed that the three-dimensional human organoids offer a promising avenue to address the. limitations of traditional animal models by providing a closer approximation to human biology for disease modelling (Eichmüller & Knoblich, 2022).
Therefore, brain organoids can mimic key aspects of the brain. Now, scientists have started probing whether computational models can help us decode and in turn, improve the capabilities of organoids. A study has shown that computational models can indeed play a useful role by decoding the intricate dynamics of brain organoids – consequently, aiding researchers to simulate, predict, and interpret organoid behaviour (Pasca, 2019).
In this article, we explore two fundamental questions: What are brain organoids? Can
