The work of various teams of scientists around the world walks the slippery line between biologically fertilized robots and cyborgs, faster than moral judgments and legislation.
Zhiqiang Yu’s team, from the Beijing Institute of Technology in China, completed a review of the results of studies on the use of biological neural networks created in the laboratory for use in robots and other artificial systems.
Yu and his colleagues reviewed the fundamentals of intelligence in biological neural networks in the laboratory, such as memory and learning. How can these biological neural networks be installed in robots through two-way communication, forming the so-called neural neural systems based on biological neural networks; What are the initial intelligent behaviors that these nervous systems display; And what are the current trends and future challenges facing neural systems based on biological neural networks.
Our human brain is a complex biological neural network consisting of billions of neurons, which not only gives rise to our intelligence but also to our consciousness. However, studying the brain as a whole is very difficult due to its complex nature. By growing a portion of brain cells in a petri dish, simpler biological neural networks such as minibrains (brain organoids) can be formed, making such networks easier to monitor and investigate. Yu argues that these mini-brains could provide valuable clues to the mysterious origins of normal consciousness and intelligence.
Interestingly, mini-brains are not only similar in structure to human brains, but can also learn and memorize information in a similar way, notes Yu. Specifically, these laboratory-created biological neural networks share the same basic structure as biological neural networks that typically form within the normal development of organisms. In either case, neurons are connected by synapses and display short-term memory. Moreover, these tiny brains can perform supervised learning and be trained to respond to cues from specific stimuli. Recently, it has been shown that biological neural networks created in the laboratory can even perform unsupervised learning tasks, including the separation of mixed incoming signals.
The capabilities of biological neural networks created in the laboratory are very interesting. However, it is not enough to develop such a small brain for consciousness and intelligence to arise. Our brain relies on our bodies to perceive, understand, and adapt to the outside world, and in the same way, these miniature brains need a body to interact with their environment. Robotics is an ideal candidate for this, which has given rise to a thriving interdisciplinary field at the intersection of neuroscience and robotics: that of neural systems based on biological neural networks.
The obvious conclusion, as the authors of a review of the study results point out, is that stable two-way communication is a prerequisite for these systems.
An artist’s recreation of a robot with living neurons. (Illustration: Jorge Monchi for NCYT from Amazings)
Yu and colleagues saw that the intelligent behaviors displayed by neural robot systems based on biological neural networks can be divided into two categories based on their dependence on computational power or on network flexibility. In computation-dependent behaviors, learning is not necessary, and the biological neural network simply acts as a data processor that generates specific neural activities in response to stimuli. However, for the second category, learning is a crucial process, as the biological neural network adapts to stimuli and these changes are necessary for the behaviors that the robot will acquire later or the way it will perform certain tasks later.
Yu’s team determined that one of the main challenges to overcome was the ability to fabricate 3D biological neural networks, making biological neural networks in the laboratory more similar to their natural counterparts.
Perhaps the most difficult aspect is how to train these biological neural networks embedded in robots, especially if the bodies of these are very different from the bodies of animals whose brain cells have been cultured.
And of course, there is the main challenge of all: unraveling the mystery of how consciousness and intelligence arise from the network of cells in our brain. This phenomenon is still far from the understanding of science. As Yu points out, when robots equipped with biological neural networks begin to proliferate, it will be possible to study the behavior of these entities (bots or cyborgs) and discover if there are key similarities with the behaviors of intelligent organisms. This may lead to difficult ethical dilemmas.
The review of the study findings is titled “An Overview of Laboratory Biological Neural Networks for Robot Intelligence”. It has been published in the academic journal Cyborg and Bionic Systems. (fountain: NCYT De Amazings)