Many neuroscientists, medical researchers and engineers specializing in artificial intelligence have attempted to understand the neural mechanisms underlying learning. While studies have revealed some essential aspects of these mechanisms, many questions remain unanswered.
Jeremy Gunawardena, a researcher at Harvard Medical School, recently introduced a new view of learning that combines ideas from cognitive psychology with biological observations. His paper, published in Procedures of the IEEEhighlights some aspects of learning that can distinguish biological organisms from computers and machines.
“My interest in learning has partly arisen from a study we conducted earlier in which we showed that the unicellular protozoa, Stentor roeseli, exhibits a complex hierarchy of avoidance behavior when irritated by a beam of particles,” Jeremy Gunawardena, one of the researchers who conducted the study, told Phys.org. first described by American biologist Herbert Spencer Jennings around 1900, but it was considered non-reproducible.”
In their previous studies, Gunawardena and his colleagues showed that the Jennings’ findings were correct. More specifically, they found that a unicellular is potentially capable of much more complex learning behavior than previously thought possible.
Inspired by these findings, Gunawardena teamed up with one of his colleagues at Harvard, Sam Gershman, who has done extensive research on the mechanisms of learning. Their work specifically examined how learning takes place in individual cells†
“The collaboration with Sam Gershman led to my research paper in Procedures of the IEEEGunawardena said. “The primary goal was to propose a definition of learning in information-theoretical terms that was not limited to animals like us, and to provide evidence from various domains in biology for the existence and significance of learning outside the nervous system†
In his recent paper, Gunawardena describes learning as a broad and universal process involving all living systems, including various animal species, as well as potential plants. Thus, he believes that a reliable characterization and description of this process could inform research in various fields. For example, it could make a major contribution to the field of systems biology, and contribute to existing theoretical perspectives, which largely focus on molecules and their organization.
“We tend to think of cells as complex molecular machines,” Gunawardena said. “The idea that cells are able to learn – to form internal models of their external environment and use those models to guide their behavior – gives them a form of ‘agency’ that most machines lack and that brings us closer. at what it means to be “alive.” Finally, unraveling these ‘internal models’ could be very useful if we want to exploit cells in a therapeutic way, for example as we are trying to do in immunotherapy.”
If confirmed experimentally, the interesting ideas introduced by Gunawardena could provide a new and valuable perspective on how countless living organisms learn and survive. Several studies have already suggested that plants or specific cells, such as T cells (ie critical components of the immune system), can “learn” based on the stimuli they come into contact with.
“We now have to show that this perspective is real through the experimental work and this is what the collaboration with Sam Gershman is all about,” added Gunawardena. “Right now we are focusing on one of the simplest forms of learning, habituation, which is extremely commonly observed in biology, from animals like us to individual cells, and which exhibits some characteristic features, despite vastly different underlying mechanisms. However, we still do not have a theory that explains this universality, nor do we have convincing explanations about how habituation works on the molecular levelthat’s what we’re trying to do now.”
Jeremy Gunawardena, Learning Beyond the Brain: Integrating Cognitive Science and Systems Biology, Procedures of the IEEE (2022). DOI: 10.1109/JPROC.2022.3162791
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