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Home » How Human And Insects Learn ‘Fly Model’ Demonstrates Similarities

How Human And Insects Learn ‘Fly Model’ Demonstrates Similarities

Fly model
Source : forbes

Even fruit fly craves a dose of the happy hormone, acc. to new study from the University of Sussex which shows how they’ll use dopamine to learn in similar manner to humans.

Informatics experts at the University of Sussex have developed a latest computational model that demonstrates long-sought-after link between insect and mammalian learning, as detailed in new paper published on (May 7, 2021) in Nature Communications.

Incorporating anatomical and functional data from recent experiments, Dr. James Bennett and colleagues modeled how the anatomy and physiology of the fruit fly’s brain can support learning consistent with the Reward Prediction Error (RPE) hypothesis.

The computational model indicates how dopamine neurons in area’ of a fruit fly’s brain, referred to as the mushroom body, can produce similar signals to dopamine neurons in mammals, and the way these dopamine signals can reliably instruct learning.

The academics believe that establishing whether flies also use prediction errors to find out could lead on to more humane animal research allowing researchers to-replace animals with more simple insect species for future studies into the mechanisms of learning.

By opening up new opportunities to review neural mechanisms of learning, the researchers hope the model could even be helpful in illuminating greater understanding of psychological state issues like depression or addiction which are underpinned by the RPE hypothesis.

Dr. Bennett, research fellow in University of Sussex’s School of Engineering and Informatics, said: “Using our computational model, we were ready to show that data from insect experiments didn’t necessarily conflict with predictions from the RPE hypothesis, as had been thought previously.

“Establishing a bridge between insect and mammal studies on learning may open up the likelihood to take advantage of the powerful genetic tools available for performing experiments in insects, and therefore the smaller scale of their brains, to form sense of brain function and disease in mammals, including humans.”

Understanding of how mammals learn has come long-way because of the RPE hypothesis, which suggests that associative memories are learned in proportion to how inaccurate they’re .

The hypothesis has had considerable success explaining experimental data about learning in mammals, and has been extensively applied to decision-making and psychological state illnesses like addiction and depression. But scientists have encountered difficulties when applying the hypothesis to learning in insects thanks to conflicting results from different experiments.

The University of Sussex research team created a computational model to point out how the main features of mushroom body anatomy and physiology can implement learning consistent with the RPE hypothesis.

The model simulates a simplification of the mushroom body, including different neuron types and therefore the connections between them, and the way the activity of these neurons promote learning and influence the choices a fly makes when certain choices are rewarded.

To further understanding of learning in fly brains, the research team used their model to form five novel predictions about the influence different neurons in mushroom-body wear learning and decision-making, within the hope that they promote future experimental work.

Dr. Bennett said: “While other models of the mushroom body are created, to the simplest of our knowledge no other model, until now has included connections between dopamine neurons and another set of neurons that predict and drive behavior towards rewards. for instance , when the reward is that the sugar content of food, these connections would allow the anticipated sugar availability to be compared with actual-sugar ingested, allowing more accurate predictions and appropriate sugar-seeking behaviors to be learned.

“The model can explain large-array of behaviors exhibited by fruit flies when the activity of particular neurons in their brains are either silenced or activated artificially in experiments. We also propose connections between dopamine neurons and other neurons within the mushroom body, which haven’t yet been reported in experiments, but would help to define even more experimental data.”

Thomas Nowotny, Professor of Informatics at the University of Sussex, said: “The model brings together learning theory and experimental knowledge in-a way that permits us to think systematically how fly brains actually work. The results show how learning in simple flies could be more same how we learn than previously thought.”

The findings are reported on Nature Communications