Feedback Loop Helps Brain Teach Itself Quickly

Biological Strategy

Zebra finch

Leo Zsembik

Image: Julie Burgher / CC BY NC ND - Creative Commons Attribution + Noncommercial + NoDerivatives

Send Electrical/Magnetic Signals

Some living systems send electric or magnetic signals, often as a way of communicating with other living systems or sensing their environment. Electric and magnetic signaling requires specialized organs, and thus appear to be less common than other types of signals, such as audible and visual ones. Electric fish produce very sophisticated electric signals that not only help them find mates, but are also sensitive enough to enable them to distinguish individual fish.

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Learn

Living systems obtain information from their environment and use it to find mates and resources, and to escape threats. Some reactions to gathered information are instinctual or innate behaviors, not based on previous experiences. But other reactions are based on previous experiences, which means that, at some level, the living system is learning. Learning can involve a living system passing information to another living system, or a living system obtaining information and using it in a feedback loop. That information can include knowledge, experience, behavior, and skills. Learning takes place when information that is new to the recipient is used to modify existing behavior or skills. The making and use of tools by some species of birds and mammals is a learned behavior. If a chimpanzee uses a stick to successfully get ants out of an ant mound and continues to do so, it has learned that behavior. If another chimpanzee observes this technique and replicates it, it has learned from the first chimp.

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Encode/Decode

Organisms are constantly taking in new information, processing it, and storing that information as memories. Sensory information and stimuli such as sounds, smell, time, and spatial organization are encoded along with our memories. Whether we’re learning a new skill or repeating a task we’ve done before, we can easily call upon and decode that information when we need it.

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Differentiate Signal From Noise

The environment surrounding any living system is full of signals, such as smells, sounds, electricity, magnetism, and more. Too many signals at once can be overwhelming, making it difficult to locate and react to any particular signal. To address this, living systems must differentiate among all signals, or “noise,” so they can focus on those they really need. During mating season, for example, male frogs gather close together in large groups to call for females. Despite their overwhelming, collective noise, females are able to find a particular male whose call is attractive to her. This is because the males use desynchronized calling, enabling individual recognition.

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Transduce/Convert Signals

Sometimes a signal, such as sound or vibration, reaches a living system and needs to be converted into a different, usable form. This requires converting from one type of energy form to another. For example, organisms with eyes have photoreceptors at the back of the eyes that convert light into electrical pulses. These pulses travel to the brain and allows it to register color, shape, and detail.

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Birds

Class Aves (“bird”): Eagles, hawks, sparrows, parrots

Birds are evolutionary engineering marvels. They are descended from dinosaurs, but are far from our idea of heavy, scaly reptiles. Of the specific adaptions that set them apart, most notable is flight—although some mammals can fly, birds take the prize for abundance in the skies. Many birds have hollow, lightweight skeletons and specially-designed wings to help them stay aloft. They also have feathers made of keratin that help them stay warm, attract mates, and improve navigation and aerodynamics in flight. In contrast to their dinosaur ancestors, they lack true teeth and have replaced them with specialized beaks and bills.

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Two brain regions in zebra finches act as "student" and "tutor" to learn songs efficiently.

For zebra finches, music is what determines whether they will keep their genetic legacy alive or be erased from the gene pool. That makes the month during which a zebra finch learns to sing the song demonstrated by its father the most important month of its life. With such high stakes, finding the perfect tutor is essential. As it turns out, the finch’s own brain might be the best teacher of all. Scientists have found that one part of the brain, deemed the “tutor,” teaches another part of the brain, the “student,” in a coordinated effort to improve performance of the finch’s song.

Birds, like musicians, hone their songs through practice. Zebra finches sing, compare what they hear to a memory of the song, and adjust the parts that are not quite right. The student part of the brain changes its control on the respiratory muscles used to sing to make adjustments to the song. However, it is the tutor part of the brain that decides what these changes should be.

Much like in humans, each brain region has its own learning style. The criteria that help a region learn best follow a set of rules that facilitate communication between neurons. These rules are vital for learning, and different parts of the brain have different rules. If the tutor region sends information to a student region based on the wrong set of criteria, the performance will be dreadful. It would be like trying to teach in French to a class that only understands Russian.

In this circuit, however, it is not only the student that learns. The teaching signal must balance its lessons on multiple levels. Sometimes, it is best to correct an erroneous sound immediately. Other times, a broader correction on the song as a whole is more helpful. The tutor part of the brain receives feedback about how well it is teaching and adapts accordingly. Simply put, while the tutor is helping the student learn to sing, the tutor is also learning how to be a more effective instructor. Given the rules that the student region needs to succeed, the teaching signal adapts within those constraints to improve the zebra finch’s song.

What works in a zebra finch’s brain can also lead to success in the human classroom. Consistent feedback on the effectiveness of an instructor’s efforts towards a student, and the ability to make adjustments accordingly, can lead to more effective teaching than when only the student’s performance is evaluated, and the teaching method remains static.

Four of zebra finches perched in a tree.

Image: Jim Bendon / CC BY SA - Creative Commons Attribution + ShareAlike

Adult zebra finches

Image: Julie Burgher / CC BY NC ND - Creative Commons Attribution + Noncommercial + NoDerivatives

Zebra finch singing

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Last Updated September 16, 2020

References

“An interesting question is whether and under what conditions such an architecture is more effective than a single-step model. Possibly, having two stages is better when a single tutor area is responsible for training several different dedicated controllers, as is likely the case in motor learning. It would then be beneficial to have an area that can learn arbitrary behaviors, perhaps at the cost of using more resources and having slower reaction times, along with the ability to transfer these behaviors into low-level circuitry that is only capable of producing stereotyped motor programs. The question then arises whether having more than two levels in this hierarchy could be useful, what the other levels might do, and whether such hierarchical learning systems are implemented in the brain.“

Tesileanu et al. 2017: 15

Journal article

Rules and mechanisms for efficient two-stage learning in neural circuits

eLife | 04/04/2017 | Tiberiu Tesileanu, Bence Olvenczky, Vijay Balasubramanian

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Reference

“Over eons, structures in the brain have adapted to each other to produce function. I suspect it’s just the case that brain areas are adapted to send messages to each other in ways that make themselves work well. I think it’s a new handle or lever for investigation to think about that: How a tutor area of the brain should structure its signals so that a student area can profit from the signal as best as possible given its constraints and its learning rule.”

Report

How songbirds teach themselves songs

Science Daily | 04/04/2017 | Vijay Balasubramanian

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Reference

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