The belief that some people are born “gifted” — and others are genetically programmed to be mediocre — is deeply rooted in our culture. However, the influence of genes on learning is not straightforward. Authors [see attached article & editorial] describe how learning can be enhanced in songbirds, by “tailoring teaching strategies” to match the genetic differences of individuals. This study [see attached article] suggests that there are not necessarily ‘high-quality’ or ‘low-quality’ gene networks when it comes to learning; instead, certain sets of genes are better suited, or worse suited, for particular learning environments. Hence, this topic fits the gene-environment interactions theme of these GEITP pages: “the environmental signal” is a bird listening to songs of other birds; “the genes responding to these signals” depends on the genetic predisposition of the individual bird.
These GEITP pages have often discussed polygenic risk scores (PRS). PRS are estimates of an individual’s tendency to display a given trait — taking into account the entire genetic architecture (i.e. underlying genetic basis of a phenotypic trait, including everything that might cause variability) of that individual. These scores have been viewed by some as a way to assess a baby’s genetic potential to develop complex disorders such as schizophrenia; PRS have also been used to assess educational success, and might be able to predict ~13% of the variation in number of years of schooling that individuals in a population will complete. But we are a long way from a genomic analysis that could direct specific educational investments, or predict which children might benefit the most. Solving this problem in humans is daunting — because we cannot experimentally control genes, and environments, simultaneously.
Interactions between genetics and learning are not unique to humans. Young songbirds acquire their vocal repertoire by imitating musical notes produced by adult songbirds. For birds, as for humans, learning is a social and cultural process — as in spoken language, vocal learning across generations produces local cultures of song dialects. Accurate learning is crucial for birds because those that do not acquire the local dialect are less likely to attract mates. In other words, “accurate learning of songs that attract birds of the opposite sex” is a trait that is important to survival of the species.
Authors decided to pin down this relationship in more detail, using a population of Bengalese finches (known to have large variations in song-learning abilities). First, they compared how well finches — tutored by their own parents — learned a song, compared with (unrelated) birds whose eggs had been moved into that nest before hatching. When birds were tutored by their own fathers, they generally learned better than did fostered birds, suggesting that a match in genetic propensity for learning is pivotal to how well birds learn songs. Authors found that cross-fostered birds did learn well — if their adoptive tutor had a song that was similar in tempo to that of their own parents. This result indicated that an interaction between genes and experience explains much of the variation in learning outcomes. It seems that certain birds are genetically tuned to learn and produce slow songs, whereas others are genetically “wired” for fast songs. Giving a “slow” bird a fast tutor is not advantageous; the reverse is also true.
Authors [see attached article] therefore used both cross-fostering and computerized instruction (with synthetic songs) to validate that matching the tutor song to individual predispositions can improve learning across a variety of genetic backgrounds. Moreover, authors found that optimizing instruction in this fashion can compensate for learning differences across individuals that might otherwise be construed as “genetically determined mediocrity”. These results demonstrate potent, synergistic interactions between genetic predisposition (genes) and social experience (the environment) in shaping the ability to sing songs (that help in sexual reproduction and survival of the species), and suggest the likely importance of such interactions for other complex learned behaviors.
eLife 8: e47216 (2019) & editorial in Nature 14 Nov 2019; 575: 290-291