Cognitive hyperplasticity drives insomnia
Huang, S.; Piao, C.; Zhao, Z.; Beuschel, C. B.; Turrel, O.; Toppe, D.; Sigrist, S. J.
Show abstract
Sleep is vital for maintenance of cognitive functions and lifespan across the animal kingdom. Here, we report our surprising findings that insomniac (inc) Drosophila short sleep mutants, which lack a crucial adaptor protein for the autism-associated Cullin-3 ubiquitin ligase, exhibited excessive olfactory memory. Through a genetic modifier screen, we find that a mild attenuation of Protein Kinase A (PKA) signaling specifically rescued the sleep and longevity phenotypes of inc mutants. Surprisingly, this mild PKA signaling reduction further boosted the excessive memory in inc mutants, coupled with further exaggerated mushroom body overgrowth phenotypes. We propose that an intrinsic hyperplasticity scenario genuine to inc mutants enhances cognitive functions. Elevating PKA signaling seems to serve as a checkpoint which allows to constrain the excessive memory and mushroom body overgrowth in these animals, albeit at the sacrifice of sleep and longevity. Our data offer a mechanistic explanation for the sleep deficits of inc mutants, which challenges traditional views on the relation between sleep and memory, and suggest that behavioral hyperplasticity, e.g., prominent in autistic patients, can provoke sleep deficits.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- Upstream open reading frames dynamically modulate CLOCK protein translation to regulate circadian rhythm and sleep 94%
- Eating breakfast and avoiding the evening snack sustains lipid oxidation 92%
- The Drosophila Amyloid Precursor Protein homologue mediates neuronal survival and neuro-glial interactions 92%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.