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1. Brain Size, Metabolism, and Social Evolution

   https://doi.org/10.3389/fphys.2021.612865  

   Coto, Zach N.; Traniello, James F. (February 2021, Frontiers in Physiology)

   null (Ed.)
2. Metabolism modulates network synchrony in the aging brain

   https://doi.org/10.1073/pnas.2025727118  

   Weistuch, Corey; Mujica-Parodi, Lilianne R.; Razban, Rostam M.; Antal, Botond; van Nieuwenhuizen, Helena; Amgalan, Anar; Dill, Ken A. (October 2021, Proceedings of the National Academy of Sciences)

   Brain aging is associated with hypometabolism and global changes in functional connectivity. Using functional MRI (fMRI), we show that network synchrony, a collective property of brain activity, decreases with age. Applying quantitative methods from statistical physics, we provide a generative (Ising) model for these changes as a function of the average communication strength between brain regions. We find that older brains are closer to a critical point of this communication strength, in which even small changes in metabolism lead to abrupt changes in network synchrony. Finally, by experimentally modulating metabolic activity in younger adults, we show how metabolism alone—independent of other changes associated with aging—can provide a plausible candidate mechanism for marked reorganization of brain network topology. 

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3. Coupling of activity, metabolism and behaviour across the Drosophila brain

   https://doi.org/10.1038/s41586-021-03497-0  

   Mann, Kevin; Deny, Stephane; Ganguli, Surya; Clandinin, Thomas R. (May 2021, Nature)

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4. Mitochondrial Metabolism in Astrocytes Regulates Brain Bioenergetics, Neurotransmission and Redox Balance

   https://doi.org/10.3389/fnins.2020.536682  

   Rose, Jordan; Brian, Christian; Pappa, Aglaia; Panayiotidis, Mihalis I.; Franco, Rodrigo (November 2020, Frontiers in Neuroscience)

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5. Brain energy metabolism as an underlying basis of slow and fast cognitive phenotypes in honeybees

   https://doi.org/10.1242/jeb.247835  

   Tait, Catherine; Chicco, Adam J; Naug, Dhruba (September 2024, Journal of Experimental Biology)

   ABSTRACT In the context of slow–fast behavioral variation, fast individuals are hypothesized to be those who prioritize speed over accuracy while slow individuals are those which do the opposite. Since energy metabolism is a critical component of neural and cognitive functioning, this predicts such differences in cognitive style to be reflected at the level of the brain. We tested this idea in honeybees by first classifying individuals into slow and fast cognitive phenotypes based on a learning assay and then measuring their brain respiration with high-resolution respirometry. Our results broadly show that inter-individual differences in cognition are reflected in differences in brain mass and accompanying energy use at the level of the brain and the whole animal. Larger brains had lower mass-specific energy usage and bees with larger brains had a higher metabolic rate. These differences in brain respiration and brain mass were, in turn, associated with cognitive differences, such that bees with larger brains were fast cognitive phenotypes whereas those with smaller brains were slow cognitive phenotypes. We discuss these results in the context of the role of energy in brain functioning and slow–fast decision making and speed accuracy trade-off. 

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