bioRxivNeurosciencePreprint
Thyroid hormone rewires cortical circuits to coordinate body-wide metabolism and exploratory drive
Daniel R. HochbaumiD, Alexandra C. Dubinsky, Hannah C Farnsworth, Lauren Hulshof, Giona KleinbergiD, Amanda UrkeiD, Wengang WangiD, Richard HakimiD, Keiramarie RobertsoniD, Canaria Park, Alyssa Solberg, Yechan Yang, Caroline Baynard, Naeem M. NadafiD, Celia C. BeroniD, Allison E. GirasoleiD, Lynne ChantranupongiD, Marissa D. Cortopassi, Shannon Prouty, Ludwig GeistlingeriD, Alexander S. BanksiD, Thomas S. ScanlaniD, Michael E. GreenbergiD, Gabriella L. BoultingiD, Evan Z. MacoskoiD, Bernardo Luis SabatiniiD
- Citations
- 5
Abstract
Animals adapt to varying environmental conditions by modifying the function of their internal organs, including the brain. To be adaptive, alterations in behavior must be coordinated with the functional state of organs throughout the body. Here we find that thyroid hormone-- a prominent regulator of metabolism in many peripheral organs-- activates cell-type specific transcriptional programs in anterior regions of cortex of adult mice via direct activation of thyroid hormone receptors. These programs are enriched for axon-guidance genes in glutamatergic projection neurons, synaptic regulators across both astrocytes and neurons, and pro-myelination factors in oligodendrocytes, suggesting widespread remodeling of cortical circuits. Indeed, whole-cell electrophysiology recordings revealed that thyroid hormone induces local transcriptional programs that rewire cortical neural circuits via pre-synaptic mechanisms, resulting in increased excitatory drive with a concomitant sensitization of recruited inhibition. We find that thyroid hormone bidirectionally regulates innate exploratory behaviors and that the transcriptionally mediated circuit changes in anterior cortex causally promote exploratory decision-making. Thus, thyroid hormone acts directly on adult cerebral cortex to coordinate exploratory behaviors with whole-body metabolic state.
- organism: mouse
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
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