@article {67828, title = {A brainstem integrator for self-localization and positional homeostasis}, journal = {Cell}, volume = {185}, year = {2022}, month = {2022 Dec 22}, pages = {5011-5027.e20}, abstract = {

To accurately track self-location, animals need to integrate their movements through space. In amniotes, representations of self-location have been found in regions such as the hippocampus. It is unknown whether more ancient brain regions contain such representations and by which pathways they may drive locomotion. Fish displaced by water currents must prevent uncontrolled drift to potentially dangerous areas. We found that larval zebrafish track such movements and can later swim back to their earlier location. Whole-brain functional imaging revealed the circuit enabling this process of positional homeostasis. Position-encoding brainstem neurons integrate optic flow, then bias future swimming to correct for past displacements by modulating inferior olive and cerebellar activity. Manipulation of position-encoding or olivary neurons abolished positional homeostasis or evoked behavior as if animals had experienced positional shifts. These results reveal a multiregional hindbrain circuit in vertebrates for optic flow integration, memory of self-location, and its neural pathway to behavior.Competing Interest StatementThe authors have declared no competing interest.

}, doi = {10.1101/2021.11.26.468907}, url = {https://www.biorxiv.org/content/early/2021/11/27/2021.11.26.468907}, author = {Yang, En and Zwart, Maarten F. and Rubinov, Mikail and James, Benjamin and Wei, Ziqiang and Narayan, Sujatha and Vladimirov, Nikita and Mensh, Brett D. and Fitzgerald, James E. and Ahrens, Misha B.} } @article {65361, title = {Cell-type specific outcome representation in primary motor cortex.}, journal = {Neuron}, volume = {107}, year = {2020}, month = {2020 Sep 9}, pages = {954-71}, abstract = {

Adaptive movements are critical to animal survival. To guide future actions, the brain monitors different outcomes, including achievement of movement and appetitive goals. The nature of outcome signals and their neuronal and network realization in motor cortex (M1), which commands the performance of skilled movements, is largely unknown. Using a dexterity task, calcium imaging, optogenetic perturbations, and behavioral manipulations, we studied outcome signals in murine M1. We find two populations of layer 2-3 neurons, {\textquotedblleft}success{\textquotedblright}- and {\textquotedblleft}failure{\textquotedblright} related neurons that develop with training and report end-result of trials. In these neurons, prolonged responses were recorded after success or failure trials, independent of reward and kinematics. In contrast, the initial state of layer-5 pyramidal tract neurons contains a memory trace of the previous trial{\textquoteright}s outcome. Inter-trial cortical activity was needed to learn new task requirements. These M1 reflective layer-specific performance outcome signals, can support reinforcement motor learning of skilled behavior.

}, doi = {10.1016/j.neuron.2020.06.006}, author = {Lavzin, Maria and Levy, Shahar and Benisty, Hadas and Dubin, Uri and Brosh, Zohar and Aeed, Fadi and Mensh, Brett D. and Schiller, Yitzhak and Meir, Ron and Barak, Omri and Talmon, Ronen and Hantman, Adam W. and Schiller, Jackie} } @article {46557, title = {A multilevel multimodal circuit enhances action selection in Drosophila.}, journal = {Nature}, volume = {520}, year = {2015}, month = {2015 Apr 20}, pages = {633-9}, abstract = {

Natural events present multiple types of sensory cues, each detected by a specialized sensory modality. Combining information from several modalities is essential for the selection of appropriate actions. Key to understanding multimodal computations is determining the structural patterns of multimodal convergence and how these patterns contribute to behaviour. Modalities could converge early, late or at multiple levels in the sensory processing hierarchy. Here we show that combining mechanosensory and nociceptive cues synergistically enhances the selection of the fastest mode of escape locomotion in Drosophila larvae. In an electron microscopy volume that spans the entire insect nervous system, we reconstructed the multisensory circuit supporting the synergy, spanning multiple levels of the sensory processing hierarchy. The wiring diagram revealed a complex multilevel multimodal convergence architecture. Using behavioural and physiological studies, we identified functionally connected circuit nodes that trigger the fastest locomotor mode, and others that facilitate it, and we provide evidence that multiple levels of multimodal integration contribute to escape mode selection. We propose that the multilevel multimodal convergence architecture may be a general feature of multisensory circuits enabling complex input{\textendash}output functions and selective tuning to ecologically relevant combinations of cues.

}, doi = {10.1038/nature14297}, author = {Ohyama, Tomoko and Schneider-Mizell, Casey M. and Fetter, Richard D. and Aleman, Javier Valdes and Franconville, Romain and Rivera-Alba, Marta and Mensh, Brett D. and Branson, Kristin M. and Simpson, Julie H. and Truman, James W. and Cardona, Albert and Zlatic, Marta} }