| Autor: |
McNamee DC; Wellcome Centre for Human Neuroimaging, University College London, London, UK. daniel.c.mcnamee@gmail.com.; Max Planck UCL Centre for Computational Psychiatry, London, UK. daniel.c.mcnamee@gmail.com.; Department of Psychology, Harvard University, Cambridge, MA, USA. daniel.c.mcnamee@gmail.com., Stachenfeld KL; Google DeepMind, London, UK., Botvinick MM; Google DeepMind, London, UK.; Gatsby Computational Neuroscience Unit, University College London, London, UK., Gershman SJ; Department of Psychology, Harvard University, Cambridge, MA, USA.; Center for Brain Science, Harvard University, Cambridge, MA, USA.; Center for Brains, Minds and Machines, MIT, Cambridge, MA, USA. |
| Abstrakt: |
Exploration, consolidation and planning depend on the generation of sequential state representations. However, these algorithms require disparate forms of sampling dynamics for optimal performance. We theorize how the brain should adapt internally generated sequences for particular cognitive functions and propose a neural mechanism by which this may be accomplished within the entorhinal-hippocampal circuit. Specifically, we demonstrate that the systematic modulation along the medial entorhinal cortex dorsoventral axis of grid population input into the hippocampus facilitates a flexible generative process that can interpolate between qualitatively distinct regimes of sequential hippocampal reactivations. By relating the emergent hippocampal activity patterns drawn from our model to empirical data, we explain and reconcile a diversity of recently observed, but apparently unrelated, phenomena such as generative cycling, diffusive hippocampal reactivations and jumping trajectory events. |
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