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Neural landscape diffusion resolves conflicts between needs across time

Animals perform flexible goal-directed behaviours to satisfy their basic physiological needs1–12. However, little is known about how unitary behaviours are chosen under conflicting needs. Here we reveal principles by which the brain resolves such conflicts between needs across time. We developed an experimental paradigm in which a hungry and thirsty mouse is given free choices between equidistant food and water. We found that mice collect need-appropriate rewards by structuring their choices into persistent bouts with stochastic transitions. High-density electrophysiological recordings during this behaviour revealed distributed single neuron and neuronal population correlates of a persistent internal goal state guiding future choices of the mouse. We captured these phenomena with a mathematical model describing a global need state that noisily diffuses across a shifting energy landscape. Model simulations successfully predicted behavioural and neural data, including population ne ....

Atlas Ccfv , Ngai Rxfp , Tprime Karsh , Jupyter Ipython , Allen Brain Institute , Electron Microscopy Sciences , Allen Institute Ccfv , Allen Institute Brain Atlas , Thermo Fisher , National Institutes Of Health , Allen Institute Mouse Brain Atlas , Stanford University , Administrative Panel , Laboratory Animal Care , National Institutes , World Precision Instruments , Jam Systems , Basler Ace , Bpod Generation , Extended Data , Harvard Apparatus , Multi Probe Manipulator , New Scale Technologies , Texas Instruments , Allen Brain Atlas , Allen Institute ,