Cerebellar climbing fibers signal flexible, rapidly adapting reward predictions.

Classical models of cerebellar computation posit that climbing fibers (CFs) operate according to supervised learning rules, correcting movements by signaling the occurrence of motor errors. However, recent findings suggest that in some behaviors, CF activity can exhibit features that resemble the instructional signals necessary for reinforcement learning, namely reward prediction errors (rPEs). Despite these initial observations, many key properties of reward-related CF responses remain unclear, thus limiting our understanding of how they operate to guide cerebellar learning.

Quantitative 2H NMR spectroscopy with 1H lock extender.

An inexpensive external unit that allows the use of the commercial high-resolution NMR spectrometer for (2)H observation with an (1)H lock system is described. The external unit does not require any tuning, is extremely easy to use, and could be a cheaper and more straightforward alternative to the more expensive (19)F lock configuration. An application for the quantitative determination of the natural isotopic ratio (2)H/(1)H of ethanol and acetic acid is reported.