Data from: Interactions between circuit architecture and plasticity in a closed-loop cerebellar system

A major challenge in neuroscience is to infer the sites and directions of
neural plasticity that underlie learned changes in behavior. In
particular, abundant feedback pathways in the brain impede reasoning about
cause and effect based on neural recording data alone. We approached this
problem by studying the interactions between feedback, neural activity,
and plasticity in the context of vestibulo-ocular reflex learning, a
closed-loop motor learning paradigm. Our strategy was to fit a series of
circuit models to a large set of neural and behavioral data. Each model
differed in the strength of efference copy feedback to Purkinje cells,
ranging from no feedback to very strong feedback. The primary dataset
before learning was obtained from male rhesus monkeys (Macaca mulatta)
trained to perform a visual fixation task, and includes neural activity
from Purkinje cells in the cerebellar flocculus and horizontal eye
velocity measurements in response to a wide range of vestibular and visual
stimuli. Data after learning was obtained from previous publications.
Whereas each model fit the extracellular recording and behavioral data,
the patterns of plasticity predicted by the models fundamentally differed,
with the direction of plasticity at a key site changing from depression to
potentiation as feedback strength increased. We find that models with weak
or no efference copy feedback to Purkinje cells are consistent with
climbing fiber-driven long term depression at parallel fiber-Purkinje cell
synapses and explain all experimental observations, including paradoxical
changes in neural activity during a closed-loop visual task that appear to
contradict the underlying plasticity. These results demonstrate how
learning-related changes in neural activity can appear to contradict the
sign of the underlying plasticity when either internal feedback or
feedback through the environment is present.