Abstract
We here provide neural evidence that the cerebellar circuit can predict future inputs from present outputs, a hallmark of an internal forward model. Recent computational studies hypothesize that the cerebellum performs state prediction known as a forward model. To test the forward-model hypothesis, we analyzed activities of 94 mossy fibers (inputs to the cerebellar cortex), 83 Purkinje cells (output from the cerebellar cortex to dentate nucleus), and 73 dentate nucleus cells (cerebellar output) in the cerebro-cerebellum, all recorded from a monkey performing step-tracking movements of the right wrist. We found that the firing rates of one population could be reconstructed as a weighted linear sum of those of preceding populations. We then went on to investigate if the current outputs of the cerebellum (dentate cells) could predict the future inputs of the cerebellum (mossy fibers). The firing rates of mossy fibers at time t + t1 could be well reconstructed from as a weighted sum of firing rates of dentate cells at time t, thereby proving that the dentate activities contained predictive information about the future inputs. The average goodness-of-fit (R2) decreased moderately from 0.89 to 0.86 when t1 was increased from 20 to 100 ms, hence indicating that the prediction is able to compensate the latency of sensory feedback. The linear equations derived from the firing rates resembled those of a predictor known as Kalman filter composed of prediction and filtering steps. In summary, our analysis of cerebellar activities supports the forward-model hypothesis of the cerebellum.
Highlights
The cerebellum plays a critical role in the control and coordination of body movements, adaptation to novel environments, and acquisition of new motor skills
We investigated if firing rates of cerebellar output (i.e., dentate cells (DCs)) at time t contained information that was predictive for future inputs to the cerebellar cortex (i.e., mossy fibers (MFs)) at time t + t1
The forward-model hypothesis was tested by applying a linearweighted model that predicted the MF activity at time t + t1 from the DC activity at time t
Summary
The cerebellum plays a critical role in the control and coordination of body movements, adaptation to novel environments, and acquisition of new motor skills. The brain always receives the Bpast^ state of the body It is known in engineering and mechanics that feedback control based on timedelayed state can behave in an oscillatory and often unstable way if the delay is on the order of time constants of system dynamics. Physical laws that govern body movements allow the brain to predict a current state from a previous state and an efference copy of motor command, essentially by solving the Newtonian mechanics.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
