A new model for Cerebellar computation

02/22/2018
by   Reza Moazzezi, et al.
0

The standard state space model is widely believed to account for the cerebellar computation in motor adaptation tasks [1]. Here we show that several recent experiments [2-4] where the visual feedback is irrelevant to the motor response challenge the standard model. Furthermore, we propose a new model that accounts for the the results presented in [2-4]. According to this new model, learning and forgetting are coupled and are error size dependent. We also show that under reasonable assumptions, our proposed model is the only model that accounts for both the classical adaptation paradigm as well as the recent experiments [2-4].

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/21/2017

Structure Learning in Motor Control:A Deep Reinforcement Learning Model

Motor adaptation displays a structure-learning effect: adaptation to a n...
research
03/25/2016

Markov substitute processes : a new model for linguistics and beyond

We introduce Markov substitute processes, a new model at the crossroad o...
research
11/11/2019

A Nonlinear Hyperbolic Model for Radiative Transfer Equation in Slab Geometry

Linear models for the radiative transfer equation have been well develop...
research
12/24/2022

Testing Distributions of Huge Objects

We initiate a study of a new model of property testing that is a hybrid ...
research
06/12/2019

Identification of Motor Parameters on Coupled Joints

The estimation of the motor torque and friction parameters are crucial f...
research
10/11/2020

A computationally and cognitively plausible model of supervised and unsupervised learning

Both empirical and mathematical demonstrations of the importance of chan...
research
01/25/2021

An Environmentally-Adaptive Hawkes Process with An Application to COVID-19

We proposed a new generalized model based on the classical Hawkes proces...

Please sign up or login with your details

Forgot password? Click here to reset