Feed-forward associative learning for volitional movement control.

نویسنده

  • Masahiko Fujita
چکیده

One of the most difficult problems in motor learning is determining the source of a learning signal, sometimes called an error signal. This problem is hidden in the adaptations of simple reflexive movements by attributing its source to sensory organs. The feed-forward associative motor learning theory proposed here attributes the source to the movement system itself. When a subject performs a corrective movement after his primary movement, the proposed neural learning device learns to associate the primary motor command with the corrective motor command by using a place-coding system. In the subsequent trials, the primary movement will involve a correction due to the participation of this mechanism, thus resulting in better performance. The theory assumes three conditions, namely, that a motor center and the learning device share the same place-encoded motor information; the motor center issues a command and a learning signal simultaneously from the same unit; and a learning signal issued with a corrective command has a heterosynaptic interaction with the previous primary command. The cerebellum is a reasonable candidate for the device satisfying these conditions. The reaction time of a corrective movement, usually 100-300 ms, almost satisfies the coincidence condition for long-term depression of the granule-to-Purkinje synapses. As an application, this theory is demonstrated to account for behavioral results regarding saccadic adaptation.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Reinforcement Learning in Associative Memory

A reinforcement learning based associative memory structure (RLAM) is proposed. In this structure, a one-layer feed forward Palm [1] model is applied to the networks. Instead of batch training, an on-line learning method is used to construct the memory. The networks are trained interactively according to reinforcement learning, which is biologically plausible. The experiment results show that t...

متن کامل

A Hierarchical Self-organizing Associative Memory for Machine Learning

This paper proposes novel hierarchical self-organizing associative memory architecture for machine learning. This memory architecture is characterized with sparse and local interconnections, self-organizing processing elements (PE), and probabilistic synaptic transmission. Each PE in the network dynamically estimates its output value from the observed input data distribution and remembers the s...

متن کامل

Test Bed for Multilayered Feed forward Neural Network Architectures as Bidirectional Associative Memory

Multilayered feed-forward neural networks are considered universal approximators and hence extensively been used for function approximation. Function approximation is an instance of supervised learning which is one of the most studied topics in machine learning, artificial neural networks, pattern recognition, and statistical curve fitting. Bidirectional associative memory is another class of n...

متن کامل

Exploring Optimal Architecture of Multi-layered Feed- forward (MLFNN) as Bidirectional Associative Memory (BAM) for Function Approximation

Function approximation is an instance of supervised learning which is one of the most studied topics in machine learning, artificial neural networks, pattern recognition, and statistical curve fitting. In principle, any of the methods studied in these fields can be used in reinforcement learning. Multi-layered feed-forward neural networks (MLFNN) have been extensively used for the purpose of fu...

متن کامل

Associative Memories for Chemical Sensing

We consider application of neural associative memories to chemical image recognition. Chemical image recognition is identification of substance using chemical sensors' data. The primary advantage of associative memories as compared with feed-forward neural networks is highspeed learning. We have made experiments on odour recognition using hetero-associative and modular autoassociative memories....

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Neuroscience research

دوره 52 2  شماره 

صفحات  -

تاریخ انتشار 2005