Distribution of tactile learning and its neural basis.
نویسندگان
چکیده
The brain's sensory processing systems are modified during perceptual learning. To learn more about the spatial organization of learning-related modifications, we trained rats to utilize the sensory signal from a single intact whisker to carry out a behavioral task. Once a rat had mastered the task, we clipped its "trained" whisker and attached a "prosthetic" one to a different whisker stub. We then tested the rat to determine how quickly it could relearn the task by using the new whisker. We observed that rats were immediately able to use the prosthetic whisker if it were attached to the stub of the trained whisker but not if it were attached to a different stub. Indeed, the greater the distance between the trained and prosthetic whisker, the more trials were needed to relearn the task. We hypothesized that this "transfer" of learning between whiskers might depend on how much the representations of individual whiskers overlap in primary somatosensory cortex. Testing this hypothesis by using 100-electrode cortical recordings, we found that the overlap between the cortical response patterns of two whiskers accounted well for the transfer of learning between them: The correlation between the electrophysiological and behavioral data was very high (r = 0.98). These findings suggest that a topographically distributed memory trace for sensory-perceptual learning may reside in primary sensory cortex.
منابع مشابه
Novel Radial Basis Function Neural Networks based on Probabilistic Evolutionary and Gaussian Mixture Model for Satellites Optimum Selection
In this study, two novel learning algorithms have been applied on Radial Basis Function Neural Network (RBFNN) to approximate the functions with high non-linear order. The Probabilistic Evolutionary (PE) and Gaussian Mixture Model (GMM) techniques are proposed to significantly minimize the error functions. The main idea is concerning the various strategies to optimize the procedure of Gradient ...
متن کاملA Differential Evolution and Spatial Distribution based Local Search for Training Fuzzy Wavelet Neural Network
Abstract Many parameter-tuning algorithms have been proposed for training Fuzzy Wavelet Neural Networks (FWNNs). Absence of appropriate structure, convergence to local optima and low speed in learning algorithms are deficiencies of FWNNs in previous studies. In this paper, a Memetic Algorithm (MA) is introduced to train FWNN for addressing aforementioned learning lacks. Differential Evolution...
متن کاملLearning Sensor Feedback Models from Demonstrations via Phase-Modulated Neural Networks
In order to robustly execute a task under environmental uncertainty, a robot needs to be able to reactively adapt to changes arising in its environment. The environment changes are usually reflected in deviation in sensory traces from nominal. These deviations in sensory traces can be used to drive the plan adaptation, and for this purpose, a feedback model is required. The feedback model maps ...
متن کاملInvestigating the performance of machine learning-based methods in classroom reverberation time estimation using neural networks (Research Article)
Classrooms, as one of the most important educational environments, play a major role in the learning and academic progress of students. reverberation time, as one of the most important acoustic parameters inside rooms, has a significant effect on sound quality. The inefficiency of classical formulas such as Sabin, caused this article to examine the use of machine learning methods as an alternat...
متن کاملRadial Basis Neural Network Based Islanding Detection in Distributed Generation
This article presents a Radial Basis Neural Network (RBNN) based islanding detection technique. Islanding detection and prevention is a mandatory requirement for grid-connected distributed generation (DG) systems. Several methods based on passive and active detection scheme have been proposed. While passive schemes have a large non detection zone (NDZ), concern has been raised on active method ...
متن کاملNeural Network Based Recognition System Integrating Feature Extraction and Classification for English Handwritten
Handwriting recognition has been one of the active and challenging research areas in the field of image processing and pattern recognition. It has numerous applications that includes, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. Neural Network (NN) with its inherent learning ability offers promising solutions for handwritten characte...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Proceedings of the National Academy of Sciences of the United States of America
دوره 96 13 شماره
صفحات -
تاریخ انتشار 1999