Spatio-temporal influences at the neural level of object recognition.
نویسنده
چکیده
In late 1988, Miyashita published work reporting recordings of single cells in the inferotemporal cortex of the macaque monkey (Miyashita 1988 Nature 335 817-20). He described the responses of neurons to a sequence of random fractal pattern images, and how many of the neurons tested were seen to respond strongly to a subset of the images on the basis of sequence presentation order, i.e. appearance in time, rather than their spatial similarity. In this work, I describe a local Hebb-like learning rule which in conjunction with a simple feedforward neural architecture is capable of replicating the type of temporal-order association apparent in the cells from which he made recordings. The paper also advances reasons for requiring such learning by describing its possible role in establishing transformation invariant representations of objects.
منابع مشابه
معرفی شبکه های عصبی پیمانه ای عمیق با ساختار فضایی-زمانی دوگانه جهت بهبود بازشناسی گفتار پیوسته فارسی
In this article, growable deep modular neural networks for continuous speech recognition are introduced. These networks can be grown to implement the spatio-temporal information of the frame sequences at their input layer as well as their labels at the output layer at the same time. The trained neural network with such double spatio-temporal association structure can learn the phonetic sequence...
متن کاملRecognition of Visual Events using Spatio-Temporal Information of the Video Signal
Recognition of visual events as a video analysis task has become popular in machine learning community. While the traditional approaches for detection of video events have been used for a long time, the recently evolved deep learning based methods have revolutionized this area. They have enabled event recognition systems to achieve detection rates which were not reachable by traditional approac...
متن کاملThe Evolution of Meaning: Spatio-temporal Dynamics of Visual Object Recognition
Research on the spatio-temporal dynamics of visual object recognition suggests a recurrent, interactive model whereby an initial feedforward sweep through the ventral stream to prefrontal cortex is followed by recurrent interactions. However, critical questions remain regarding the factors that mediate the degree of recurrent interactions necessary for meaningful object recognition. The novel p...
متن کاملModeling and Spatio-Temporal Analysis of the Distribution of O3 in Tehran City Based on Neural Network and Spatial Analysis in GIS Environment
Air pollution is one of the most problems that people are facing today in metropolitan areas. Suspended particulates, carbon monoxide, sulfur dioxide, ozone and nitrogen dioxide are the five major pollutants of air that pose many problems to human health. The goal of this study is to propose a spatial approach for estimation and analyzing the spatial and temporal distribution of ozone based on ...
متن کاملEvolving Probabilistic Spiking Neural Networks for Spatio-temporal Pattern Recognition: A Preliminary Study on Moving Object Recognition
This paper proposes a novel architecture for continuous spatio-temporal data modeling and pattern recognition utilizing evolving probabilistic spiking neural network ’reservoirs’ (epSNNr). The paper demonstrates on a simple experimental data for moving object recognition that: (1) The epSNNr approach is more accurate and flexible than using standard SNN; (2) The use of probabilistic neuronal mo...
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:
- Network
دوره 9 2 شماره
صفحات -
تاریخ انتشار 1998