Object activation from features in the semantic system.

نویسندگان

  • Michael A Kraut
  • Sarah Kremen
  • Jessica B Segal
  • Vincent Calhoun
  • Lauren R Moo
  • John Hart
چکیده

The human brain is thought to elicit an object representation via co-activation of neural regions that encode various object features. The cortical regions and mechanisms involved in this process have never been elucidated for the semantic system. We used functional magnetic resonance imaging (fMRI) to evaluate regions activated during a task designed to elicit object activation within the semantic system (e.g., presenting the words "desert" and "humps" with the task to determine if they combine to form an object, in this case a "camel"). There were signal changes in the thalamus for word pairs that activated an object, but not for pairs that (a) failed to activate an object, (b) were simply semantically associated, or (c) were members of the same category. These results suggest that the thalamus has a critical role in coordinating the cortical activity required for activating an object concept in the semantic system.

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

برچسب‌زنی نقش معنایی جملات فارسی با رویکرد یادگیری مبتنی بر حافظه

Abstract Extracting semantic roles is one of the major steps in representing text meaning. It refers to finding the semantic relations between a predicate and syntactic constituents in a sentence. In this paper we present a semantic role labeling system for Persian, using memory-based learning model and standard features. Our proposed system implements a two-phase architecture to first identify...

متن کامل

Automatic Hashtag Recommendation in Social Networking and Microblogging Platforms Using a Knowledge-Intensive Content-based Approach

In social networking/microblogging environments, #tag is often used for categorizing messages and marking their key points. Also, since some social networks such as twitter apply restrictions on the number of characters in messages, #tags can serve as a useful tool for helping users express their messages. In this paper, a new knowledge-intensive content-based #tag recommendation system is intr...

متن کامل

Urban Vegetation Recognition Based on the Decision Level Fusion of Hyperspectral and Lidar Data

Introduction: Information about vegetation cover and their health has always been interesting to ecologists due to its importance in terms of habitat, energy production and other important characteristics of plants on the earth planet. Nowadays, developments in remote sensing technologies caused more remotely sensed data accessible to researchers. The combination of these data improves the obje...

متن کامل

Semantic Preserving Data Reduction using Artificial Immune Systems

Artificial Immune Systems (AIS) can be defined as soft computing systems inspired by immune system of vertebrates. Immune system is an adaptive pattern recognition system. AIS have been used in pattern recognition, machine learning, optimization and clustering. Feature reduction refers to the problem of selecting those input features that are most predictive of a given outcome; a problem encoun...

متن کامل

A Novel Architecture for Detecting Phishing Webpages using Cost-based Feature Selection

Phishing is one of the luring techniques used to exploit personal information. A phishing webpage detection system (PWDS) extracts features to determine whether it is a phishing webpage or not. Selecting appropriate features improves the performance of PWDS. Performance criteria are detection accuracy and system response time. The major time consumed by PWDS arises from feature extraction that ...

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:
  • Journal of cognitive neuroscience

دوره 14 1  شماره 

صفحات  -

تاریخ انتشار 2002