Music and natural image processing share a common feature-integration rule

نویسندگان

  • Michelle P. S. To
  • David J. Tolhurst
چکیده

The world is rich in sensory information, and the challenge for any neural sensory system is to piece together the diverse messages from large arrays of feature detectors. In vision and auditory research, there has been speculation about the rules governing combination of signals from different neural channels: e.g. linear (city-block) addition, Euclidian (energy) summation, or a maximum rule. These are all special cases of a more general Minkowski summation rule (Cue1+Cue2), where m=1, 2 and infinity respectively. Recently, we reported that Minkowski summation with exponent m=2.84 accurately models combination of visual cues in photographs [To et al. (2008). Proc Roy Soc B, 275, 2299]. Here, we ask whether this rule is equally applicable to cue combinations across different auditory dimensions: such as intensity, pitch, timbre and content. We found that in suprathreshold discrimination tasks using musical sequences, a Minkowski summation with exponent close to 3 (m=2.95) outperformed city-block, Euclidian or maximum combination rules in describing cue integration across feature dimensions. That the same exponent is found in this music experiment and our previous vision experiments, suggests the possibility of a universal “Minkowski summation Law” in sensory feature integration. We postulate that this particular Minkowski exponent relates to the degree of correlation in activity between different sensory neurons when stimulated by natural stimuli, and could reflect an overall economical and efficient encoding mechanism underlying perceptual integration of features in the natural world. K eywords: Music; Auditory perception; Feature integration; Minkowski Summation; Visual perception.

برای دانلود 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

Comparison of Artificial Neural Network Training Algorithms for Predicting the Weight of Kurdi Sheep using Image Processing

Extended Abstract Introduction and Objective: Due to weakness, the occurrence of unwanted errors, the impact of the environment and exposure to natural events, human always make mistakes in their diagnoses of the environment or different topics, so that different people 's perception of a single and unique event may be very different and be diverse. Nowadays, with the development of image proc...

متن کامل

Diagnosis of brain tumor using image processing and determination of its type with RVM neural networks

Typically, the diagnosis of a tumor is done through surgical sampling, which is more precise with existing methods. The difference is that this is an aggressive, time consuming and expensive way. In the statistical method, due to the complexity of the brain tissues and the similarity between the cancerous cells and the natural tissues, even a radiologist or an expert physician may also be in er...

متن کامل

Evaluation of Retinal Optic Disc Segmentation in Patients with Glaucoma and Comparison with Other Methods of Medical Image Processing

Introduction: Glaucoma is the most common cause of blindness in some countries. In the meantime, the field of retinal image processing has been proposed in order to provide automatic systems for disease diagnosis. Among the methods of medical image processing, image segmentation is a process of identification and change in the display of an image. The objective of this study was to use t...

متن کامل

Contourlet-Based Edge Extraction for Image Registration

Image registration is a crucial step in most image processing tasks for which the final result is achieved from a combination of various resources. In general, the majority of registration methods consist of the following four steps: feature extraction, feature matching, transform modeling, and finally image resampling. As the accuracy of a registration process is highly dependent to the fe...

متن کامل

Determining Effective Features for Face Detection Using a Hybrid Feature Approach

Detecting faces in cluttered backgrounds and real world has remained as an unsolved problem yet. In this paper, by using composition of some kind of independent features and one of the most common appearance based approaches, and multilayered perceptron (MLP) neural networks, not only some questions have been answered, but also the designed system achieved better performance rather than the pre...

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

برای دانلود 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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009