idw – Informationsdienst Wissenschaft

Nachrichten, Termine, Experten

Grafik: idw-Logo
idw-Abo
Medienpartner:
Wissenschaftsjahr


Share on: 
05/08/2019 20:00

“Number sense” arises from the recognition of visible objects

Dr. Karl Guido Rijkhoek Hochschulkommunikation
Eberhard Karls Universität Tübingen

    University of Tübingen researchers use an artificial neural network to model the visual system

    Humans and animals have a “number sense,” an inborn ability to register the number of objects in a scene. The neural basis of this ability is believed to be what are called the number neurons, which respond to certain numbers and have been found in both human and animal brains. Researchers have long wondered whether these number neurons are formed in the brain merely by the ability to see – and if so, how. Now, a team of researchers headed by Professor Andreas Nieder at the University of Tübingen’s Institute of Neurobiology has investigated the origins of number sense using an artificial neural network. The results indicate that it is created spontaneously by the visual system, without any experience in counting. The study has just been published in the latest edition of Science Advances.

    The researchers started out by training an artificial “deep learning” network to recognize pictured objects such as tennis balls, necklaces, spiders and dogs. “The network model is based on an architecture structured like the early developmental stage of the human visual cortex,” Andreas Nieder explains. “It has been discovered there that nerve cells work together in different hierarchical levels to enable vision.” The artificial network learned to recognize objects on the basis of 1.2 million images which were classified into one thousand categories. After this training the network was able to classify thousands of new images with a high proportion of success.

    Number sense arises from existing neural networks

    The network is in two parts. One of these extracts the object’s characteristics from the images and transforms these into an abstract representation; the second part sorts the object into a category on the basis of probability. “We separated the two network parts and to the first part we presented not photos but simple dot patterns of one to 30 dots,” Nieder says. In the following cycles of the experiment, the patterns were repeated with varying dot patterns and densities. Then the researchers analyzed whether the network’s artificial neurons reacted to the same number of points independently of other characteristics. "Almost ten percent of the artificial neurons had each specialized in a certain number, although the network was never trained to differentiate between numbers. The network had spontaneously developed a sense of numbers," says Nieder.

    Researchers had suspected that the ability to count developed from the visual system. The most fundamental task of vision is to recognize visible objects, Nieder says. The new study shows how number neurons can develop spontaneously from an artificial visual system that was only trained to recognize visible objects, he adds. Furthermore, the artificial neurons’ responses resembled that of real number neurons in animals and humans. “Number sense does not seem to depend on a specific, specialized area of the brain, but rather on neural networks formed by vision. This now makes it possible to explain why even newborns or untrained, wild animals have a number sense," Nieder explains.


    Contact for scientific information:

    Professor Dr. Andreas Nieder
    University of Tübingen
    Institute of Neurobiology
    Phone +49 7071 29-75347
    andreas.nieder[at]uni-tuebingen.de


    Original publication:

    Khaled Nasr, Pooja Viswanathan, Andreas Nieder: Number detectors spontaneously emerge in a deep neural network designed for visual object recognition. Science Advances 2019; 5:eaav7903, 8 May 2019


    Criteria of this press release:
    Journalists, Scientists and scholars
    Biology
    transregional, national
    Research results, Scientific Publications
    English


    In this deep-learning neural network - trained only via the correct assignment of photos - artificial neurons formed spontaneously which were attuned to various preferred numbers.


    For download

    x

    Help

    Search / advanced search of the idw archives
    Combination of search terms

    You can combine search terms with and, or and/or not, e.g. Philo not logy.

    Brackets

    You can use brackets to separate combinations from each other, e.g. (Philo not logy) or (Psycho and logy).

    Phrases

    Coherent groups of words will be located as complete phrases if you put them into quotation marks, e.g. “Federal Republic of Germany”.

    Selection criteria

    You can also use the advanced search without entering search terms. It will then follow the criteria you have selected (e.g. country or subject area).

    If you have not selected any criteria in a given category, the entire category will be searched (e.g. all subject areas or all countries).

    Cookies optimize the use of our services. By surfing on idw-online.de you agree to the use of cookies. Data Confidentiality Statement
    Okay