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The necessity of connection structures in neural models of variable binding.

van der Velde F, de Kamps M - Cogn Neurodyn (2015)

Bottom Line: Contrary to his conclusion, connectivity based models are the only viable candidates for models of novel variable binding because they are the only type of models that can produce behavior.Feldman's analysis that novel variable binding can be achieved without existing connection structures seems to result from analyzing the binding problem in a wrong frame of reference, in particular in an outside instead of the required inside frame of reference.Connectivity based models can be models of novel variable binding when they possess a connection structure that resembles a small-world network, as found in the brain.

View Article: PubMed Central - PubMed

Affiliation: Technical Cognition, CPE-CTIT, University of Twente, P.O. Box 217, Enschede, 7500 AE The Netherlands ; IO, Leiden University, Leiden, The Netherlands.

ABSTRACT
In his review of neural binding problems, Feldman (Cogn Neurodyn 7:1-11, 2013) addressed two types of models as solutions of (novel) variable binding. The one type uses labels such as phase synchrony of activation. The other ('connectivity based') type uses dedicated connections structures to achieve novel variable binding. Feldman argued that label (synchrony) based models are the only possible candidates to handle novel variable binding, whereas connectivity based models lack the flexibility required for that. We argue and illustrate that Feldman's analysis is incorrect. Contrary to his conclusion, connectivity based models are the only viable candidates for models of novel variable binding because they are the only type of models that can produce behavior. We will show that the label (synchrony) based models analyzed by Feldman are in fact examples of connectivity based models. Feldman's analysis that novel variable binding can be achieved without existing connection structures seems to result from analyzing the binding problem in a wrong frame of reference, in particular in an outside instead of the required inside frame of reference. Connectivity based models can be models of novel variable binding when they possess a connection structure that resembles a small-world network, as found in the brain. We will illustrate binding with this type of model with episode binding and the binding of words, including novel words, in sentence structures.

No MeSH data available.


Variable binding based on synchrony of activation in Shruti (based on Shastri and Ajjanagadde, 1993, Figure 12). The nodes for arguments and thematic roles are in synchrony: John with giver (green, unbroken lines), Mary with recipient (red, long-dashed lines), and book with given-object (blue, short-dashed lines). Synchronous nodes activate coincidence detectors (triangles), which activate a proposition detector (‘fact node’) for John gives Mary a book. A reasoning process can then activate Mary owns a book (recip = recipient, g-obj = given-object). (Color figure online)
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Fig1: Variable binding based on synchrony of activation in Shruti (based on Shastri and Ajjanagadde, 1993, Figure 12). The nodes for arguments and thematic roles are in synchrony: John with giver (green, unbroken lines), Mary with recipient (red, long-dashed lines), and book with given-object (blue, short-dashed lines). Synchronous nodes activate coincidence detectors (triangles), which activate a proposition detector (‘fact node’) for John gives Mary a book. A reasoning process can then activate Mary owns a book (recip = recipient, g-obj = given-object). (Color figure online)

Mentions: In Fig. 1 we represent a part of the connection circuit in Figure 12 of Shastri and Ajjanagadde (1993) that instantiates the inference that if John gives Mary a book then Mary owns a book. In this connection circuit there are item nodes for John, Mary and book, and thematic relation nodes for giver, recipient (recip) and given-object (g-obj). There is also a ‘fact node’ (F1 in Figure 12 of Shastri and Ajjanagadde 1993) or ‘collector node’ (Wendelken and Shastri 2004) for the particular fact or belief John gives Mary a book. The activation of this fact node is essential for making the inference Mary owns a book. The role of synchrony is to ensure the selective activation of this fact node. So, in Fig. 1 the fact node for John gives Mary a book is activated because the activation of John is in synchrony with giver, the activation of Mary is in synchrony with recipient and the activation of book is in synchrony with given-object.Fig. 1


The necessity of connection structures in neural models of variable binding.

van der Velde F, de Kamps M - Cogn Neurodyn (2015)

Variable binding based on synchrony of activation in Shruti (based on Shastri and Ajjanagadde, 1993, Figure 12). The nodes for arguments and thematic roles are in synchrony: John with giver (green, unbroken lines), Mary with recipient (red, long-dashed lines), and book with given-object (blue, short-dashed lines). Synchronous nodes activate coincidence detectors (triangles), which activate a proposition detector (‘fact node’) for John gives Mary a book. A reasoning process can then activate Mary owns a book (recip = recipient, g-obj = given-object). (Color figure online)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4491338&req=5

Fig1: Variable binding based on synchrony of activation in Shruti (based on Shastri and Ajjanagadde, 1993, Figure 12). The nodes for arguments and thematic roles are in synchrony: John with giver (green, unbroken lines), Mary with recipient (red, long-dashed lines), and book with given-object (blue, short-dashed lines). Synchronous nodes activate coincidence detectors (triangles), which activate a proposition detector (‘fact node’) for John gives Mary a book. A reasoning process can then activate Mary owns a book (recip = recipient, g-obj = given-object). (Color figure online)
Mentions: In Fig. 1 we represent a part of the connection circuit in Figure 12 of Shastri and Ajjanagadde (1993) that instantiates the inference that if John gives Mary a book then Mary owns a book. In this connection circuit there are item nodes for John, Mary and book, and thematic relation nodes for giver, recipient (recip) and given-object (g-obj). There is also a ‘fact node’ (F1 in Figure 12 of Shastri and Ajjanagadde 1993) or ‘collector node’ (Wendelken and Shastri 2004) for the particular fact or belief John gives Mary a book. The activation of this fact node is essential for making the inference Mary owns a book. The role of synchrony is to ensure the selective activation of this fact node. So, in Fig. 1 the fact node for John gives Mary a book is activated because the activation of John is in synchrony with giver, the activation of Mary is in synchrony with recipient and the activation of book is in synchrony with given-object.Fig. 1

Bottom Line: Contrary to his conclusion, connectivity based models are the only viable candidates for models of novel variable binding because they are the only type of models that can produce behavior.Feldman's analysis that novel variable binding can be achieved without existing connection structures seems to result from analyzing the binding problem in a wrong frame of reference, in particular in an outside instead of the required inside frame of reference.Connectivity based models can be models of novel variable binding when they possess a connection structure that resembles a small-world network, as found in the brain.

View Article: PubMed Central - PubMed

Affiliation: Technical Cognition, CPE-CTIT, University of Twente, P.O. Box 217, Enschede, 7500 AE The Netherlands ; IO, Leiden University, Leiden, The Netherlands.

ABSTRACT
In his review of neural binding problems, Feldman (Cogn Neurodyn 7:1-11, 2013) addressed two types of models as solutions of (novel) variable binding. The one type uses labels such as phase synchrony of activation. The other ('connectivity based') type uses dedicated connections structures to achieve novel variable binding. Feldman argued that label (synchrony) based models are the only possible candidates to handle novel variable binding, whereas connectivity based models lack the flexibility required for that. We argue and illustrate that Feldman's analysis is incorrect. Contrary to his conclusion, connectivity based models are the only viable candidates for models of novel variable binding because they are the only type of models that can produce behavior. We will show that the label (synchrony) based models analyzed by Feldman are in fact examples of connectivity based models. Feldman's analysis that novel variable binding can be achieved without existing connection structures seems to result from analyzing the binding problem in a wrong frame of reference, in particular in an outside instead of the required inside frame of reference. Connectivity based models can be models of novel variable binding when they possess a connection structure that resembles a small-world network, as found in the brain. We will illustrate binding with this type of model with episode binding and the binding of words, including novel words, in sentence structures.

No MeSH data available.