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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.We will illustrate binding with this type of model with episode binding and the binding of words, including novel words, in sentence structures.

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.


Related in: MedlinePlus

The importance of the frame of reference in analyzing synchrony of activation. In situation I, two source nodes (A, B) are in synchrony (red, unbroken lines) in an outside frame of reference. They are also in synchrony in the frame of reference of the target (Fact) node, because their activation arrives in synchrony (red, unbroken lines). In situation II, A and B are in synchrony in the outside frame of reference (red, unbroken lines), but not in the frame of reference of the Fact node, because their activation does not arrive in synchrony (green and blue, dashed lines). In situation III, A and B are in not synchrony in the outside frame of reference (green and blue, dashed lines), but they are in synchrony in the frame of reference of the Fact node, because their activation arrives in synchrony (red, unbroken lines). (Color figure online)
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Fig3: The importance of the frame of reference in analyzing synchrony of activation. In situation I, two source nodes (A, B) are in synchrony (red, unbroken lines) in an outside frame of reference. They are also in synchrony in the frame of reference of the target (Fact) node, because their activation arrives in synchrony (red, unbroken lines). In situation II, A and B are in synchrony in the outside frame of reference (red, unbroken lines), but not in the frame of reference of the Fact node, because their activation does not arrive in synchrony (green and blue, dashed lines). In situation III, A and B are in not synchrony in the outside frame of reference (green and blue, dashed lines), but they are in synchrony in the frame of reference of the Fact node, because their activation arrives in synchrony (red, unbroken lines). (Color figure online)

Mentions: We can illustrate this with synchrony based models of binding. Feldman (2013, Fig. 3) illustrated the Shruti inference network (Shastri and Ajjanagadde 1993; Wendelken and Shastri 2004). The inference illustrated concerns the notion that a buyer of an object is also the owner of the object. However, Feldman (2013) presented only a part of the inference network, as do Wendelken and Shastri (2004). The (more) complete circuit, accounting for the production of behavior (the inference in this case) is found in Figure 12 of Shastri and Ajjanagadde (1993). This figure illustrates two closely related inferences: buys(x, y) ⇒ owns (x, y) and gives (x, y, z) ⇒ owns (y, z).


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

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

The importance of the frame of reference in analyzing synchrony of activation. In situation I, two source nodes (A, B) are in synchrony (red, unbroken lines) in an outside frame of reference. They are also in synchrony in the frame of reference of the target (Fact) node, because their activation arrives in synchrony (red, unbroken lines). In situation II, A and B are in synchrony in the outside frame of reference (red, unbroken lines), but not in the frame of reference of the Fact node, because their activation does not arrive in synchrony (green and blue, dashed lines). In situation III, A and B are in not synchrony in the outside frame of reference (green and blue, dashed lines), but they are in synchrony in the frame of reference of the Fact node, because their activation arrives in synchrony (red, unbroken lines). (Color figure online)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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Fig3: The importance of the frame of reference in analyzing synchrony of activation. In situation I, two source nodes (A, B) are in synchrony (red, unbroken lines) in an outside frame of reference. They are also in synchrony in the frame of reference of the target (Fact) node, because their activation arrives in synchrony (red, unbroken lines). In situation II, A and B are in synchrony in the outside frame of reference (red, unbroken lines), but not in the frame of reference of the Fact node, because their activation does not arrive in synchrony (green and blue, dashed lines). In situation III, A and B are in not synchrony in the outside frame of reference (green and blue, dashed lines), but they are in synchrony in the frame of reference of the Fact node, because their activation arrives in synchrony (red, unbroken lines). (Color figure online)
Mentions: We can illustrate this with synchrony based models of binding. Feldman (2013, Fig. 3) illustrated the Shruti inference network (Shastri and Ajjanagadde 1993; Wendelken and Shastri 2004). The inference illustrated concerns the notion that a buyer of an object is also the owner of the object. However, Feldman (2013) presented only a part of the inference network, as do Wendelken and Shastri (2004). The (more) complete circuit, accounting for the production of behavior (the inference in this case) is found in Figure 12 of Shastri and Ajjanagadde (1993). This figure illustrates two closely related inferences: buys(x, y) ⇒ owns (x, y) and gives (x, y, z) ⇒ owns (y, z).

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.We will illustrate binding with this type of model with episode binding and the binding of words, including novel words, in sentence structures.

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.


Related in: MedlinePlus