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The Role of Competitive Inhibition and Top-Down Feedback in Binding during Object Recognition.

Wyatte D, Herd S, Mingus B, O'Reilly R - Front Psychol (2012)

Bottom Line: Specifically, we describe how inhibition creates competition among neural populations that code different features, effectively suppressing irrelevant information, and thus minimizing illusory conjunctions.Finally, we argue that temporal synchrony plays only a limited role in binding - it does not simultaneously bind multiple objects, but does aid in creating additional contrast between relevant and irrelevant features.Thus, our overall theory constitutes a solution to the binding problem that relies only on simple neural principles without any binding-specific processes.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychology and Neuroscience, University of Colorado Boulder Boulder, CO, USA.

ABSTRACT
How does the brain bind together visual features that are processed concurrently by different neurons into a unified percept suitable for processes such as object recognition? Here, we describe how simple, commonly accepted principles of neural processing can interact over time to solve the brain's binding problem. We focus on mechanisms of neural inhibition and top-down feedback. Specifically, we describe how inhibition creates competition among neural populations that code different features, effectively suppressing irrelevant information, and thus minimizing illusory conjunctions. Top-down feedback contributes to binding in a similar manner, but by reinforcing relevant features. Together, inhibition and top-down feedback contribute to a competitive environment that ensures only the most appropriate features are bound together. We demonstrate this overall proposal using a biologically realistic neural model of vision that processes features across a hierarchy of interconnected brain areas. Finally, we argue that temporal synchrony plays only a limited role in binding - it does not simultaneously bind multiple objects, but does aid in creating additional contrast between relevant and irrelevant features. Thus, our overall theory constitutes a solution to the binding problem that relies only on simple neural principles without any binding-specific processes.

No MeSH data available.


Binding multiple objects. (A) The same mechanisms of neural inhibition and top-down feedback extend to binding when multiple objects are present in a display. The competition created from having multiple IT units active that represent multiple objects causes one set of units to “win” and one set to “lose” (in this case, the bicycle units win). Inhibition suppresses the responses from units corresponding to the losing object as well as responses from completely irrelevant units. Top-down feedback serves to reinforce units from the winning object that may not have been initially active. (B) Binding errors occur when completely irrelevant units become erroneously active, leading to the inability to suppress invalid responses. This creates illusory conjunctions of features across the objects in the display, leading to a representation that does not resemble either category.
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Figure 3: Binding multiple objects. (A) The same mechanisms of neural inhibition and top-down feedback extend to binding when multiple objects are present in a display. The competition created from having multiple IT units active that represent multiple objects causes one set of units to “win” and one set to “lose” (in this case, the bicycle units win). Inhibition suppresses the responses from units corresponding to the losing object as well as responses from completely irrelevant units. Top-down feedback serves to reinforce units from the winning object that may not have been initially active. (B) Binding errors occur when completely irrelevant units become erroneously active, leading to the inability to suppress invalid responses. This creates illusory conjunctions of features across the objects in the display, leading to a representation that does not resemble either category.

Mentions: We propose that neural inhibition combined with top-down feedback can solve the problem of binding when multiple objects are present in a similar manner to the way they aid in binding visual features into singular, coherent objects. We demonstrate the plausibility of this idea in Figure 3. As is the case with single objects presented in isolation, a large number of IT neurons fire initially when multiple objects are present. Grouping these neurons according to the object to which they are selective illustrates the interactions between inhibition and top-down feedback. Generally, neurons that code visual features shared by both objects are the first to respond, since they constitute the best overall fit with the stimulus itself. In the case of the gun and bicycle pictured in Figure 3A, these first responders might be neurons that code the horizontal edges that compose the barrel of the gun and the top tube of the bicycle. Neurons that code unique features for each of the object categories are the next to respond. However, inhibition between these columns of neurons ensures that the features of only one of these objects are selected in the end, “winning” the competition (in this case, the bicycle neurons) and contributing to the final bound representation. When a single object is selected for the bound representation, top-down feedback can reinforce neurons that code meaningful features from that object that may not have initially responded (possibly due to initial inhibitory influences from neurons corresponding to the “losing” object).


The Role of Competitive Inhibition and Top-Down Feedback in Binding during Object Recognition.

Wyatte D, Herd S, Mingus B, O'Reilly R - Front Psychol (2012)

Binding multiple objects. (A) The same mechanisms of neural inhibition and top-down feedback extend to binding when multiple objects are present in a display. The competition created from having multiple IT units active that represent multiple objects causes one set of units to “win” and one set to “lose” (in this case, the bicycle units win). Inhibition suppresses the responses from units corresponding to the losing object as well as responses from completely irrelevant units. Top-down feedback serves to reinforce units from the winning object that may not have been initially active. (B) Binding errors occur when completely irrelevant units become erroneously active, leading to the inability to suppress invalid responses. This creates illusory conjunctions of features across the objects in the display, leading to a representation that does not resemble either category.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3376426&req=5

Figure 3: Binding multiple objects. (A) The same mechanisms of neural inhibition and top-down feedback extend to binding when multiple objects are present in a display. The competition created from having multiple IT units active that represent multiple objects causes one set of units to “win” and one set to “lose” (in this case, the bicycle units win). Inhibition suppresses the responses from units corresponding to the losing object as well as responses from completely irrelevant units. Top-down feedback serves to reinforce units from the winning object that may not have been initially active. (B) Binding errors occur when completely irrelevant units become erroneously active, leading to the inability to suppress invalid responses. This creates illusory conjunctions of features across the objects in the display, leading to a representation that does not resemble either category.
Mentions: We propose that neural inhibition combined with top-down feedback can solve the problem of binding when multiple objects are present in a similar manner to the way they aid in binding visual features into singular, coherent objects. We demonstrate the plausibility of this idea in Figure 3. As is the case with single objects presented in isolation, a large number of IT neurons fire initially when multiple objects are present. Grouping these neurons according to the object to which they are selective illustrates the interactions between inhibition and top-down feedback. Generally, neurons that code visual features shared by both objects are the first to respond, since they constitute the best overall fit with the stimulus itself. In the case of the gun and bicycle pictured in Figure 3A, these first responders might be neurons that code the horizontal edges that compose the barrel of the gun and the top tube of the bicycle. Neurons that code unique features for each of the object categories are the next to respond. However, inhibition between these columns of neurons ensures that the features of only one of these objects are selected in the end, “winning” the competition (in this case, the bicycle neurons) and contributing to the final bound representation. When a single object is selected for the bound representation, top-down feedback can reinforce neurons that code meaningful features from that object that may not have initially responded (possibly due to initial inhibitory influences from neurons corresponding to the “losing” object).

Bottom Line: Specifically, we describe how inhibition creates competition among neural populations that code different features, effectively suppressing irrelevant information, and thus minimizing illusory conjunctions.Finally, we argue that temporal synchrony plays only a limited role in binding - it does not simultaneously bind multiple objects, but does aid in creating additional contrast between relevant and irrelevant features.Thus, our overall theory constitutes a solution to the binding problem that relies only on simple neural principles without any binding-specific processes.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychology and Neuroscience, University of Colorado Boulder Boulder, CO, USA.

ABSTRACT
How does the brain bind together visual features that are processed concurrently by different neurons into a unified percept suitable for processes such as object recognition? Here, we describe how simple, commonly accepted principles of neural processing can interact over time to solve the brain's binding problem. We focus on mechanisms of neural inhibition and top-down feedback. Specifically, we describe how inhibition creates competition among neural populations that code different features, effectively suppressing irrelevant information, and thus minimizing illusory conjunctions. Top-down feedback contributes to binding in a similar manner, but by reinforcing relevant features. Together, inhibition and top-down feedback contribute to a competitive environment that ensures only the most appropriate features are bound together. We demonstrate this overall proposal using a biologically realistic neural model of vision that processes features across a hierarchy of interconnected brain areas. Finally, we argue that temporal synchrony plays only a limited role in binding - it does not simultaneously bind multiple objects, but does aid in creating additional contrast between relevant and irrelevant features. Thus, our overall theory constitutes a solution to the binding problem that relies only on simple neural principles without any binding-specific processes.

No MeSH data available.