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Using data-driven model-brain mappings to constrain formal models of cognition.

Borst JP, Nijboer M, Taatgen NA, van Rijn H, Anderson JR - PLoS ONE (2015)

Bottom Line: Although such mappings can be based on the experience of the modeler or on a reading of the literature, a formal method is preferred to prevent researcher-based biases.We then validated this mapping by applying it to two new datasets with associated models.The new mapping was at least as powerful as an existing mapping that was based on the literature, and indicated where the models were supported by the data and where they have to be improved.

View Article: PubMed Central - PubMed

Affiliation: Carnegie Mellon University, Dept. of Psychology, Pittsburgh, United States of America; University of Groningen, Dept. of Artificial Intelligence, Groningen, the Netherlands.

ABSTRACT
In this paper we propose a method to create data-driven mappings from components of cognitive models to brain regions. Cognitive models are notoriously hard to evaluate, especially based on behavioral measures alone. Neuroimaging data can provide additional constraints, but this requires a mapping from model components to brain regions. Although such mappings can be based on the experience of the modeler or on a reading of the literature, a formal method is preferred to prevent researcher-based biases. In this paper we used model-based fMRI analysis to create a data-driven model-brain mapping for five modules of the ACT-R cognitive architecture. We then validated this mapping by applying it to two new datasets with associated models. The new mapping was at least as powerful as an existing mapping that was based on the literature, and indicated where the models were supported by the data and where they have to be improved. We conclude that data-driven model-brain mappings can provide strong constraints on cognitive models, and that model-based fMRI is a suitable way to create such mappings.

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The new mapping of ACT-R modules to brain regions.Yellow indicates the new mapping, white the original one (the original visual ROI is not shown because it is located on different slices—its center is −43, −60, −16). Coordinates are the center of mass in the MNI system.
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pone.0119673.g004: The new mapping of ACT-R modules to brain regions.Yellow indicates the new mapping, white the original one (the original visual ROI is not shown because it is located on different slices—its center is −43, −60, −16). Coordinates are the center of mass in the MNI system.

Mentions: The regions that we created in this manner were all left-lateralized because the most significant voxels were located in the left hemisphere. To create right-hemisphere homologues, we mirrored these regions. The resulting ROIs are shown in Fig. 4, in yellow, and summarized in Table 1. The white squares indicate the original mapping of ACT-R (the original visual ROI is not shown, as it is located outside the displayed slices). For most modules the original and the new mapping overlap in part. However, the new region for the problem state is more anterior than in the original mapping, and the new visual region is in a completely different location than the original ROI (located in the fusiform gyrus; x = −43, y = −60, z = −16). In addition, unlike the original mapping, the new mapping follows brain structures, which might increase the power of the analysis (assuming that brain functions do not cross structural boundaries). The new ROIs can be downloaded from http://www.jelmerborst.nl/models, both as binary images and as MarsBar ROI definitions for use with the SPM analysis software [54].


Using data-driven model-brain mappings to constrain formal models of cognition.

Borst JP, Nijboer M, Taatgen NA, van Rijn H, Anderson JR - PLoS ONE (2015)

The new mapping of ACT-R modules to brain regions.Yellow indicates the new mapping, white the original one (the original visual ROI is not shown because it is located on different slices—its center is −43, −60, −16). Coordinates are the center of mass in the MNI system.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4352055&req=5

pone.0119673.g004: The new mapping of ACT-R modules to brain regions.Yellow indicates the new mapping, white the original one (the original visual ROI is not shown because it is located on different slices—its center is −43, −60, −16). Coordinates are the center of mass in the MNI system.
Mentions: The regions that we created in this manner were all left-lateralized because the most significant voxels were located in the left hemisphere. To create right-hemisphere homologues, we mirrored these regions. The resulting ROIs are shown in Fig. 4, in yellow, and summarized in Table 1. The white squares indicate the original mapping of ACT-R (the original visual ROI is not shown, as it is located outside the displayed slices). For most modules the original and the new mapping overlap in part. However, the new region for the problem state is more anterior than in the original mapping, and the new visual region is in a completely different location than the original ROI (located in the fusiform gyrus; x = −43, y = −60, z = −16). In addition, unlike the original mapping, the new mapping follows brain structures, which might increase the power of the analysis (assuming that brain functions do not cross structural boundaries). The new ROIs can be downloaded from http://www.jelmerborst.nl/models, both as binary images and as MarsBar ROI definitions for use with the SPM analysis software [54].

Bottom Line: Although such mappings can be based on the experience of the modeler or on a reading of the literature, a formal method is preferred to prevent researcher-based biases.We then validated this mapping by applying it to two new datasets with associated models.The new mapping was at least as powerful as an existing mapping that was based on the literature, and indicated where the models were supported by the data and where they have to be improved.

View Article: PubMed Central - PubMed

Affiliation: Carnegie Mellon University, Dept. of Psychology, Pittsburgh, United States of America; University of Groningen, Dept. of Artificial Intelligence, Groningen, the Netherlands.

ABSTRACT
In this paper we propose a method to create data-driven mappings from components of cognitive models to brain regions. Cognitive models are notoriously hard to evaluate, especially based on behavioral measures alone. Neuroimaging data can provide additional constraints, but this requires a mapping from model components to brain regions. Although such mappings can be based on the experience of the modeler or on a reading of the literature, a formal method is preferred to prevent researcher-based biases. In this paper we used model-based fMRI analysis to create a data-driven model-brain mapping for five modules of the ACT-R cognitive architecture. We then validated this mapping by applying it to two new datasets with associated models. The new mapping was at least as powerful as an existing mapping that was based on the literature, and indicated where the models were supported by the data and where they have to be improved. We conclude that data-driven model-brain mappings can provide strong constraints on cognitive models, and that model-based fMRI is a suitable way to create such mappings.

Show MeSH