Mapping Mental Function to Brain Structure: How Can Cognitive Neuroimaging Succeed? - PubMed (original) (raw)

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Mapping Mental Function to Brain Structure: How Can Cognitive Neuroimaging Succeed?

Russell A Poldrack. Perspect Psychol Sci. 2010 Nov.

Abstract

The goal of cognitive neuroscience is to identify the mapping between brain function and mental processing. In this article, I examine the strategies that have been used to identify such mappings and argue that they may be fundamentally unable to identify selective structure-function mappings. To understand the functional anatomy of mental processes, it will be necessary for researchers to move from the brain-mapping strategies that the field has employed toward a search for selective associations. This will require a greater focus on the structure of cognitive processes, which can be achieved through the development of formal ontologies that describe the structure of mental processes. In this article, I outline the Cognitive Atlas Project, which is developing such ontologies, and show how this knowledge could be used in conjunction with data-mining approaches to more directly relate mental processes and brain function.

Keywords: machine learning; neuroimaging; ontology; prediction.

© The Author(s) 2010.

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Figures

Figure 1

Figure 1

Loading of several individual regions onto mental concepts was computed by projecting the average activity for each of the 8 tasks in the Poldrack et al. (2009) dataset onto a matrix describing the relation between tasks and mental concepts. Strength of loading is depicted using a tag cloud, with the size of the term representing the strength of the loading and the color of the term representing positive [red] or negative [blue] loading. The upper panels depict reasonable loadings of basic processes onto cortical regions, given the known function of those regions. The bottom left panel shows predictable negative signals associated with decision making in the medial prefrontal region, which is known to exhibit deactivation across a wide range of cognitive tasks (Gusnard et al., 2001). The bottom right shows the pattern for right inferior frontal operculum, which shows an unexpected pattern with strongest loading on vision.

Figure 2

Figure 2

Depiction of the structure of the Cognitive Atlas knowledge base. The left panel shows examples of mental concepts (such as “working memory”) and relations between them. The right panel shows an example of a particular mental task, the Sternberg Item Recognition Task, and two indicators for the task. It is these task/indicator combinations that link directly to mental concepts, as show by the “is measured by” relations in this figure.

Figure 3

Figure 3

Selectivity analysis of several mental concepts using the BrainMap database Lenartowicz et al. (from 2010). Discriminability (A’) values were obtained using a k-nearest neighbor classifier (k=3). The bottom right triangle of the figure is a gray scale depiction of A’ values, with brighter tones denoting greater discriminability. The top left triangle is a reconstruction of which regions provided discriminability between each pair of concepts. WM: working memory, TS: task switching, RI: response inhibition, CC: cognitive control, BI: bilingual language.

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