The Nature of Functional Specialization

The functional role played by any component (e.g., cortical area, subarea, or neuronal population) of the brain is defined by its connections. Certain patterns of cortical projections are so common that they could amount to rules of connectivity. "These rules revolve around one, apparently, overriding strategy that the cerebral cortex uses—that of functional specialization" (Zeki, 1990). Functional specialization demands that cells with common functional properties be grouped together. This architectural constraint necessitates both convergence and divergence of cortical connections. Extrinsic connections between cortical regions are not continuous but occur in patches or clusters. This patchiness has a clear relationship to functional specialization. For example, a visual area at the back of the brain (V2) has a distinctive cytochrome oxidase staining pattern, consisting of thick stripes, thin stripes, and interstripes. When recordings are made in V2, directionally selective (but not wavelength- or color-selective) neurons are found exclusively in the thick stripes. Retrograde (i.e., backwards) labeling of cells in a functionally homogeneous area that is specialized for visual motion (V5) is limited to these thick stripes. Evidence of this nature supports the notion that patchy connectivity is the anatomical substrate of functional specialization. If neurons in a given area share a common responsiveness (by virtue of their connections) to some sensorimotor or cognitive attribute, then this functional specialization is also an anatomical one.

The search for specialized cortical areas still rests upon the axis established in the nineteenth century, namely the lesion-deficit model and brain excitation methods. Current

Image Time-Series

Kernel

Design Matrix

Statistical Parametrical Map (SPM)

Figure 1. Mapping specialization in the brain.

The transformations that constitute an analysis of functional images create a statistical parametric map (SPM). SPMs can be thought of as X rays of the significance of an effect (e.g., activation in a specialized area revealed by subtracting scans obtained in one condition from those obtained in another). After realignment the images are subject to nonlinear warping to match a template that conforms to some standard anatomical space. After smoothing, the general linear model is employed to perform the appropriate statistical test at every voxel (i.e., volume element). The test statistics that ensue (usually t- or F statistics) constitute the SPM. SPMs are used to make inferences about brain responses that are then characterized using the fitted responses or parameter estimates. Adjustments to p-values, for the enormous number of tests implicit in an SPM, are usually made using distributional approximations from the theory of Gaussian fields.

Gausian Field Theory p <0.05

Figure 1. Mapping specialization in the brain.

The transformations that constitute an analysis of functional images create a statistical parametric map (SPM). SPMs can be thought of as X rays of the significance of an effect (e.g., activation in a specialized area revealed by subtracting scans obtained in one condition from those obtained in another). After realignment the images are subject to nonlinear warping to match a template that conforms to some standard anatomical space. After smoothing, the general linear model is employed to perform the appropriate statistical test at every voxel (i.e., volume element). The test statistics that ensue (usually t- or F statistics) constitute the SPM. SPMs are used to make inferences about brain responses that are then characterized using the fitted responses or parameter estimates. Adjustments to p-values, for the enormous number of tests implicit in an SPM, are usually made using distributional approximations from the theory of Gaussian fields.

approaches rely on (1) the functional deficits following circumscribed brain injury (neuropsychology), and (2) functional neuroimaging. Although important, the inferences about neuronal architectures, based solely on the lesion-deficit model, are fundamentally limited. The integration of neuropsychology, psychophysics, and neuroimaging has revolutionized our view of the brain, literally and conceptually. Challenging subjects with the appropriate sensori-motor attribute or cognitive process leads to activity changes in, and only in, the relevant specialized areas. This is the model upon which functional imaging is based.

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