The Parieto-Frontal Integration Theory (P-FIT) of intelligence: Converging neuroimaging evidence
Top Cited Papers
- 1 April 2007
- journal article
- review article
- Published by Cambridge University Press (CUP) in Behavioral and Brain Sciences
- Vol. 30 (2), 135-154
- https://doi.org/10.1017/s0140525x07001185
Abstract
“Is there a biology of intelligence which is characteristic of the normal human nervous system?” Here we review 37 modern neuroimaging studies in an attempt to address this question posed by Halstead (1947) as he and other icons of the last century endeavored to understand how brain and behavior are linked through the expression of intelligence and reason. Reviewing studies from functional (i.e., functional magnetic resonance imaging, positron emission tomography) and structural (i.e., magnetic resonance spectroscopy, diffusion tensor imaging, voxel-based morphometry) neuroimaging paradigms, we report a striking consensus suggesting that variations in a distributed network predict individual differences found on intelligence and reasoning tasks. We describe this network as theParieto-Frontal Integration Theory(P-FIT). The P-FIT model includes, by Brodmann areas (BAs): the dorsolateral prefrontal cortex (BAs 6, 9, 10, 45, 46, 47), the inferior (BAs 39, 40) and superior (BA 7) parietal lobule, the anterior cingulate (BA 32), and regions within the temporal (BAs 21, 37) and occipital (BAs 18, 19) lobes. White matter regions (i.e., arcuate fasciculus) are also implicated. The P-FIT is examined in light of findings from human lesion studies, including missile wounds, frontal lobotomy/leukotomy, temporal lobectomy, and lesions resulting in damage to the language network (e.g., aphasia), as well as findings from imaging research identifying brain regions under significant genetic control. Overall, we conclude that modern neuroimaging techniques are beginning to articulate a biology of intelligence. We propose that the P-FIT provides a parsimonious account for many of the empirical observations, to date, which relate individual differences in intelligence test scores to variations in brain structure and function. Moreover, the model provides a framework for testing new hypotheses in future experimental designs.Keywords
This publication has 176 references indexed in Scilit:
- Developmental instability and the neural dynamics of the speed–intelligence relationshipNeuroImage, 2006
- Methods for studying the aging brain: Volumetric analyses versus VBMNeurobiology of Aging, 2005
- Sex-related differences in general intelligence g, brain size, and social statusPersonality and Individual Differences, 2005
- Fluid intelligence and neural efficiency: effects of task complexity and sexPersonality and Individual Differences, 2003
- A functional MRI study of high-level cognition: II. The game of GOCognitive Brain Research, 2003
- Dual Voxel Proton Magnetic Resonance Spectroscopy in the Healthy Elderly: Subcortical-Frontal Axonal N-Acetylaspartate Levels Are Correlated with Fluid Cognitive Abilities Independent of Structural Brain ChangesNeuroImage, 2000
- Voxel-Based Morphometry—The MethodsNeuroImage, 2000
- Albert Einstein's brainThe Lancet, 1999
- The origin of the mammalian brain as a case of evolutionary irreversibilityMedical Hypotheses, 1992
- Circuitry of the frontal association cortex and its relevance to dementiaArchives of Gerontology and Geriatrics, 1987