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Intelligence is composed of a set of cognitive abilities hierarchically organized. General and specific abilities capture distinguishable, but related, facets of the intelligence construct. Here, we analyze gray matter with three morphometric indices (volume, cortical surface area, and cortical thickness) at three levels of the intelligence hierarchy (tests, first-order factors, and a higher-order general factor, g). A group of one hundred and four healthy young adults completed a cognitive battery and underwent high-resolution structural MRI. Latent scores were computed for the intelligence factors and tests were also analyzed. The key finding reveals substantial variability in gray matter correlates at the test level, which is substantially reduced for the first-order and the higher-order factors. This supports a reversed hierarchy in the brain with respect to cognitive abilities at different psychometric levels: the greater the generality, the smaller the number of relevant gray matter clusters accounting for individual differences in intelligent performance.

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Evidence from neuroimaging studies suggests that intelligence differences may be supported by a parieto-frontal network. Research shows that this network is also relevant for cognitive functions such as working memory and attention. However, previous studies have not explicitly analyzed the commonality of brain areas between a broad array of intelligence factors and cognitive functions tested in the same sample. Here fluid, crystallized, and spatial intelligence, along with working memory, executive updating, attention, and processing speed were each measured by three diverse tests or tasks. These twenty-one measures were completed by a group of one hundred and four healthy young adults. Three cortical measures (cortical gray matter volume, cortical surface area, and cortical thickness) were regressed against psychological latent scores obtained from a confirmatory factor analysis for removing test and task specific variance. For cortical gray matter volume and cortical surface area, the main overlapping clusters were observed in the middle frontal gyrus and involved fluid intelligence and working memory. Crystallized intelligence showed an overlapping cluster with fluid intelligence and working memory in the middle frontal gyrus. The inferior frontal gyrus showed overlap for crystallized intelligence, spatial intelligence, attention, and processing speed. The fusiform gyrus in temporal cortex showed overlap for spatial intelligence and attention. Parietal and occipital areas did not show any overlap across intelligence and cognitive factors. Taken together, these findings underscore that structural features of gray matter in the frontal lobes support those aspects of intelligence related to basic cognitive processes.

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BACKGROUND: Previous studies have identified brain areas related to cognitive abilities and personality, respectively. In this exploratory study, we extend the application of modern neuroimaging techniques to another area of individual differences, vocational interests, and relate the results to an earlier study of cognitive abilities salient for vocations. FINDINGS: First, we examined the psychometric relationships between vocational interests and abilities in a large sample. The primary relationships between those domains were between Investigative (scientific) interests and general intelligence and between Realistic ("blue-collar") interests and spatial ability. Then, using MRI and voxel-based morphometry, we investigated the relationships between regional gray matter volume and vocational interests. Specific clusters of gray matter were found to be correlated with Investigative and Realistic interests. Overlap analyses indicated some common brain areas between the correlates of Investigative interests and general intelligence and between the correlates of Realistic interests and spatial ability. CONCLUSIONS: Two of six vocational-interest scales show substantial relationships with regional gray matter volume. The overlap between the brain correlates of these scales and cognitive-ability factors suggest there are relationships between individual differences in brain structure and vocations.

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Adults with Down syndrome (DS) are at risk for developing Alzheimer's disease (AD). While plasma amyloid-ß (Aß) is known to be elevated in DS, its relationship to cognitive functioning is unknown. To assess this relationship, samples from two groups of subjects were used. In the first group, nondemented adults with DS were compared to: 1) a group of young and old individuals without DS and 2) to a group of patients with AD. Compared to these controls, there were significantly higher levels of plasma Aß in nondemented adults with DS while AD patients showed lower levels of plasma Aß. A larger second group included demented and nondemented adults with DS, in order to test the hypothesis that plasma Aß may vary as a function of dementia and Apolipoprotein E (ApoE) genotype. Plasma Aß levels alone did not dissociate DS adults with and without dementia. However, in demented adults with DS, ApoE4 was associated with higher Aß40 but not Aß42. After controlling for level of intellectual disability (mild, moderate, severe) and the presence or absence of dementia, there was an improved prediction of neuropsychological scores by plasma Aß. In summary, plasma Aß can help predict cognitive function in adults with DS independently of the presence or absence of dementia.

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BACKGROUND: Individual differences in cognitive abilities provide information that is valuable for vocational guidance, but there is an ongoing debate about the role of ability factors, including general intelligence (g), compared to individual tests. Neuroimaging can help identify brain parameters that may account for individual differences in both factors and tests. Here we investigate how eight tests used in vocational guidance correlate to regional gray matter. We compare brain networks identified by using scores for ability factors (general and specific) to those identified by using individual tests to determine whether these relatively broad and narrow approaches yield similar results. FINDINGS: Using MRI and voxel-based morphometry (VBM), we correlated gray matter with independent ability factors (general intelligence, speed of reasoning, numerical, spatial, memory) and individual test scores from a battery of cognitive tests completed by 40 individuals seeking vocational guidance. Patterns of gray matter correlations differed between group ability factors and individual tests. Moreover, tests within the same factor showed qualitatively different brain correlates to some degree. CONCLUSIONS: The psychometric factor structure of cognitive tests can help identify brain networks related to cognitive abilities beyond a general intelligence factor (g). Correlates of individual ability tests with gray matter, however, appear to have some differences from the correlates for group factors.

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That creativity and psychopathology are somehow linked remains a popular but controversial idea in neuroscience research. Brain regions implicated in both psychosis-proneness and creative cognition include frontal projection zones and association fibers. In normal subjects, we have previously demonstrated that a composite measure of divergent thinking (DT) ability exhibited significant inverse relationships in frontal lobe areas with both cortical thickness and metabolite concentration of N-acetyl-aspartate (NAA). These findings support the idea that creativity may reside upon a continuum with psychopathology. Here we examine whether white matter integrity, assessed by Fractional Anisotropy (FA), is related to two measures of creativity (Divergent Thinking and Openness to Experience). Based on previous findings, we hypothesize inverse correlations within fronto-striatal circuits. Seventy-two healthy, young adult (18-29 years) subjects were scanned on a 3 Tesla scanner with Diffusion Tensor Imaging. DT measures were scored by four raters (alpha = .81) using the Consensual Assessment Technique, from which a composite creativity index (CCI) was derived. We found that the CCI was significantly inversely related to FA within the left inferior frontal white matter (t = 5.36, p = .01), and Openness was inversely related to FA within the right inferior frontal white matter (t = 4.61, p = .04). These findings demonstrate an apparent overlap in specific white matter architecture underlying the normal variance of divergent thinking, openness, and psychotic-spectrum traits, consistent with the idea of a continuum.

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Creativity has long been a construct of interest to philosophers, psychologists and, more recently, neuroscientists. Recent efforts have focused on cognitive processes likely to be important to the manifestation of novelty and usefulness within a given social context. One such cognitive process - divergent thinking - is the process by which one extrapolates many possible answers to an initial stimulus or target data set. We sought to link well established measures of divergent thinking and creative achievement (Creative Achievement Questionnaire - CAQ) to cortical thickness in a cohort of young (23.7 +/- 4.2 years), healthy subjects. Three independent judges ranked the creative products of each subject using the consensual assessment technique (Amabile, 1982) from which a "composite creativity index" (CCI) was derived. Structural magnetic resonance imaging was obtained at 1.5 Tesla Siemens scanner. Cortical reconstruction and volumetric segmentation were performed with the FreeSurfer image analysis suite. A region within the lingual gyrus was negatively correlated with CCI; the right posterior cingulate correlated positively with the CCI. For the CAQ, lower left lateral orbitofrontal volume correlated with higher creative achievement; higher cortical thickness was related to higher scores on the CAQ in the right angular gyrus. This is the first study to link cortical thickness measures to psychometric measures of creativity. The distribution of brain regions, associated with both divergent thinking and creative achievement, suggests that cognitive control of information flow among brain areas may be critical to understanding creative cognition.

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Intelligence can be defined as a general mental ability for reasoning, problem solving, and learning. Because of its general nature, intelligence integrates cognitive functions such as perception, attention, memory, language, or planning. On the basis of this definition, intelligence can be reliably measured by standardized tests with obtained scores predicting several broad social outcomes such as educational achievement, job performance, health, and longevity. A detailed understanding of the brain mechanisms underlying this general mental ability could provide significant individual and societal benefits. Structural and functional neuroimaging studies have generally supported a frontoparietal network relevant for intelligence. This same network has also been found to underlie cognitive functions related to perception, short-term memory storage, and language. The distributed nature of this network and its involvement in a wide range of cognitive functions fits well with the integrative nature of intelligence. A new key phase of research is beginning to investigate how functional networks relate to structural networks, with emphasis on how distributed brain areas communicate with each other.

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BACKGROUND: Neuro-imaging studies demonstrate plasticity of cortical gray matter before and after practice for some motor and cognitive tasks in adults. Other imaging studies show functional changes after practice, but there is not yet direct evidence of how structural and functional changes may be related. A fundamental question is whether they occur at the same cortical sites, adjacent sites, or sites in other parts of a network. FINDINGS: Using a 3 T MRI, we obtained structural and functional images in adolescent girls before and after practice on a visual-spatial problem-solving computer game, Tetris. After three months of practice, compared to the structural scans of controls, the group with Tetris practice showed thicker cortex, primarily in two areas: left BAs 6 and 22/38. Based on fMRI BOLD signals, the Tetris group showed cortical activations throughout the brain while playing Tetris, but significant BOLD decreases, mostly in frontal areas, were observed after practice. None of these BOLD decreases, however, overlapped with the cortical thickness changes. CONCLUSION: Regional cortical thickness changes were observed after three months of Tetris practice. Over the same period, brain activity decreases were observed in several other areas. These data indicate that structural change in one brain area does not necessarily result in functional change in the same location, at least on the levels assessed with these MRI methods.

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General intelligence (g) is highly correlated with working-memory capacity (WMC). It has been argued that these central psychological constructs should share common neural systems. The present study examines this hypothesis using structural magnetic resonance imaging to determine any overlap in brain areas where regional grey matter volumes are correlated to measures of general intelligence and to memory span. In normal volunteers (N = 48) the results (p < .05, corrected for multiple comparisons) indicate that a common anatomic framework for these constructs implicates mainly frontal grey matter regions belonging to Brodmann area (BA) 10 (right superior frontal gyrus and left middle frontal gyrus) and, to a lesser degree, the right inferior parietal lobule (BA 40). These findings support the nuclear role of a discrete parieto-frontal network.

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"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 the Parieto-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.

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The general factor of intelligence (g) results from the empirical fact that almost all cognitive tests are positively correlated with one another. Individual tests can be classified according to the degree to which they involve g. Here, regional brain volumes associated with g are investigated by means of structural magnetic resonance imaging and voxel-based morphometry. First, individual differences in the amount of regional gray matter volumes across the entire brain were correlated with eight cognitive tests showing distinguishable g-involvement. Results show that increasing g-involvement of individual tests was associated with increased gray matter volume throughout the brain. Second, it is shown that two prototypical measures of verbal and non-verbal g (i.e., vocabulary and block design) correlate with the amount of regional gray matter across frontal, parietal, temporal, and occipital lobes, suggesting that the general factor of intelligence relates to areas distributed across the brain as opposed to the view that g derives exclusively from the frontal lobes.

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Response time (RT) generally slows with aging, but the contribution of structural brain changes to this slowing is unknown. We used voxel-based morphometry (VBM) to determine gray matter (GM) and white matter (WM) brain volumes in 9 middle-aged adults (38-58 years old) and 9 seniors (66-82 years old). We correlated brain volumes with RT assessed in both a simple visual stimulus-response task and a visual continuous recognition memory task. No GM correlations with simple RT were significant; there was one WM correlation in the right fusiform gyrus. In the memory task, faster RT was correlated (p < .05, corrected) with less GM in the globus pallidus, the parahippocampus, and the thalamus for both groups. Several Brodmann areas (BA) differed between the groups such that in each area, less GM was correlated with slower RTs in the middle-aged group but with faster RTs in the senior group (BAs 19, 37, 46, 9, 8, 6, 13, 10, 41, and 7). The results suggest that individual differences in specific brain structure volumes should be considered as potential moderating factors in cognitive brain imaging studies.

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Researchers have long attempted to determine brain correlates of intelligence using available neuroimaging technology including CT, MRI, PET, and fMRI. Although structural and functional imaging techniques are well suited to assess gross cortical regions associated with intelligence, the integrity and functioning of underlying white matter networks critical to coordinated cortical integration remain comparatively understudied. A relatively recent neuroimaging advance is magnetic resonance spectroscopy (MRS) which allows for interrogation of biochemical substrates of brain structure and function in vivo. In this study, we examined twenty-seven normal control subjects (17 male, 10 female) to determine whether N-acetylaspartate (NAA), a metabolite found primarily within neurons, is related to intelligence as assessed by the Wechsler Adult Intelligence Scale-III. Of the three white matter regions studied (i.e., left frontal, right frontal, left occipito-parietal), we found that a model including only left occipito-parietal white matter predicted intellectual performance [F(1,25) = 8.65, P = .007; r2 = .26], providing regional specificity to our previous findings of NAA-IQ relationships. Moreover, we found that a complex combination of left frontal and left occipito-parietal NAA strongly predicted performance in women, but not men [F(2,7) = 21.84, P < .001; adjusted r2 = .82]. Our results highlight a biochemical substrate of normal intellectual performance, mediated by sex, within white matter association fibers linking posterior to frontal brain regions.

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We examined the relationship between structural brain variation and general intelligence using voxel-based morphometric analysis of MRI data in men and women with equivalent IQ scores. Compared to men, women show more white matter and fewer gray matter areas related to intelligence. In men IQ/gray matter correlations are strongest in frontal and parietal lobes (BA 8, 9, 39, 40), whereas the strongest correlations in women are in the frontal lobe (BA10) along with Broca's area. Men and women apparently achieve similar IQ results with different brain regions, suggesting that there is no singular underlying neuroanatomical structure to general intelligence and that different types of brain designs may manifest equivalent intellectual performance.

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Total brain volume accounts for about 16% of the variance in general intelligence scores (IQ), but how volumes of specific regions-of-interest (ROIs) relate to IQ is not known. We used voxel-based morphometry (VBM) in two independent samples to identify substantial gray matter (GM) correlates of IQ. Based on statistical conjunction of both samples (N = 47; P < 0.05 corrected for multiple comparisons), more gray matter is associated with higher IQ in discrete Brodmann areas (BA) including frontal (BA 10, 46, 9), temporal (BA 21, 37, 22, 42), parietal (BA 43 and 3), and occipital (BA 19) lobes and near BA 39 for white matter (WM). These results underscore the distributed neural basis of intelligence and suggest a developmental course for volume--IQ relationships in adulthood.

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BACKGROUND: To elucidate neural correlates associated with processing of tonic aching pain, the authors used high-field (3-T) functional magnetic resonance imaging with a blocked parametric study design and characterized regional brain responses to electrical stimulation according to stimulus intensity-response functions. METHODS: Pain was induced in six male volunteers using a 5-Hz electrical stimulus applied to the right index finger. Scanning sequences involved different levels of stimulation corresponding to tingling sensation (P1), mild pain (P2), or high pain (P3). Common effects across subjects were sought using a conjunction analyses approach, as implemented in statistical parametric mapping (SPM-99). RESULTS: The contralateral posterior/mid insula and contralateral primary somatosensory cortex were most associated with encoding stimulus intensity because they showed a positive linear relation between blood oxygenation level-dependent signal responses and increasing stimulation intensity (P1 < P2 < P3). The contralateral secondary somatosensory cortex demonstrated a response function most consistent with a role in pain intensity encoding because it had no significant response during the innocuous condition (P1) but proportionally increased activity with increasingly painful stimulus intensities (0 < P2 < P3). Finally, a portion of the anterior cingulate cortex (area 24) and supplementary motor area 6 demonstrated a high pain-specific response (P3). CONCLUSIONS: The use of response function modeling, conjunction analysis, and high-field imaging reveals dissociable regional responses to a tonic aching electrical pain. Most specifically, the primary somatosensory cortex and insula seem to encode stimulus intensity information, whereas the secondary somatosensory cortex encodes pain intensity information. The cingulate findings are consistent with its proposed role in processing affective-motivational aspects of pain.

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Previous structural brain imaging studies of Down Syndrome (DS) have offered important insights into the underlying morphometric aberrations associated with the condition. These previous studies have relied almost exclusively on classic region-of-interest (ROI)-based morphometry, a method in which a finite number of anatomical structures must be defined and delineated a priori. Here we use the fully automated voxel-based morphometry (VBM) approach on 19 nondemented individuals with DS and 11 age-matched controls in order to provide a full-brain assessment of DS morphology. Foci of statistically significant (P < 0.05, corrected for multiple comparisons) reductions in gray matter (GM) tissue were observed in the cerebellum, cingulate gyrus, left medial frontal lobe, right middle/superior temporal gyrus, and the left CA2/CA3 region of the hippocampus. Significant decreases in white matter (WM) tissue were noted throughout the inferior brainstem. Foci of statistically significant (P < 0.05, corrected for multiple comparisons) increases in GM tissue were observed in a superior/caudal portion of the brainstem and left parahippocampal gyrus. Significant increases in WM tissue were noted bilaterally in the parahippocampal gyrus. We also noted significant increases in cerebral spinal fluid in regions suggesting enlarged lateral ventricles in the DS group. While these results are generally consistent with prior ROI-based imaging studies of nondemented DS individuals, the present findings provide additional understanding of the three-dimensional topography of DS morphology throughout the brain. The consistency of these findings with prior imaging reports demonstrates the utility of the VBM technique for investigating the neuroanatomy of DS.

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