Distributed neural system for general intelligence revealed by lesion mapping

Gläscher, Jan; Rudrauf, David; Colom, Roberto; Paul, Lynn K.; Tranel, Daniel; Damásio, Hanna; Adolphs, Ralph

doi:10.1073/pnas.0910397107

Cited by 264 publications

(215 citation statements)

References 50 publications

(58 reference statements)

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“…Correspondingly, factor analyses of such tests show separate as well as shared variance between subtests, and different subtests are affected by different patterns of brain damage (30). To the extent that the common element reflects fluid intelligence, however, our data suggest specific association with MD cortex (19).…”

Section: Discussioncontrasting

confidence: 50%

See 1 more Smart Citation

Fluid intelligence loss linked to restricted regions of damage within frontal and parietal cortex

Woolgar

Parr²,

Cusack³

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

193

148

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The authors note that on page 14900, right column, first paragraph, lines 1-5, the following statement appeared incorrectly: "In the group with frontal lesions (n = 44), only MD lesion volume was retained as a significant predictor (r = −0.40; P = 0.004) (Fig. 3A). The correlation between behavioral deficit and MD lesion volume also remained significant if non-MD lesion volume was first partialled out (r = −0.27; P = 0.037)." The statement should instead appear as: "In the group with frontal lesions (n = 44), MD lesion volume was significantly predictive of behavioral deficit (r = −0.35; P = 0.009) (Fig. 3A). However, the correlation was no longer significant if non-MD lesion volume was first partialled out (r = −0.19; P = 0.106). Accordingly, MD lesion volume was not retained as a significant predictor in the multiple regression." "MD" refers to the multiple demand regions (1). This error does not affect the conclusions of the article.

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Section: Discussioncontrasting

confidence: 50%

“…Others have reported similar deficits across frontal and parietal cortex (18). An important recent study showed correlations with g for lesions in several regions of left frontal and parietal cortex as well as for damage to major white matter tracts (19). In this study we examined the specific causal role of MD regions as defined by functional imaging.…”

mentioning

confidence: 99%

Fluid intelligence loss linked to restricted regions of damage within frontal and parietal cortex

Woolgar

Parr²,

Cusack³

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

193

148

View full text Add to dashboard Cite

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“…A regional pattern of cortical area-cognition relationships was present in all lobes. This finding fits with the notion that GCA is supported by distributed brain networks (44,45). Using genetically defined cortical clusters (6,35), there was evidence that especially prefrontal and medial and posterolateral temporal clusters related more strongly to GCA.…”

Section: Discussionsupporting

confidence: 78%

Neurodevelopmental origins of lifespan changes in brain and cognition

Walhovd

Krogsrud

Amlien

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

179

174

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Neurodevelopmental origins of functional variation in older age are increasingly being acknowledged, but identification of how early factors impact human brain and cognition throughout life has remained challenging. Much focus has been on age-specific mechanisms affecting neural foundations of cognition and their change. In contrast to this approach, we tested whether cerebral correlates of general cognitive ability (GCA) in development could be extended to the rest of the lifespan, and whether early factors traceable to prenatal stages, such as birth weight and parental education, may exert continuous influences. We measured the area of the cerebral cortex in a longitudinal sample of 974 individuals aged 4-88 y (1,633 observations). An extensive cortical region was identified wherein area related positively to GCA in development. By tracking area of the cortical region identified in the child sample throughout the lifespan, we showed that the cortical change trajectories of higher and lower GCA groups were parallel through life, suggesting continued influences of early life factors. Birth weight and parental education obtained from the Norwegian Mother-Child Cohort study were identified as such early factors of possible lifelong influence. Support for a genetic component was obtained in a separate twin sample (Vietnam Era Twin Study of Aging), but birth weight in the child sample had an effect on cortical area also when controlling for possible genetic differences in terms of parental height. Our results provide novel evidence for stability in brain-cognition relationships throughout life, and indicate that early life factors impact brain and cognition for the entire life course. development | aging | cortical change I t is well-established that both brain and cognition change with age, and that although there are early gains, older age brings with it decrements in aspects of both (1, 2). Much focus has been on age-specific mechanisms of neural foundations of cognition and their change (3, 4). In contrast, neurodevelopmental origins of functional variation in older age are now increasingly being acknowledged (5-8), but identification of how early factors may impact human brain and cognition throughout the lifespan has remained challenging.General cognitive ability (GCA) is essential to human beings, relates to a multitude of health and social outcomes (9), and necessarily originates in characteristics of the central nervous system at all ages. Paradoxically, even though GCA is highly vulnerable to the influence of aging, there is a remarkable stability in individuals' GCA relative to their same-age peers (10, 11). It has even been shown that childhood GCA can account for GCA-cortical thickness associations in old age (12). Cortical thickness is known to decrease with age monotonously from relatively early childhood through the entire lifespan (6,13,14). This thinning, albeit continuous, signifies different neurobiological events at different stages of life (15, 16), and does not have a stable functional correla...

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“…Due to the spatial distribution of highly specialized brain areas (Gläscher et al, 2010) and that the main function of the myelin sheet is to isolate the axons, thereby facilitating conduction of action potentials over long distances, individual differences in WM structure are expected to affect cognitive performance, e.g., processing speed (O'Sullivan et al, 2001;Madden et al, 2004Madden et al, , 2009Schulte et al, 2005;Deary et al, 2006;Grieve et al, 2007;Bucur et al, 2008;Correia et al, 2008;Turken et al, 2008;Kennedy and Raz, 2009;Vernooij et al, 2009). The present results confirm a relationship between mRT from the congruent condition and DTI parameters, in that significant effects were seen for AD and MD in the genu and middle sections (body) of the corpus callosum, and in the left anterior thalamic radiation and forceps minor for AD.…”

Section: Wm Characteristics and Information Processing Speedmentioning

confidence: 99%

“…The significance of white matter (WM) integrity for cognitive function is rooted in the spatial distribution of cognitive processes in the brain, involving a complex interplay between multiple areas (Gläscher et al, 2010). Lower fiber integrity may cause less stable flow of electrical currents in dendrites and axons, resulting in neural noise, disruptions of the conduction of action potentials, and possibly increased intraindividual variability (IIV) in task performance (MacDonald et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Reduced White Matter Integrity Is Related to Cognitive Instability

Fjell

Westlye²,

Amlien³

et al. 2011

J. Neurosci.

120

105

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Increased performance variability has been demonstrated in several groups and conditions, including aging and cognitive decline. Structural brain characteristics underlying this phenomenon have so far been elusive. However, there is reason to expect that disconnectivity in associative pathways, whether caused by immature or degraded white matter (WM) tracts, will increase performance variability by neural noise. The aim of this study was to test whether the quality of WM, measured by diffusion tensor imaging, is related to performance variability in healthy adults. Intraindividual standard deviation of the reaction time (sdRT) across trials and median reaction time (mRT) from 270 participants were obtained from a speeded continuous performance task (Eriksen flanker task) with two conditions (congruent, incongruent). Tract-based spatial statistics was used to test the relationship with diffusion characteristics [fractional anisotropy (FA), mean diffusion (MD), radial diffusion (RD), axial diffusion (AD)]. Robust relationships between sdRT and all diffusion measures were found in most WM areas, independently of mRT, age, and sex. The effects were anatomically more widespread in the congruent than the incongruent condition, covering almost 50% of the voxels for RD and MD, and Ͼ25% of the voxels for FA and AD. Partial betas were in the range 0.45-0.55, and the strength of the relationships increased significantly with age. For mRT, the effects were smaller and unstable across condition. We concluded that performance variability is a likely consequence of individual differences in WM integrity, and that it is a promising behavioral correlate of individual differences in WM microstructure.

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Distributed neural system for general intelligence revealed by lesion mapping

Cited by 264 publications

References 50 publications

Fluid intelligence loss linked to restricted regions of damage within frontal and parietal cortex

Fluid intelligence loss linked to restricted regions of damage within frontal and parietal cortex

Neurodevelopmental origins of lifespan changes in brain and cognition

Reduced White Matter Integrity Is Related to Cognitive Instability

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