Kenia Martínez

Neuroanatomic overlap between intelligence and cognitive factors: morphometry methods provide support for the key role of the frontal lobes.

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.

Subcortical regional morphology correlates with fluid and spatial intelligence.

Neuroimaging studies have revealed associations between intelligence and brain morphology. However, researchers have focused primarily on the anatomical features of the cerebral cortex, whereas subcortical structures, such as the basal ganglia (BG), have often been neglected despite extensive functional evidence on their relation with higher‐order cognition. Here we performed shape analyses to understand how individual differences in BG local morphology account for variability in cognitive performance. Structural MRI was acquired in 104 young adults (45 men, 59 women, mean age = 19.83, SD = 1.64), and the outer surface of striatal structures (caudate, nucleus accumbens, and putamen), globus pallidus, and thalamus was estimated for each subject and hemisphere. Further, nine cognitive tests were used to measure fluid (Gf), crystallized (Gc), and spatial intelligence (Gv). Latent scores for these factors were computed by means of confirmatory factor analysis and regressed vertex‐wise against subcortical shape (local displacements of vertex position), controlling for age, sex, and adjusted for brain size. Significant results (FDR < 5%) were found for Gf and Gv, but not Gc, for the right striatal structures and thalamus. The main results show a relative enlargement of the rostral putamen, which is functionally connected to the right dorsolateral prefrontal cortex and other intelligence‐related prefrontal areas. Hum Brain Mapp 35:1957–1968, 2014.

Changes in resting-state functionally connected parietofrontal networks after videogame practice

Neuroimaging studies provide evidence for organized intrinsic activity under task‐free conditions. This activity serves functionally relevant brain systems supporting cognition. Here, we analyze changes in resting‐state functional connectivity after videogame practice applying a test–retest design. Twenty young females were selected from a group of 100 participants tested on four standardized cognitive ability tests. The practice and control groups were carefully matched on their ability scores. The practice group played during two sessions per week across 4 weeks (16 h total) under strict supervision in the laboratory, showing systematic performance improvements in the game. A group independent component analysis (GICA) applying multisession temporal concatenation on test–retest resting‐state fMRI, jointly with a dual‐regression approach, was computed. Supporting the main hypothesis, the key finding reveals an increased correlated activity during rest in certain predefined resting state networks (albeit using uncorrected statistics) attributable to practice with the cognitively demanding tasks of the videogame. Observed changes were mainly concentrated on parietofrontal networks involved in heterogeneous cognitive functions. Hum Brain Mapp 34:3143–3157, 2013.

Sensation‐to‐cognition cortical streams in attention‐deficit/hyperactivity disorder

We sought to determine whether functional connectivity streams that link sensory, attentional, and higher‐order cognitive circuits are atypical in attention‐deficit/hyperactivity disorder (ADHD). We applied a graph‐theory method to the resting‐state functional magnetic resonance imaging data of 120 children with ADHD and 120 age‐matched typically developing children (TDC). Starting in unimodal primary cortex—visual, auditory, and somatosensory—we used stepwise functional connectivity to calculate functional connectivity paths at discrete numbers of relay stations (or link‐step distances). First, we characterized the functional connectivity streams that link sensory, attentional, and higher‐order cognitive circuits in TDC and found that systems do not reach the level of integration achieved by adults. Second, we searched for stepwise functional connectivity differences between children with ADHD and TDC. We found that, at the initial steps of sensory functional connectivity streams, patients display significant enhancements of connectivity degree within neighboring areas of primary cortex, while connectivity to attention‐regulatory areas is reduced. Third, at subsequent link‐step distances from primary sensory cortex, children with ADHD show decreased connectivity to executive processing areas and increased degree of connections to default mode regions. Fourth, in examining medication histories in children with ADHD, we found that children medicated with psychostimulants present functional connectivity streams with higher degree of connectivity to regions subserving attentional and executive processes compared to medication‐naïve children. We conclude that predominance of local sensory processing and lesser influx of information to attentional and executive regions may reduce the ability to organize and control the balance between external and internal sources of information in ADHD. Hum Brain Mapp 36:2544–2557, 2015.

Reversed hierarchy in the brain for general and specific cognitive abilities: A morphometric analysis

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. Hum Brain Mapp 35:3805–3818, 2014.

Sex differences in neocortical structure and cognitive performance: A surface-based morphometry study.

On average, men show larger brain volumes than women. Regional differences have been also observed, although most of the available studies apply voxel-based morphometry (VBM). Reports applying surface-based morphometry (SBM) have been focused mainly on cortical thickness (CT). Here we apply SBM for obtaining global and regional indices of CT, cortical surface area (CSA), and cortical gray matter volume (CGMV) from samples of men (N=40) and women (N=40) matched for their performance on four cognitive factors varying in their complexity: processing speed, attention control, working memory capacity, and fluid intelligence. These were the main findings: 1) CT and CSA produced very weak correlations in both sexes, 2) men showed larger values in CT, CSA, and CGMV, and 3) cognitive performance was unrelated to brain structural variation within sexes. Therefore, we found substantial group differences in brain structure, but there was no relationship with cognitive performance both between and within-sexes.

Reduced Gyrification Is Related to Reduced Interhemispheric Connectivity in Autism Spectrum Disorders.

OBJECTIVE Autism spectrum disorders (ASD) have been associated with atypical cortical gray and subcortical white matter development. Neurodevelopmental theories postulate that a relation between cortical maturation and structural brain connectivity may exist. We therefore investigated the development of gyrification and white matter connectivity and their relationship in individuals with ASD and their typically developing peers. METHOD T1- and diffusion-weighted images were acquired from a representative sample of 30 children and adolescents with ASD (aged 8-18 years), and 29 typically developing children matched for age, sex, hand preference, and socioeconomic status. The FreeSurfer suite was used to calculate cortical volume, surface area, and gyrification index. Measures of structural connectivity were estimated using probabilistic tractography and tract-based spatial statistics (TBSS). RESULTS Left prefrontal and parietal cortex showed a relative, age-dependent decrease in gyrification index in children and adolescents with ASD compared to typically developing controls. This result was replicated in an age-and IQ-matched sample provided by the Autism Brain Imaging Data Exchange (ABIDE) initiative. Furthermore, tractography and TBSS showed a complementary pattern in which left prefrontal gyrification was negatively related to radial diffusivity in the forceps minor in participants with ASD. CONCLUSION The present study builds on earlier findings of abnormal gyrification and structural connectivity in the prefrontal cortex in ASD. It provides a more comprehensive neurodevelopmental characterization of ASD, involving interdependent changes in microstructural white and cortical gray matter. The findings of related abnormal patterns of gyrification and white matter connectivity support the notion of the intertwined development of 2 major morphometric domains in ASD.

Reproducibility of brain‐cognition relationships using three cortical surface‐based protocols: An exhaustive analysis based on cortical thickness

People differ in their cognitive functioning. This variability has been exhaustively examined at the behavioral, neural and genetic level to uncover the mechanisms by which some individuals are more cognitively efficient than others. Studies investigating the neural underpinnings of interindividual differences in cognition aim to establish a reliable nexus between functional/structural properties of a given brain network and higher order cognitive performance. However, these studies have produced inconsistent results, which might be partly attributed to methodological variations. In the current study, 82 healthy young participants underwent MRI scanning and completed a comprehensive cognitive battery including measurements of fluid, crystallized, and spatial intelligence, along with working memory capacity/executive updating, controlled attention, and processing speed. The cognitive scores were obtained by confirmatory factor analyses. T1‐weighted images were processed using three different surface‐based morphometry (SBM) pipelines, varying in their degree of user intervention, for obtaining measures of cortical thickness (CT) across the brain surface. Distribution and variability of CT and CT‐cognition relationships were systematically compared across pipelines and between two cognitively/demographically matched samples to overcome potential sources of variability affecting the reproducibility of findings. We demonstrated that estimation of CT was not consistent across methods. In addition, among SBM methods, there was considerable variation in the spatial pattern of CT‐cognition relationships. Finally, within each SBM method, results did not replicate in matched subsamples. Hum Brain Mapp 36:3227–3245, 2015.

Disparate Connectivity for Structural and Functional Networks is Revealed When Physical Location of the Connected Nodes is Considered

Macroscopic brain networks have been widely described with the manifold of metrics available using graph theory. However, most analyses do not incorporate information about the physical position of network nodes. Here, we provide a multimodal macroscopic network characterization while considering the physical positions of nodes. To do so, we examined anatomical and functional macroscopic brain networks in a sample of twenty healthy subjects. Anatomical networks are obtained with a graph based tractography algorithm from diffusion-weighted magnetic resonance images (DW-MRI). Anatomical connections identified via DW-MRI provided probabilistic constraints for determining the connectedness of 90 different brain areas. Functional networks are derived from temporal linear correlations between blood-oxygenation level-dependent signals derived from the same brain areas. Rentian Scaling analysis, a technique adapted from very-large-scale integration circuits analyses, shows that functional networks are more random and less optimized than the anatomical networks. We also provide a new metric that allows quantifying the global connectivity arrangements for both structural and functional networks. While the functional networks show a higher contribution of inter-hemispheric connections, the anatomical networks highest connections are identified in a dorsal–ventral arrangement. These results indicate that anatomical and functional networks present different connectivity organizations that can only be identified when the physical locations of the nodes are included in the analysis.

Enhanced structural connectivity within a brain sub-network supporting working memory and engagement processes after cognitive training

HIGHLIGHTSHere we study brain changes after cognitive training within the connectome framework.Network‐based statistics (NBS) and graph theoretical analyses were applied for studying the interaction groups × times.The training group show enhanced connectivity, strength and global efficiency.The identified network supports cognitive processes required by the training. ABSTRACT The structural connectome provides relevant information about experience and training‐related changes in the brain. Here, we used network‐based statistics (NBS) and graph theoretical analyses to study structural changes in the brain as a function of cognitive training. Fifty‐six young women were divided in two groups (experimental and control). We assessed their cognitive function before and after completing a working memory intervention using a comprehensive battery that included fluid and crystallized abilities, working memory and attention control, and we also obtained structural MRI images. We acquired and analyzed diffusion‐weighted images to reconstruct the anatomical connectome and we computed standardized changes in connectivity as well as group differences across time using NBS. We also compared group differences relying on a variety of graph‐theory indices (clustering, characteristic path length, global and local efficiency and strength) for the whole network as well as for the sub‐network derived from NBS analyses. Finally, we calculated correlations between these graph indices and training performance as well as the behavioral changes in cognitive function. Our results revealed enhanced connectivity for the training group within one specific network comprised of nodes/regions supporting cognitive processes required by the training (working memory, interference resolution, inhibition, and task engagement). Significant group differences were also observed for strength and global efficiency indices in the sub‐network detected by NBS. Therefore, the connectome approach is a valuable method for tracking the effects of cognitive training interventions across specific sub‐networks. Moreover, this approach allows for the computation of graph theoretical network metrics to quantify the topological architecture of the brain network detected. The observed structural brain changes support the behavioral results reported earlier (see Colom, Román, et al., 2013)