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

Association of exercise with better olfactory performance and higher functional connectivity between the olfactory cortex and the prefrontal cortex: a resting-state fNIRS study

BACKGROUND

Olfactory deterioration is suggested to be a predictor of some neurodegenerative diseases. Recent studies indicate that physical exercise has a positive relationship with olfactory performance, and a subregion in the prefrontal cortex (PFC) may play an important role in olfactory processing. The PFC is not only related to olfactory function, but also engages in complex functions such as cognition and emotional processing.

METHODOLOGY

Our study compared the functional connectivity between the olfactory cortex and the prefrontal cortex in healthy individuals who exercised regularly and healthy persons who did not. Those who exercised more than 3 times/week for at least 30 min each time were considered the exercise group, and those who did not meet this exercise criteria were considered the non-exercise group. We also assessed their odor threshold. Participants were aged 55 years or older, and the two groups were balanced for age, sex, body mass index, and educational level.

RESULTS

We found that compared with individuals who did not exercise, exercisers had a significantly lower threshold for detecting odors. In addition, the olfactory cortex had stronger connectivity with the PFC in exercisers than in non-exercisers. More specifically, when the PFC was grouped into three subregions, namely, the ventrolateral prefrontal cortex (VLPFC), dorsolateral prefrontal cortex (DLPFC), and frontopolar cortex (FPA), Pearson correlation analysis revealed stronger connectivity between the VLPFC and the OFC, between the OFC and the FPA, and between the left and right OFC hemispheres in the exercisers. In addition, Granger causality indicated higher directional connectivity from the DLPFC to the OFC in exercisers than in non-exercisers.

CONCLUSION

Our findings indicated that the exercise group not only had better olfactory performance but also had stronger functional connectivity between the olfactory cortex and the PFC than non-exercise group.

Characterizing Subcortical Structural Heterogeneity in Autism

Autism presents with significant phenotypic and neuroanatomical heterogeneity, and neuroimaging studies of the thalamus, globus pallidus and striatum in autism have produced inconsistent and contradictory results. These structures are critical mediators of functions known to be atypical in autism, including sensory gating and motor function. We examined both volumetric and fine-grained localized shape differences in autism using a large (n=3145, 1045-1318 after strict quality control), cross-sectional dataset of T1-weighted structural MRI scans from 32 sites, including both males and females (assigned-at-birth). We investigated three potentially important sources of neuroanatomical heterogeneity: sex, age, and intelligence quotient (IQ), using a meta-analytic technique after strict quality control to minimize non-biological sources of variation. We observed no volumetric differences in the thalamus, globus pallidus, or striatum in autism. Rather, we identified a variety of localized shape differences in all three structures. Including age, but not sex or IQ, in the statistical model improved the fit for both the pallidum and striatum, but not for the thalamus. Age-centered shape analysis indicated a variety of age-dependent regional differences. Overall, our findings help confirm that the neurodevelopment of the striatum, globus pallidus and thalamus are atypical in autism, in a subtle location-dependent manner that is not reflected in overall structure volumes, and that is highly non-uniform across the lifespan.

Structural and functional variations in the prefrontal cortex are associated with learning in pre-adolescent common marmosets (Callithrix jacchus)

There is substantial evidence linking the prefrontal cortex (PFC) to a variety of cognitive abilities, with adolescence being a critical period in its development. In the current study, we investigated the neural basis of differences in learning in pre-adolescent common marmosets. At 8 months old, marmosets were given anatomical and resting state MRI scans (n = 24). At 9 months old, association learning and inhibitory control was tested using a 'go/no go' visual discrimination (VD) task. Marmosets were grouped into 'learners' (n = 12) and "non-learners" (n = 12), and associations between cognitive performance and sub-regional PFC volumes, as well as PFC connectivity patterns, were investigated. "Learners" had significantly (p < 0.05) larger volumes of areas 11, 25, 47 and 32 than 'non-learners', although 'non-learners' had significantly larger volumes of areas 24a and 8 v than "learners". There was also a significant correlation between average % correct responses to the 'punished' stimulus and volume of area 47. Further, 'non-learners' had significantly greater global PFC connections, as well as significantly greater numbers of connections between the PFC and basal ganglia, cerebellum and hippocampus, compared to 'learners'. These results suggest that larger sub-regions of the orbitofrontal cortex and ventromedial PFC, as well more refined PFC connectivity patterns to other brain regions associated with learning, may be important in successful response inhibition. This study therefore offers new information on the neurodevelopment of individual differences in cognition during pre-adolescence in non-human primates.

Is Early Bilingual Experience Associated with Greater Fluid Intelligence in Adults?

Emerging evidence suggests that early bilingual experience constrains the development of attentional processes in infants, and that some of these early bilingual adaptations could last into adulthood. However, it is not known whether the early adaptations in the attentional domain alter more general cognitive abilities. If they do, then we would expect that bilingual adults who learned their second language early in life would score more highly across cognitive tasks than bilingual adults who learned their second language later in life. To test this hypothesis, 170 adult participants were administered a well-established (non-verbal) measure of fluid intelligence: Raven’s Advanced Progressive Matrices (RAPM). Fluid intelligence (the ability to solve novel reasoning problems, independent of acquired knowledge) is highly correlated with numerous cognitive abilities across development. Performance on the RAPM was greater in bilinguals than monolinguals, and greater in ‘early bilinguals’ (adults who learned their second language between 0–6 years) than ‘late bilinguals’ (adults who learned their second language after age 6 years). The groups did not significantly differ on a proxy of socioeconomic status. These results suggest that the difference in fluid intelligence between bilinguals and monolinguals is not a consequence of bilingualism per se, but of early adaptive processes. However, the finding may depend on how bilingualism is operationalized, and thus needs to be replicated with a larger sample and more detailed measures.

Processing speed dysfunction is associated with functional corticostriatal circuit alterations in childhood epilepsy with centrotemporal spikes: a PET and fMRI study

Purpose

Epilepsy with centrotemporal spikes (ECTS) is the most common epilepsy syndrome in children and usually presents with cognitive dysfunctions. However, little is known about the processing speed dysfunction and the associated neuroimaging mechanism in ECTS. This study aims to investigate the brain functional abnormality of processing speed dysfunction in ECTS patients by using the ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET) and resting-state functional magnetic resonance imaging (rs-fMRI).

Methods

This prospective study recruited twenty-eight ECTS patients who underwent the ¹⁸F-FDG PET, rs-fMRI, and neuropsychological examinations. Twenty children with extracranial tumors were included as PET controls, and 20 healthy children were recruited as MRI controls. The PET image analysis investigated glucose metabolism by determining standardized uptake value ratio (SUVR). The MRI image analysis explored abnormal functional connectivity (FC) within the cortical–striatal circuit through network-based statistical (NBS) analysis. Correlation analysis was performed to explore the relationship between SUVR, FC, and processing speed index (PSI).

Results

Compared with healthy controls, ECTS patients showed normal intelligence quotient but significantly decreased PSI (P = 0.04). PET analysis showed significantly decreased SUVRs within bilateral caudate, putamen, pallidum, left NAc, right rostral middle frontal gyrus, and frontal pole of ECTS patients (P < 0.05). Rs-fMRI analysis showed absolute values of 20 FCs were significantly decreased in ECTS patients compared with MRI controls, which connected 16 distinct ROIs. The average SUVR of right caudate and the average of 20 FCs were positively correlated with PSI in ECTS patients (P = 0.034 and P = 0.005, respectively).

Conclusion

This study indicated that ECTS patients presented significantly reduced PSI, which is closely associated with decreased SUVR and FC of cortical–striatal circuit. Caudate played an important role in processing speed dysfunction.

Clinical trial registration

NCT04954729; registered on July 8, 2021, public site, https://clinicaltrials.gov/ct2/show/NCT04954729

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-022-05740-w.

The central executive network and executive function in healthy and persons with schizophrenia groups: a meta-analysis of structural and functional MRI

This meta-analysis evaluated the extent to which executive function can be understood with structural and functional magnetic resonance imaging. Studies included structural in schizophrenia (k = 8; n = 241) and healthy controls (k = 12; n = 1660), and functional in schizophrenia (k = 4; n = 104) and healthy controls (k = 12; n = 712). Results revealed a positive association in the brain behavior relationship when pooled across schizophrenia and control samples for structural (pr = 0.27) and functional (pr = 0.29) modalities. Subgroup analyses revealed no significant difference for functional neuroimaging (pr = .43, 95%CI = -.08-.77, p = .088) but with structural neuroimaging (pr = .37, 95%CI = -.08-.69, p = .015) the association to executive functions is lower in the control group. Subgroup analyses also revealed no significant differences in the strength of the brain-behavior relationship in the schizophrenia group (pr = .59, 95%CI = .58-.61, p = .881) or the control group (pr = 0.19, 95%CI = 0.18-0.19, p = 0.920), suggesting concordance.

Distinct Regionalization Patterns of Cortical Morphology are Associated with Cognitive Performance Across Different Domains

Cognitive performance in children is predictive of academic and social outcomes; therefore, understanding neurobiological mechanisms underlying individual differences in cognition during development may be important for improving quality of life. The belief that a single, psychological construct underlies many cognitive processes is pervasive throughout society. However, it is unclear if there is a consistent neural substrate underlying many cognitive processes. Here, we show that a distributed configuration of cortical surface area and apparent thickness, when controlling for global imaging measures, is differentially associated with cognitive performance on different types of tasks in a large sample (N = 10 145) of 9-11-year-old children from the Adolescent Brain and Cognitive DevelopmentSM (ABCD) study. The minimal overlap in these regionalization patterns of association has implications for competing theories about developing intellectual functions. Surprisingly, not controlling for sociodemographic factors increased the similarity between these regionalization patterns. This highlights the importance of understanding the shared variance between sociodemographic factors, cognition and brain structure, particularly with a population-based sample such as ABCD.

Cortical Structure and Cognition in Infants and Toddlers

Cortical structure has been consistently related to cognitive abilities in children and adults, yet we know little about how the cortex develops to support emergent cognition in infancy and toddlerhood when cortical thickness (CT) and surface area (SA) are maturing rapidly. In this report, we assessed how regional and global measures of CT and SA in a sample (N = 487) of healthy neonates, 1-year-olds, and 2-year-olds related to motor, language, visual reception, and general cognitive ability. We report novel findings that thicker cortices at ages 1 and 2 and larger SA at birth, age 1, and age 2 confer a cognitive advantage in infancy and toddlerhood. While several expected brain-cognition relationships were observed, overlapping cortical regions were also implicated across cognitive domains, suggesting that infancy marks a period of plasticity and refinement in cortical structure to support burgeoning motor, language, and cognitive abilities. CT may be a particularly important morphological indicator of ability, but its impact on cognition is relatively weak when compared with gestational age and maternal education. Findings suggest that prenatal and early postnatal cortical developments are important for cognition in infants and toddlers but should be considered in relation to other child and demographic factors.

Neocortical Age and Fluid Ability: Greater Accelerated Brain Aging for Thickness, but Smaller for Surface Area, in High Cognitive Ability Individuals

Biological (BA) and chronological (CA) age may or may not fit. The available evidence reveals remarkable individual differences in the overlap/mismatch between BA and CA. Increased mismatch can be interpreted as delayed (BA/CA < 1) or accelerated biological aging (BA/CA > 1). Body and brain health are correlated and both predict aging outcomes associated with physical and mental fitness. Moreover, research has shown that older brain age at midlife correlates negatively with cognitive ability measured in early childhood, which suggests early life predisposition to accelerated aging in adulthood. Under this framework, here we test if increased cognitive ability is associated with delayed brain aging, analyzing structural MRI data of 188 individuals, sixty of whom were recruited from MENSA, an association comprising individuals who obtained cognitive ability scores in the top 2 percent of the population. These high ability individuals (HCA) showed an average advantage of 33 IQ points, on a fluid reasoning test they completed for this research, over those other recruited because of their average cognitive ability (ACA). Next, brain age was computed at the individual level for two distinguishable neocortical features (thickness and surface area) according to models trained in an independent large-scale sample of 2377 individuals. Results revealed a stronger pattern of accelerated brain aging in HCA compared to ACA individuals for thickness, while the opposite pattern was suggested for surface area. The findings align well with the greater relevance of individual differences in cortical surface area for enhancing our understanding of cognitive differences at the brain level.

Lower regional grey matter in alcohol use disorders: evidence from a voxel-based meta-analysis

BACKGROUND

Previous research using whole-brain neuroimaging techniques has revealed structural differences of grey matter (GM) in alcohol use disorder (AUD) patients. However, some of the findings diverge from other neuroimaging studies and require further replication. The quantity of relevant research has, thus far, been limited and the association between GM and abstinence duration of AUD patients has not yet been systematically reviewed.

METHODS

The present research conducted a meta-analysis of voxel-based GM studies in AUD patients published before Jan 2021. The study utilised a whole brain-based d-mapping approach to explore GM changes in AUD patients, and further analysed the relationship between GM deficits, abstinence duration and individual differences.

RESULTS

The current research included 23 studies with a sample size of 846 AUD patients and 878 controls. The d-mapping approach identified lower GM in brain regions including the right cingulate gyrus, right insula and left middle frontal gyrus in AUD patients compared to controls. Meta-regression analyses found increasing GM atrophy in the right insula associated with the longer mean abstinence duration of the samples in the studies in our analysis. GM atrophy was also found positively correlated with the mean age of the samples in the right insula, and positively correlated with male ratio in the left middle frontal gyrus.

CONCLUSIONS

GM atrophy was found in the cingulate gyrus and insula in AUD patients. These findings align with published meta-analyses, suggesting they are potential deficits for AUD patients. Abstinence duration, age and gender also affect GM atrophy in AUD patients. This research provides some evidence of the underlying neuroanatomical nature of AUD.

Linking Brain Biology to Intellectual Endowment: A Review on the Associations of Human Intelligence With Neuroimaging Data

Human intelligence has always been a fascinating subject for scientists. Since the inception of Spearman's general intelligence in the early 1900s, there has been significant progress towards characterizing different aspects of intelligence and its relationship with structural and functional features of the brain. In recent years, the invention of sophisticated brain imaging devices using Diffusion-Weighted Imaging (DWI) and functional Magnetic Resonance Imaging (fMRI) has allowed researchers to test hypotheses about neural correlates of intelligence in humans.This review summarizes recent findings on the associations of human intelligence with neuroimaging data. To this end, first, we review the literature that has related brain morphometry to intelligence. Next, we elaborate on the applications of DWI and restingstate fMRI on the investigation of intelligence. Then, we provide a survey of literature that has used multimodal DWI-fMRI to shed light on intelligence. Finally, we discuss the state-of-the-art of individualized prediction of intelligence from neuroimaging data and point out future strategies. Future studies hold promising outcomes for machine learning-based predictive frameworks using neuroimaging features to estimate human intelligence.

The effects of poverty stereotype threat on inhibition ability in individuals from different income-level families

INTRODUCTION

Poverty is characterized by a scarcity of resources and a threat of certain stereotypes. However, the effects of stereotype threat are largely dependent on various factors, both negative and positive. Few psychophysiological studies have studied the effects of poverty stereotype threats on inhibition ability in wealth and impoverished individuals.

METHODS

To fill this gap in the literature, this study used the event-related potential (ERP) technique to explore the brain mechanisms associated with stereotype threat in 135 participants.

RESULTS

Behavioral results showed that the rich group (participants from higher-income families) had better inhibition ability than the impoverished group (participants from lower-income families), with significantly shorter reaction time and significantly greater accuracy for poverty-related stimuli when in the nonthreat condition. Additionally, poverty stereotype threat could improve performance of the impoverished group for poverty-related stimuli. The electrophysiological results showed significantly larger P3 mean amplitude and significantly longer P3 latency in the rich group than the impoverished group in the nonthreat condition. Although no significant between-group differences were found in the threat condition, the results show that the effect of poverty stereotype threat varies with different income-level persons, for both behavioral and P3 data.

CONCLUSION

These findings suggest that impoverished people have worse inhibition abilities. Further, poverty stereotype threat has different effects on people according to their income level and could help to explain irrational consumption behaviors in people.

The association of striatal volume and positive schizotypy in healthy subjects: intelligence as a moderating factor

BACKGROUND

Schizotypy, a putative schizophrenia endophenotype, has been associated with brain-structural variations partly overlapping with those in psychotic disorders. Variations in precuneus structure have been repeatedly reported, whereas the involvement of fronto-striatal networks - as in schizophrenia - is less clear. While shared genetic architecture is thought to increase vulnerability to environmental insults, beneficial factors like general intelligence might buffer their effect.

METHODS

To further investigate the role of fronto-striatal networks in schizotypy, we examined the relationship of voxel- and surface-based brain morphometry and a measure of schizotypal traits (Schizotypal Personality Questionnaire, with subscores Cognitive-Perceptual, Interpersonal, Disorganised) in 115 healthy participants [54 female, mean age (s.d.) = 27.57(8.02)]. We tested intelligence (MWT-B) as a potential moderator.

RESULTS

We found a positive association of SPQ Cognitive-Perceptual with putamen volume (p = 0.040, FWE peak level-corrected), moderated by intelligence: with increasing IQ, the correlation of SPQ Cognitive-Perceptual and striatal volume decreased (p = 0.022). SPQ Disorganised was positively correlated with precentral volume (p = 0.013, FWE peak level-corrected). In an exploratory analysis (p < 0.001, uncorrected), SPQ total score was positively associated with gyrification in the precuneus and postcentral gyrus, and SPQ Disorganised was negatively associated with gyrification in the inferior frontal gyrus.

CONCLUSIONS

Our findings support the role of fronto-striatal networks for schizotypal features in healthy individuals, and suggest that these are influenced by buffering factors like intelligence. We conclude that protective factors, like general cognitive capacity, might attenuate the psychosis risk associated with schizotypy. These results endorse the idea of a continuous nature of schizotypy, mirroring similar findings in schizophrenia.

Predicting intelligence from brain gray matter volume

A positive association between brain size and intelligence is firmly established, but whether region-specific anatomical differences contribute to general intelligence remains an open question. Results from voxel-based morphometry (VBM) - one of the most widely used morphometric methods - have remained inconclusive so far. Here, we applied cross-validated machine learning-based predictive modeling to test whether out-of-sample prediction of individual intelligence scores is possible on the basis of voxel-wise gray matter volume. Features were derived from structural magnetic resonance imaging data (N = 308) using (a) a purely data-driven method (principal component analysis) and (b) a domain knowledge-based approach (atlas parcellation). When using relative gray matter (corrected for total brain size), only the atlas-based approach provided significant prediction, while absolute gray matter (uncorrected) allowed for above-chance prediction with both approaches. Importantly, in all significant predictions, the absolute error was relatively high, i.e., greater than ten IQ points, and in the atlas-based models, the predicted IQ scores varied closely around the sample mean. This renders the practical value even of statistically significant prediction results questionable. Analyses based on the gray matter of functional brain networks yielded significant predictions for the fronto-parietal network and the cerebellum. However, the mean absolute errors were not reduced in contrast to the global models, suggesting that general intelligence may be related more to global than region-specific differences in gray matter volume. More generally, our study highlights the importance of predictive statistical analysis approaches for clarifying the neurobiological bases of intelligence and provides important suggestions for future research using predictive modeling.

Evolving White Matter Injury following Pediatric Traumatic Brain Injury

This study is unique in that it examines the evolution of white matter injury very early and at 12 months post-injury in pediatric patients following traumatic brain injury (TBI). Diffusion tensor imaging (DTI) was acquired at two time-points: acutely at 6-17 days and 12 months following a complicated mild (cMild)/moderate (mod) or severe TBI. Regional measures of anisotropy and diffusivity were compared between TBI groups and against a group of age-matched healthy controls and used to predict performance on measures of attention, memory, and intellectual functioning at 12-months post-injury. Analysis of the acute DTI data using tract based spatial statistics revealed a small number of regional decreases in fractional anisotropy (FA) in both the cMild/mod and severe TBI groups compared with controls. These changes were observed in the occipital white matter, anterior limb of the internal capsule (ALIC)/basal ganglia, and corpus callosum. The severe TBI group showed regional differences in axial diffusivity (AD) in the brainstem and corpus callosum that were not seen in the cMild/mod TBI group. By 12-months, widespread decreases in FA and increases in apparent diffusion coefficient (ADC) and radial diffusivity (RD) were observed in both TBI groups compared with controls, with the overall number of regions with abnormal DTI metrics increasing over time. The early changes in regional DTI metrics were associated with 12-month performance IQ scores. These findings suggest that there may be regional differences in the brain's reparative processes or that mechanisms associated with the brain's plasticity to recover may also be region based.

The Shared Genetic Basis of Educational Attainment and Cerebral Cortical Morphology

Individual differences in educational attainment are linked to differences in intelligence, and predict important social, economic, and health outcomes. Previous studies have found common genetic factors that influence educational achievement, cognitive performance and total brain volume (i.e., brain size). Here, in a large sample of participants from the UK Biobank, we investigate the shared genetic basis between educational attainment and fine-grained cerebral cortical morphological features, and associate this genetic variation with a related aspect of cognitive ability. Importantly, we execute novel statistical methods that enable high-dimensional genetic correlation analysis, and compute high-resolution surface maps for the genetic correlations between educational attainment and vertex-wise morphological measurements. We conduct secondary analyses, using the UK Biobank verbal-numerical reasoning score, to confirm that variation in educational attainment that is genetically correlated with cortical morphology is related to differences in cognitive performance. Our analyses relate the genetic overlap between cognitive ability and cortical thickness measurements to bilateral primary motor cortex as well as predominantly left superior temporal cortex and proximal regions. These findings extend our understanding of the neurobiology that connects genetic variation to individual differences in educational attainment and cognitive performance.

Disrupted Regional Cerebral Blood Flow in Children With Newly-Diagnosed Type 1 Diabetes Mellitus: An Arterial Spin Labeling Perfusion Magnetic Resonance Imaging Study

Object: Diabetes is associated with cerebral vascular dysfunction and increased vascular cognitive impairment. The objective of this study was to use arterial spin labeling (ASL) perfusion-weighted magnetic resonance imaging to investigate whether cerebral perfusion was changed in newly-diagnosed children with type 1 diabetes mellitus (T1DM) and the possible relationship between aberrant cerebral blood flow (CBF) with cognitive as well as clinical variables.

Methods: Between January 2017 and February 2018, 34 children with newly-diagnosed T1DM and 34 age, gender, and education-matched healthy controls were included. Three dimensional pseudo-continuous ASL perfusion MRI was used to evaluate CBF. A conventional T2WI sequence was added to exclude intracranial disease. Regions with CBF differences between T1DM children and the controls were detected via voxel-wise comparisons in REST software. Associations among the result of neuropsychological test, clinical variables, and CBF values of different brains were investigated by using partial correlation analysis.

Results: Compared with the controls, T1DM children show decreased CBF in the left calcarine and postcentral gyrus, and right precentral gyrus. The perfusion in the postcentral gyrus was positively correlated with IQ performance. No significant correlations were found between CBF and HbA1c, blood glucose level before imaging and IQ in other brain regions in T1DM children.

Conclusion: There is an abnormal cerebral perfusion in children with newly diagnosed T1DM. The visual and sensorimotor areas are brain areas where perfusion is prone to change at the beginning of T1DM. Our study provided clues for cerebral pathophysiological changes in the initial stage of T1DM.

Stress & executive functioning: A review considering moderating factors

A multitude of studies investigating the effects of stress on cognition has produced an inconsistent picture on whether - and under which conditions - stress has advantageous or disadvantageous effects on executive functions (EF). This review provides a short introduction to the concept of stress and its neurobiology, before discussing the need to consider moderating factors in the association between stress and EF. Three core domains are described and discussed in relation to the interplay between stress and cognition: the influence of different paradigms on physiological stress reactivity, individual differences in demographic and biological factors, and task-related features of cognitive tasks. Although some moderating variables such as the endocrine stress response have frequently been considered in single studies, no attempt of a holistic overview has been made so far. Therefore, we propose a more nuanced and systematic framework to study the effects of stress on executive functioning, comprising a holistic overview from the induction of stress, via biological mechanisms and interactions with individual differences, to the influence of stress on cognitive performance.

Resting State Glucose Utilization and Adult Reading Test Performance

Adult reading tests (ART) have been widely used in both research and clinical settings as a measure of premorbid cognitive abilities or cognitive reserve. However, the neural substrates underlying ART performance are largely unknown. Furthermore, it has not yet been examined whether the neural substrates of ART performance reflect the cortical regions associated with premorbid intelligence or cognitive reserve. The aim of the study is to identify the functional neural correlates of ART performance using 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) imaging in the cognitively normal (CN) middle- and old-aged adults. Voxel-wise analyses revealed positive correlations between glucose metabolism and ART performance in the frontal and primary somatosensory regions, more specifically the lateral frontal cortex, anterior cingulate cortex and postcentral gyrus (PCG). When conducted again only for amyloid-β (Aβ)-negative individuals, the voxel-wise analysis showed significant correlations in broader areas of the frontal and primary somatosensory regions. This is the first neuroimaging study to directly demonstrate the cerebral resting-state glucose utilization associated with ART performance. Our findings provide important evidence at the neural level that ART predicts premorbid general intelligence and cognitive reserve, as brain areas that showed significant correlations with ART performance correspond to regions that have been associated with general intelligence and cognitive reserve.

Cognitive and neural architecture of decision making competence

Although cognitive neuroscience has made remarkable progress in understanding the neural foundations of goal-directed behavior and decision making, neuroscience research on decision making competence, the capacity to resist biases in human judgment and decision making, remain to be established. Here, we investigated the cognitive and neural mechanisms of decision making competence in 283 healthy young adults. We administered the Adult Decision Making Competence battery to assess the respondent's capacity to resist standard biases in decision making, including: (1) resistance to framing, (2) recognizing social norms, (3) over/under confidence, (4) applying decision rules, (5) consistency in risk perception, and (6) resistance to sunk costs. Decision making competence was assessed in relation to core facets of intelligence, including measures of crystallized intelligence (Shipley Vocabulary), fluid intelligence (Figure Series), and logical reasoning (LSAT). Structural equation modeling was applied to examine the relationship(s) between each cognitive domain, followed by an investigation of their association with individual differences in cortical thickness, cortical surface area, and cortical gray matter volume as measured by high-resolution structural MRI. The results suggest that: (i) decision making competence is associated with cognitive operations for logical reasoning, and (ii) these convergent processes are associated with individual differences within cortical regions that are widely implicated in cognitive control (left dACC) and social decision making (right superior temporal sulcus; STS). Our findings motivate an integrative framework for understanding the neural mechanisms of decision making competence, suggesting that individual differences in the cortical surface area of left dACC and right STS are associated with the capacity to overcome decision biases and exhibit competence in decision making.

Individual differences in sustained attention are associated with cortical thickness

Several studies have examined how individual differences in sustained attention relate to functional brain measures (e.g., functional connectivity), but far fewer studies relate sustained attention ability, or cognition in general, to individual differences in cortical structure. Functional magnetic resonance imaging meta-analyses and patient work have highlighted that frontoparietal regions, lateralized to the right hemisphere, are critical for sustained attention, though recent work implicates a broader expanse of brain regions. The current study sought to determine if and where variation in cortical thickness is significantly associated with sustained attention performance. Sustained attention was measured using the gradual onset continuous performance task and the Test of Variables of Attention in 125 adult Veteran participants after acquiring two high-resolution structural MRI scans. Whole-brain vertex-wise analyses of the cortex demonstrated that better sustained attention was associated with increased thickness in visual, somatomotor, frontal, and parietal cortices, especially in the right hemisphere. Network-based analyses revealed relationships between sustained attention and cortical thickness in the dorsal attention, ventral attention, somatomotor, and visual networks. These results indicate cortical thickness in multiple regions and networks is associated with sustained attention, and add to the growing knowledge of how structural MRI can help explain individual differences in cognition.

EEG microstates distinguish between cognitive components of fluid reasoning

Fluid reasoning is considered central to general intelligence. How its psychometric structure relates to brain function remains poorly understood. For instance, what is the dynamic composition of ability-specific processes underlying fluid reasoning? We investigated whether distinct fluid reasoning abilities could be differentiated by electroencephalography (EEG) microstate profiles. EEG microstates specifically capture rapidly altering activity of distributed cortical networks with a high temporal resolution as scalp potential topographies that dynamically vary over time in an organized manner. EEG was recorded simultaneously with functional magnetic resonance imaging (fMRI) in twenty healthy adult participants during cognitively distinct fluid reasoning tasks: induction, spatial relationships and visualization. Microstate parameters successfully discriminated between fluid reasoning and visuomotor control tasks as well as between the fluid reasoning tasks. Mainly, microstate B coverage was significantly higher during spatial relationships and visualization, compared to induction, while microstate C coverage was significantly decreased during spatial relationships and visualization, compared to induction. Additionally, microstate D coverage was highest during spatial relationships and microstate A coverage was most strongly reduced during the same condition. Consistently, multivariate analysis with a leave-one-out cross-validation procedure accurately classified the fluid reasoning tasks based on the coverage parameter. These EEG data and their correlation with fMRI data suggest that especially the tasks most strongly relying on visuospatial processing modulated visual and default mode network activity. We propose that EEG microstates can provide valuable information about neural activity patterns with a dynamic and complex temporal structure during fluid reasoning, suggesting cognitive ability-specific interplays between multiple brain networks.

The cortical structure of functional networks associated with age-related cognitive abilities in older adults

Age and cortical structure are both associated with cognition, but characterizing this relationship remains a challenge. A popular approach is to use functional network organization of the cortex as an organizing principle for post-hoc interpretations of structural results. In the current study, we introduce two complimentary approaches to structural analyses that are guided by a-priori functional network maps. Specifically, we systematically investigated the relationship of cortical structure (thickness and surface area) of distinct functional networks to two cognitive domains sensitive to age-related decline thought to rely on both common and distinct processes (executive function and episodic memory) in older adults. We quantified the cortical structure of individual functional network's predictive ability and spatial extent (i.e., number of significant regions) with cognition and its mediating role in the age-cognition relationship. We found that cortical thickness, rather than surface area, predicted cognition across the majority of functional networks. The default mode and somatomotor network emerged as particularly important as they appeared to be the only two networks to mediate the age-cognition relationship for both cognitive domains. In contrast, thickness of the salience network predicted executive function and mediated the age-cognition relationship for executive function. These relationships remained significant even after accounting for global cortical thickness. Quantifying the number of regions related to cognition and mediating the age-cognition relationship yielded similar patterns of results. This study provides a potential approach to organize and describe the apparent widespread regional cortical structural relationships with cognition and age in older adults.

Intelligence and uncertainty: Implications of hierarchical predictive processing for the neuroscience of cognitive ability

Hierarchical predictive processing (PP) has recently emerged as a candidate theoretical paradigm for neurobehavioral research. To date, PP has found support through its success in offering compelling explanations for a number of perceptual, cognitive, and psychiatric phenomena, as well as from accumulating neurophysiological evidence. However, its implications for understanding intelligence and its neural basis have received relatively little attention. The present review outlines the key tenets and evidence for PP, and assesses its implications for intelligence research. It is argued that PP suggests indeterminacy as a unifying principle from which to investigate the cognitive hierarchy and brain-ability correlations. The resulting framework not only accommodates prominent psychometric models of intelligence, but also incorporates key findings from neuroanatomical and functional activation research, and motivates new predictions via the mechanisms of prediction-error minimization. Because PP also suggests unique neural signatures of experience-dependent activity, it may also help clarify environmental contributions to intellectual development. It is concluded that PP represents a plausible, integrative framework that could enhance progress in the neuroscience of intelligence.

The association between visual creativity and cortical thickness in healthy adults

Creativity is necessary to human survival, human prosperity, civilization and well-being. Visual creativity is an important part of creativity and is the ability to create products of novel and useful visual forms, playing important role in many fields such as art, painting and sculpture. There have been several neuroimaging studies exploring the neural basis of visual creativity. However, to date, little is known about the relationship between cortical structure and visual creativity as measured by the Torrance Tests of Creative Thinking. Here, we investigated the association between cortical thickness and visual creativity in a large sample of 310 healthy adults. We used multiple regression to analyze the correlation between cortical thickness and visual creativity, adjusting for gender, age and general intelligence. The results showed that visual creativity was significantly negatively correlated with cortical thickness in the left middle frontal gyrus (MFG), right inferior frontal gyrus (IFG), right supplementary motor cortex (SMA) and the left insula. These observations have implications for understanding that a thinner prefrontal cortex (PFC) (e.g. IFG, MFG), SMA and insula correspond to higher visual creative performance, presumably due to their role in executive attention, cognitive control, motor planning and dynamic switching.

Neurobiology of the dorsolateral prefrontal cortex in GAD: Aberrant neurometabolic correlation to hippocampus and relationship to anxiety sensitivity and IQ

INTRODUCTION

The neurometabolism underlying the cognitive and affective symptoms associated with generalized anxiety disorder (GAD) remain poorly understood. After we have linked worry to intelligence in patients with GAD, we hypothesized that aberrant neurometabolic correlations between hippocampus and neocortical regions may underlie a shared substrate in GAD patients for both anxiety sensitivity and intelligence.

METHODS

GAD patients (n = 16; F = 11) and healthy volunteers (n = 16; F = 10) were assessed using ¹H-MRSI. Co-axial planes I [hippocampus (HIPP)] and co-axial plane III [dorsolateral prefrontal cortex (DLPFC), central gyrus (CG)] were examined. Using general linear models, we examined resting metabolite concentrations using HIPP as a hub to CG and DLPFC. Neocortical ROIs were related to Anxiety Sensitivity Index (ASI) and Full Scale IQ (FSIQ) in GAD patients versus controls.

RESULTS

Right hippocampal Cho/Cr directly predicted left DLPFC Cho/Cr in GAD (r = 0.75), an effect distinguishable (p = 0.0004) from controls. Left HIPP Cho/Cr positively predicted left CG Cho/Cr in GAD, an effect distinguishable from controls. In patients, both left and right DLPFC Cho/Cr positively predicted ASI but only left DLPFC Cho/Cr inversely predicted IQ. By contrast, IQ in controls correlated directly with left CG Cho/Cr.

LIMITATIONS

Small sample size precluded us from investigating how gender and FSIQ subscales related to neurochemical correlations in the ROIs examined.

CONCLUSIONS

Aberrant resting state neurochemical correlation between left DLPFC and right HIPP may contribute to GAD symptomatology. Unlike controls, in GAD, IQ and worry may share a common yet inverse neurometabolic substrate in left DLPFC.

Global associations between regional gray matter volume and diverse complex cognitive functions: evidence from a large sample study

Correlations between regional gray matter volume (rGMV) and psychometric test scores have been measured to investigate the neural bases for individual differences in complex cognitive abilities (CCAs). However, such studies have yielded different rGMV correlates of the same CCA. Based on the available evidence, we hypothesized that diverse CCAs are all positively but only weakly associated with rGMV in widespread brain areas. To test this hypothesis, we used the data from a large sample of healthy young adults [776 males and 560 females; mean age: 20.8 years, standard deviation (SD) = 0.8] and investigated associations between rGMV and scores on multiple CCA tasks (including non-verbal reasoning, verbal working memory, Stroop interference, and complex processing speed tasks involving spatial cognition and reasoning). Better performance scores on all tasks except non-verbal reasoning were associated with greater rGMV across widespread brain areas. The effect sizes of individual associations were generally low, consistent with our previous studies. The lack of strong correlations between rGMV and specific CCAs, combined with stringent corrections for multiple comparisons, may lead to different and diverse findings in the field.

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

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 allowsfor the computation of graph theoretical network metricstoquantifythetopological architecture of the brain networkdetected. The observed structural brain changes support the behavioral results reported earlier (see Colom, Román, et al., 2013).

Making Brains run Faster: are they Becoming Smarter?

A brief overview of structural and functional brain characteristics related to g is presented in the light of major neurobiological theories of intelligence: Neural Efficiency, P-FIT and Multiple-Demand system. These theories provide a framework to discuss the main objective of the paper: what is the relationship between individual alpha frequency (IAF) and g? Three studies were conducted in order to investigate this relationship: two correlational studies and a third study in which we experimentally induced changes in IAF by means of transcranial alternating current stimulation (tACS). (1) In a large scale study (n = 417), no significant correlations between IAF and IQ were observed. However, in males IAF positively correlated with mental rotation and shape manipulation and with an attentional focus on detail. (2) The second study showed sex-specific correlations between IAF (obtained during task performance) and scope of attention in males and between IAF and reaction time in females. (3) In the third study, individuals’ IAF was increased with tACS. The induced changes in IAF had a disrupting effect on male performance on Raven’s matrices, whereas a mild positive effect was observed for females. Neuro-electric activity after verum tACS showed increased desynchronization in the upper alpha band and dissociation between fronto-parietal and right temporal brain areas during performance on Raven’s matrices. The results are discussed in the light of gender differences in brain structure and activity.

Test Review: An Interview With Amy Gabel: About the WISC-V

Whenever a major intelligence or achievement test is revised, there is always renewed interest in the underlying structure of the test as well as a renewed interest in the scoring, administration, and interpretation changes. In this interview, Amy Gabel discusses the most recent revision of the Wechsler Intelligence Scale for Children–Fifth Edition (WISC-V). She addresses issues concerning clinical use, standardization, validity, reliability, and other uses of the test as well as addresses new subtests and their use.

Imaging structural covariance in the development of intelligence

Verbal and non-verbal intelligence in children is highly correlated, and thus, it has been difficult to differentiate their neural substrates. Nevertheless, recent studies have shown that verbal and non-verbal intelligence can be dissociated and focal cortical regions corresponding to each have been demonstrated. However, the pattern of structural covariance corresponding to verbal and non-verbal intelligence remains unexplored. In this study, we used 586 longitudinal anatomical MRI scans of subjects aged 6-18 years, who had concurrent intelligence quotient (IQ) testing on the Wechsler Abbreviated Scale of Intelligence. Structural covariance networks (SCNs) were constructed using interregional correlations in cortical thickness for low-IQ (Performance IQ=100±8, Verbal IQ=100±7) and high-IQ (PIQ=121±8, VIQ=120±9) groups. From low- to high-VIQ group, we observed constrained patterns of anatomical coupling among cortical regions, complemented by observations of higher global efficiency and modularity, and lower local efficiency in high-VIQ group, suggesting a shift towards a more optimal topological organization. Analysis of nodal topological properties (regional efficiency and participation coefficient) revealed greater involvement of left-hemispheric language related regions including inferior frontal and superior temporal gyri for high-VIQ group. From low- to high-PIQ group, we did not observe significant differences in anatomical coupling patterns, global and nodal topological properties. Our findings indicate that people with higher verbal intelligence have structural brain differences from people with lower verbal intelligence - not only in localized cortical regions, but also in the patterns of anatomical coupling among widely distributed cortical regions, possibly resulting to a system-level reorganization that might lead to a more efficient organization in high-VIQ group.

Cortical thickness and surface area correlates with cognitive dysfunction among first-episode psychosis patients

BACKGROUND

In studies using magnetic resonance imaging (MRI), some have reported specific brain structure-function relationships among first-episode psychosis (FEP) patients, but findings are inconsistent. We aimed to localize the brain regions where cortical thickness (CTh) and surface area (cortical area; CA) relate to neurocognition, by performing an MRI on participants and measuring their neurocognitive performance using the Cambridge Neuropsychological Test Automated Battery (CANTAB), in order to investigate any significant differences between FEP patients and control subjects (CS).

METHOD

Exploration of potential correlations between specific cognitive functions and brain structure was performed using CANTAB computer-based neurocognitive testing and a vertex-by-vertex whole-brain MRI analysis of 63 FEP patients and 30 CS.

RESULTS

Significant correlations were found between cortical parameters in the frontal, temporal, cingular and occipital brain regions and performance in set-shifting, working memory manipulation, strategy usage and sustained attention tests. These correlations were significantly dissimilar between FEP patients and CS.

CONCLUSIONS

Significant correlations between CTh and CA with neurocognitive performance were localized in brain areas known to be involved in cognition. The results also suggested a disrupted structure-function relationship in FEP patients compared with CS.

Regional Variations in Brain Gyrification Are Associated with General Cognitive Ability in Humans

Searching for a neurobiological understanding of human intellectual capabilities has long occupied those very capabilities. Brain gyrification, or folding of the cortex, is as highly evolved and variable a characteristic in humans as is intelligence. Indeed, gyrification scales with brain size, and relationships between brain size and intelligence have been demonstrated in humans [1-3]. However, gyrification shows a large degree of variability that is independent from brain size [4-6], suggesting that the former may independently contribute to cognitive abilities and thus supporting a direct investigation of this parameter in the context of intelligence. Moreover, uncovering the regional pattern of such an association could offer insights into evolutionary and neural mechanisms. We tested for this brain-behavior relationship in two separate, independently collected, large cohorts-440 healthy adults and 662 healthy children-using high-resolution structural neuroimaging and comprehensive neuropsychometric batteries. In both samples, general cognitive ability was significantly associated (pFDR < 0.01) with increasing gyrification in a network of neocortical regions, including large portions of the prefrontal cortex, inferior parietal lobule, and temporoparietal junction, as well as the insula, cingulate cortex, and fusiform gyrus, a regional distribution that was nearly identical in both samples (Dice similarity coefficient = 0.80). This neuroanatomical pattern is consistent with an existing, well-known proposal, the Parieto-Frontal Integration Theory of intelligence [7], and is also consistent with research in comparative evolutionary biology showing rapid neocortical expansion of these regions in humans relative to other species. These data provide a framework for understanding the neurobiology of human cognitive abilities and suggest a potential neurocellular association.

Extending the 'cross-disorder' relevance of executive functions to dimensional neuropsychiatric traits in youth

BACKGROUND

Evidence that different neuropsychiatric conditions share genetic liability has increased interest in phenotypes with 'cross-disorder' relevance, as they may contribute to revised models of psychopathology. Cognition is a promising construct for study; yet, evidence that the same cognitive functions are impaired across different forms of psychopathology comes primarily from separate studies of individual categorical diagnoses versus controls. Given growing support for dimensional models that cut across traditional diagnostic boundaries, we aimed to determine, within a single cohort, whether performance on measures of executive functions (EFs) predicted dimensions of different psychopathological conditions known to share genetic liability.

METHODS

Data are from 393 participants, ages 8-17, consecutively enrolled in the Longitudinal Study of Genetic Influences on Cognition (LOGIC). This project is conducting deep phenotyping and genomic analyses in youth referred for neuropsychiatric evaluation. Using structural equation modeling, we examined whether EFs predicted variation in core dimensions of the autism spectrum disorder, bipolar illness, and schizophrenia (including social responsiveness, mania/emotion regulation, and positive symptoms of psychosis, respectively).

RESULTS

We modeled three cognitive factors (working memory, shifting, and executive processing speed) that loaded on a second-order EF factor. The EF factor predicted variation in our three target traits, but not in a negative control (somatization). Moreover, this EF factor was primarily associated with the overlapping (rather than unique) variance across the three outcome measures, suggesting that it related to a general increase in psychopathology symptoms across those dimensions.

CONCLUSIONS

Findings extend support for the relevance of cognition to neuropsychiatric conditions that share underlying genetic risk. They suggest that higher-order cognition, including EFs, relates to the dimensional spectrum of each of these disorders and not just the clinical diagnoses. Moreover, results have implications for bottom-up models linking genes, cognition, and a general psychopathology liability.

Cortical morphometry in frontoparietal and default mode networks in math-gifted adolescents

Math-gifted subjects are characterized by above-age performance in intelligence tests, exceptional creativity, and high task commitment. Neuroimaging studies reveal enhanced functional brain organization and white matter microstructure in the frontoparietal executive network of math-gifted individuals. However, the cortical morphometry of these subjects remains largely unknown. The main goal of this study was to compare the cortical morphometry of math-gifted adolescents with that of an age- and IQ-matched control group. We used surface-based methods to perform a vertex-wise analysis of cortical thickness and surface area. Our results show that math-gifted adolescents present a thinner cortex and a larger surface area in key regions of the frontoparietal and default mode networks, which are involved in executive processing and creative thinking, respectively. The combination of reduced cortical thickness and larger surface area suggests above-age neural maturation of these networks in math-gifted individuals. Hum Brain Mapp 37:1893-1902, 2016. © 2016 Wiley Periodicals, Inc.

Structural asymmetry of the human cerebral cortex: Regional and between-subject variability of surface area, cortical thickness, and local gyrification

Structural asymmetry varies across individuals, brain regions, and metrics of cortical organization. The current study investigated regional differences in asymmetry of cortical surface area, thickness, and local gyrification, and the extent of between-subject variability in these metrics, in a sample of healthy young adults (N=200). Between-subject variability in cortical structure may provide a means to assess the extent of biological flexibility or constraint of brain regions, and we explored the potential influence of this variability on the phenotypic expression of structural asymmetry. The findings demonstrate that structural asymmetries are nearly ubiquitous across the cortex, with differing regional organization for the three cortical metrics. This implies that there are multiple, only partially overlapping, maps of structural asymmetry. The results further indicate that the degree of asymmetry of a brain region can be predicted by the extent of the region's between-subject variability. These findings provide evidence that reduced biological constraint promotes the expression of strong structural asymmetry.

Gray matter responsiveness to adaptive working memory training: a surface-based morphometry study

Here we analyze gray matter indices before and after completing a challenging adaptive cognitive training program based on the n-back task. The considered gray matter indices were cortical thickness (CT) and cortical surface area (CSA). Twenty-eight young women (age range 17-22 years) completed 24 training sessions over the course of 3 months (12 weeks, 24 sessions), showing expected performance improvements. CT and CSA values for the training group were compared with those of a matched control group. Statistical analyses were computed using a ROI framework defined by brain areas distinguished by their genetic underpinning. The interaction between group and time was analyzed. Middle temporal, ventral frontal, inferior parietal cortices, and pars opercularis were the regions where the training group showed conservation of gray matter with respect to the control group. These regions support working memory, resistance to interference, and inhibition. Furthermore, an interaction with baseline intelligence differences showed that the expected decreasing trend at the biological level for individuals showing relatively low intelligence levels at baseline was attenuated by the completed training.

Fluid Intelligence and Automatic Neural Processes in Facial Expression Perception: An Event-Related Potential Study

The relationship between human fluid intelligence and social-emotional abilities has been a topic of considerable interest. The current study investigated whether adolescents with different intellectual levels had different automatic neural processing of facial expressions. Two groups of adolescent males were enrolled: a high IQ group and an average IQ group. Age and parental socioeconomic status were matched between the two groups. Participants counted the numbers of the central cross changes while paired facial expressions were presented bilaterally in an oddball paradigm. There were two experimental conditions: a happy condition, in which neutral expressions were standard stimuli (p = 0.8) and happy expressions were deviant stimuli (p = 0.2), and a fearful condition, in which neutral expressions were standard stimuli (p = 0.8) and fearful expressions were deviant stimuli (p = 0.2). Participants were required to concentrate on the primary task of counting the central cross changes and to ignore the expressions to ensure that facial expression processing was automatic. Event-related potentials (ERPs) were obtained during the tasks. The visual mismatch negativity (vMMN) components were analyzed to index the automatic neural processing of facial expressions. For the early vMMN (50-130 ms), the high IQ group showed more negative vMMN amplitudes than the average IQ group in the happy condition. For the late vMMN (320-450 ms), the high IQ group had greater vMMN responses than the average IQ group over frontal and occipito-temporal areas in the fearful condition, and the average IQ group evoked larger vMMN amplitudes than the high IQ group over occipito-temporal areas in the happy condition. The present study elucidated the close relationships between fluid intelligence and pre-attentive change detection on social-emotional information.