Neural correlates of superior intelligence: stronger recruitment of posterior parietal cortex

Neuromodulatory effects of parietal high-definition transcranial direct-current stimulation on network-level activity serving fluid intelligence

Fluid intelligence (Gf) involves rational thinking skills and requires the integration of information from different cortical regions to resolve novel complex problems. The effects of non-invasive brain stimulation on Gf have been studied in attempts to improve Gf, but such studies are rare and the few existing have reached conflicting conclusions. The parieto-frontal integration theory of intelligence (P-FIT) postulates that the parietal and frontal lobes play a critical role in Gf. To investigate the suggested role of parietal cortices, we applied high-definition transcranial direct current stimulation (HD-tDCS) to the left and right parietal cortices of 39 healthy adults (age 19-33 years) for 20 min in three separate sessions (left active, right active and sham). After completing the stimulation session, the participants completed a logical reasoning task based on Raven's Progressive Matrices during magnetoencephalography. Significant neural responses at the sensor level across all stimulation conditions were imaged using a beamformer. Whole-brain, spectrally constrained functional connectivity was then computed to examine the network-level activity. Behaviourally, we found that participants were significantly more accurate following left compared to right parietal stimulation. Regarding neural findings, we found significant HD-tDCS montage-related effects in brain networks thought to be critical for P-FIT, including parieto-occipital, fronto-occipital, fronto-parietal and occipito-cerebellar connectivity during task performance. In conclusion, our findings showed that left parietal stimulation improved abstract reasoning abilities relative to right parietal stimulation and support both P-FIT and the neural efficiency hypothesis. KEY POINTS: Abstract reasoning is a critical component of fluid intelligence and is known to be served by multispectral oscillatory activity in the fronto-parietal cortices. Recent studies have aimed to improve abstract reasoning abilities and fluid intelligence overall through behavioural training, but the results have been mixed. High-definition transcranial direct-current stimulation (HD-tDCS) applied to the parietal cortices modulated task performance and neural oscillations during abstract reasoning. Left parietal stimulation resulted in increased accuracy and decreased functional connectivity between occipital regions and frontal, parietal, and cerebellar regions. Future studies should investigate whether HD-tDCS alters abstract reasoning abilities in those who exhibit declines in performance, such as healthy ageing populations.

Changes in concentration performance and alternating attention after short-term virtual reality training in E-athletes: a pilot study

In the dynamic landscape of e-sports, where intense competitive gaming demands high cognitive abilities, concentration performance and alternating attention play a pivotal role. E-sports encompass diverse genres, each requiring specific cognitive functions. Maintaining unwavering focus is crucial, as split-second decisions can determine victory. The study explores the potential of Virtual Reality (VR) training to enhance concentration performance and alternating attention, shedding light on the importance and possibilities of optimizing cognitive abilities for e-athletes. VR training emerges as a promising intervention, offering immersive environments for cognitive exercises. The study investigates the impact of VR training on concentration performance and alternating attention in amateur e-athletes, utilizing standardized tests. A randomized controlled trial with 66 participants reveals significant improvements in the VR training group, highlighting the adaptability and plasticity of cognitive processes. The findings suggest that VR training can enhance concentration abilities, providing valuable insights for e-sports and potentially extending to other fields requiring sustained attention and rapid task-switching. The study underscores the convergence of cognitive psychology, neuroscience, and VR technology, paving the way for innovative training methodologies and advancements in e-sports performance.

Healthy aging alters the oscillatory dynamics and fronto-parietal connectivity serving fluid intelligence

Fluid intelligence (Gf) involves logical reasoning and novel problem-solving abilities. Often, abstract reasoning tasks like Raven's progressive matrices are used to assess Gf. Prior work has shown an age-related decline in fluid intelligence capabilities, and although many studies have sought to identify the underlying mechanisms, our understanding of the critical brain regions and dynamics remains largely incomplete. In this study, we utilized magnetoencephalography (MEG) to investigate 78 individuals, ages 20-65 years, as they completed an abstract reasoning task. MEG data was co-registered with structural MRI data, transformed into the time-frequency domain, and the resulting neural oscillations were imaged using a beamformer. We found worsening behavioral performance with age, including prolonged reaction times and reduced accuracy. MEG analyses indicated robust oscillations in the theta, alpha/beta, and gamma range during the task. Whole brain correlation analyses with age revealed relationships in the theta and alpha/beta frequency bands, such that theta oscillations became stronger with increasing age in a right prefrontal region and alpha/beta oscillations became stronger with increasing age in parietal and right motor cortices. Follow-up connectivity analyses revealed increasing parieto-frontal connectivity with increasing age in the alpha/beta frequency range. Importantly, our findings are consistent with the parieto-frontal integration theory of intelligence (P-FIT). These results further suggest that as people age, there may be alterations in neural responses that are spectrally specific, such that older people exhibit stronger alpha/beta oscillations across the parieto-frontal network during abstract reasoning tasks.

Structural brain correlates of non-verbal cognitive ability in 5-year-old children: Findings from the FinnBrain birth cohort study

Non-verbal cognitive ability predicts multiple important life outcomes, for example, school and job performance. It has been associated with parieto-frontal cortical anatomy in prior studies in adult and adolescent populations, while young children have received relatively little attention. We explored the associations between cortical anatomy and non-verbal cognitive ability in 165 5-year-old participants (mean scan age 5.40 years, SD 0.13; 90 males) from the FinnBrain Birth Cohort study. T1-weighted brain magnetic resonance images were processed using FreeSurfer. Non-verbal cognitive ability was measured using the Performance Intelligence Quotient (PIQ) estimated from the Block Design and Matrix Reasoning subtests from the Wechsler Preschool and Primary Scale of Intelligence (WPPSI-III). In vertex-wise general linear models, PIQ scores associated positively with volumes in the left caudal middle frontal and right pericalcarine regions, as well as surface area in left the caudal middle frontal, left inferior temporal, and right lingual regions. There were no associations between PIQ and cortical thickness. To the best of our knowledge, this is the first study to examine structural correlates of non-verbal cognitive ability in a large sample of typically developing 5-year-olds. The findings are generally in line with prior findings from older age groups, with the important addition of the positive association between volume / surface area in the right medial occipital region and non-verbal cognitive ability. This finding adds to the literature by discovering a new brain region that should be considered in future studies exploring the role of cortical structure for cognitive development in young children.

Neuromyths and knowledge about intellectual giftedness in a highly educated multilingual country

Introduction

Understanding brain functioning and intellectual giftedness can be challenging and give rise to various misconceptions. Nonetheless, there seems to be a widespread fascination and appetite for these subjects among the lay public and diverse professionals. The present study is the first to investigate general knowledge about the brain, neuromyths and knowledge about giftedness in a highly multilingual and educated country.

Methods

Starting from and extending two seminal studies on neuromyths, several novel statements on intellectual giftedness have been included in order to explore knowledge and misconceptions concerning giftedness. Our sample (N = 200) was composed of Luxembourgish education professionals, including students in educational science and cognitive psychology, thus allowing to analyze responses in general and according to training and professional profiles. Specifically, Group 1 consisted of teachers and futures teachers (n = 152). Group 2 consisted of other education professionals and psychology students (n = 48).

Results

Despite the size and the unbalanced distribution of the sample, our findings indicate a good level of general knowledge about the brain and learning (71.3% of correct responses in average) which does, however, not preclude the presence of the typically observed original neuromyths. Thus, we replicate the classical finding that misconceptions on Learning Styles (70% of error rate) and the Multiple Intelligence Theory (71.5% of error rate) are the most represented, both in (future and in-service) teachers and other education professionals. Moreover, the present sample also revealed a high presence of misconceptions on intellectual giftedness.

Discussion

Limitations and future directions are discussed.

Effects of a developmental dyslexia remediation protocol based on the training of audio-phonological cognitive processes in dyslexic children with high intellectual potential: study protocol for a multiple-baseline single-case experimental design

BACKGROUND

The significant prevalence of children with high intellectual potential (HIP) in the school-age population and the high rate of comorbidity with learning disabilities such as dyslexia has increased the demand for speech and language therapy and made it more complex. However, the management of dyslexic patients with high intellectual potential (HIP-DD) is poorly referenced in the literature. A large majority of studies on HIP-DD children focus on the screening and diagnosis of developmental dyslexia, but only a few address remediation. Developmental dyslexia is a severe and persistent disorder that affects the acquisition of reading and implies the impairment of several underlying cognitive processes. These include deficits in Categorical Perception, Rapid Automatized Naming, and phonological awareness, particularly phonemic awareness. Some authors claim that HIP-DD children's underlying deficits mainly concern rapid automatized naming and phonological awareness. Thus, the purpose of this study is to present a remediation protocol for developmental dyslexia in HIP-DD children. This protocol proposes to compare the effects on reading skills of an intensive intervention targeting categorical perception, rapid automatized naming, and phonemic analysis versus standard speech therapy remediation in HIP-DD children.

METHODS

A multiple-baseline single-case experimental design (A1BCA2) will be proposed to 4 French HIP-DD patients for a period of 30 weeks. Intervention phases B and C correspond to categorical perception training and rapid automatized naming training. During phases B and C, each training session will be associated with phonemic analysis training and a reading and writing task. At inclusion, a speech and language, psychological, and neuropsychological assessment will be performed to define the four patients' profiles. Patients will be assigned to the different baseline lengths using a simple computerized randomization procedure. The duration of the phases will be counterbalanced. The study will be double blinded. A weekly measurement of phonological and reading skills will be performed for the full duration of the study.

DISCUSSION

The purpose of this protocol is to observe the evolution of reading skills with each type of intervention. From this observation, hypotheses concerning the remediation of developmental dyslexia in HIP-DD children can be tested. The strengths and limitations of the study are discussed.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT04028310 . Registered on July 18, 2019. Version identifier is no. ID RCB 2019-A01453-54, 19-HPNCL-02, 07/18/2019.

A transdiagnostic network for psychiatric illness derived from atrophy and lesions

Psychiatric disorders share neurobiology and frequently co-occur. This neurobiological and clinical overlap highlights opportunities for transdiagnostic treatments. In this study, we used coordinate and lesion network mapping to test for a shared brain network across psychiatric disorders. In our meta-analysis of 193 studies, atrophy coordinates across six psychiatric disorders mapped to a common brain network defined by positive connectivity to anterior cingulate and insula, and by negative connectivity to posterior parietal and lateral occipital cortex. This network was robust to leave-one-diagnosis-out cross-validation and specific to atrophy coordinates from psychiatric versus neurodegenerative disorders (72 studies). In 194 patients with penetrating head trauma, lesion damage to this network correlated with the number of post-lesion psychiatric diagnoses. Neurosurgical ablation targets for psychiatric illness (four targets) also aligned with the network. This convergent brain network for psychiatric illness may partially explain high rates of psychiatric comorbidity and could highlight neuromodulation targets for patients with more than one psychiatric disorder.

Neural Contributions to Reduced Fluid Intelligence across the Adult Lifespan

Fluid intelligence, the ability to solve novel, complex problems, declines steeply during healthy human aging. Using fMRI, fluid intelligence has been repeatedly associated with activation of a frontoparietal brain network, and impairment following focal damage to these regions suggests that fluid intelligence depends on their integrity. It is therefore possible that age-related functional differences in frontoparietal activity contribute to the reduction in fluid intelligence. This paper reports on analysis of the Cambridge Center for Ageing and Neuroscience data, a large, population-based cohort of healthy males and females across the adult lifespan. The data support a model in which age-related differences in fluid intelligence are partially mediated by the responsiveness of frontoparietal regions to novel problem-solving. We first replicate a prior finding of such mediation using an independent sample. We then precisely localize the mediating brain regions, and show that mediation is specifically associated with voxels most activated by cognitive demand, but not with voxels suppressed by cognitive demand. We quantify the robustness of this result to potential unmodeled confounders, and estimate the causal direction of the effects. Finally, exploratory analyses suggest that neural mediation of age-related differences in fluid intelligence is moderated by the variety of regular physical activities, more reliably than by their frequency or duration. An additional moderating role of the variety of nonphysical activities emerged when controlling for head motion. A better understanding of the mechanisms that link healthy aging with lower fluid intelligence may suggest strategies for mitigating such decline.SIGNIFICANCE STATEMENT Global populations are living longer, driving urgency to understand age-related cognitive declines. Fluid intelligence is of prime importance because it reflects performance across many domains, and declines especially steeply during healthy aging. Despite consensus that fluid intelligence is associated with particular frontoparietal brain regions, little research has investigated suggestions that under-responsiveness of these regions mediates age-related decline. We replicate a recent demonstration of such mediation, showing specific association with brain regions most activated by cognitive demand, and robustness to moderate confounding by unmodeled variables. By showing that this mediation model is moderated by the variety of regular physical activities, more reliably than by their frequency or duration, we identify a potential modifiable lifestyle factor that may help promote successful aging.

Language evolution is not limited to speech acquisition: a large study of language development in children with language deficits highlights the importance of the voluntary imagination component of language

Did the boy bite the cat or was it the other way around? When processing a sentence with several objects, one has to establish ‘who did what to whom’. When a sentence cannot be interpreted by recalling an image from memory, we rely on the special type of voluntary constructive imagination called Prefrontal synthesis (PFS). PFS is defined as the ability to juxtapose mental visuospatial objects at will. We hypothesised that PFS has fundamental importance for language acquisition. To test this hypothesis, we designed a PFS-targeting intervention and administered it to 6,454 children with language deficiencies (age 2 to 12 years). The results from the three-year-long study demonstrated that children who engaged with the PFS intervention showed 2.2-fold improvement in combinatorial language comprehension compared to children with similar initial evaluations. These findings suggest that language can be improved by training the PFS and exposes the importance of the visuospatial component of language. This manuscript reflects on the experimental findings from the point of view of human language evolution. When used as a proxy for evolutionary language acquisition, the study results suggest a dichotomy of language evolution, with its speech component and its visuospatial component developing in parallel. The study highlights the radical idea that evolutionary acquisition of language was driven primarily by improvements of voluntary imagination rather than by improvements in the speech apparatus.

This is the way: Network perspective on targets for spatial ability development programmes

BACKGROUND

Spatial ability (SA) was shown to be important for success in different fields, including STEM. Recent research suggested that SA is a unitary construct, rather than a set of related skills. However, it is not clear how individual differences in different facets of SA emerge, and how they relate to variance in general cognitive ability.

AIMS

The aim of the present study was threefold: 1) to examine the structure of SA testing nine theoretical models; 2) to explore the relation between 16 different facets of SA with general cognitive ability; and 3) to identify central facet(s) within the network of SA - with most links and/or strongest links to other facets.

SAMPLE

The study participants were 958 university students from Russia.

METHODS

The study used a comprehensive battery of 16 SA tests and a verbal ability measure.

RESULTS

Results supported previous research, suggesting moderate overlap between all SA facets. Factor analysis suggested several potential structures, with similar fit indices for five different theoretically driven models, including split into small- and large scale; partially independent manipulation, visualization and navigation facets. Confirmatory factor analysis, mediation and network analyses showed spatial ability being largely independent from verbal ability. In addition, network analysis showed that navigation according to directions is in the centre of the network, potentially linking all SA facets.

CONCLUSION

The results have potential implications for identifying the best targets for SA interventions. The next step in research is conducting experimental studies to evaluate effectiveness of interventions targeting navigation in comparison with other facets of SA.

Neuropsychological Profile of Intellectually Gifted Children: A Systematic Review

OBJECTIVE

The term intellectually gifted (IG) refers to children of high intelligence, which is classically measured by the intelligence quotient (IQ). Some researchers assume that the cognitive profiles of these children are characterized by both strengths and weaknesses, compared with those of their typically developing (TD) peers of average IQ. The aim of the present systematic review was to verify this assumption, by compiling data from empirical studies of cognitive functions (language, motor skills, visuospatial processing, memory, attention and executive functions, social and emotional cognition) and academic performances.

METHOD

The literature search yielded 658 articles, 15 of which met the selection criteria taken from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses model. We undertook a qualitative summary, to highlight any discrepancies between cognitive functions.

RESULTS

IG children exhibited better skills than TD children in a number of domains, including attention, language, mathematics, verbal working memory, shifting, and social problem solving. However, the two groups had comparable skills in visuospatial processing, memory, planning, inhibition, and visual working memory, or facial recognition.

CONCLUSION

Although IG children may have some strengths, many studies have failed to find differences between this population and their TD peers on many other cognitive measures. Just like any other children, they can display learning disabilities, which can be responsible for academic underachievement. Further studies are needed to better understand this heterogeneity. The present review provides pointers for overcoming methodological problems and opens up new avenues for giftedness research.

Current and Potential Cognitive Development in Healthy Children: A New Approach to Raven Coloured Progressive Matrices

In clinical practice and research, Raven’s Coloured Progressive Matrices (RCPMs) continue to be used according to a single procedure that aims to evaluate a single overall score of the current general intelligence level. This study aimed to examine potential cognitive development in a sample of 450 typically developing children, aged from 6 to 10 years, by administering RCPMs according to the standard procedure followed immediately by a standardized interview on incorrect items. In addition, the study aimed to analyze how performance differed across age groups. The results analysis was examined on the basis of three different factors in which the items were grouped in previous factorial studies. The results found that performance improved markedly and significantly after the interview; however, the improvement was not homogeneous in the three factors across age groups or within each age group. The age groups showed a different development potential in relation to the nature of the task: the younger ones showed a greater increase on items requiring figure completion, and the older ones showed a greater increase on analogical reasoning items. Finally, the children who showed the greatest improvement were those with the best performance in standard RCPM administration. The procedure described in the present research could represent a useful tool in clinical practice and in the research for a broader cognitive assessment focused on potential cognitive development, as well as on real cognitive development, and to favor the planning of more adequate rehabilitation and educational treatments.

Spatio-Temporal Brain Dynamic Differences in Fluid Intelligence

Human fluid intelligence is closely linked to the sequential solving of complex problems. It has been associated with a distributed cognitive control or multiple-demand (MD) network, comprising regions of lateral frontal, insular, dorsomedial frontal, and parietal cortex. Previous neuroimaging research suggests that the MD network may orchestrate the allocation of attentional resources to individual parts of a complex task: in a complex target detection task with multiple independent rules, applied one at a time, reduced response to rule-critical events across the MD network in lower fluid intelligence was observed. This was in particular the case with increasing task complexity (i.e., larger sets of rules), and was accompanied by impairment in performance. Here, we examined the early spatiotemporal neural dynamics of this process in electroencephalography (EEG) source analyses using a similar task paradigm. Levels of fluid intelligence specifically predicted early neural responses in a left inferiorparietal MD region around 200-300 ms post stimulus onset. Evoked source amplitudes in left parietal cortex within this early time window also correlated with behavioural performance measures. Like in previous research, we observed impaired performance in lower fluid intelligence with increasing number of task rules. This links fluid intelligence to a process of attentional focus on those parts of a task that are most critical for the current behaviour. Within the MD system, our time re-resolved measures suggest that the left parietal cortex specifically impacts on early processes of attentional focus on task critical features. This is novel evidence on the neurocognitive correlates of fluid intelligence suggesting that individual differences are critically linked to an early process of attentional focus on task-relevant information, which is supported by left parietal MD regions.

A New Perspective on Individual Reliability beyond Group Effect for Event-related Potentials: A Multisensory Investigation and Computational Modeling

The dominant approach in investigating the individual reliability for event-related potentials (ERPs) is to extract peak-related features at electrodes showing the strongest group effects. Such a peak-based approach implicitly assumes ERP components showing a stronger group effect are also more reliable, but this assumption has not been substantially validated and few studies have investigated the reliability of ERPs beyond peaks. In this study, we performed a rigorous evaluation of the test-retest reliability of ERPs collected in a multisensory and cognitive experiment from 82 healthy adolescents, each having two sessions. By comparing group effects and individual reliability, we found that a stronger group-level response in ERPs did not guarantee higher reliability. A perspective of neural oscillation should be adopted for the analysis of reliability. Further, by simulating ERPs with an oscillation-based computational model, we found that the consistency between group-level ERP responses and individual reliability was modulated by inter-subject latency jitter and inter-trial variability. The current findings suggest that the conventional peak-based approach may underestimate the individual reliability in ERPs and a neural oscillation perspective on ERP reliability should be considered. Hence, a comprehensive evaluation of the reliability of ERP measurements should be considered in individual-level neurophysiological trait evaluation and psychiatric disorder diagnosis.

The Domain-General Multiple Demand Network Is More Active in Early Balanced Bilinguals Than Monolinguals During Executive Processing

The bilingual experience may place special cognitive demands on speakers and has been argued to lead to improvements in domain-general executive abilities, like cognitive control and working memory. Such improvements have been argued for based on both behavioral and brain imaging evidence. However, the empirical landscape is complex and ridden with controversy. Here we attempt to shed light on this question through an fMRI investigation of relatively large, relatively homogeneous, and carefully matched samples of early balanced bilinguals (n = 55) and monolinguals (n = 54), using robust, previously validated individual-level markers of neural activity in the domain-general multiple demand (MD) network, which supports executive functions. We find that the bilinguals, compared to the monolinguals, show significantly stronger neural responses to an executive (spatial working memory) task, and a larger difference between a harder and an easier condition of the task, across the MD network. These stronger neural responses are accompanied by better behavioral performance on the working memory task. We further show that the bilingual-vs.-monolingual difference in neural responses is not ubiquitous across the brain as no group difference in magnitude is observed in primary visual areas, which also respond to the task. Although the neural group difference in the MD network appears robust, it remains difficult to causally link it to bilingual experience specifically.

The role of neural load effects in predicting individual differences in working memory function

Studies of working memory (WM) function have tended to adopt either a within-subject approach, focusing on effects of load manipulations, or a between-subjects approach, focusing on individual differences. This dichotomy extends to WM neuroimaging studies, with different neural correlates being identified for within- and between-subjects variation in WM. Here, we examined this issue in a systematic fashion, leveraging the large-sample Human Connectome Project dataset, to conduct a well-powered, whole-brain analysis of the N-back WM task. We first demonstrate the advantages of parcellation schemes for dimension reduction, in terms of load-related effect sizes. This parcel-based approach is then utilized to directly compare the relationship between load-related (within-subject) and behavioral individual differences (between-subject) effects through both correlational and predictive analyses. The results suggest a strong linkage of within-subject and between-subject variation, with larger load-effects linked to stronger brain-behavior correlations. In frontoparietal cortex no hemispheric biases were found towards one type of variation, but the Dorsal Attention Network did exhibit greater sensitivity to between over within-subjects variation, whereas in the Somatomotor network, the reverse pattern was observed. Cross-validated predictive modeling capitalizing on this tight relationship between the two effects indicated greater predictive power for load-activated than load-deactivated parcels, while also demonstrating that load-related effect size can serve as an effective guide to feature (i.e., parcel) selection, in maximizing predictive power while maintaining interpretability. Together, the findings demonstrate an important consistency across within- and between-subjects approaches to identifying the neural substrates of WM, which can be effectively harnessed to develop more powerful predictive models.

Directed Connectivity Analysis of the Brain Network in Mathematically Gifted Adolescents

The neurocognitive characteristics of mathematically gifted adolescents are characterized by highly developed functional interactions between the right hemisphere and excellent cognitive control of the prefrontal cortex, enhanced frontoparietal cortex, and posterior parietal cortex. However, it is still unclear when and how these cortical interactions occur. In this paper, we used directional coherence analysis based on Granger causality to study the interactions between the frontal brain area and the posterior brain area in the mathematical frontoparietal network system during deductive reasoning tasks. Specifically, the scalp electroencephalography (EEG) signal was first converted into a cortical dipole source signal to construct a Granger causality network over the θ-band and γ-band ranges. We constructed the binary Granger causality network at the 40 pairs of cortical nodes in the frontal lobe and parietal lobe across the θ-band and the γ-band, which were selected as regions of interest (ROI). We then used graph theory to analyze the network differences. It was found that, in the process of reasoning tasks, the frontoparietal regions of the mathematically gifted show stronger working memory information processing at the θ-band. Additionally, in the middle and late stages of the conclusion period, the mathematically talented individuals have less information flow in the anterior and posterior parietal regions of the brain than the normal subjects. We draw the conclusion that the mathematically gifted brain frontoparietal network appears to have more “automated” information processing during reasoning tasks.

A Review of Working Memory Training in the Management of Attention Deficit Hyperactivity Disorder

Attention deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders among children. Working memory deficits underlie many of the behavioural symptoms of ADHD. Alongside psychostimulant medications, strategies to improve working memory may play an important adjuvant role in the management of ADHD. In this study, we review the role of working memory deficits in ADHD, the evidence surrounding working memory training strategies in the management of the condition, and the factors affecting the success of these strategies in alleviating ADHD symptoms. More specifically, we review several non-pharmacological interventions that target working memory deficits in ADHD, with special emphasis on cognitive working memory training. We conclude that the development of evidence-based interventions such as computerised cognitive training (CCT) could provide an alternative or adjunct to the use of psychostimulants, especially in cases where side effects are a major issue.

Distance-based functional criticality in the human brain: intelligence and emotional intelligence

Background

Anatomical distance has been identified as a key factor in the organizational principles of the human brain. On the other hand, criticality was proposed to accommodate the multiscale properties of human brain dynamics, and functional criticality based on resting-state functional magnetic resonance imaging (rfMRI) is a sensitive neuroimaging marker for human brain dynamics. Hence, to explore the effects of anatomical distance of the human brain on behaviors in terms of functional criticality, we proposed a revised algorithm of functional criticality called the distance-based vertex-wise index of functional criticality, and assessed this algorithm compared with the original neighborhood-based functional criticality.

Results

We recruited two groups of healthy participants, including young adults and middle-aged participants, for a total of 60 datasets including rfMRI and intelligence as well as emotional intelligence to study how human brain functional criticalities at different spatial scales contribute to individual behaviors. Furthermore, we defined the average distance between the particular behavioral map and vertices with significant functional connectivity as connectivity distance. Our results demonstrated that intelligence and emotional intelligence mapped to different brain regions at different ages. Additionally, intelligence was related to a wider distance range compared to emotional intelligence.

Conclusions

For different age groups, our findings not only provided a linkage between intelligence/emotional intelligence and functional criticality but also quantitatively characterized individual behaviors in terms of anatomical distance.

The Raven's Coloured Progressive Matrices in Healthy Children: A Qualitative Approach

Studies on the structure of intelligence refer to two main theoretical models: the first one considers intelligence as a unitary construct, the second one assumes the involvement of a plurality of factors. Studies using Raven's Coloured Progressive Matrices (RCPM) tasks have often highlighted the involvement of different cognitive abilities and brain structures, but in the clinical setting, RCPM measurement continues to be used as a single score. The current study aimed to analyse the RCPM performance following qualitative clustering, in order to provide an interpretation of the intelligence assessment through a factorial criterion. The RCPM have been administered to a large group of typically developing children between 6 and 11 years of age. The sample was divided into twelve age groups, and the performance of each age group was shown. Three qualitative item clusters were identified through a factorial criterion. Data showed that performance on RCPM may arise from different cognitive abilities, starting from basic attentional skills up to the more complex ones that require perceptual or analogical reasoning. The qualitative parameters could provide more effective diagnostic and treatment suggestions than a single total score in the clinical setting, and may be crucial for focusing on strength and weakness in the intellectual functionality evaluation of children.

Activity in the fronto-parietal multiple-demand network is robustly associated with individual differences in working memory and fluid intelligence

Numerous brain lesion and fMRI studies have linked individual differences in executive abilities and fluid intelligence to brain regions of the fronto-parietal "multiple-demand" (MD) network. Yet, fMRI studies have yielded conflicting evidence as to whether better executive abilities are associated with stronger or weaker MD activations and whether this relationship is restricted to the MD network. Here, in a large-sample (n = 216) fMRI investigation, we found that stronger activity in MD regions - functionally defined in individual participants - was robustly associated with more accurate and faster responses on a spatial working memory task performed in the scanner, as well as fluid intelligence measured independently (n = 114). In line with some prior claims about a relationship between language and fluid intelligence, we also found a weak association between activity in the brain regions of the left fronto-temporal language network during an independent passive reading task, and performance on the working memory task. However, controlling for the level of MD activity abolished this relationship, whereas the MD activity-behavior association remained highly reliable after controlling for the level of activity in the language network. Finally, we demonstrate how unreliable MD activity measures, coupled with small sample sizes, could falsely lead to the opposite, negative, association that has been reported in some prior studies. Taken together, these results demonstrate that a core component of individual differences variance in executive abilities and fluid intelligence is selectively and robustly positively associated with the level of activity in the MD network, a result that aligns well with lesion studies.

Toward a "treadmill test" for cognition: Improved prediction of general cognitive ability from the task activated brain

General cognitive ability (GCA) refers to a trait-like ability that contributes to performance across diverse cognitive tasks. Identifying brain-based markers of GCA has been a longstanding goal of cognitive and clinical neuroscience. Recently, predictive modeling methods have emerged that build whole-brain, distributed neural signatures for phenotypes of interest. In this study, we employ a predictive modeling approach to predict GCA based on fMRI task activation patterns during the N-back working memory task as well as six other tasks in the Human Connectome Project dataset (n = 967), encompassing 15 task contrasts in total. We found tasks are a highly effective basis for prediction of GCA: The 2-back versus 0-back contrast achieved a 0.50 correlation with GCA scores in 10-fold cross-validation, and 13 out of 15 task contrasts afforded statistically significant prediction of GCA. Additionally, we found that task contrasts that produce greater frontoparietal activation and default mode network deactivation-a brain activation pattern associated with executive processing and higher cognitive demand-are more effective in the prediction of GCA. These results suggest a picture analogous to treadmill testing for cardiac function: Placing the brain in a more cognitively demanding task state significantly improves brain-based prediction of GCA.

Multi-Hypergraph Learning-Based Brain Functional Connectivity Analysis in fMRI Data

Recently, a hypergraph constructed from functional magnetic resonance imaging (fMRI) was utilized to explore brain functional connectivity networks (FCNs) for the classification of neurodegenerative diseases. Each edge of a hypergraph (called hyperedge) can connect any number of brain regions-of-interest (ROIs) instead of only two ROIs, and thus characterizes high-order relations among multiple ROIs that cannot be uncovered by a simple graph in the traditional graph based FCN construction methods. Unlike the existing hypergraph based methods where all hyperedges are assumed to have equal weights and only certain topological features are extracted from the hypergraphs, we propose a hypergraph learning based method for FCN construction in this paper. Specifically, we first generate hyperedges from fMRI time series based on sparse representation, then employ hypergraph learning to adaptively learn hyperedge weights, and finally define a hypergraph similarity matrix to represent the FCN. In our proposed method, weighting hyperedges results in better discriminative FCNs across subjects, and the defined hypergraph similarity matrix can better reveal the overall structure of brain network than using those hypergraph topological features. Moreover, we propose a multi-hypergraph learning based method by integrating multi-paradigm fMRI data, where the hyperedge weights associated with each fMRI paradigm are jointly learned and then a unified hypergraph similarity matrix is computed to represent the FCN. We validate the effectiveness of the proposed method on the Philadelphia Neurodevelopmental Cohort dataset for the classification of individuals' learning ability from three paradigms of fMRI data. Experimental results demonstrate that our proposed approach outperforms the traditional graph based methods (i.e., Pearson's correlation and partial correlation with the graphical Lasso) and the existing unweighted hypergraph based methods, which sheds light on how to optimize estimation of FCNs for cognitive and behavioral study.

The neural code of intelligence: From correlation to causation

Research into the neural underpinning of intelligence has mainly adopted a construct perspective: trying to find structural and functional brain characteristics that would accommodate the psychological concept of g. Few attempts have been made to explain intelligence exclusively based on brain characteristics - the brain perspective. From a methodological viewpoint the brain intelligence relation has been studied by means of correlational and interventional studies. The later providing a causal elucidation of the brain - intelligence relation. The best neuro-anatomical predictor of intelligence is brain volume showing a modest positive correlation with g, explaining between 9 to 16% of variance. The most likely explanation was that larger brains, containing more neurons, have a greater computational power and in that way allow more complex cognitive processing. Correlations with brain surface, thickness, convolution and callosal shape showed less consistent patterns. The development of diffusion tensor imaging has allowed researchers to look also into the microstructure of brain tissue. Consistently observed was a positively correlation between white matter integrity and intelligence, supporting the idea that efficient information transfer between hemispheres and brain areas is crucial for higher intellectual competence. Based on functional studies of the brain intelligence relationship three theories have been put forward: the neural efficiency, the P-FIT and the multi demand (MD) system theory. On the other hand, The Network Neuroscience Theory of g, based on methods from mathematics, physics, and computer science, is an example for the brain perspective on neurobiological underpinning of intelligence. In this framework network flexibility and dynamics provide the foundation for general intelligence. With respect to intervention studies the most promising results have been achieved with noninvasive brain stimulation and behavioral training providing tentative support for findings put forward by the correlational approach. To date the best consensus based on the diversity of results reported would be that g is predominantly determined by lateral prefrontal attentional control of structured sensory episodes in posterior brain areas. The capacity of flexible transitions between these network states represents the essence of intelligence - g.

Topological Modification of Brain Networks Organization in Children With High Intelligence Quotient: A Resting-State fMRI Study

The idea that intelligence is embedded not only in a single brain network, but instead in a complex, well-optimized system of complementary networks, has led to the development of whole brain network analysis. Using graph theory to analyze resting-state functional MRI data, we investigated the brain graph networks (or brain networks) of high intelligence quotient (HIQ) children. To this end, we computed the "hub disruption index κ," an index sensitive to graph network modifications. We found significant topological differences in the integration and segregation properties of brain networks in HIQ compared to standard IQ children, not only for the whole brain graph, but also for each hemispheric graph, and for the homotopic connectivity. Moreover, two profiles of HIQ children, homogenous and heterogeneous, based on the differences between the two main IQ subscales [verbal comprehension index (VCI) and perceptual reasoning index (PRI)], were compared. Brain network changes were more pronounced in the heterogeneous than in the homogeneous HIQ subgroups. Finally, we found significant correlations between the graph networks' changes and the full-scale IQ (FSIQ), as well as the subscales VCI and PRI. Specifically, the higher the FSIQ the greater was the brain organization modification in the whole brain, the left hemisphere, and the homotopic connectivity. These results shed new light on the relation between functional connectivity topology and high intelligence, as well as on different intelligence profiles.

Human paleoneurology: Shaping cortical evolution in fossil hominids

Evolutionary neuroanatomy must integrate two different sources of information, namely from fossil and from living species. Fossils supply information concerning the process of evolution, whereas living species supply information on the product of evolution. Unfortunately, the fossil record is partial and fragmented, and often cannot support validations for specific evolutionary hypotheses. Living species can provide more comprehensive indications, but they do not represent ancestral groups or primitive forms. Macaques or chimpanzees are frequently used as proxy for human ancestral conditions, despite the fact they are divergent and specialized lineages, with their own biological features. Similarly, in paleoanthropology independent lineages (such as Neanderthals) should not be confused with ancestral modern human stages. In this comparative framework, paleoneurology deals with the analysis of the endocranial cavity in extinct species, in order to make inferences on brain evolution. A main target of this field is to distinguish the endocranial variations due to brain changes, from those due to cranial constraints. Digital anatomy and computed morphometrics have provided major advances in this field. However, brains and endocasts can be hard to analyze with geometrical models, because of uncertainties due to the localization of cortical landmarks and boundaries. The study of the evolution of the parietal cortex supplies an interesting case-study in which paleontological and neontological data can integrate and test evolutionary hypotheses based on multiple sources of evidence. The relationships with visuospatial functions and brain-body-tool integration stress further that the analysis of the cognitive system should go beyond the neural boundaries of the brain.

Distributed neural efficiency: Intelligence and age modulate adaptive allocation of resources in the brain

Whether superior intelligence is associated with global lower resource consumption in the brain remains unresolved. In order to tap fluid intelligence "Gf" cortical networks, 50 neurologically healthy adults were functionally neuro-imaged while solving a modified version of the Raven Advanced Progressive Matrices. "Gf" predicted increased activation of key components of the dorsal attention network (DAN); and age predicted extent of simultaneous deactivation in key components of the default mode network (DMN) during problem-solving. However, there was no significant difference in mean levels of whole brain activation even when cognitively taxed. This suggests that the brain may dynamically switch resource consumption between these anti-correlated DAN and DMN networks, concentrating processing power in regions critical to enhanced cognitive performance. We term this mechanism of activation increase and decrease of these anti-correlated DAN/DMN systems, modulated by "Gf" and age, as "distributed neural efficiency". This may achieve local cost-efficiency trade-offs, while maintaining global energy homeostasis.

Spearman's hypothesis tested comparing Korean young adults with various other groups of young adults on the items of the Advanced Progressive Matrices

Spearman's hypothesis tested at the subtest level of an IQ battery states that differences between races on the subtests of an IQ battery are a function of the g loadings of these subtests, such that there are small differences between races on subtests with low g loadings and large differences between races on subtests with high g loadings. Jensen (1998) stated that Spearman's hypothesis is a law-like phenomenon. It has also been confirmed many times at the level of items of the Raven's Progressive Matrices. This study hypothesizes that with concern to Spearman's hypothesis, subtests and items function in fundamentally the same way, and tested whether Spearman's hypothesis is confirmed at the item level for White-East Asian comparisons. A group of Korean young adults (N=205) was compared with other groups of young adults from Canada, the US, Russia, Peru and South Africa (total N=4770) who took the Advanced Progressive Matrices. Spearman's hypothesis was strongly confirmed with a sample-size-weighted r with a value of 0.63. Computing the g loadings of the items of the Raven with either the Raven-g or the Wechsler-g led to the same conclusions. Tests of Spearman's hypothesis yielded less-strong outcomes when the 36-item Advanced Progressive Matrices were used than when the 60-item Standard Progressive Matrices were used. There is a substantial correlation between sample size and the outcome of Spearman's hypothesis. So, all four hypotheses were confirmed, showing that a part of the subtest-level nomological net replicates at the item level, strengthening the position that, with concern to Spearman's hypothesis, subtests and items function fundamentally the same. It is concluded that Spearman's hypothesis is still a law-like phenomenon. Detailed suggestions for follow-up research are made.

Correspondence between cerebral glucose metabolism and BOLD reveals relative power and cost in human brain

The correspondence between cerebral glucose metabolism (indexing energy utilization) and synchronous fluctuations in blood oxygenation (indexing neuronal activity) is relevant for neuronal specialization and is affected by brain disorders. Here, we define novel measures of relative power (rPWR, extent of concurrent energy utilization and activity) and relative cost (rCST, extent that energy utilization exceeds activity), derived from FDG-PET and fMRI. We show that resting-state networks have distinct energetic signatures and that brain could be classified into major bilateral segments based on rPWR and rCST. While medial-visual and default-mode networks have the highest rPWR, frontoparietal networks have the highest rCST. rPWR and rCST estimates are generalizable to other indexes of energy supply and neuronal activity, and are sensitive to neurocognitive effects of acute and chronic alcohol exposure. rPWR and rCST are informative metrics for characterizing brain pathology and alternative energy use, and may provide new multimodal biomarkers of neuropsychiatric disorders.

The brain primarily uses glucose to generate energy, but the relationship of neuronal activity to glucose utilization is not necessarily a simple linear one. Here, the authors introduce relative power (rPWR) and relative cost (rCST) as new metrics to quantify how brain activity relates to glucose consumption.

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 Neural Correlates of Relational Reasoning: A Meta-analysis of 47 Functional Magnetic Resonance Studies

It is a core cognitive ability of humans to represent and reason about relational information, such as “the train station is north of the hotel” or “Charles is richer than Jim.” However, the neural processes underlying the ability to draw conclusions about relations are still not sufficiently understood. Central open questions are as follows: (1) What are the neural correlates of relational reasoning? (2) Where can deductive and inductive reasoning be localized? (3) What is the impact of different informational types on cerebral activity? For that, we conducted a meta-analysis of 47 neuroimaging studies. We found activation of the frontoparietal network during both deductive and inductive reasoning, with additional activation in an extended network during inductive reasoning in the basal ganglia and the inferior parietal cortex. Analyses revealed a double dissociation concerning the lateral and medial Brodmann's area 6 during deductive and inductive reasoning, indicating differences in terms of processing verbal information in deductive and spatial information in inductive tasks. During semantic and symbolic tasks, the frontoparietal network was found active, whereas geometric tasks only elicited prefrontal activation, which can be explained by the reduced demand for the construction of a mental representation in geometric tasks. Our study provides new insights into the cognitive mechanisms underlying relational reasoning and clarifies previous controversies concerning involved brain areas.

Eight Weddings and Six Funerals: An fMRI Study on Autobiographical Memories

“Autobiographical memory” (AM) refers to remote memories from one's own life. Previous neuroimaging studies have highlighted that voluntary retrieval processes from AM involve different forms of memory and cognitive functions. Thus, a complex and widespread brain functional network has been found to support AM. The present functional magnetic resonance imaging (fMRI) study used a multivariate approach to determine whether neural activity within the AM circuit would recognize memories of real autobiographical events, and to evaluate individual differences in the recruitment of this network. Fourteen right-handed females took part in the study. During scanning, subjects were presented with sentences representing a detail of a highly emotional real event (positive or negative) and were asked to indicate whether the sentence described something that had or had not really happened to them. Group analysis showed a set of cortical areas able to discriminate the truthfulness of the recalled events: medial prefrontal cortex, posterior cingulate/retrosplenial cortex, precuneus, bilateral angular, superior frontal gyri, and early visual cortical areas. Single-subject results showed that the decoding occurred at different time points. No differences were found between recalling a positive or a negative event. Our results show that the entire AM network is engaged in monitoring the veracity of AMs. This process is not affected by the emotional valence of the experience but rather by individual differences in cognitive strategies used to retrieve AMs.

Differences Between APOE Carriers and Non-APOE Carriers on Neurocognitive Tests: Jensen Effects?

BACKGROUND

Being a carrier of the apolipoprotein E (APOE) ε4 allele is a clear risk factor for development of Alzheimer's disease (AD). On some neurocognitive tests, there are smaller differences between carriers and noncarriers, while other tests show larger differences.

AIMS

We explore whether the size of the difference between carriers and noncarriers is a function of how well the tests measure general intelligence, so whether there are Jensen effects.

METHODS

We used the method of correlated vectors on 441 Korean older adults at risk for AD and 44 with AD.

RESULTS

Correlations between APOE carriership and test scores ranged from -.05 to .11 (normal), and -.23 to .54 (AD). The differences between carriers and noncarriers were Jensen effects: r = .31 and r = .54, respectively.

CONCLUSION

A composite neurocognitive score may show a clearer contrast between APOE carriers and noncarriers than a large number of scores of single neurocognitive tests.

Beyond Domain-Specific Expertise: Neural Signatures of Face and Spatial Working Memory in Baduk (Go Game) Experts

Recent advances of neuroimaging methodology and artificial intelligence have resulted in renewed interest in board games like chess and Baduk (called Go game in the West) and have provided clues as to the mechanisms behind the games. However, an interesting question that remains to be answered is whether the board game expertise as one of cognitive skills goes beyond just being good at the trained game and how it maps on networks associated with cognitive abilities that are not directly trained. To address this issue, we examined functional activity and connectivity in Baduk experts, compared to novices, while performing a visual n-back working memory (WM) task. We found that experts, compared to novices, had greater activation in superior parietal cortex during face WM, though there were no group differences in behavioral performances. Using a data-driven, whole-brain multivariate approach, we also found significant group differences in the multivariate pattern of connectivity in frontal pole and inferior parietal cortex, further showing greater connectivity between frontal and parietal regions and between frontal and temporal regions in experts. Our findings suggest that long-term trained Baduk experts have the reorganization of functional interactions between brain regions even for untrained cognitive ability.

Working Memory and Reasoning Benefit from Different Modes of Large-scale Brain Dynamics in Healthy Older Adults

Researchers have proposed that solving complex reasoning problems, a key indicator of fluid intelligence, involves the same cognitive processes as solving working memory tasks. This proposal is supported by an overlap of the functional brain activations associated with the two types of tasks and by high correlations between interindividual differences in performance. We replicated these findings in 53 older participants but also showed that solving reasoning and working memory problems benefits from different configurations of the functional connectome and that this dissimilarity increases with a higher difficulty load. Specifically, superior performance in a typical working memory paradigm ( n-back) was associated with upregulation of modularity (increased between-network segregation), whereas performance in the reasoning task was associated with effective downregulation of modularity. We also showed that working memory training promotes task-invariant increases in modularity. Because superior reasoning performance is associated with downregulation of modular dynamics, training may thus have fostered an inefficient way of solving the reasoning tasks. This could help explain why working memory training does little to promote complex reasoning performance. The study concludes that complex reasoning abilities cannot be reduced to working memory and suggests the need to reconsider the feasibility of using working memory training interventions to attempt to achieve effects that transfer to broader cognition.

Verbal and visual cognition: Individual differences in the lab, in the brain, and in the classroom

In many ways, individuals vary in their thought processes, and in their cognitive strengths and weaknesses. Among the findings revealed by individual differences research, one major dividing line highlighted recurrently by decades of experimental studies is that between linguistically-mediated cognitive operations (verbal cognition), versus cognition, which primarily operates on visual - or visuospatial - representations (visual cognition). In this article, we review findings from three research areas-cognitive abilities, working memory, and task strategies-focusing on individual differences in verbal and visual cognition. In each area we highlight behavioral, neuroimaging, and classroom-based findings, bridging the perspectives of these different methodologies.

Development of the Mental Synthesis Evaluation Checklist (MSEC): A Parent-Report Tool for Mental Synthesis Ability Assessment in Children with Language Delay

Mental synthesis is the conscious purposeful process of synthesizing novel mental images from objects stored in memory. Mental synthesis ability is essential for understanding complex syntax, spatial prepositions, and verb tenses. In typical children, the timeline of mental synthesis acquisition is highly correlated with an increasing vocabulary. Children with Autism Spectrum Disorder (ASD), on the other hand, may learn hundreds of words but never acquire mental synthesis. In these individuals, tests assessing vocabulary comprehension may fail to demonstrate the profound deficit in mental synthesis. We developed a parent-reported Mental Synthesis Evaluation Checklist (MSEC) designed to assess mental synthesis acquisition in ASD children. The psychometric quality of MSEC was tested with 3715 parents of ASD children. Internal reliability of the 20-item MSEC was good (Cronbach's alpha >0.9). MSEC exhibited adequate test⁻retest reliability; good construct validity, supported by a positive correlation with the Autism Treatment Evaluation Checklist (ATEC) Communication subscale; and good known group validity reflected by the difference in MSEC scores for children of different ASD severity levels. The MSEC questionnaire is copyright-free and can be used by researchers as a complimentary subscale for the ATEC evaluation. We hope that the addition of MSEC will make the combined assessment more sensitive to small steps in a child's development. As MSEC does not rely on productive language, it may be an especially useful tool for assessing the development of nonverbal and minimally verbal children.

Frontoparietal tDCS Benefits Visual Working Memory in Older Adults With Low Working Memory Capacity

Working memory (WM) permits maintenance of information over brief delays and is an essential executive function. Unfortunately, WM is subject to age-related decline. Some evidence supports the use of transcranial direct current stimulation (tDCS) to improve visual WM. A gap in knowledge is an understanding of the mechanism characterizing these tDCS linked effects. To address this gap, we compared the effects of two tDCS montages designed on visual working memory (VWM) performance. The bifrontal montage was designed to stimulate the heightened bilateral frontal activity observed in aging adults. The unilateral frontoparietal montage was designed to stimulate activation patterns observed in young adults. Participants completed three sessions (bilateral frontal, right frontoparietal, sham) of anodal tDCS (20 min, 2 mA). During stimulation, participants performed a visual long-term memory (LTM) control task and a visual WM task. There was no effect of tDCS on the LTM task. Participants receiving right unilateral tDCS showed a WM benefit. This pattern was most robust in older adults with low WM capacity. To address the concern that the key difference between the two tDCS montages could be tDCS over the posterior parietal cortex (PPC), we included new analyses from a previous study applying tDCS targeting the PPC paired with a recognition VWM task. No significant main effects were found. A subsequent experiment in young adults found no significant effect of either tDCS montage on either task. These data indicate that tDCS montage, age and WM capacity should be considered when designing tDCS protocols. We interpret these findings as suggestive that protocols designed to restore more youthful patterns of brain activity are superior to those that compensate for age-related changes.

Fluid Intelligence: Review of Foreign Studies

The present review focuses on modern research of fluid intelligence. The concept of fluid intelligence, the place of fluid intelligence in the structure of cognitive abilities, its relation to general intelligence is revealed. The current models of fluid intelligence are considered, including the current leading Cattell–Horn–Carroll model. The neurobiological processes underlying the flexibility of fluid reasoning processes in solving novel problems are discussed. In particular, studies are presented showing that fluid intelligence is mediated by subregions of the prefrontal cortex. Studies of the relationship between fluid intelligence and working memory, as well as studies of fluid intelligence in clinical groups such as children with ADHD and adults with schizophrenia are also discussed. Clinical evidence suggests that fluid intelligence may be key to understanding the structure of cognitive deficits in ADHD syndrome.

Network attributes underlying intellectual giftedness in the developing brain

Brain network is organized to maximize the efficiency of both segregated and integrated information processing that may be related to human intelligence. However, there have been surprisingly few studies that focus on the topological characteristics of brain network underlying extremely high intelligence that is intellectual giftedness, particularly in adolescents. Here, we examined the network topology in 25 adolescents with superior intelligence (SI-Adol), 25 adolescents with average intelligence (AI-Adol), and 27 young adults with AI (AI-Adult). We found that SI-Adol had network topological properties of high global efficiency as well as high clustering with a low wiring cost, relative to AI-Adol. However, contrary to the suggested role that brain hub regions play in general intelligence, the network efficiency of rich club connection matrix, which represents connections among brain hubs, was low in SI-Adol in comparison to AI-Adol. Rather, a higher level of local connection density was observed in SI-Adol than in AI-Adol. The highly intelligent brain may not follow this efficient yet somewhat stereotypical process of information integration entirely. Taken together, our results suggest that a highly intelligent brain may communicate more extensively, while being less dependent on rich club communications during adolescence.

A Putative Multiple-Demand System in the Macaque Brain

In humans, cognitively demanding tasks of many types recruit common frontoparietal brain areas. Pervasive activation of this "multiple-demand" (MD) network suggests a core function in supporting goal-oriented behavior. A similar network might therefore be predicted in nonhuman primates that readily perform similar tasks after training. However, an MD network in nonhuman primates has not been described. Single-cell recordings from macaque frontal and parietal cortex show some similar properties to human MD fMRI responses (e.g., adaptive coding of task-relevant information). Invasive recordings, however, come from limited prespecified locations, so they do not delineate a macaque homolog of the MD system and their positioning could benefit from knowledge of where MD foci lie. Challenges of scanning behaving animals mean that few macaque fMRI studies specifically contrast levels of cognitive demand, so we sought to identify a macaque counterpart to the human MD system using fMRI connectivity in 35 rhesus macaques. Putative macaque MD regions, mapped from frontoparietal MD regions defined in humans, were found to be functionally connected under anesthesia. To further refine these regions, an iterative process was used to maximize their connectivity cross-validated across animals. Finally, whole-brain connectivity analyses identified voxels that were robustly connected to MD regions, revealing seven clusters across frontoparietal and insular cortex comparable to human MD regions and one unexpected cluster in the lateral fissure. The proposed macaque MD regions can be used to guide future electrophysiological investigation of MD neural coding and in task-based fMRI to test predictions of similar functional properties to human MD cortex.

SIGNIFICANCE STATEMENT

In humans, a frontoparietal "multiple-demand" (MD) brain network is recruited during a wide range of cognitively demanding tasks. Because this suggests a fundamental function, one might expect a similar network to exist in nonhuman primates, but this remains controversial. Here, we sought to identify a macaque counterpart to the human MD system using fMRI connectivity. Putative macaque MD regions were functionally connected under anesthesia and were further refined by iterative optimization. The result is a network including lateral frontal, dorsomedial frontal, and insular and inferior parietal regions closely similar to the human counterpart. The proposed macaque MD regions can be useful in guiding electrophysiological recordings or in task-based fMRI to test predictions of similar functional properties to human MD cortex.

The posterior parietal cortex as integrative hub for whisker sensorimotor information

Our daily life consists of a continuous interplay between incoming sensory information and outgoing motor plans. Particularly during goal-directed behavior and active exploration of the sensory environment, brain circuits are merging sensory and motor signals. This is referred to as sensorimotor integration and is relevant for locomotion, vision or tactile exploration. The somatosensory (tactile) system is an attractive modality to study sensorimotor integration in health and disease, motivated by the need for revolutionary technology that builds upon conceptual understanding of sensorimotor integration, such as brain-machine-interfaces and neuro-prosthetics. In this perspective, we focus on the rat whisker system and put forward the posterior parietal cortex as a potential circuit where sensorimotor integration could occur during active somatosensation.

Fluid and flexible minds: Intelligence reflects synchrony in the brain's intrinsic network architecture

Human intelligence has been conceptualized as a complex system of dissociable cognitive processes, yet studies investigating the neural basis of intelligence have typically emphasized the contributions of discrete brain regions or, more recently, of specific networks of functionally connected regions. Here we take a broader, systems perspective in order to investigate whether intelligence is an emergent property of synchrony within the brain’s intrinsic network architecture. Using a large sample of resting-state fMRI and cognitive data (n = 830), we report that the synchrony of functional interactions within and across distributed brain networks reliably predicts fluid and flexible intellectual functioning. By adopting a whole-brain, systems-level approach, we were able to reliably predict individual differences in human intelligence by characterizing features of the brain’s intrinsic network architecture. These findings hold promise for the eventual development of neural markers to predict changes in intellectual function that are associated with neurodevelopment, normal aging, and brain disease.

In our study, we aimed to understand how individual differences in intellectual functioning are reflected in the intrinsic network architecture of the human brain. We applied statistical methods, known as spectral decompositions, in order to identify individual differences in the synchronous patterns of spontaneous brain activity that reliably predict core aspects of human intelligence. The synchrony of brain activity at rest across multiple discrete neural networks demonstrated positive relationships with fluid intelligence. In contrast, global synchrony within the brain’s network architecture reliably, and inversely, predicted mental flexibility, a core facet of intellectual functioning. The multinetwork systems approach described here represents a methodological and conceptual extension of earlier efforts that related differences in intellectual ability to variations in specific brain regions, networks, or their interactions. Our findings suggest that the neural basis of complex, integrative cognitive functions can be most completely understood from the perspective of network neuroscience.