Architecture of fluid intelligence and working memory revealed by lesion mapping

Cross-sectional and Longitudinal Age-related Disintegration in Functional Connectivity: Reference Ability Neural Network Cohort

Some theories of aging have linked age-related cognitive decline to a reduction in distinctiveness of neural processing. Observed age-related correlation increases among disparate cognitive tasks have supported the dedifferentiation hypothesis. We previously showed cross-sectional evidence for age-related correlation decreases instead, supporting an alternative disintegration hypothesis. In the current study, we extended our previous research to a longitudinal sample. We tested 135 participants (20-80 years) at two time points-baseline and 5-year follow-up-on a battery of 12 in-scanner tests, each tapping one of four reference abilities. We performed between-tasks correlations within domain (convergent) and between domain (discriminant) at both the behavioral and neural level, calculating a single measure of construct validity (convergent - discriminant). Cross-sectionally, behavioral construct validity was significantly different from chance at each time point, but longitudinal change was not significant. Analysis by median age split revealed that older adults showed higher behavioral validity, driven by higher discriminant validity (lower between-tasks correlations). Participant-level neural validity decreased over time, with convergent validity consistently greater than discriminant validity; this finding was also observed at the cross-sectional level. In addition, a disproportionate decrease in neural validity with age remained significant after controlling for demographic factors. Factors predicting longitudinal changes in global cognition (mean performance across all 12 tasks) included age, change in neural validity, education, and National Adult Reading Test (premorbid intelligence). Change in neural validity partially mediated the effect of age on change in global cognition. Our findings support the theory of age-related disintegration, linking cognitive decline to changes in neural representations over time.

Examining the neurostructural architecture of intelligence: The Lothian Birth Cohort 1936 study

Examining underlying neurostructural correlates of specific cognitive abilities is practically and theoretically complicated by the existence of the positive manifold (all cognitive tests positively correlate): if a brain structure is associated with a cognitive task, how much of this is uniquely related to the cognitive domain, and how much is due to covariance with all other tests across domains (captured by general cognitive functioning, also known as general intelligence, or 'g')? We quantitatively address this question by examining associations between brain structural and diffusion MRI measures (global tissue volumes, white matter hyperintensities, global white matter diffusion fractional anisotropy and mean diffusivity, and FreeSurfer processed vertex-wise cortical volumes, smoothed at 20mm fwhm) with g and cognitive domains (processing speed, crystallised ability, memory, visuospatial ability). The cognitive domains were modelled using confirmatory factor analysis to derive both hierarchical and bifactor solutions using 13 cognitive tests in 697 participants from the Lothian Birth Cohort 1936 study (mean age 72.5 years; SD = .7). Associations between the extracted cognitive factor scores for each domain and g were computed for each brain measure covarying for age, sex and intracranial volume, and corrected for false discovery rate. There were a range of significant associations between cognitive domains and global MRI brain structural measures (r range .008 to .269, p < .05). Regions implicated by vertex-wise regional cortical volume included a widespread number of medial and lateral areas of the frontal, temporal and parietal lobes. However, at both global and regional level, much of the domain-MRI associations were shared (statistically accounted for by g). Removing g-related variance from cognitive domains attenuated association magnitudes with global brain MRI measures by 27.9-59.7% (M = 46.2%), with only processing speed retaining all significant associations. At the regional cortical level, g appeared to account for the majority (range 22.1-88.4%; M = 52.8% across cognitive domains) of regional domain-specific associations. Crystallised and memory domains had almost no unique cortical correlates, whereas processing speed and visuospatial ability retained limited cortical volumetric associations. The greatest spatial overlaps across cognitive domains (as denoted by g) were present in the medial and lateral temporal, lateral parietal and lateral frontal areas.

Cerebellar Theta Burst Stimulation Impairs Working Memory

Working memory refers to the process of temporarily storing and manipulating information. The role of the cerebellum in working memory is thought to be achieved through its connections with the prefrontal cortex. Previous studies showed that theta burst stimulation (TBS), a form of repetitive transcranial magnetic stimulation, of the cerebellum changes its functional connectivity with the prefrontal cortex. Specifically, excitatory intermittent TBS (iTBS) increases, whereas inhibitory continuous TBS (cTBS) decreases this functional connectivity. We hypothesized that iTBS on the cerebellum will improve working memory, whereas cTBS will disrupt it. Sixteen healthy participants (10 women) participated in this study. Bilateral cerebellar stimulation was applied with a figure-of-eight coil at 3 cm lateral and 1 cm below the inion. The participants received iTBS, cTBS, and sham iTBS in three separate sessions in random order. Within 30 min after TBS, the participants performed four working memory tasks: letter 1-Back and 2-Back, digit span forward, and digit span backward. Repeated measures analysis of variance revealed a significant effect of the type of stimulation (iTBS/cTBS/Sham) on performance in the digit span backward task (p = 0.02). The planned comparison showed that the cTBS condition had significantly lower scores than the sham condition (p = 0.01). iTBS and cTBS did not affect performance in the 1- and 2-Back and the digit span forward tasks compared to sham stimulation. The findings support the hypothesis that the cerebellum is involved in working memory, and this contribution may be disrupted by cTBS.

Studying the social mind: An updated summary of findings from the Vietnam Head Injury Study

Lesion mapping studies allow us to evaluate the potential causal contribution of specific brain areas to human cognition and complement other cognitive neuroscience methods, as several authors have recently pointed out. Here, we present an updated summary of the findings from the Vietnam Head Injury Study (VHIS) focusing on the studies conducted over the last decade, that examined the social mind and its intricate neural and cognitive underpinnings. The VHIS is a prospective, long-term follow-up study of Vietnam veterans with penetrating traumatic brain injury (pTBI) and healthy controls (HC). The scope of the work is to present the studies from the latest phases (3 and 4) of the VHIS, 70 studies since 2011, when the Raymont et al. paper was published (Raymont et al., 2011). These studies have contributed to our understanding of human social cognition, including political and religious beliefs, theory of mind, but also executive functions, intelligence, and personality. This work finally discusses the usefulness of lesion mapping as an approach to understanding the functions of the human brain from basic science and clinical perspectives.

Atypical paroxysmal slow cortical activity in healthy adults: Relationship to age and cognitive performance

Paroxysmal patterns of slow cortical activity have been detected in EEG recordings from individuals with age-related neuropathology and have been shown to be correlated with cognitive dysfunction and blood-brain barrier disruption in these participants. The prevalence of these events in healthy participants, however, has not been studied. In this work, we inspect MEG recordings from 623 healthy participants from the Cam-CAN dataset for the presence of paroxysmal slow wave events (PSWEs). PSWEs were detected in approximately 20% of healthy participants in the dataset, and participants with PSWEs tended to be older and have lower cognitive performance than those without PSWEs. In addition, event features changed linearly with age and cognitive performance, resulting in longer and slower events in older adults, and more widespread events in those with low cognitive performance. These findings provide the first evidence of PSWEs in a subset of purportedly healthy adults. Going forward, these events may have utility as a diagnostic biomarker for atypical brain activity in older adults.

EEG-based neurophysiological indices for expert psychomotor performance - a review

A primary objective of current human neuropsychological performance research is to define the physiological correlates of adaptive knowledge utilization, in order to support the enhanced execution of both simple and complex tasks. Within the present article, electroencephalography-based neurophysiological indices characterizing expert psychomotor performance, will be explored. As a means of characterizing fundamental processes underlying efficient psychometric performance, the neural efficiency model will be evaluated in terms of alpha-wave-based selective cortical processes. Cognitive and motor domains will initially be explored independently, which will act to encapsulate the task-related neuronal adaptive requirements for enhanced psychomotor performance associating with the neural efficiency model. Moderating variables impacting the practical application of such neuropsychological model, will also be investigated. As a result, the aim of this review is to provide insight into detectable task-related modulation involved in developed neurocognitive strategies which support heightened psychomotor performance, for the implementation within practical settings requiring a high degree of expert performance (such as sports or military operational settings).

The effect of processing speed on verbal and visual memory of adults with a chronic acquired brain injury

OBJECTIVE

Memory problems are among the most frequently reported cognitive complaints by individuals with an acquired brain injury (ABI). Processing speed and working memory deficits are often the result of ABI. These cognitive deficits significantly impact the acquisition and retention of information necessary for memory formation. This study investigated the influence of processing speed and working memory on immediate and delayed recall for verbal and visual memory, as well as overall memory recall in adults living with a chronic ABI.

METHODS

Sixty-three participants living with a chronic ABI, who were at least one-year post-injury, were cognitively assessed with the CNS-Vital Signs (CNS-VS) computerized cognitive battery and Wechsler Test of Adult Reading.

RESULTS

The CNS-VS Processing Speed significantly predicted delayed recall for verbal memory and overall memory performance. The CNS-VS Working Memory was not a significant predictor of memory recall.

CONCLUSIONS

Processing speed deficits negatively impact memory in individuals with a chronic ABI. These findings suggest the memory recall of adults with a chronic ABI is associated with poor processing speed and poor acquisition of information. Therefore, cognitive rehabilitation that improves processing speed should be the focus for individuals with ABI to improve memory performance as well as impaired processing speed.

Event-related delta and theta responses may reflect the valence discrimination in the emotional oddball task

How emotion and cognition interact is still a matter of debate. Investigation of this interaction in terms of the brain oscillatory dynamics appears to be an essential approach. To investigate this topic, we designed two separate three-stimulus oddball tasks, including emotional stimuli with different valences. Twenty healthy young subjects were included in the study. They completed two tasks, namely: the positive emotional oddball task and the negative emotional oddball task. Each task included the target, non-target, and distractor stimuli. Positive and negative pictures were the target stimuli in the positive and negative emotional oddball task. We asked participants to determine the number of target stimuli in each task. During sessions, EEGs were recorded with 32 electrodes. We found that (negative) target stimuli elicit higher delta (1-3.5 Hz) and theta (4-7 Hz) power responses but not the phase-locking responses compared to (positive) distractor stimuli during the negative oddball task. On the other hand, the same effect was not seen during the positive emotional oddball task. Here, we showed that the valence dimension interacted with the target status. Finally, we summarized our results that the presence of negative distractors attenuated the target effect of the positive stimuli due to the negative bias.

Connectome-based predictive modeling of fluid intelligence: evidence for a global system of functionally integrated brain networks

Cognitive neuroscience continues to advance our understanding of the neural foundations of human intelligence, with significant progress elucidating the role of the frontoparietal network in cognitive control mechanisms for flexible, intelligent behavior. Recent evidence in network neuroscience further suggests that this finding may represent the tip of the iceberg and that fluid intelligence may depend on the collective interaction of multiple brain networks. However, the global brain mechanisms underlying fluid intelligence and the nature of multi-network interactions remain to be well established. We therefore conducted a large-scale Connectome-based Predictive Modeling study, administering resting-state fMRI to 159 healthy college students and examining the contributions of seven intrinsic connectivity networks to the prediction of fluid intelligence, as measured by a state-of-the-art cognitive task (the Bochum Matrices Test). Specifically, we aimed to: (i) identify whether fluid intelligence relies on a primary brain network or instead engages multiple brain networks; and (ii) elucidate the nature of brain network interactions by assessing network allegiance (within- versus between-network connections) and network topology (strong versus weak connections) in the prediction of fluid intelligence. Our results demonstrate that whole-brain predictive models account for a large and significant proportion of variance in fluid intelligence (18%) and illustrate that the contribution of individual networks is relatively modest by comparison. In addition, we provide novel evidence that the global architecture of fluid intelligence prioritizes between-network connections and flexibility through weak ties. Our findings support a network neuroscience approach to understanding the collective role of brain networks in fluid intelligence and elucidate the system-wide network mechanisms from which flexible, adaptive behavior is constructed.

Using predictive validity to compare associations between brain damage and behavior

Lesion-behavior mapping (LBM) provides a statistical map of the association between voxel-wise brain damage and individual differences in behavior. To understand whether two behaviors are mediated by damage to distinct regions, researchers often compare LBM weight outputs by either the Overlap method or the Correlation method. However, these methods lack statistical criteria to determine whether two LBM are distinct versus the same and are disconnected from a major goal of LBMs: predicting behavior from brain damage. Without such criteria, researchers may draw conclusions from numeric differences between LBMs that are irrelevant to predicting behavior. We developed and validated a predictive validity comparison method (PVC) that establishes a statistical criterion for comparing two LBMs using predictive accuracy: two LBMs are distinct if and only if they provide unique predictive power for the behaviors being assessed. We applied PVC to two lesion-behavior stroke data sets, demonstrating its utility for determining when behaviors arise from the same versus different lesion patterns. Using region-of-interest-based simulations derived from proportion damage from a large data set (n = 131), PVC accurately detected when behaviors were mediated by different regions (high sensitivity) versus the same region (high specificity). Both the Overlap method and Correlation method performed poorly on the simulated data. By objectively determining whether two behavioral deficits can be explained by single versus distinct patterns of brain damage, PVC provides a critical advance in establishing the brain bases of behavior. We have developed and released a GUI-driven web app to encourage widespread adoption.

Identifying the Neural Bases of Math Competence Based on Structural and Functional Properties of the Human Brain

Human populations show large individual differences in math performance and math learning abilities. Early math skill acquisition is critical for providing the foundation for higher quantitative skill acquisition and succeeding in modern society. However, the neural bases underlying individual differences in math competence remain unclear. Modern neuroimaging techniques allow us to not only identify distinct local cortical regions but also investigate large-scale neural networks underlying math competence both structurally and functionally. To gain insights into the neural bases of math competence, this review provides an overview of the structural and functional neural markers for math competence in both typical and atypical populations of children and adults. Although including discussion of arithmetic skills in children, this review primarily focuses on the neural markers associated with complex math skills. Basic number comprehension and number comparison skills are outside the scope of this review. By synthesizing current research findings, we conclude that neural markers related to math competence are not confined to one particular region; rather, they are characterized by a distributed and interconnected network of regions across the brain, primarily focused on frontal and parietal cortices. Given that human brain is a complex network organized to minimize the cost of information processing, an efficient brain is capable of integrating information from different regions and coordinating the activity of various brain regions in a manner that maximizes the overall efficiency of the network to achieve the goal. We end by proposing that frontoparietal network efficiency is critical for math competence, which enables the recruitment of task-relevant neural resources and the engagement of distributed neural circuits in a goal-oriented manner. Thus, it will be important for future studies to not only examine brain activation patterns of discrete regions but also examine distributed network patterns across the brain, both structurally and functionally.

Investigating cognitive neuroscience theories of human intelligence: A connectome-based predictive modeling approach

Central to modern neuroscientific theories of human intelligence is the notion that general intelligence depends on a primary brain region or network, engaging spatially localized (rather than global) neural representations. Recent findings in network neuroscience, however, challenge this assumption, providing evidence that general intelligence may depend on system-wide network mechanisms, suggesting that local representations are necessary but not sufficient to account for the neural architecture of human intelligence. Despite the importance of this key theoretical distinction, prior research has not systematically investigated the role of local versus global neural representations in predicting general intelligence. We conducted a large-scale connectome-based predictive modeling study (N = 297), administering resting-state fMRI and a comprehensive cognitive battery to evaluate the efficacy of modern neuroscientific theories of human intelligence, including spatially localized theories (Lateral Prefrontal Cortex Theory, Parieto-Frontal Integration Theory, and Multiple Demand Theory) and recent global accounts (Process Overlap Theory and Network Neuroscience Theory). The results of our study demonstrate that general intelligence can be predicted by local functional connectivity profiles but is most robustly explained by global profiles of whole-brain connectivity. Our findings further suggest that the improved efficacy of global theories is not reducible to a greater strength or number of connections, but instead results from considering both strong and weak connections that provide the basis for intelligence (as predicted by the Network Neuroscience Theory). Our results highlight the importance of considering local neural representations in the context of a global information-processing architecture, suggesting future directions for theory-driven research on system-wide network mechanisms underlying general intelligence.

Robust associations between white matter microstructure and general intelligence

Few tract-based spatial statistics (TBSS) studies have investigated the relations between intelligence and white matter microstructure in healthy (young) adults, and those have yielded mixed observations, yet white matter is fundamental for efficient and accurate information transfer throughout the human brain. We used a multicenter approach to identify white matter regions that show replicable structure-function associations, employing data from 4 independent samples comprising over 2000 healthy participants. TBSS indicated 188 voxels exhibited significant positive associations between g factor scores and fractional anisotropy (FA) in all 4 data sets. Replicable voxels formed 3 clusters, located around the left-hemispheric forceps minor, superior longitudinal fasciculus, and cingulum-cingulate gyrus with extensions into their surrounding areas (anterior thalamic radiation, inferior fronto-occipital fasciculus). Our results suggested that individual differences in general intelligence are robustly associated with white matter FA in specific fiber bundles distributed across the brain, consistent with the Parieto-Frontal Integration Theory of intelligence. Three possible reasons higher FA values might create links with higher g are faster information processing due to greater myelination, more direct information processing due to parallel, homogenous fiber orientation distributions, or more parallel information processing due to greater axon density.

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.

Graph lesion-deficit mapping of fluid intelligence

Fluid intelligence is arguably the defining feature of human cognition. Yet the nature of its relationship with the brain remains a contentious topic. Influential proposals drawing primarily on functional imaging data have implicated 'multiple demand' frontoparietal and more widely distributed cortical networks, but extant lesion-deficit studies with greater causal power are almost all small, methodologically constrained, and inconclusive. The task demands large samples of patients, comprehensive investigation of performance, fine-grained anatomical mapping, and robust lesion-deficit inference, yet to be brought to bear on it. We assessed 165 healthy controls and 227 frontal or non-frontal patients with unilateral brain lesions on the best-established test of fluid intelligence, Raven's Advanced Progressive Matrices, employing an array of lesion-deficit inferential models responsive to the potentially distributed nature of fluid intelligence. Non-parametric Bayesian stochastic block models were used to reveal the community structure of lesion deficit networks, disentangling functional from confounding pathological distributed effects. Impaired performance was confined to patients with frontal lesions [F(2,387) = 18.491; P < 0.001; frontal worse than non-frontal and healthy participants P < 0.01, P <0.001], more marked on the right than left [F(4,385) = 12.237; P < 0.001; right worse than left and healthy participants P < 0.01, P < 0.001]. Patients with non-frontal lesions were indistinguishable from controls and showed no modulation by laterality. Neither the presence nor the extent of multiple demand network involvement affected performance. Both conventional network-based statistics and non-parametric Bayesian stochastic block modelling heavily implicated the right frontal lobe. Crucially, this localization was confirmed on explicitly disentangling functional from pathology-driven effects within a layered stochastic block model, prominently highlighting a right frontal network involving middle and inferior frontal gyrus, pre- and post-central gyri, with a weak contribution from right superior parietal lobule. Similar results were obtained with standard lesion-deficit analyses. Our study represents the first large-scale investigation of the distributed neural substrates of fluid intelligence in the focally injured brain. Combining novel graph-based lesion-deficit mapping with detailed investigation of cognitive performance in a large sample of patients provides crucial information about the neural basis of intelligence. Our findings indicate that a set of predominantly right frontal regions, rather than a more widely distributed network, is critical to the high-level functions involved in fluid intelligence. Further they suggest that Raven's Advanced Progressive Matrices is a useful clinical index of fluid intelligence and a sensitive marker of right frontal lobe dysfunction.

The Effects of Four Weeks of Chiropractic Spinal Adjustments on Blood Biomarkers in Adults with Chronic Stroke: Secondary Outcomes of a Randomized Controlled Trial

Certain blood biomarkers are associated with neural protection and neural plasticity in healthy people and individuals with prior brain injury. To date, no studies have evaluated the effects chiropractic care on serum brain-derived neurotrophic factor (BDNF), insulin-like growth factor-II (IGF-II) and glial cell-derived neurotrophic factor (GDNF) in people with stroke. This manuscript reports pre-specified, exploratory, secondary outcomes from a previously completed parallel group randomized controlled trial. We evaluated differences between four weeks of chiropractic spinal adjustments combined with the usual physical therapy (chiro + PT) and sham chiropractic with physical therapy (sham + PT) on resting serum BDNF, IGF-II and GDNF in 63 adults with chronic stroke. Blood samples were assessed at baseline, four weeks (post-intervention), and eight weeks (follow-up). Data were analyzed using a linear multivariate mixed effects model. Within both groups there was a significant decrease in the mean log-concentration of BDNF and IGF-II at each follow-up, and significant increase log-concentration of GDNF at eight-weeks' follow-up. However, no significant between-group differences in any of the blood biomarkers at each time-point were found. Further research is required to explore which factors influence changes in serum BDNF, IGF-II and GDNF following chiropractic spinal adjustments and physical therapy.

Cross-cohort replicability and generalizability of connectivity-based psychometric prediction patterns

An increasing number of studies have investigated the relationships between inter-individual variability in brain regions' connectivity and behavioral phenotypes, making use of large population neuroimaging datasets. However, the replicability of brain-behavior associations identified by these approaches remains an open question. In this study, we examined the cross-dataset replicability of brain-behavior association patterns for fluid cognition and openness predictions using a previously developed region-wise approach, as well as using a standard whole-brain approach. Overall, we found moderate similarity in patterns for fluid cognition predictions across cohorts, especially in the Human Connectome Project Young Adult, Human Connectome Project Aging, and Enhanced Nathan Kline Institute Rockland Sample cohorts, but low similarity in patterns for openness predictions. In addition, we assessed the generalizability of prediction models in cross-dataset predictions, by training the model in one dataset and testing in another. Making use of the region-wise prediction approach, we showed that first, a moderate extent of generalizability could be achieved with fluid cognition prediction, and that, second, a set of common brain regions related to fluid cognition across cohorts could be identified. Nevertheless, the moderate replicability and generalizability could only be achieved in specific contexts. Thus, we argue that replicability and generalizability in connectivity-based prediction remain limited and deserve greater attention in future studies.

A multicohort geometric deep learning study of age dependent cortical and subcortical morphologic interactions for fluid intelligence prediction

The relationship of human brain structure to cognitive function is complex, and how this relationship differs between childhood and adulthood is poorly understood. One strong hypothesis suggests the cognitive function of Fluid Intelligence (Gf) is dependent on prefrontal cortex and parietal cortex. In this work, we developed a novel graph convolutional neural networks (gCNNs) for the analysis of localized anatomic shape and prediction of Gf. Morphologic information of the cortical ribbons and subcortical structures was extracted from T1-weighted MRIs within two independent cohorts, the Adolescent Brain Cognitive Development Study (ABCD; age: 9.93 ± 0.62 years) of children and the Human Connectome Project (HCP; age: 28.81 ± 3.70 years). Prediction combining cortical and subcortical surfaces together yielded the highest accuracy of Gf for both ABCD (R = 0.314) and HCP datasets (R = 0.454), outperforming the state-of-the-art prediction of Gf from any other brain measures in the literature. Across both datasets, the morphology of the amygdala, hippocampus, and nucleus accumbens, along with temporal, parietal and cingulate cortex consistently drove the prediction of Gf, suggesting a significant reframing of the relationship between brain morphology and Gf to include systems involved with reward/aversion processing, judgment and decision-making, motivation, and emotion.

Learning to play a musical instrument in the middle school is associated with superior audiovisual working memory and fluid intelligence: A cross-sectional behavioral study

Music training, in all its forms, is known to have an impact on behavior both in childhood and even in aging. In the delicate life period of transition from childhood to adulthood, music training might have a special role for behavioral and cognitive maturation. Among the several kinds of music training programs implemented in the educational communities, we focused on instrumental training incorporated in the public middle school curriculum in Italy that includes both individual, group and collective (orchestral) lessons several times a week. At three middle schools, we tested 285 preadolescent children (aged 10–14 years) with a test and questionnaire battery including adaptive tests for visuo-spatial working memory skills (with the Jack and Jill test), fluid intelligence (with a matrix reasoning test) and music-related perceptual and memory abilities (with listening tests). Of these children, 163 belonged to a music curriculum within the school and 122 to a standard curriculum. Significant differences between students of the music and standard curricula were found in both perceptual and cognitive domains, even when controlling for pre-existing individual differences in musical sophistication. The music children attending the third and last grade of middle school had better performance and showed the largest advantage compared to the control group on both audiovisual working memory and fluid intelligence. Furthermore, some gender differences were found for several tests and across groups in favor of females. The present results indicate that learning to play a musical instrument as part of the middle school curriculum represents a resource for preadolescent education. Even though the current evidence is not sufficient to establish the causality of the found effects, it can still guide future research evaluation with longitudinal data.

Enhancing memory capacity by experimentally slowing theta frequency oscillations using combined EEG-tACS

The coupling of gamma oscillation (~ 40+ Hz) amplitude to the phase of ongoing theta (~ 6 Hz) oscillations has been proposed to be directly relevant for memory performance. Current theories suggest that memory capacity scales with number of gamma cycles that can be fitted into the preferred phase of a theta cycle. Following this logic, transcranial alternating current stimulation (tACS) may be used to adjust theta cycles (increasing/decreasing theta frequency) to decrease or increase memory performance during stimulation. Here, we used individualized EEG-informed theta tACS to (1) experimentally “slow down” individual theta frequency (ITF), (2) evaluate cognitive after effects on a battery of memory and learning tasks, and (3) link the cognitive performance changes to tACS-induced effects on theta-band oscillations as measured by post EEG. We found frequency- and task-specific tACS after effects demonstrating a specific enhancement in memory capacity. This tACS-induced cognitive enhancement was specific to the visual memory task performed immediately after tACS offset, and specific to the ITF-1 Hz (slowing) stimulation condition and thus following a protocol specifically designed to slow down theta frequency to enhance memory capacity. Follow-up correlation analyses in this group linked the enhanced memory performance to increased left frontal-parietal theta-band connectivity. Interestingly, resting-state theta power immediately after tACS offset revealed a theta power increase not for the ITF-1 Hz group, but only for the ITF group where the tACS frequency was ‘optimal’ for entrainment. These results suggest that while individually calibrated tACS at peak frequency maximally modulates resting-state oscillatory power, tACS stimulation slightly below this optimal peak theta frequency is better suited to enhance memory capacity performance. Importantly, our results further suggest that such cognitive enhancement effects can last beyond the period of stimulation and are linked to increased network connectivity, opening the door towards more clinical and applied relevance of using tACS in cognitive rehabilitation and/or neurocognitive enhancement.

Subject-performed task effect on working memory performance in children with autism spectrum disorder

A previous study found that children with autism spectrum disorder (ASD) have better recall when they perform instructions (subject-performed task [SPT]) than when they passively hear instructions (verbal task [VT]) in a working memory task for instructions, an effect that is called the SPT effect. This study explored whether the SPT effect exhibited by ASD children is caused by the movement component or by processing materials twice. More importantly, this study explored whether intelligence influences the SPT effect exhibited by ASD children. ASD children with three levels of intelligence (N = 56) and a control group, children with intellectual disability (ID) who had low intelligence but did not have ASD (N = 21), were asked to perform working memory tasks for instructions under VT, SPT and repeated (hearing the instruction twice) conditions. No significant difference in performance was observed between the VT and repeated conditions, regardless of the child's level of intelligence. ASD children with lower-middle intelligence exhibited a smaller SPT effect than ASD children with upper-middle intelligence. Critically, while ASD children with low intelligence did not exhibit the SPT effect, an ID group with equivalent low intelligence did show this effect. Therefore, these results show that the SPT effect for ASD children is caused by the movement component and is uniquely associated with a certain level of intelligence, namely, lower middle and higher levels of intelligence. LAY SUMMARY: In ASD children, the benefit of physically performing instructions for working memory performance is uniquely associated with a certain level of intelligence. Only ASD children with lower-middle intelligence (and higher) benefit from physically performing instructions, and higher intelligence increases this benefit; ASD children with low intelligence do not show this benefit. This benefit in ASD children is attributed to the additional motoric code generated by physical performance.

Overlapping and dissociable brain activations for fluid intelligence and executive functions

Cognitive enhancement interventions aimed at boosting human fluid intelligence (gf) have targeted executive functions (EFs), such as updating, inhibition, and switching, in the context of transfer-inducing cognitive training. However, even though the link between EFs and gf has been demonstrated at the psychometric level, their neurofunctional overlap has not been quantitatively investigated. Identifying whether and how EFs and gf might share neural activation patterns could provide important insights into the overall hierarchical organization of human higher-order cognition, as well as suggest specific targets for interventions aimed at maximizing cognitive transfer. We present the results of a quantitative meta-analysis of the available fMRI and PET literature on EFs and gf in humans, showing the similarity between gf and (i) the overall global EF network, as well as (ii) specific maps for updating, switching, and inhibition. Results highlight a higher degree of similarity between gf and updating (80% overlap) compared with gf and inhibition (34%), and gf and switching (17%). Moreover, three brain regions activated for both gf and each of the three EFs also were identified, located in the left middle frontal gyrus, left inferior parietal lobule, and anterior cingulate cortex. Finally, resting-state functional connectivity analysis on two independent fMRI datasets showed the preferential behavioural correlation and anatomical overlap between updating and gf. These findings confirm a close link between gf and EFs, with implications for brain stimulation and cognitive training interventions.

The effects of offline and online prefrontal vs parietal transcranial direct current stimulation (tDCS) on verbal and spatial working memory

Working memory (WM) is a limited-capacity system or set of processes that enables temporary storage and manipulation of information essential for complex cognitive processes. The WM performance is supported by a widespread neural network in which fronto-parietal functional connections have a pivotal role. Transcranial direct current stimulation (tDCS) is rapidly emerging as a promising tool for understanding the role of various cortical areas and their functional networks on cognitive performance. Here we comprehensively evaluated the effects of tDCS on WM by conducting three cross-over counterbalanced sham-controlled experiments in which we contrasted the effects and interactions of the anodal (i.e. facilitatory) tDCS across anterior-posterior (i.e. DLPFC vs PPC) and left-right (i.e. the lateralization) axes, and across online and offline protocols using both verbal and spatial WM (3-back) tasks as outcomes. In the offline protocols, left DLPFC stimulation affected neither verbal nor spatial WM, while left PPC stimulation increased spatial WM. When applied offline over right DLPFC, tDCS improved verbal WM task and marginally enhanced spatial WM; while when tDCS was applied over the right PPC, facilitatory effects were observed on verbal WM. In the online protocol, tDCS did not modulate WM regardless of the task modality or stimulation loci. In summary, the study did not replicate the left DLPFC tDCS effect on WM, found in some of the previous studies, but demonstrated positive effects of stimulation of the right DLPFC as well as PPC bilaterally. The observed effects varied across modality of the 3-back task, and tDCS protocol applied. The results of this study argue for moving towards targeting the lesser-explored stimulation sites within the fronto-parietal network, such as PPC, to gain a better understanding of the usefulness of tDCS for WM neuromodulation.

Is the Brixton Spatial Anticipation Test sensitive to frontal dysfunction? Evidence from patients with frontal and posterior lesions

INTRODUCTION

The Brixton Spatial Anticipation Test is a widely used neuropsychological test, thought to assess executive functions and to be sensitive to frontal lobe lesions. Our aim was to investigate Brixton performance in patients with focal frontal or posterior lesions and healthy controls.

METHOD

We compared performance on the Brixton in a sample of 24 frontal patients, 18 posterior patients and 22 healthy controls. Both overall performance (total number of errors) and error types were analyzed.

RESULTS

We found no significant differences between frontal and posterior patients and healthy controls in overall Brixton performance. Moreover, our error analysis showed no difference between frontal patients, posterior patients and healthy controls. The only exception was that posterior patients had a greater tendency to guess and make more errors when following specific rules than healthy controls but this was no longer significant once fluid intelligence was controlled for. We also found no significant difference between the performance of patients with left lateral (n = 11), right lateral (n = 10) or superior medial (n = 18) frontal lesions and healthy controls.

CONCLUSIONS

The Brixton test is not sensitive to frontal lobe dysfunction. It is likely that the test draws on a range of cognitive abilities not specific to frontal lobe lesions. Hence, caution should be taken when drawing conclusions about its neural substrates.

Cognitive reserve attenuates age-related cognitive decline in the context of putatively accelerated brain ageing in schizophrenia-spectrum disorders

BACKGROUND

In schizophrenia, relative stability in the magnitude of cognitive deficits across age and illness duration is inconsistent with the evidence of accelerated deterioration in brain regions known to support these functions. These discrepant brain-cognition outcomes may be explained by variability in cognitive reserve (CR), which in neurological disorders has been shown to buffer against brain pathology and minimize its impact on cognitive or clinical indicators of illness.

METHODS

Age-related change in fluid reasoning, working memory and frontal brain volume, area and thickness were mapped using regression analysis in 214 individuals with schizophrenia or schizoaffective disorder and 168 healthy controls. In patients, these changes were modelled as a function of CR.

RESULTS

Patients showed exaggerated age-related decline in brain structure, but not fluid reasoning compared to controls. In the patient group, no moderation of age-related brain structural change by CR was evident. However, age-related cognitive change was moderated by CR, such that only patients with low CR showed evidence of exaggerated fluid reasoning decline that paralleled the exaggerated age-related deterioration of underpinning brain structures seen in all patients.

CONCLUSIONS

In schizophrenia-spectrum illness, CR may negate ageing effects on fluid reasoning by buffering against pathologically exaggerated structural brain deterioration through some form of compensation. CR may represent an important modifier that could explain inconsistencies in brain structure - cognition outcomes in the extant literature.

Cognitive training in adults with intellectual disability: pilot study applying a cognitive tele-rehabilitation program

INTRODUCTION

This pilot study analyzes the effect of a cognitive training program in adults with intellectual disability (ID).

METHOD

Twenty subjects (mean age 52.7 ± 9.77 years) with mild and moderate ID were divided in control and experimental group. Only the experimental group received the training program. This program was applied through the GNPT® (Guttmann, NeuroPersonalTrainer®) platform for people with ID.

RESULTS

The results revealed a significant improvement in the Kaufman Brief Intelligence Test-2 scores (Matrices subtest) in the experimental group [Z = 2.12; p = .03] after the intervention, indicating an enhancement in fluid ability due to effect of cognitive training program.

CONCLUSION

Findings provide evidence of the importance of applying these programs in a systematized way in adults with ID.

Fluid intelligence is associated with cortical volume and white matter tract integrity within multiple-demand system across adult lifespan

BACKGROUND

Fluid intelligence (Gf) is the innate ability of an individual to respond to complex and unexpected situations. Although some studies have considered that the multiple-demand (MD) system of the brain was the biological foundation for Gf, further characterization of their relationships in the context of aging is limited. The present study hypothesized that the structural metrics of the MD system, including cortical thickness, cortical volumes, and white matter (WM) tract integrity, was the brain correlates for Gf across the adult life span. Partial correlation analysis was performed to investigate whether the MD system could still explain Gf independent of the age effect. Moreover, the partial correlations between Gf and left/right structural metrics within the MD regions were compared to test whether the correlations displayed distinct lateralization.

METHODS

The participants were recruited from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) databank, comprising the images of 603 healthy participants aged 18-88 years acquired on a 3-T system. The MRI data included high-resolution T1-weighted and diffusion-weighted images, from which gray matter and WM structural metrics of the MD system were analyzed, respectively. The structural metrics of gray matter were quantified in terms of cortical volume/thickness of five pairs of cortical regions, and those of WM were quantified in terms of the mean axial diffusivity (D_A), radial diffusivity (D_R), mean diffusivity (D_M), and generalized fractional anisotropy (GFA) on five pairs of tracts. Partial correlation controlling for age and sex effects, was performed to investigate the associations of Gf scores with the mean D_A, D_R, D_M and GFA of all tracts in the MD system, those of left and right hemispheric tracts, and those of each tract. Fisher's exact test was used to compare the partial correlations between left and right MD regions.

RESULTS

The linear relationship between cortical volumes and Gf was evident across all levels of the MD system even after controlling for age and sex. For the WM integrity, diffusion indices including D_A, D_R, D_M and GFA displayed linear relationships with Gf scores at various levels of the MD system. Among the 10 WM tracts connecting the MD regions, bilateral superior longitudinal fasciculus I and bilateral frontal aslant tracts exhibited the strongest and significant associations. Our results did not show significant inter-hemispheric differences in the associations between structural metrics of the MD system and Gf.

CONCLUSION

Our results demonstrate significant associations between Gf and both cortical volumes and tract integrity of the MD system across the adult lifespan in a population-based cohort. We found that the association remained significant in the entire adult lifespan despite simultaneous decline of Gf and the MD system. Our results suggest that the MD system might be a structural underpinning of Gf and support the fronto-parietal model of cognitive aging. However, we did not find hemispheric differences in the Gf-MD correlations, not supporting the hemi-aging hypothesis.

Differential Contribution of Cortical Thickness, Surface Area, and Gyrification to Fluid and Crystallized Intelligence

Human intelligence can be broadly subdivided into fluid (gf) and crystallized (gc) intelligence, each tapping into distinct cognitive abilities. Although neuroanatomical correlates of intelligence have been previously studied, differential contribution of cortical morphologies to gf and gc has not been fully delineated. Here, we tried to disentangle the contribution of cortical thickness, cortical surface area, and cortical gyrification to gf and gc in a large sample of healthy young subjects (n = 740, Human Connectome Project) with high-resolution MRIs, followed by replication in a separate data set with distinct cognitive measures indexing gf and gc. We found that while gyrification in distributed cortical regions had positive association with both gf and gc, surface area and thickness showed more regional associations. Specifically, higher performance in gf was associated with cortical expansion in regions related to working memory, attention, and visuo-spatial processing, while gc was associated with thinner cortex as well as higher cortical surface area in language-related networks. We discuss the results in a framework where "horizontal" cortical expansion enables higher resource allocation, computational capacity, and functional specificity relevant to gf and gc, while lower cortical thickness possibly reflects cortical pruning facilitating "vertical" intracolumnar efficiency in knowledge-based tasks relevant mostly to gc.

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.

Differential functional patterns of the human posterior cingulate cortex during activation and deactivation: a meta-analytic connectivity model

The posterior cingulate cortex (PCC) has been implicated in a host of cognitive and behavioral processes in addition to serving as a central hub in the default mode network (DMN). Moreover, the PCC has been shown to be involved in a range of psychiatric and neurological disorders. However, very little is known about the specific activated/deactivated functional profiles of the PCC. Here, we employed a dual analytic approach using robust quantitative meta-analytical connectivity modeling (MACM) and ultra-high field, high resolution resting state functional magnetic resonance imaging (rs-fMRI) to identify state-specific functional activity patterns of the human PCC. The MACM results provided evidence for regions of convergence for PCC co-activation and co-deactivation (i.e., left medial frontal gyrus, left amygdala, and left anterior cingulate) as well as regions of divergence specific to either PCC activation (i.e., bilateral inferior frontal gyri) or PCC deactivation (i.e., left parahippocampal gyrus). In addition, exploratory MACMs on dorsal and ventral subregions of the PCC revealed differential functional activity patterns such as greater co-activation of the right PCC and left inferior parietal lobule with the dorsal PCC and greater co-activation of right precuneus with the ventral PCC. Resting state connectivity analyses showed widespread connectivity similar to that of the PCC co-activation-based MACM, but also demonstrated additional regions of activity, including bilateral superior parietal regions and right superior temporal regions. These analyses highlight the diverse neurofunctional repertoire of the human PCC, provide additional insight into its dynamic functional activity patterns as it switches between activated and deactivated states, and elucidates the cognitive processes that may be implicated in clinical populations.

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.

Serum levels of insulin-like growth factor-1 and brain-derived neurotrophic factor as potential recovery biomarkers in stroke

OBJECTIVES

Our objectives were: 1) to determine whether maximal aerobic exercise increased serum neurotrophins in chronic stroke and 2) to determine the factors that predict resting and exercise-dependent levels.

METHODS

We investigated the potential predictors of resting and exercise-dependent serum insulin-like growth factor-1 and brain-derived neurotrophic factor among 35 chronic stroke patients. Predictors from three domains (demographic, disease burden, and cardiometabolic) were entered into 4 separate stepwise linear regression models with outcome variables: resting insulin-like growth factor, resting brain-derived neurotrophic factor, exercise-dependent change in insulin-like growth factor, and exercise-dependent change brain-derived neurotrophic factor.

RESULTS

Insulin-like growth factor decreased after exercise (p = 0.001) while brain-derived neurotrophic factor did not change (p = 0.38). Greater lower extremity impairment predicted higher resting brain-derived neurotrophic factor (p = 0.004, r² = 0.23). Higher fluid intelligence predicted greater brain-derived neurotrophic factor response to exercise (p = 0.01, r² = 0.18). There were no significant predictors of resting or percent change insulin-like growth factor-1.

DISCUSSION

Biomarkers have the potential to characterize an individual's potential for recovery from stroke. Neurotrophins such as insulin-like growth factor-1 and brain-derived neurotrophic factor are thought to be important in neurorehabilitation; however, the factors that modulate these biomarkers are not well understood. Resting brain-derived neurotrophic factor and percent change in brain-derived neurotrophic factor were related to physical and cognitive recovery in chronic stroke, albeit weakly. Insulin-like growth factor-1 was not an informative biomarker among chronic stroke patients. The novel finding that fluid intelligence positively correlated with exercise-induced change in brain-derived neurotrophic factor warrants further research.

Relationship of Working Memory, Processing Speed, and Fluid Reasoning in Psychiatric Patients

OBJECTIVE

The present study aimed to investigate relationship among cognitive factors (working memory and processing speed) and fluid reasoning (Gf) in psychiatric patients using a standardized clinical tool.

METHODS

We included the responses of 115 heterogeneous patients who were diagnosed with the MINI-Plus 5.0 and WAIS-IV/WMSIV was administered. For our analysis, structured equation modeling (SEM) was conducted to evaluate which cognitive variables are closely related to the Gf.

RESULTS

The results showed that the visual working memory was the strongest predictor of the Gf compared to other cognitive factors.

CONCLUSION

Processing speed was capable of predicting the Gf, when visual working memory was controlled. The inter-relationship among the Gf and other cognitive factors and its clinical implications were further discussed.

Changes in discourse structure over time following traumatic brain injury

The objective of the present study was to investigate structural changes in the narrative discourse of individuals with penetrating traumatic brain injury (pTBI) following immediate and delayed story retellings. Additionally, the potential influence of immediate memory, working memory, and executive functions on narrative discourse performance were examined. The narrative discourse of two groups, 123 with pTBI and 44 non-brain injured (NBI), was sampled. Participants were asked to retell a wordless picture story immediately after viewing it and again 30-min later. Story narratives were analyzed using a variety of microlinguistic and macrostructural measures. Results revealed significant group differences of both microlinguistic and macrostructural measures following the immediate retell, but not following the delayed retell. Regression analyses revealed that immediate memory accounted for a modest degree of the explained variance for the production of critical content during narrative discourse. The observed deficits were relatively stable over a short delay (30 min) and appeared attributable, in part, to difficulty with the encoding and consolidation of story content.

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.

Task-induced brain state manipulation improves prediction of individual traits

Recent work has begun to relate individual differences in brain functional organization to human behaviors and cognition, but the best brain state to reveal such relationships remains an open question. In two large, independent data sets, we here show that cognitive tasks amplify trait-relevant individual differences in patterns of functional connectivity, such that predictive models built from task fMRI data outperform models built from resting-state fMRI data. Further, certain tasks consistently yield better predictions of fluid intelligence than others, and the task that generates the best-performing models varies by sex. By considering task-induced brain state and sex, the best-performing model explains over 20% of the variance in fluid intelligence scores, as compared to <6% of variance explained by rest-based models. This suggests that identifying and inducing the right brain state in a given group can better reveal brain-behavior relationships, motivating a paradigm shift from rest- to task-based functional connectivity analyses.

Damage to the left uncinate fasciculus is associated with heightened schizotypal traits: A multimodal lesion-mapping study

A growing body of evidence suggests that individuals with pronounced schizotypal traits also display particular neurophysiological and morphological features - notably with regard to left frontotemporal connectivity. However, the studies published to date have focused on subclinical subjects and psychiatric patients, rather than brain-damaged patients. Here, we used the French version of the Schizotypal Personality Questionnaire to assess schizotypal traits in a sample of 97 patients having undergone surgical resection of a diffuse low-grade glioma. Patients having received other neurooncological treatments (including chemotherapy and radiotherapy) were not included. A combination of ROI-based based voxel-wise and tract-wise lesion-symptom mapping and a disconnectome analysis were performed, in order to identify the putative neural network associated with schizotypy. The ROI-based lesion-symptom mapping revealed a significant relationship between the cognitive-perceptual (positive) dimension of schizotypy and the left inferior gyrus (including the pars opercularis and the pars orbitalis). Importantly, we found that disconnection of the left uncinate fasciculus (UF) was a powerful predictor of the positive dimension of schizotypy. Lastly, the disconnection analysis indicated that the positive dimension of schizotypy was significantly associated with the white matter fibres deep in the left orbital and inferior frontal gyri and the left superior temporal pole, which mainly correspond to the spatial topography of the left UF. Taken as a whole, our results suggest that dysconnectivity of the neural network supplied by the left UF is associated with heightened positive schizotypal traits. Our new findings may be of value in interpreting current research in the field of biological psychiatry.

Double dissociation of structure-function relationships in memory and fluid intelligence observed with magnetic resonance elastography

Brain tissue mechanical properties, measured in vivo with magnetic resonance elastography (MRE), have proven to be sensitive metrics of neural tissue integrity. Recently, our group has reported on the positive relationship between viscoelasticity of the hippocampus and performance on a relational memory task in healthy young adults, which highlighted the potential of sensitive MRE measures for studying brain health and its relation to cognitive function; however, structure-function relationships outside of the hippocampus have not yet been explored. In this study, we examined the relationships between viscoelasticity of both the hippocampus and the orbitofrontal cortex and performance on behavioral assessments of relational memory and fluid intelligence. In a sample of healthy, young adults (N = 53), there was a significant, positive relationship between orbitofrontal cortex viscoelasticity and fluid intelligence performance (r = 0.42; p = .002). This finding is consistent with the previously reported relationship between hippocampal viscoelasticity and relational memory performance (r = 0.41; p = .002). Further, a significant double dissociation between the orbitofrontal-fluid intelligence relationship and the hippocampal-relational memory relationship was observed. These data support the specificity of regional brain MRE measures in support of separable cognitive functions. This report of a structure-function relationship observed with MRE beyond the hippocampus suggests a future role for MRE as a sensitive neuroimaging technique for brain mapping.

Neural mechanisms of two different verbal working memory tasks: A VLSM study

Currently, a distributed bilateral network of frontal-parietal areas is regarded as the neural substrate of working memory (WM), with the verbal WM network being more left-lateralized. This conclusion is based primarily on functional magnetic resonance imaging (fMRI) data that provides correlational evidence for brain regions involved in a task. However, fMRI cannot differentiate the areas that are fundamentally required for performing a task. These data can only come from brain-injured individuals who fail the task after the loss of specific brain areas. In addition to the lack of complimentary data, is the issue of the variety in the WM tasks used to assess verbal WM. When different tasks are assumed to measure the same behavior, this may mask the contributions of different brain regions. Here, we investigated the neural substrate of WM by using voxel-based lesion symptom mapping (VLSM) in 49 individuals with stroke-induced left hemisphere brain injuries. These participants completed two different verbal WM tasks: complex listening span and a word 2-back task. Behavioral results indicated that the two tasks were only slightly related, while the VLSM analysis revealed different critical regions associated with each task. Specifically, significant detriments in performance on the complex span task were found with lesions in the inferior frontal gyrus, while for the 2-back task, significant deficits were seen after injury to the superior and middle temporal gyri. Thus, the two tasks depend on the structural integrity of different, non-overlapping frontal and temporal brain regions, suggesting distinct neural and cognitive mechanisms triggered by the two tasks: rehearsal and cue-dependent selection in the complex span task, versus updating/auditory recognition in the 2-back task. These findings call into question the common practice of using these two tasks interchangeably in verbal WM research and undermine the legitimacy of aggregating data from studies with different WM tasks. Thus, the present study points out the importance of lesion studies in complementing functional neuroimaging findings and highlights the need to consider task demands in neuroimaging and neuropsychological investigations of WM.

Socioeconomic disparities and sexual dimorphism in neurotoxic effects of ambient fine particles on youth IQ: A longitudinal analysis

Mounting evidence indicates that early-life exposure to particulate air pollutants pose threats to children's cognitive development, but studies about the neurotoxic effects associated with exposures during adolescence remain unclear. We examined whether exposure to ambient fine particles (PM2.5) at residential locations affects intelligence quotient (IQ) during pre-/early- adolescence (ages 9-11) and emerging adulthood (ages 18-20) in a demographically-diverse population (N = 1,360) residing in Southern California. Increased ambient PM2.5 levels were associated with decreased IQ scores. This association was more evident for Performance IQ (PIQ), but less for Verbal IQ, assessed by the Wechsler Abbreviated Scale of Intelligence. For each inter-quartile (7.73 μg/m3) increase in one-year PM2.5 preceding each assessment, the average PIQ score decreased by 3.08 points (95% confidence interval = [-6.04, -0.12]) accounting for within-family/within-individual correlations, demographic characteristics, family socioeconomic status (SES), parents' cognitive abilities, neighborhood characteristics, and other spatial confounders. The adverse effect was 150% greater in low SES families and 89% stronger in males, compared to their counterparts. Better understanding of the social disparities and sexual dimorphism in the adverse PM2.5-IQ effects may help elucidate the underlying mechanisms and shed light on prevention strategies.

Network Neuroscience Theory of Human Intelligence

An enduring aim of research in the psychological and brain sciences is to understand the nature of individual differences in human intelligence, examining the stunning breadth and diversity of intellectual abilities and the remarkable neurobiological mechanisms from which they arise. This Opinion article surveys recent neuroscience evidence to elucidate how general intelligence, g, emerges from individual differences in the network architecture of the human brain. The reviewed findings motivate new insights about how network topology and dynamics account for individual differences in g, represented by the Network Neuroscience Theory. According to this framework, g emerges from the small-world topology of brain networks and the dynamic reorganization of its community structure in the service of system-wide flexibility and adaptation.