APC7 mediates ubiquitin signaling in constitutive heterochromatin in the developing mammalian brain.

Neurodevelopmental cognitive disorders provide insights into mechanisms of human brain development. Here, we report an intellectual disability syndrome caused by the loss of APC7, a core component of the E3 ubiquitin ligase anaphase promoting complex (APC). In mechanistic studies, we uncover a critical role for APC7 during the recruitment and ubiquitination of APC substrates. In proteomics analyses of the brain from mice harboring the patient-specific APC7 mutation, we identify the chromatin-associated protein Ki-67 as an APC7-dependent substrate of the APC in neurons. Conditional knockout of the APC coactivator protein Cdh1, but not Cdc20, leads to the accumulation of Ki-67 protein in neurons in vivo, suggesting that APC7 is required for the function of Cdh1-APC in the brain. Deregulated neuronal Ki-67 upon APC7 loss localizes predominantly to constitutive heterochromatin. Our findings define an essential function for APC7 and Cdh1-APC in neuronal heterochromatin regulation, with implications for understanding human brain development and disease.

Expertise increases planning depth in human gameplay.

A hallmark of human intelligence is the ability to plan multiple steps into the future1,2. Despite decades of research3-5, it is still debated whether skilled decision-makers plan more steps ahead than novices6-8. Traditionally, the study of expertise in planning has used board games such as chess, but the complexity of these games poses a barrier to quantitative estimates of planning depth. Conversely, common planning tasks in cognitive science often have a lower complexity9,10 and impose a ceiling for the depth to which any player can plan. Here we investigate expertise in a complex board game that offers ample opportunity for skilled players to plan deeply. We use model fitting methods to show that human behaviour can be captured using a computational cognitive model based on heuristic search. To validate this model, we predict human choices, response times and eye movements. We also perform a Turing test and a reconstruction experiment. Using the model, we find robust evidence for increased planning depth with expertise in both laboratory and large-scale mobile data. Experts memorize and reconstruct board features more accurately. Using complex tasks combined with precise behavioural modelling might expand our understanding of human planning and help to bridge the gap with progress in artificial intelligence.

Sleep Spindles: Mechanisms and Functions.

Sleep spindles are burstlike signals in the electroencephalogram (EEG) of the sleeping mammalian brain and electrical surface correlates of neuronal oscillations in thalamus. As one of the most inheritable sleep EEG signatures, sleep spindles probably reflect the strength and malleability of thalamocortical circuits that underlie individual cognitive profiles. We review the characteristics, organization, regulation, and origins of sleep spindles and their implication in non-rapid-eye-movement sleep (NREMS) and its functions, focusing on human and rodent. Spatially, sleep spindle-related neuronal activity appears on scales ranging from small thalamic circuits to functional cortical areas, and generates a cortical state favoring intracortical plasticity while limiting cortical output. Temporally, sleep spindles are discrete events, part of a continuous power band, and elements grouped on an infraslow time scale over which NREMS alternates between continuity and fragility. We synthesize diverse and seemingly unlinked functions of sleep spindles for sleep architecture, sensory processing, synaptic plasticity, memory formation, and cognitive abilities into a unifying sleep spindle concept, according to which sleep spindles 1) generate neural conditions of large-scale functional connectivity and plasticity that outlast their appearance as discrete EEG events, 2) appear preferentially in thalamic circuits engaged in learning and attention-based experience during wakefulness, and 3) enable a selective reactivation and routing of wake-instated neuronal traces between brain areas such as hippocampus and cortex. Their fine spatiotemporal organization reflects NREMS as a physiological state coordinated over brain and body and may indicate, if not anticipate and ultimately differentiate, pathologies in sleep and neurodevelopmental, -degenerative, and -psychiatric conditions.

Genome-wide detection of tandem DNA repeats that are expanded in autism.

Tandem DNA repeats vary in the size and sequence of each unit (motif). When expanded, these tandem DNA repeats have been associated with more than 40 monogenic disorders1. Their involvement in disorders with complex genetics is largely unknown, as is the extent of their heterogeneity. Here we investigated the genome-wide characteristics of tandem repeats that had motifs with a length of 2-20 base pairs in 17,231 genomes of families containing individuals with autism spectrum disorder (ASD)2,3 and population control individuals4. We found extensive polymorphism in the size and sequence of motifs. Many of the tandem repeat loci that we detected correlated with cytogenetic fragile sites. At 2,588 loci, gene-associated expansions of tandem repeats that were rare among population control individuals were significantly more prevalent among individuals with ASD than their siblings without ASD, particularly in exons and near splice junctions, and in genes related to the development of the nervous system and cardiovascular system or muscle. Rare tandem repeat expansions had a prevalence of 23.3% in children with ASD compared with 20.7% in children without ASD, which suggests that tandem repeat expansions make a collective contribution to the risk of ASD of 2.6%. These rare tandem repeat expansions included previously undescribed ASD-linked expansions in DMPK and FXN, which are associated with neuromuscular conditions, and in previously unknown loci such as FGF14 and CACNB1. Rare tandem repeat expansions were associated with lower IQ and adaptive ability. Our results show that tandem DNA repeat expansions contribute strongly to the genetic aetiology and phenotypic complexity of ASD.

Automating hybrid collective intelligence in open-ended medical diagnostics.

Collective intelligence has emerged as a powerful mechanism to boost decision accuracy across many domains, such as geopolitical forecasting, investment, and medical diagnostics. However, collective intelligence has been mostly applied to relatively simple decision tasks (e.g., binary classifications). Applications in more open-ended tasks with a much larger problem space, such as emergency management or general medical diagnostics, are largely lacking, due to the challenge of integrating unstandardized inputs from different crowd members. Here, we present a fully automated approach for harnessing collective intelligence in the domain of general medical diagnostics. Our approach leverages semantic knowledge graphs, natural language processing, and the SNOMED CT medical ontology to overcome a major hurdle to collective intelligence in open-ended medical diagnostics, namely to identify the intended diagnosis from unstructured text. We tested our method on 1,333 medical cases diagnosed on a medical crowdsourcing platform: The Human Diagnosis Project. Each case was independently rated by ten diagnosticians. Comparing the diagnostic accuracy of single diagnosticians with the collective diagnosis of differently sized groups, we find that our method substantially increases diagnostic accuracy: While single diagnosticians achieved 46% accuracy, pooling the decisions of ten diagnosticians increased this to 76%. Improvements occurred across medical specialties, chief complaints, and diagnosticians' tenure levels. Our results show the life-saving potential of tapping into the collective intelligence of the global medical community to reduce diagnostic errors and increase patient safety.

Incentivizing free riders improves collective intelligence in social dilemmas.

Collective intelligence challenges are often entangled with collective action problems. For example, voting, rating, and social innovation are collective intelligence tasks that require costly individual contributions. As a result, members of a group often free ride on the information contributed by intrinsically motivated people. Are intrinsically motivated agents the best participants in collective decisions? We embedded a collective intelligence task in a large-scale, virtual world public good game and found that participants who joined the information system but were reluctant to contribute to the public good (free riders) provided more accurate evaluations, whereas participants who rated frequently underperformed. Testing the underlying mechanism revealed that a negative rating bias in free riders is associated with higher accuracy. Importantly, incentivizing evaluations amplifies the relative influence of participants who tend to free ride without altering the (higher) quality of their evaluations, thereby improving collective intelligence. These results suggest that many of the currently available information systems, which strongly select for intrinsically motivated participants, underperform and that collective intelligence can benefit from incentivizing free riding members to engage. More generally, enhancing the diversity of contributor motivations can improve collective intelligence in settings that are entangled with collective action problems.

Neonatal Docosahexaenoic Acid in Preterm Infants and Intelligence at 5 Years.

BACKGROUND: Docosahexaenoic acid (DHA) is a component of neural tissue. Because its accretion into the brain is greatest during the final trimester of pregnancy, infants born before 29 weeks' gestation do not receive the normal supply of DHA. The effect of this deficiency on subsequent cognitive development is not well understood. METHODS: We assessed general intelligence at 5 years in children who had been enrolled in a trial of neonatal DHA supplementation to prevent bronchopulmonary dysplasia. In the previous trial, infants born before 29 weeks' gestation had been randomly assigned in a 1:1 ratio to receive an enteral emulsion that provided 60 mg of DHA per kilogram of body weight per day or a control emulsion from the first 3 days of enteral feeds until 36 weeks of postmenstrual age or discharge home, whichever occurred first. Children from 5 of the 13 centers in the original trial were invited to undergo assessment with the Wechsler Preschool and Primary Scale of Intelligence (WPPSI) at 5 years of corrected age. The primary outcome was the full-scale intelligence quotient (FSIQ) score. Secondary outcomes included the components of WPPSI. RESULTS: A total of 1273 infants underwent randomization in the original trial; of the 656 surviving children who had undergone randomization at the centers included in this follow-up study, 480 (73%) had an FSIQ score available - 241 in the DHA group and 239 in the control group. After imputation of missing data, the mean (±SD) FSIQ scores were 95.4±17.3 in the DHA group and 91.9±19.1 in the control group (adjusted difference, 3.45; 95% confidence interval, 0.38 to 6.53; P = 0.03). The results for secondary outcomes generally did not support that obtained for the primary outcome. Adverse events were similar in the two groups. CONCLUSIONS: In infants born before 29 weeks' gestation who had been enrolled in a trial to assess the effect of DHA supplementation on bronchopulmonary dysplasia, the use of an enteral DHA emulsion until 36 weeks of postmenstrual age was associated with modestly higher FSIQ scores at 5 years of age than control feeding. (Funded by the Australian National Health and Medical Research Council and Nu-Mega Ingredients; N3RO Australian New Zealand Clinical Trials Registry number, ACTRN12612000503820.).

Computer gaming alters resting-state brain networks, enhancing cognitive and fluid intelligence in players: evidence from brain imaging-derived phenotypes-wide Mendelian randomization.

The debate on whether computer gaming enhances players' cognitive function is an ongoing and contentious issue. Aiming to delve into the potential impacts of computer gaming on the players' cognitive function, we embarked on a brain imaging-derived phenotypes (IDPs)-wide Mendelian randomization (MR) study, utilizing publicly available data from a European population. Our findings indicate that computer gaming has a positive impact on fluid intelligence (odds ratio [OR] = 6.264, P = 4.361 × 10-10, 95% confidence interval [CI] 3.520-11.147) and cognitive function (OR = 3.322, P = 0.002, 95% CI 1.563-7.062). Out of the 3062 brain IDPs analyzed, only one phenotype, IDP NET100 0378, was significantly influenced by computer gaming (OR = 4.697, P = 1.10 × 10-5, 95% CI 2.357-9.361). Further MR analysis suggested that alterations in the IDP NET100 0378 caused by computer gaming may be a potential factor affecting fluid intelligence (OR = 1.076, P = 0.041, 95% CI 1.003-1.153). Our MR study lends support to the notion that computer gaming can facilitate the development of players' fluid intelligence by enhancing the connectivity between the motor cortex in the resting-state brain and key regions such as the left dorsolateral prefrontal cortex and the language center.

Stable individual differences from dynamic patterns of function: brain network flexibility predicts openness/intellect, intelligence, and psychoticism.

A growing understanding of the nature of brain function has led to increased interest in interpreting the properties of large-scale brain networks. Methodological advances in network neuroscience provide means to decompose these networks into smaller functional communities and measure how they reconfigure over time as an index of their dynamic and flexible properties. Recent evidence has identified associations between flexibility and a variety of traits pertaining to complex cognition including creativity and working memory. The present study used measures of dynamic resting-state functional connectivity in data from the Human Connectome Project (n = 994) to test associations with Openness/Intellect, general intelligence, and psychoticism, three traits that involve flexible cognition. Using a machine-learning cross-validation approach, we identified reliable associations of intelligence with cohesive flexibility of parcels in large communities across the cortex, of psychoticism with disjoint flexibility, and of Openness/Intellect with overall flexibility among parcels in smaller communities. These findings are reasonably consistent with previous theories of the neural correlates of these traits and help to expand on previous associations of behavior with dynamic functional connectivity, in the context of broad personality dimensions.

The Moral Psychology of Artificial Intelligence.

Moral psychology was shaped around three categories of agents and patients: humans, other animals, and supernatural beings. Rapid progress in artificial intelligence has introduced a fourth category for our moral psychology to deal with: intelligent machines. Machines can perform as moral agents, making decisions that affect the outcomes of human patients or solving moral dilemmas without human supervision. Machines can be perceived as moral patients, whose outcomes can be affected by human decisions, with important consequences for human-machine cooperation. Machines can be moral proxies that human agents and patients send as their delegates to moral interactions or use as a disguise in these interactions. Here we review the experimental literature on machines as moral agents, moral patients, and moral proxies, with a focus on recent findings and the open questions that they suggest.

Expanding the phenotype of Kleefstra syndrome: speech, language and cognition in 103 individuals.

OBJECTIVES: Speech and language impairments are core features of the neurodevelopmental genetic condition Kleefstra syndrome. Communication has not been systematically examined to guide intervention recommendations. We define the speech, language and cognitive phenotypic spectrum in a large cohort of individuals with Kleefstra syndrome. METHOD: 103 individuals with Kleefstra syndrome (40 males, median age 9.5 years, range 1-43 years) with pathogenic variants (52 9q34.3 deletions, 50 intragenic variants, 1 balanced translocation) were included. Speech, language and non-verbal communication were assessed. Cognitive, health and neurodevelopmental data were obtained. RESULTS: The cognitive spectrum ranged from average intelligence (12/79, 15%) to severe intellectual disability (12/79, 15%). Language ability also ranged from average intelligence (10/90, 11%) to severe intellectual disability (53/90, 59%). Speech disorders occurred in 48/49 (98%) verbal individuals and even occurred alongside average language and cognition. Developmental regression occurred in 11/80 (14%) individuals across motor, language and psychosocial domains. Communication aids, such as sign and speech-generating devices, were crucial for 61/103 (59%) individuals including those who were minimally verbal, had a speech disorder or following regression. CONCLUSIONS: The speech, language and cognitive profile of Kleefstra syndrome is broad, ranging from severe impairment to average ability. Genotype and age do not explain the phenotypic variability. Early access to communication aids may improve communication and quality of life.

Twisting for soft intelligent autonomous robot in unstructured environments.

Soft robots that can harvest energy from environmental resources for autonomous locomotion is highly desired; however, few are capable of adaptive navigation without human interventions. Here, we report twisting soft robots with embodied physical intelligence for adaptive, intelligent autonomous locomotion in various unstructured environments, without on-board or external controls and human interventions. The soft robots are constructed of twisted thermal-responsive liquid crystal elastomer ribbons with a straight centerline. They can harvest thermal energy from environments to roll on outdoor hard surfaces and challenging granular substrates without slip, including ascending loose sandy slopes, crossing sand ripples, escaping from burying sand, and crossing rocks with additional camouflaging features. The twisting body provides anchoring functionality by burrowing into loose sand. When encountering obstacles, they can either self-turn or self-snap for obstacle negotiation and avoidance. Theoretical models and finite element simulation reveal that such physical intelligence is achieved by spontaneously snapping-through its soft body upon active and adaptive soft body-obstacle interactions. Utilizing this strategy, they can intelligently escape from confined spaces and maze-like obstacle courses without any human intervention. This work presents a de novo design of embodied physical intelligence by harnessing the twisting geometry and snap-through instability for adaptive soft robot-environment interactions.

Comparing the reliability and predictive power of child, teacher, and guardian reports of noncognitive skills.

Children's noncognitive or socioemotional skills (e.g., persistence and self-control) are typically measured using surveys in which either children rate their own skills or adults rate the skills of children. For many purposes-including program evaluation and monitoring school systems-ratings are often collected from multiple perspectives about a single child (e.g., from both the child and an adult). Collecting data from multiple perspectives is costly, and there is limited evidence on the benefits of this approach. Using a longitudinal survey, this study compares children's noncognitive skills as reported by themselves, their guardians, and their teachers. Although reports from all three types of respondents are correlated with each other, teacher reports have the highest internal consistency and are the most predictive of children's later cognitive outcomes and behavior in school. The teacher reports add predictive power beyond baseline measures of Intelligence Quotient (IQ) for most outcomes in schools. Measures collected from children and guardians add minimal predictive power beyond the teacher reports.

Signatures of adaptive evolution in platyrrhine primate genomes.

The platyrrhine family Cebidae (capuchin and squirrel monkeys) exhibit among the largest primate encephalization quotients. Each cebid lineage is also characterized by notable lineage-specific traits, with capuchins showing striking similarities to Hominidae such as high sensorimotor intelligence with tool use, advanced cognitive abilities, and behavioral flexibility. Here, we take a comparative genomics approach, performing genome-wide tests for positive selection across five cebid branches, to gain insight into major periods of cebid adaptive evolution. We uncover candidate targets of selection across cebid evolutionary history that may underlie the emergence of lineage-specific traits. Our analyses highlight shifting and sustained selective pressures on genes related to brain development, longevity, reproduction, and morphology, including evidence for cumulative and diversifying neurobiological adaptations across cebid evolution. In addition to generating a high-quality reference genome assembly for robust capuchins, our results lend to a better understanding of the adaptive diversification of this distinctive primate clade.

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.

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.

Is cancer an intelligent species?

Some relevant emerging properties of intelligent systems are "adaptation to a changing environment," "reaction to unexpected situations," "capacity of problem solving," and "ability to communicate." Single cells have remarkable abilities to adapt, make adequate context-dependent decision, take constructive actions, and communicate, thus theoretically meeting all the above-mentioned requirements. From a biological point of view, cancer can be viewed as an invasive species, composed of cells that move from primary to distant sites, being continuously exposed to changes in the environmental conditions. Blood represents the first hostile habitat that a cancer cell encounters once detached from the primary site, so that cancer cells must rapidly carry out multiple adaptation strategies to survive. The aim of this review was to deepen the adaptation mechanisms of cancer cells in the blood microenvironment, particularly referring to four adaptation strategies typical of animal species (phenotypic adaptation, metabolic adaptation, niche adaptation, and collective adaptation), which together define the broad concept of biological intelligence. We provided evidence that the required adaptations (either structural, metabolic, and related to metastatic niche formation) and "social" behavior are useful principles allowing putting into a coherent frame many features of circulating cancer cells. This interpretative frame is described by the comparison with analog behavioral traits typical of various animal models.

Comparison of approaches to control for intracranial volume in research on the association of brain volumes with cognitive outcomes.

Most neuroimaging studies linking regional brain volumes with cognition correct for total intracranial volume (ICV), but methods used for this correction differ across studies. It is unknown whether different ICV correction methods yield consistent results. Using a brain-wide association approach in the MRI substudy of UK Biobank (N = 41,964; mean age = 64.5 years), we used regression models to estimate the associations of 58 regional brain volumetric measures with eight cognitive outcomes, comparing no correction and four ICV correction approaches. Approaches evaluated included: no correction; dividing regional volumes by ICV (proportional approach); including ICV as a covariate in the regression (adjustment approach); and regressing the regional volumes against ICV in different normative samples and using calculated residuals to determine associations (residual approach). We used Spearman-rank correlations and two consistency measures to quantify the extent to which associations were inconsistent across ICV correction approaches for each possible brain region and cognitive outcome pair across 2320 regression models. When the association between brain volume and cognitive performance was close to null, all approaches produced similar estimates close to the null. When associations between a regional volume and cognitive test were not null, the adjustment and residual approaches typically produced similar estimates, but these estimates were inconsistent with results from the crude and proportional approaches. For example, when using the crude approach, an increase of 0.114 (95% confidence interval [CI]: 0.103-0.125) in fluid intelligence was associated with each unit increase in hippocampal volume. However, when using the adjustment approach, the increase was 0.055 (95% CI: 0.043-0.068), while the proportional approach showed a decrease of -0.025 (95% CI: -0.035 to -0.014). Different commonly used methods to correct for ICV yielded inconsistent results. The proportional method diverges notably from other methods and results were sometimes biologically implausible. A simple regression adjustment for ICV produced biologically plausible associations.

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.