Brain Structural Networks Associated with Intelligence and Visuomotor Ability

Cognitive Polygenic Index is Associated with Occupational Complexity over and above Brain Morphometry

Although the impact of occupation on cognitive skills has been extensively studied, there is limited research examining if genetically predicted cognitive score may influence occupation. We examined the association between Cognitive Polygenic Index (PGI) and occupation, including the role of brain measures. Participants were recruited for the Reference Ability Neural Network and the Cognitive Reserve studies. Occupational complexity ratings for Data, People, or Things came from the Dictionary of Occupational Titles. A previously-created Cognitive PGI and linear regression models were used for the analyses. Age, sex, education, and the first 20 genetic Principal Components (PCs) of the sample were covariates. Total cortical thickness and total gray matter volume were further covariates. We included 168 white-ethnicity participants, 20-80 years old. After initial adjustment, higher Cognitive PGI was associated with higher Data complexity (B=-0.526, SE = 0.227, Beta= -0.526 p = 0.022, R2 = 0.259) (lower score implies higher complexity). Associations for People or Things were not significant. After adding brain measures, association for Data remained significant (B=-0.496, SE: 0.245, Beta= -0.422, p = 0.045, R2 = 0.254). Similarly, for a further, fully-adjusted analysis including all the three occupational complexity measures (B=-0.568, SE = 0.237, Beta= -0.483, p = 0.018, R2 = 0.327). Cognitive genes were associated with occupational complexity over and above brain morphometry. Working with Data occupational complexity probably acquires higher cognitive status, which can be significantly genetically predetermined.

Recent breakthroughs in understanding the cerebellum's role in fetal alcohol spectrum disorder: A systematic review

Exposure to alcohol during fetal development can lead to structural and functional abnormalities in the cerebellum, a brain region responsible for motor coordination, balance, and specific cognitive functions. In this systematic review, we comprehensively analyze a vast body of research conducted on vertebrate animals and humans over the past 13 years. We identified studies through PubMed and screened them following PRISMA guidelines. Data extraction and quality analysis were conducted using Covidence systematic review software. A total of 108 studies met our inclusion criteria, with the majority (79 studies) involving vertebrate animal models and 29 studies focusing on human subjects. Animal models included zebrafish, mice, rats, sheep, and non-human primates, investigating the impact of ethanol on cerebellar structure, gene/protein expression, physiology, and cerebellar-dependent behaviors. Additionally, some animal studies explored potential therapeutic interventions against ethanol-induced cerebellar damage. The human studies predominantly adopted cohort designs, exploring the effects of prenatal alcohol exposure on cerebellar structure and function. Certain human studies delved into innovative cerebellar-based diagnostic approaches for fetal alcohol spectrum disorder (FASD). The collective findings from these studies clearly indicate that the cerebellum is involved in various neurophysiological deficits associated with FASD, emphasizing the importance of evaluating both cerebellar structure and function in the diagnostic process for this condition. Moreover, this review sheds light into potential therapeutic strategies that can mitigate prenatal alcohol exposure-induced cerebellar damage.

Evaluating the associations between intelligence quotient and multi-tissue proteome from the brain, CSF and plasma

Intelligence quotient is a vital index to evaluate the ability of an individual to think rationally, learn from experience and deal with the environment effectively. However, limited efforts have been paid to explore the potential associations of intelligence quotient traits with the tissue proteins from the brain, CSF and plasma. The information of protein quantitative trait loci was collected from a recently released genome-wide association study conducted on quantification data of proteins from the tissues including the brain, CSF and plasma. Using the individual-level genotypic data from the UK Biobank cohort, we calculated the polygenic risk scores for each protein based on the protein quantitative trait locus data sets above. Then, Pearson correlation analysis was applied to evaluate the relationships between intelligence quotient traits (including 120 330 subjects for 'fluid intelligence score' and 38 949 subjects for 'maximum digits remembered correctly') and polygenic risk scores of each protein in the brain (17 protein polygenic risk scores), CSF (116 protein polygenic risk scores) and plasma (59 protein polygenic risk scores). The Bonferroni corrected P-value threshold was P < 1.30 × 10-4 (0.05/384). Finally, Mendelian randomization analysis was conducted to test the causal relationships between 'fluid intelligence score' and pre-specific proteins from correlation analysis results. Pearson correlation analysis identified significant association signals between the protein of macrophage-stimulating protein and fluid intelligence in brain and CSF tissues (P brain = 1.21 × 10-8, P CSF = 1.10 × 10-7), as well as between B-cell lymphoma 6 protein and fluid intelligence in CSF (P CSF = 1.23 × 10-4). Other proteins showed close-to-significant associations with the trait of 'fluid intelligence score', such as plasma protease C1 inhibitor (P CSF = 4.19 × 10-4, P plasma = 6.97 × 10-4), and with the trait of 'maximum digits remembered correctly', such as tenascin (P plasma = 3.42 × 10-4). Additionally, Mendelian randomization analysis results suggested that macrophage-stimulating protein (Mendelian randomization-Egger: β = 0.54, P = 1.64 × 10-61 in the brain; β = 0.09, P = 1.60 × 10-12 in CSF) had causal effects on fluid intelligence score. We observed functional relevance of specific tissue proteins to intelligence quotient and identified several candidate proteins, such as macrophage-stimulating protein. This study provided a novel insight to the relationship between tissue proteins and intelligence quotient traits.

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.

Evaluation of behavioral variance/covariance explained by the neuroimaging data through a pattern-based regression

Neuroimaging data have been widely used to understand the neural bases of human behaviors. However, most studies were either based on a few predefined regions of interest or only able to reveal limited vital regions, hence not providing an overarching description of the relationship between neuroimaging and behaviors. Here, we proposed a voxel-based pattern regression that not only could investigate the overall brain-associated variance (BAV) for a given behavioral measure but could also evaluate the shared neural bases between different behaviors across multiple neuroimaging data. The proposed method demonstrated consistently high reliability and accuracy through comprehensive simulations. We further implemented this approach on real data of adolescents (IMAGEN project, n = 2089) and adults (HCP project, n = 808) to investigate brain-based variances of multiple behavioral measures, for instance, cognitive behaviors, substance use, and psychiatric disorders. Notably, intelligence-related scores showed similar high BAVs with the gray matter volume across both datasets. Further, our approach allows us to reveal the latent brain-based correlation across multiple behavioral measures, which are challenging to obtain otherwise. For instance, we observed a shared brain architecture underlying depression and externalizing problems in adolescents, while the symptom comorbidity may only emerge later in adults. Overall, our approach will provide an important statistical tool for understanding human behaviors using neuroimaging data.

Improved estimation of general cognitive ability and its neural correlates with a large battery of cognitive tasks

Elucidating the neural mechanisms of general cognitive ability (GCA) is an important mission of cognitive neuroscience. Recent large-sample cohort studies measured GCA through multiple cognitive tasks and explored its neural basis, but they did not investigate how task number, factor models, and neural data type affect the estimation of GCA and its neural correlates. To address these issues, we tested 1,605 Chinese young adults with 19 cognitive tasks and Raven's Advanced Progressive Matrices (RAPM) and collected resting state and n-back task fMRI data from a subsample of 683 individuals. Results showed that GCA could be reliably estimated by multiple tasks. Increasing task number enhances both reliability and validity of GCA estimates and reliably strengthens their correlations with brain data. The Spearman model and hierarchical bifactor model yield similar GCA estimates. The bifactor model has better model fit and stronger correlation with RAPM but explains less variance and shows weaker correlations with brain data than does the Spearman model. Notably, the n-back task-based functional connectivity patterns outperform resting-state fMRI in predicting GCA. These results suggest that GCA derived from a multitude of cognitive tasks serves as a valid measure of general intelligence and that its neural correlates could be better characterized by task fMRI than resting-state fMRI data.

Association of Cognitive Polygenic Index and Cognitive Performance with Age in Cognitively Healthy Adults

Genome-wide association studies have discovered common genetic variants associated with cognitive performance. Polygenic scores that summarize these discoveries explain up to 10% of the variance in cognitive test performance in samples of adults. However, the role these genetics play in cognitive aging is not well understood. We analyzed data from 168 cognitively healthy participants aged 23-77 years old, with data on genetics, neuropsychological assessment, and brain-imaging measurements from two large ongoing studies, the Reference Abilities Neural Networks, and the Cognitive Reserve study. We tested whether a polygenic index previously related to cognition (Cog PGI) would moderate the relationship between age and measurements of the cognitive domains extracted from a neuropsychological evaluation: fluid reasoning, memory, vocabulary, and speed of processing. We further explored the relationship of Cog PGI and age on cognition using Johnson-Neyman intervals for two-way interactions. Sex, education, and brain measures of cortical thickness, total gray matter volume, and white matter hyperintensity were considered covariates. The analysis controlled for population structure-ancestry. There was a significant interaction effect of Cog PGI on the association between age and the domains of memory (Standardized coefficient = -0.158, p-value = 0.022), fluid reasoning (Standardized coefficient = -0.146, p-value = 0.020), and vocabulary (Standardized coefficient = -0.191, p-value = 0.001). Higher PGI strengthened the negative relationship between age and the domains of memory and fluid reasoning while PGI weakened the positive relationship between age and vocabulary. Based on the Johnson-Neyman intervals, Cog PGI was significantly associated with domains of memory, reasoning, and vocabulary for younger adults. There is a significant moderation effect of genetic predisposition for cognition for the association between age and cognitive performance. Genetics discovered in genome-wide association studies of cognitive performance show a stronger association in young and midlife older adults.

Exome-wide analysis reveals role of LRP1 and additional novel loci in cognition

Cognitive functioning is heritable, with metabolic risk factors known to accelerate age-associated cognitive decline. Identifying genetic underpinnings of cognition is thus crucial. Here, we undertake single-variant and gene-based association analyses upon 6 neurocognitive phenotypes across 6 cognition domains in whole-exome sequencing data from 157,160 individuals of the UK Biobank cohort to expound the genetic architecture of human cognition. We report 20 independent loci associated with 5 cognitive domains while controlling for APOE isoform-carrier status and metabolic risk factors; 18 of which were not previously reported, and implicated genes relating to oxidative stress, synaptic plasticity and connectivity, and neuroinflammation. A subset of significant hits for cognition indicates mediating effects via metabolic traits. Some of these variants also exhibit pleiotropic effects on metabolic traits. We further identify previously unknown interactions of APOE variants with LRP1 (rs34949484 and others, suggestively significant), AMIGO1 (rs146766120; pAla25Thr, significant), and ITPR3 (rs111522866, significant), controlling for lipid and glycemic risks. Our gene-based analysis also suggests that APOC1 and LRP1 have plausible roles along shared pathways of amyloid beta (Aβ) and lipid and/or glucose metabolism in affecting complex processing speed and visual attention. In addition, we report pairwise suggestive interactions of variants harbored in these genes with APOE affecting visual attention. Our report based on this large-scale exome-wide study highlights the effects of neuronal genes, such as LRP1, AMIGO1, and other genomic loci, thus providing further evidence of the genetic underpinnings for cognition during aging.

Dynamic weighted hypergraph convolutional network for brain functional connectome analysis

The hypergraph structure has been utilized to characterize the brain functional connectome (FC) by capturing the high order relationships among multiple brain regions of interest (ROIs) compared with a simple graph. Accordingly, hypergraph neural network (HGNN) models have emerged and provided efficient tools for hypergraph embedding learning. However, most existing HGNN models can only be applied to pre-constructed hypergraphs with a static structure during model training, which might not be a sufficient representation of the complex brain networks. In this study, we propose a dynamic weighted hypergraph convolutional network (dwHGCN) framework to consider a dynamic hypergraph with learnable hyperedge weights. Specifically, we generate hyperedges based on sparse representation and calculate the hyper similarity as node features. The hypergraph and node features are fed into a neural network model, where the hyperedge weights are updated adaptively during training. The dwHGCN facilitates the learning of brain FC features by assigning larger weights to hyperedges with higher discriminative power. The weighting strategy also improves the interpretability of the model by identifying the highly active interactions among ROIs shared by a common hyperedge. We validate the performance of the proposed model on two classification tasks with three paradigms functional magnetic resonance imaging (fMRI) data from Philadelphia Neurodevelopmental Cohort. Experimental results demonstrate the superiority of our proposed method over existing hypergraph neural networks. We believe our model can be applied to other applications in neuroimaging for its strength in representation learning and interpretation.

Brain structural abnormalities in adult major depressive disorder revealed by voxel- and source-based morphometry: evidence from the REST-meta-MDD Consortium

BACKGROUND

Neuroimaging studies on major depressive disorder (MDD) have identified an extensive range of brain structural abnormalities, but the exact neural mechanisms associated with MDD remain elusive. Most previous studies were performed with voxel- or surface-based morphometry which were univariate methods without considering spatial information across voxels/vertices.

METHODS

Brain morphology was investigated using voxel-based morphometry (VBM) and source-based morphometry (SBM) in 1082 MDD patients and 990 healthy controls (HCs) from the REST-meta-MDD Consortium. We first examined group differences in regional grey matter (GM) volumes and structural covariance networks between patients and HCs. We then compared first-episode, drug-naïve (FEDN) patients, and recurrent patients. Additionally, we assessed the effects of symptom severity and illness duration on brain alterations.

RESULTS

VBM showed decreased GM volume in various regions in MDD patients including the superior temporal cortex, anterior and middle cingulate cortex, inferior frontal cortex, and precuneus. SBM returned differences only in the prefrontal network. Comparisons between FEDN and recurrent MDD patients showed no significant differences by VBM, but SBM showed greater decreases in prefrontal, basal ganglia, visual, and cerebellar networks in the recurrent group. Moreover, depression severity was associated with volumes in the inferior frontal gyrus and precuneus, as well as the prefrontal network.

CONCLUSIONS

Simultaneous application of VBM and SBM methods revealed brain alterations in MDD patients and specified differences between recurrent and FEDN patients, which tentatively provide an effective multivariate method to identify potential neurobiological markers for depression.

Genetic background of idiopathic neurodevelopmental delay patients with significant brain deviation volume

BACKGROUND

Significant brain volume deviation is an essential phenotype in children with neurodevelopmental delay (NDD), but its genetic basis has not been fully characterized. This study attempted to analyze the genetic factors associated with significant whole-brain deviation volume (WBDV).

METHODS

We established a reference curve based on 4222 subjects ranging in age from the first postnatal day to 18 years. We recruited only NDD patients without acquired etiologies or positive genetic results. Cranial magnetic resonance imaging (MRI) and clinical exome sequencing (2742 genes) data were acquired. A genetic burden test was performed, and the results were compared between patients with and without significant WBDV. Literature review analyses and BrainSpan analysis based on the human brain developmental transcriptome were performed to detect the potential role of genetic risk factors in human brain development.

RESULTS

We recruited a total of 253 NDD patients. Among them, 26 had significantly decreased WBDV (<-2 standard deviations [SDs]), and 14 had significantly increased WBDV (>+2 SDs). NDD patients with significant WBDV had higher rates of motor development delay (49.8% [106/213] vs . 75.0% [30/40], P  = 0.003) than patients without significant WBDV. Genetic burden analyses found 30 genes with an increased allele frequency of rare variants in patients with significant WBDV. Analyses of the literature further demonstrated that these genes were not randomly identified: burden genes were more related to the brain development than background genes ( P  = 1.656e -9 ). In seven human brain regions related to motor development, we observed burden genes had higher expression before 37-week gestational age than postnatal stages. Functional analyses found that burden genes were enriched in embryonic brain development, with positive regulation of synaptic growth at the neuromuscular junction, positive regulation of deoxyribonucleic acid templated transcription, and response to hormone, and these genes were shown to be expressed in neural progenitors. Based on single cell sequencing analyses, we found TUBB2B gene had elevated expression levels in neural progenitor cells, interneuron, and excitatory neuron and SOX15 had high expression in interneuron and excitatory neuron.

CONCLUSION

Idiopathic NDD patients with significant brain volume changes detected by MRI had an increased prevalence of motor development delay, which could be explained by the genetic differences characterized herein.

Polygenic indices for cognition in healthy aging; the role of brain measures

Background

Genome-wide association studies (GWAS) have identified large numbers of genetic variants associated with cognition. However, little is known about how these genetic discoveries impact cognitive aging.

Methods

We conducted polygenic-index (PGI) analysis of cognitive performance in n = 168 European-ancestry adults aged 20-80. We computed PGIs based on GWAS of cognitive performance in young/middle-aged and older adults. We tested associations of the PGI with cognitive performance, as measured through neuropsychological evaluation. We explored whether these associations were accounted for by magnetic resonance imaging (MRI) measures of brain-aging phenotypes: total gray matter volume (GM), cortical thickness (CT), and white matter hyperintensities burden (WMH).

Results

Participants with higher PGI values performed better on cognitive tests (B = 0.627, SE = 0.196, p = 0.002) (age, sex, and principal components as covariates). Associations remained significant with inclusion of covariates for MRI measures of brain aging; B = 0.439, SE: 0.198, p = 0.028). PGI associations were stronger in young and middle-aged (age<65) as compared to older adults. For further validation, linear regression for Cog PGI and cognition in the fully adjusted model and adding the interaction between age group and Cog PGI, showed significant results (B = 0.892, SE: 0.325, p = 0.007) driven by young and middle-aged adults (B = -0.403, SE: 0.193, p = 0.039). In ancillary analysis, the Cognitive PGI was not associated with any of the brain measures.

Conclusions

Genetics discovered in GWAS of cognition are associated with cognitive performance in healthy adults across age, but most strongly in young and middle-aged adults. Associations were not explained by brain-structural markers of brain aging. Genetics uncovered in GWAS of cognitive performance may contribute to individual differences established relatively early in life and may not reflect genetic mechanisms of cognitive aging.

A neglected symptom? Parietal gait lateropulsion as primary manifestation of acute is-chemic stroke

INTRODUCTION

Gait disorders are commonly overlooked as a presenting manifestation of stroke and underrepresented in case series. We describe four cases of sudden-onset gait lateropulsion as primary manifestation of parietal lobe stroke.

CASE REPORT

Four patients presented after sudden-onset gait lateropulsion. On neurological examination, all patients had at least one cortical sensory deficit and wide-based gait with lateropulsion towards the side of the cortical deficit. Neuroimaging revealed a subacute parietal lobe stroke contralateral to the side of gait lateropulsion. In two patients we found bilateral lateropulsion with predominance towards the side of cortical deficit and increase of unsteadiness with eye closure (an apparent Romberg sign), with neuroimaging revealing bilateral parietal strokes (subacute contralateral and chronic ipsilateral to gait lateropulsion).

CONCLUSION

We report gait lateropulsion as a novel primary manifestation of acute stroke of the parietal lobe (parietal gait lateropulsion). Given its role as the destination of proprioceptive pathways, parietal strokes can result in gait lateropulsion, with bilateral lesions even mimicking sensory ataxia with bilateral lateropulsion and unsteadiness upon eye closure.

Disturbed hippocampal intra-network in first-episode of drug-naïve major depressive disorder

Complex networks inside the hippocampus could provide new insights into hippocampal abnormalities in various psychiatric disorders and dementia. However, evaluating intra-networks in the hippocampus using MRI is challenging. Here, we employed a high spatial resolution of conventional structural imaging and independent component analysis to investigate intra-networks structural covariance in the hippocampus. We extracted the intra-networks based on the intrinsic connectivity of each 0.9 mm isotropic voxel to every other voxel using a data-driven approach. With a total volume of 3 cc, the hippocampus contains 4115 voxels for a 0.9 mm isotropic voxel size or 375 voxels for a 2 mm isotropic voxel of high-resolution functional or diffusion tensor imaging. Therefore, the novel method presented in the current study could evaluate the hippocampal intra-networks in detail. Furthermore, we investigated the abnormality of the intra-networks in major depressive disorders. A total of 77 patients with first-episode drug-naïve major depressive disorder and 79 healthy subjects were recruited. The independent component analysis extracted seven intra-networks from hippocampal structural images, which were divided into four bilateral networks and three networks along the longitudinal axis. A significant difference was observed in the bilateral hippocampal tail network between patients with major depressive disorder and healthy subjects. In the logistic regression analysis, two bilateral networks were significant predictors of major depressive disorder, with an accuracy of 78.1%. In conclusion, we present a novel method for evaluating intra-networks in the hippocampus. One advantage of this method is that a detailed network can be estimated using conventional structural imaging. In addition, we found novel bilateral networks in the hippocampus that were disturbed in patients with major depressive disorders, and these bilateral networks could predict major depressive disorders.

Reserve and Maintenance in the Aging Brain: A Longitudinal Study of Healthy Older Adults

The aging brain undergoes structural changes even in very healthy individuals. Quantifying these changes could help disentangle pathologic changes from those associated with the normal human aging process. Using longitudinal magnetic resonance imaging (MRI) data from 227 carefully selected healthy human cohort with age ranging from 50 to 80 years old at baseline scan, we quantified age-related volumetric changes in the brain of healthy human older adults. Longitudinally, the rates of tissue loss in total gray matter (GM) and white matter (WM) were 2497.5 and 2579.8 mm³ per year, respectively. Across the whole brain, the rates of GM decline varied with regions in the frontal and parietal lobes having faster rates of decline, whereas some regions in the occipital and temporal lobes appeared relatively preserved. In contrast, cross-sectional changes were mainly observed in the temporal-occipital regions. Similar longitudinal atrophic changes were also observed in subcortical regions including thalamus, hippocampus, putamen, and caudate, whereas the pallidum showed an increasing volume with age. Overall, regions maturing late in development (frontal, parietal) are more vulnerable to longitudinal decline, whereas those that fully mature in the early stage (temporal, occipital) are mainly affected by cross-sectional changes in healthy older cohort. This may suggest that, for a successful healthy aging, the former needs to be maximally developed at an earlier age to compensate for the longitudinal decline later in life and the latter to remain relatively preserved even in old age, consistent with both concepts of reserve and brain maintenance.

Maternal vitamin B12, folate during pregnancy and neurocognitive outcomes in young adults of the Pune Maternal Nutrition Study (PMNS) prospective birth cohort: study protocol

INTRODUCTION

The Developmental Origins of Health and Disease (DOHaD) hypothesis proposes that intrauterine and early life exposures significantly influence fetal development and risk for disease in later life. Evidence from prospective birth cohorts suggests a role for maternal B₁₂ and folate in influencing neurocognitive outcomes in the offspring. In the Indian setting, B₁₂ deficiency is common during the pregnancy while rates of folate deficiency are lower. The long-term influences of maternal nutrition during the pregnancy on adult neurocognitive outcomes have not been examined. The Pune Maternal Nutrition Study (PMNS) is a preconceptional birth cohort into its 24th year and is considered a unique resource to study the DOHaD hypothesis. We found an association between maternal B₁₂ status in pregnancy and child's neurocognitive status at 9 years of age. We now plan to assess neurocognitive function and MRI measurements of brain structural-functional connectivity at young adult age to study its association with maternal nutritional exposures during the pregnancy.

METHODS AND ANALYSIS

As part of ongoing prospective follow-up in young adults of the PMNS at the Diabetes Unit, KEM Hospital Research Center, Pune India, the following measurements will be done: neurocognitive performance (Standardised Tests of Intelligence, Verbal and Visual Memory, Attention and Executive Functions), temperament (Adult Temperament Questionnaire), psychopathology (Brief Symptom Inventory and Clinical Interview on Mini Neuropsychiatric Interview 7.0). Brain MRI for structural T1, resting-state functional connectivity and diffusion tensor imaging will be performed on a subset of the cohort (selected based on exposure to a lower or higher maternal B₁₂ status at 18 weeks of pregnancy).

ETHICS AND DISSEMINATION

The study is approved by Institutional ethics committee of KEM Hospital Research Center, Pune. The results will be shared at national and international scientific conferences and published in peer-reviewed scientific journals.

TRIAL REGISTRATION NUMBER

NCT03096028.

Multilobed Magnetic Liposomes Enable Remotely Controlled Collection, Transport, and Delivery of Membrane-Soluble Cargos to Vesicles and Cells

Lipid bilayers are the basic structural components of all living systems, forming the membranes of cells, sub-cellular organelles, and extracellular vesicles. A class of man-made lipidic vesicles called multilobed magnetic liposomes (MMLs) is reported in this work; these MMLs possess a previously unattained combination of features owing to their unique multilobe structure and composition. MMLs consist of a central cluster of lipid-coated magnetic iron oxide nanoparticles that lend them a magnetophoretic velocity comparable to the most efficient living microswimmers. Multiple liposome-like lobes protrude from the central region; these can incorporate both water-soluble and lipid-soluble molecular payloads at high carrying capacity and exchange the incorporated substances with the membranes of both artificial and live cells by the contact diffusion mechanism. The size of MMLs is controllable in the range of 200-800 nm. Their functionality is demonstrated by completing a model mission where MMLs are remotely controlled to collect, transport, and deliver a cargo to live cells.

Static and dynamic functional connectivity supports the configuration of brain networks associated with creative cognition

Creative cognition is recognized to involve the integration of multiple spontaneous cognitive processes and is manifested as complex networks within and between the distributed brain regions. We propose that the processing of creative cognition involves the static and dynamic re-configuration of brain networks associated with complex cognitive processes. We applied the sliding-window approach followed by a community detection algorithm and novel measures of network flexibility on the blood-oxygen level dependent (BOLD) signal of 8 major functional brain networks to reveal static and dynamic alterations in the network reconfiguration during creative cognition using functional magnetic resonance imaging (fMRI). Our results demonstrate the temporal connectivity of the dynamic large-scale creative networks between default mode network (DMN), salience network, and cerebellar network during creative cognition, and advance our understanding of the network neuroscience of creative cognition.

Spatiotemporal complexity patterns of resting-state bioelectrical activity explain fluid intelligence: Sex matters

Neural complexity is thought to be associated with efficient information processing but the exact nature of this relation remains unclear. Here, the relationship of fluid intelligence (gf) with the resting-state EEG (rsEEG) complexity over different timescales and different electrodes was investigated. A 6-min rsEEG blocks of eyes open were analyzed. The results of 119 subjects (57 men, mean age = 22.85 ± 2.84 years) were examined using multivariate multiscale sample entropy (mMSE) that quantifies changes in information richness of rsEEG in multiple data channels at fine and coarse timescales. gf factor was extracted from six intelligence tests. Partial least square regression analysis revealed that mainly predictors of the rsEEG complexity at coarse timescales in the frontoparietal network (FPN) and the temporo-parietal complexities at fine timescales were relevant to higher gf. Sex differently affected the relationship between fluid intelligence and EEG complexity at rest. In men, gf was mainly positively related to the complexity at coarse timescales in the FPN. Furthermore, at fine and coarse timescales positive relations in the parietal region were revealed. In women, positive relations with gf were mostly observed for the overall and the coarse complexity in the FPN, whereas negative associations with gf were found for the complexity at fine timescales in the parietal and centro-temporal region. These outcomes indicate that two separate time pathways (corresponding to fine and coarse timescales) used to characterize rsEEG complexity (expressed by mMSE features) are beneficial for effective information processing.

Training effects of attention and EF strategy-based training "Nexxo" in school-age students

Given the importance of attention and executive functions in children's behavior, programs directed to improve these processes are of interest. Nexxo-training combines the use of the Nexxo touchscreen application (go/no-go and stop signal tasks) with procedural metacognitive strategies. The present paper reports a test of Nexxo's impact on children aged 6-7 and 8-9 years. We conducted a randomized active-controlled trial involving 108 typically-developing children: 1st grade (N = 61, M = 6.46 years, SD = 0.35) and 3rd grade (N = 47, M = 8.5 years, SD = 0.27), randomly assigned to: (1) experimental, (2) active-control, or (3) passive-control groups. A 2-month follow-up was carried out after the intervention. The 3rd grade experimental group displayed a significant reduction in attentional problems at follow-up compared to both control groups. Executive Function problems were also reduced at follow-up in the experimental group. Participants in this group improved in Supervision (self-monitoring) at post-intervention and follow-up compared to passive-controls. Although group effect was not significant at t1, it was significant at post measures in experimental group compared to passive-controls. Nexxo-training revealed a trend-level improvement in attention and executive functions for children in the 3rd grade.

Evolving White Matter Injury following Pediatric Traumatic Brain Injury

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

Developmental trajectories of metacognitive processing and executive function from childhood to older age

The modern understanding of the term metacognition encompasses two levels of processing: a lower level awareness or knowledge of one’s own thoughts and a higher level regulation or control of our thinking. Metacognition, therefore, bears conceptual similarity with executive function: both are concerned with top-down monitoring and control of cognition in the service of ongoing goal-directed behaviour. Previous studies have shown a possible executive function advantage in multilingual speakers but also a possible disadvantage in metacognitive processing. To progress theory on metacognitive processing and the relationship with executive function and linguistic experience across the lifespan, we conducted a study testing 330 healthy individuals in four age groups from 7 to 80 years old. All participants performed a metacognition task and two measures of executive function, which included the Simon task and the Tower of London task. Half the participants were multilingual speakers since birth. We built developmental trajectories of metacognitive and executive function across the lifespan. The best metacognitive efficiency was observed in mid-adulthood, whereas the best executive function processing reached its peak in young adulthood. A steep cognitive decline was observed in older age, while metacognitive efficiency was preserved. Exploratory factor analysis indicated that metacognition and executive function are served by different factors across all ages. Contrary to previous findings in the bilingual literature, a multilinguistic experience conferred neither any significant advantage nor disadvantage in both executive function and metacognitive processing across the lifespan.

Association of Sedentary Behavior with Brain Structure and Intelligence in Children with Overweight or Obesity: The ActiveBrains Project

We investigated the associations of different sedentary behaviors (SB) with gray matter volume and we tested whether SB related to gray matter volume is associated with intelligence. Methods: 99 children with overweight or obesity aged 8–11 years participated in this cross-sectional study. SB was measured using the Youth Activity Profile-Spain questionnaire. T1-weighted images were acquired with a 3.0 T Magnetom Tim Trio system. Intelligence was assessed with the Kaufman Brief Test. Whole-brain voxel-wise multiple regression models were used to test the associations of each SB with gray matter volume. Results: Watching TV was associated with lower gray matter volume in six brain regions (β ranging −0.314 to −0.489 and cluster size 106 to 323 voxels; p < 0.001), playing video games in three brain regions (β ranging −0.391 to −0.359, and cluster size 96 to 461 voxels; p < 0.001) and total sedentary time in two brain regions (β ranging −0.341 to −0.352, and cluster size 897 to 2455 voxels; p < 0.001). No brain regions showed a significant positive association (all p > 0.05). Two brain regions were related, or borderline related, to intelligence. Conclusions: SB could have the potential to negatively influence brain structure and, in turn, intelligence in children with overweight/obesity.

APOE-ε4 Shapes the Cerebral Organization in Cognitively Intact Individuals as Reflected by Structural Gray Matter Networks

Gray matter networks (GMn) provide essential information on the intrinsic organization of the brain and appear to be disrupted in Alzheimer’s disease (AD). Apolipoprotein E (APOE)-ε4 represents the major genetic risk factor for AD, yet the association between APOE-ε4 and GMn has remained unexplored. Here, we determine the impact of APOE-ε4 on GMn in a large sample of cognitively unimpaired individuals, which was enriched for the genetic risk of AD. We used independent component analysis to retrieve sources of structural covariance and analyzed APOE group differences within and between networks. Analyses were repeated in a subsample of amyloid-negative subjects. Compared with noncarriers and heterozygotes, APOE-ε4 homozygotes showed increased covariance in one network including primarily right-lateralized, parietal, inferior frontal, as well as inferior and middle temporal regions, which mirrored the formerly described AD-signature. This result was confirmed in a subsample of amyloid-negative individuals. APOE-ε4 carriers showed reduced covariance between two networks encompassing frontal and temporal regions, which constitute preferential target of amyloid deposition. Our data indicate that, in asymptomatic individuals, APOE-ε4 shapes the cerebral organization in a way that recapitulates focal morphometric alterations observed in AD patients, even in absence of amyloid pathology. This suggests that structural vulnerability in neuronal networks associated with APOE-ε4 may be an early event in AD pathogenesis, possibly upstream of amyloid deposition.

Cerebellar Morphometry and Cognition in the Context of Chronic Alcohol Consumption and Cigarette Smoking

BACKGROUND

Cerebellar atrophy (especially involving the superior-anterior cerebellar vermis) is among the most salient and clinically significant effects of chronic hazardous alcohol consumption on brain structure. Smaller cerebellar volumes are also associated with chronic cigarette smoking. The present study investigated effects of both chronic alcohol consumption and cigarette smoking on cerebellar structure and its relation to performance on select cognitive/behavioral tasks.

METHODS

Using T1-weighted Magnetic Resonance Images (MRIs), the Cerebellar Analysis Tool Kit segmented the cerebellum into bilateral hemispheres and 3 vermis parcels from 4 participant groups: smoking (s) and nonsmoking (ns) abstinent alcohol-dependent treatment seekers (ALC) and controls (CON) (i.e., sALC, nsALC, sCON, and nsCON). Cognitive and behavioral data were also obtained.

RESULTS

We found detrimental effects of chronic drinking on all cerebellar structural measures in ALC participants, with largest reductions seen in vermis areas. Furthermore, both smoking groups had smaller volumes of cerebellar hemispheres but not vermis areas compared to their nonsmoking counterparts. In exploratory analyses, smaller cerebellar volumes were related to lower measures of intelligence. In sCON, but not sALC, greater smoking severity was related to smaller cerebellar volume and smaller superior-anterior vermis area. In sALC, greater abstinence duration was associated with larger cerebellar and superior-anterior vermis areas, suggesting some recovery with abstinence.

CONCLUSIONS

Our results show that both smoking and alcohol status are associated with smaller cerebellar structural measurements, with vermal areas more vulnerable to chronic alcohol consumption and less affected by chronic smoking. These morphometric cerebellar deficits were also associated with lower intelligence and related to duration of abstinence in sALC only.

Associations between brain structural networks and neurological soft signs in healthy adults

Neurological soft signs (NSS), as minor neurological deficits, have been identified in several psychiatric disorders, especially in schizophrenia. However, it's unclear how the neuropathological processes of the disease affect NSS related brain morphological changes and whether it is confounded by the use of medication. As NSS also exist in healthy people, the potential confounding effects of psychopathology or medication will be excluded if NSS are investigated in healthy people. Therefore, we applied a novel multivariate approach, source-based morphometry (SBM), to study structural networks in relation to NSS in healthy adults based on structural magnetic resonance imaging (MRI) data. The Heidelberg Scale was applied to evaluate NSS. Using SBM, we constructed structural networks and investigated their associations with NSS in healthy adults. Six grey matter (GM) structural networks were identified. Sensory integration subscores were associated with the cerebellar component and the cortico-basal ganglia-thalamic component. Motor coordination subscores and total NSS scores were associated with the sensorimotor component. The present findings indicated that structural network abnormalities in cerebellar, subcortical and cortical sensorimotor areas contribute to NSS performance in healthy adults.

Knitting induced fronto-central theta rhythm

Fronto-central theta rhythms on EEG have been associated with cognitive tasks requiring attention and concentration, such as mental arithmetic or geometric construction. With the advent of video monitoring, there have been reports of new, task-specific, fronto-central theta rhythms reported with active texting or playing videogames on mobile phones. Concentration or attention combined with manual dexterous acts is challenging to simulate in an artificial and non-spontaneous environment, such as an epilepsy monitoring unit. We report a case of a fronto-central theta rhythm during active knitting using a needle and yarn with only passive concentration to highlight involvement of a corticomotor component underlying the neural networks involved in the efferent expression of scalp EEG to differentiate it from similar rhythms.

The neural code of intelligence: From correlation to causation

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

Schoolchildren's Compensatory Strategies and Skills in Relation to Attention and Executive Function App Training

BACKGROUND

Given the importance of attention and executive functions (EF) in children's behavior, programs aimed at improving these processes are of special interest. Nexxo-training combines the use of the Nexxo touchscreen application (inhibition and vigilance tasks) with procedural metacognitive strategies (imparted by an instructor) for all the individuals using the app, regardless of their level of ability, plus compensatory strategies based on individual child performance. This study presents an analysis of the compensatory strategies that schoolchildren (aged 6-8 years old) receive when experiencing difficulties with EF tasks, in addition to an analysis of the developmental factors and cognitive skills that may modulate EF task performance.

METHODS

For this study, we use data from a previous randomized active-controlled study (under review), in which forty-six typically developing children aged between 6 and 8 years old (24 girls/22 boys) were enrolled in the training group. The selected children were in the 1st grade (n = 28, x ¯ = 78.32 ± 4.037 months) and 3rd grade of primary education (n = 18, x ¯ = 102.11 ± 3.445). We collected data on EF training performance, compensatory strategies needed and neuropsychological assessments.

RESULTS

A total of 80.43% participants required some form of compensatory strategy during training. Regarding required compensatory strategies, those who had lower scores in EF training needed more compensatory strategies, in particular, instructional comprehension (r = -0.561, p < 0.001 for inhibition-tasks; r = -0.342, p < 0.001 for vigilance-tasks). Concerning developmental factors, age significantly predicted better performance in both EF tasks (β = 0.613, p < 0.001 for inhibition; β = 0.706, p < 0.001 for attention). As regards task performance, those with better performance in inhibition tasks also had better performance in vigilance tasks (r = 0.72, p < 0.001). Finally, regarding cognitive skills, participants with higher performance in fluid intelligence (Q1, n = 12) had higher scores (U = 14.5, p < 0.05) than the group with the lowest performance (Q4, n = 11) in vigilance.

CONCLUSION

As previous literature suggests, inhibition is one of the core processes of EF. Therefore, we should focus training on the core EF processes. Inhibition and vigilance are closely related processes. In terms of the use of compensatory strategies, these are more needed for participants with lower levels of performance in inhibition or vigilance. Regarding strategy analysis, instructional comprehension and self-instruction (goal setting and planning) seem to be the most useful strategies for those with difficulties in inhibitory and vigilance task performance. Regarding development, as expected, age moderates task performance in inhibition and attention. Finally, cognitive skills, such as fluid intelligence and cognitive flexibility, predicted better results in attention. EF training using not only an app, but also compensatory strategies based on user performance, is a new research direction offering more opportunities to generalize EF training in everyday life.

Cerebellar Gray Matter Volume Is Associated With Cognitive Function and Psychopathology in Adolescence

BACKGROUND

Accumulating evidence supports cerebellar involvement in mental disorders, such as schizophrenia, bipolar disorder, depression, anxiety disorders, and attention-deficit/hyperactivity disorder. However, little is known about the cerebellum in developmental stages of these disorders. In particular, whether cerebellar morphology is associated with early expression of specific symptom domains remains unclear.

METHODS

We used machine learning to test whether cerebellar morphometric features could robustly predict general cognitive function and psychiatric symptoms in a large and well-characterized developmental community sample centered on adolescence (Philadelphia Neurodevelopmental Cohort, n = 1401, age 8-23 years).

RESULTS

Cerebellar morphology was associated with both general cognitive function and general psychopathology (mean correlations between predicted and observed values: r = .20 and r = .13; p < .001). Analyses of specific symptom domains revealed significant associations with rates of norm-violating behavior (r = .17; p < .001) as well as psychosis (r = .12; p < .001) and anxiety (r = .09; p = .012) symptoms. In contrast, we observed no associations with attention deficits or depressive, manic, or obsessive-compulsive symptoms. Crucially, across 52 brain-wide anatomical features, cerebellar features emerged as the most important for prediction of general psychopathology, psychotic symptoms, and norm-violating behavior. Moreover, the association between cerebellar volume and psychotic symptoms and, to a lesser extent, norm-violating behavior remained significant when adjusting for several potentially confounding factors.

CONCLUSIONS

The robust associations with psychiatric symptoms in the age range when these typically emerge highlight the cerebellum as a key brain structure in the development of severe mental disorders.

Predicting Cognitive Scores from Resting fMRI Data and Geometric Features of the Brain

Anatomical T1 weighted Magnetic Resonance Imaging (MRI) and functional magnetic resonance imaging collected during resting (rfMRI) are promising markers that offer insight into the structure and function of the human brain. The objective of this work is to explore the use of a deep learning neural network to predict cognitive performance scores for a population of normal controls and subjects with Attention Deficit Hyperactivity Disorder (ADHD). Specifically, we predict verbal and performance IQs and ADHD index from features derived from T1 and rfMRI imaging data. First, we processed the rfMRI and MRI data of subjects using the BrainSuite fMRI Processing (BFP) pipeline to perform anatomical and functional preprocessing. This produces for each subject fMRI and geometric (anatomical) features represented in a standardized grayordinate system. The geometric and functional cortical data corresponding to the two hemispheres were then transformed to 128×128 multichannel images and input to a convolutional component of the neural network. Subcortical data were presented in a standard vector form and inputted to a input layer of the network. The neural network was implemented in Python using the Keras library with a TensorFlow backend. Training was performed on 168 images with 90 images used for testing. We observed a high correlation between predicted and actual values of the indices tested: Performance IQ: 0.47; Verbal IQ: 0.41, ADHD: 0.57. Comparing these values to those from network trained on functional-only and structural-only data, we saw that rfMRI is more informative than MRI, but the two modalities are highly complementary in terms of predicting these indices.

Effect of tDCS on Aberrant Functional Network Connectivity in Refractory Hallucinatory Schizophrenia: A Pilot Study

We aim to investigate the effect of fronto-temporal transcranial direct current stimulation (tDCS) on the interactions among functional networks and its association with psychotic symptoms. In this pilot study, we will determine possible candidate functional networks and an adequate sample size for future research. Seven schizophrenia patients with treatment-refractory auditory hallucinations underwent tDCS twice daily for 5 days. Resting-state fMRI data and measures of the severity of psychotic symptoms were acquired at baseline and after completion of the tDCS sessions. At baseline, decreased functional network interaction was negatively correlated with increased hallucinatory behavior. After tDCS, the previously reduced functional network connectivity significantly increased. Our results showed that fronto-temporal tDCS could possibly remediate aberrant hallucination-related functional network interactions in patients with schizophrenia.

Cognitive Development and Quality of Life Associated With BPD in 10-Year-Olds Born Preterm

OBJECTIVES

To compare neurocognitive, language, executive function, academic achievement, neurologic and behavioral outcomes, and quality of life at age 10 years in children born extremely preterm who developed bronchopulmonary dysplasia (BPD) to children who did not develop BPD.

METHODS

The Extremely Low Gestational Age Newborns study population included 863 children born extremely preterm whose BPD status before discharge was known had an IQ (Differential Ability Scales II [DAS II]) assessment at 10 years. We evaluated the association of BPD with any cognitive (DAS II), executive function (NEuroPSYchological Assessment II), academic achievement (Wechsler Individual Achievement Test-III and Oral and Written Language Scales [OWLS]) as well as social dysfunctions (Social Responsiveness Scale). We used logistic regression models, adjusting for potential confounding factors, to assess the strength of association between the severity of BPD and each outcomes.

RESULTS

Three hundred and seventy-two (43%) children were oxygen-dependent at 36 weeks postconception age, whereas an additional 78 (9%) were also oxygen- and ventilator-dependent. IQ scores 2 or more SDs below the expected mean (ie, z scores ≤-2) occurred twice as commonly among children who had BPD as among those who did not. Children with severe BPD consistently had the lowest scores on DAS II, OWLS, Wechsler Individual Achievement Test-III, NEuroPSYchological Assessment II, and Social Responsiveness Scale assessments.

CONCLUSIONS

Among 10-year-old children born extremely preterm, those who had BPD were at increased risk of cognitive, language, and executive dysfunctions; academic achievement limitations; social skill deficits; and low scores on assessments of health-related quality of life.

Cerebellar Structural Abnormalities Associated With Cognitive Function in Patients With First-Episode Psychosis

Introduction: The fundamental role of the cerebellum in higher cognitive processing has recently been highlighted. However, inconsistent findings exist in schizophrenia with respect to the exact nature of cerebellar structural abnormalities and their associations with cognitive and clinical features. Materials and Methods: We undertook a detailed investigation of cerebellar lobular volumes in 40 patients with first-episode psychosis (FEP) and 40 healthy controls (HCs) using the spatially unbiased atlas template of the cerebellum (SUIT). We examined the functional significance of cerebellar structural abnormalities in relation to cognitive and clinical outcomes in patients. Results: We found that left cerebellar lobules VI and X volumes were lower in FEP patients, compared to HCs. Smaller left lobules VI and X volumes were associated with fewer number of categories completed on the Wisconsin Card Sorting Test (WCST) in patients. In addition, smaller left lobule X volume was related to performance delay on the Trail Making Test (TMT) Part B in patients. Conclusion: Our results demonstrate that cerebellar structural abnormalities are present at the early stage of schizophrenia. We suggest functional associations of cerebellar structural changes with non-verbal executive dysfunctions in FEP.