Rapid microstructural plasticity in the cortical semantic network following a short language learning session.

Despite the clear importance of language in our life, our vital ability to quickly and effectively learn new words and meanings is neurobiologically poorly understood. Conventional knowledge maintains that language learning-especially in adulthood-is slow and laborious. Furthermore, its structural basis remains unclear. Even though behavioural manifestations of learning are evident near instantly, previous neuroimaging work across a range of semantic categories has largely studied neural changes associated with months or years of practice. Here, we address rapid neuroanatomical plasticity accompanying new lexicon acquisition, specifically focussing on the learning of action-related language, which has been linked to the brain's motor systems. Our results show that it is possible to measure and to externally modulate (using transcranial magnetic stimulation (TMS) of motor cortex) cortical microanatomic reorganisation after mere minutes of new word learning. Learning-induced microstructural changes, as measured by diffusion kurtosis imaging (DKI) and machine learning-based analysis, were evident in prefrontal, temporal, and parietal neocortical sites, likely reflecting integrative lexico-semantic processing and formation of new memory circuits immediately during the learning tasks. These results suggest a structural basis for the rapid neocortical word encoding mechanism and reveal the causally interactive relationship of modal and associative brain regions in supporting learning and word acquisition.

Improved sensitivity and microvascular weighting of 3T laminar fMRI with GE-BOLD using NORDIC and phase regression.

INTRODUCTION: Functional MRI with spatial resolution in the submillimeter domain enables measurements of activation across cortical layers in humans. This is valuable as different types of cortical computations, e.g., feedforward versus feedback related activity, take place in different cortical layers. Laminar fMRI studies have almost exclusively employed 7T scanners to overcome the reduced signal stability associated with small voxels. However, such systems are relatively rare and only a subset of those are clinically approved. In the present study, we examined if the feasibility of laminar fMRI at 3T could be improved by use of NORDIC denoising and phase regression. METHODS: 5 healthy subjects were scanned on a Siemens MAGNETOM Prisma 3T scanner. To assess across-session reliability, each subject was scanned in 3-8 sessions on 3-4 consecutive days. A 3D gradient echo EPI (GE-EPI) sequence was used for BOLD acquisitions (voxel size 0.82 mm isotopic, TR = 2.2 s) using a block design finger tapping paradigm. NORDIC denoising was applied to the magnitude and phase time series to overcome limitations in temporal signal-to-noise ratio (tSNR) and the denoised phase time series were subsequently used to correct for large vein contamination through phase regression. RESULTS AND CONCLUSION: NORDIC denoising resulted in tSNR values comparable to or higher than commonly observed at 7T. Layer-dependent activation profiles could thus be extracted robustly, within and across sessions, from regions of interest located in the hand knob of the primary motor cortex (M1). Phase regression led to substantially reduced superficial bias in obtained layer profiles, although residual macrovascular contribution remained. We believe the present results support an improved feasibility of laminar fMRI at 3T.

Physiological response in E. coli to YdgR overexpression depends on whether the protein has an intact function.

Membrane transport proteins are essential for the transport of a wide variety of molecules across the cell membrane to maintain cellular homeostasis. Generally, these transport proteins can be overexpressed in a suitable host (bacteria, yeast, or mammalian cells), and it is well documented that overexpression of membrane proteins alters the global metabolomic and proteomic profiles of the host cells. In the present study, we investigated the physiological consequences of overexpression of a membrane transport protein YdgR that belongs to the POT/PTR family from E. coli by using the lab strain BL21 (DE3)pLysS in its functional and attenuated mutant YdgR-E33Q. We found significant differences between the omics (metabolomics and proteomics) profiles of the cells expressing functional YdgR as compared to cells expressing attenuated YdgR, e.g., upregulation of several uncharacterized y-proteins and enzymes involved in the metabolism of peptides and amino acids. Furthermore, molecular network analysis suggested a relatively higher presence of proline-containing tripeptides in cells expressing functional YdgR. We envisage that an in-depth investigation of physiological alterations due to protein over-expression may be used for the deorphanization of the y-gene transportome.

Essentiality of the Escherichia coli YgfZ Protein for the In Vivo Thiomethylation of Ribosomal Protein S12 by the RimO Enzyme.

Enzymes carrying Iron-Sulfur (Fe-S) clusters perform many important cellular functions and their biogenesis require complex protein machinery. In mitochondria, the IBA57 protein is essential and promotes assembly of [4Fe-4S] clusters and their insertion into acceptor proteins. YgfZ is the bacterial homologue of IBA57 but its precise role in Fe-S cluster metabolism is uncharacterized. YgfZ is needed for activity of the radical S-adenosyl methionine [4Fe-4S] cluster enzyme MiaB which thiomethylates some tRNAs. The growth of cells lacking YgfZ is compromised especially at low temperature. The RimO enzyme is homologous to MiaB and thiomethylates a conserved aspartic acid in ribosomal protein S12. To quantitate thiomethylation by RimO, we developed a bottom-up LC-MS2 analysis of total cell extracts. We show here that the in vivo activity of RimO is very low in the absence of YgfZ and independent of growth temperature. We discuss these results in relation to the hypotheses relating to the role of the auxiliary 4Fe-4S cluster in the Radical SAM enzymes that make Carbon-Sulfur bonds.

Diffusional kurtosis imaging as a possible prognostic marker of cervical incomplete spinal cord injury outcome: a prospective pilot study.

BACKGROUND: Spinal cord injury (SCI) is associated with substantial chronic morbidity and mortality. Routine imaging techniques such as T1- and T2-weighted magnetic resonance imaging (MRI) are not effective in predicting neurological deficiency grade or outcome. Diffusional kurtosis imaging (DKI) is an MR imaging technique that provides microstructural information about biological tissue. There are no longitudinal prospective studies assessing DKI metrics in acute traumatic SCI. Therefore, the purpose of this study was to establish a DKI protocol for acute SCI and correlate the DKI metrics to the functional neurological outcome of the patients. METHODS: Eight consecutive SCI patients referred to our institution with cervical SCI were included in the study. An acute diagnostic MRI scan was supplemented with a novel fast, mean kurtosis DKI protocol, which describes the average deviation from Gaussian diffusional along nine different directions. Mean kurtosis values were measured at the injury site and normalized to the mean kurtosis values of a non-injured site. At discharge form specialized rehabilitation, patients were evaluated using the Spinal Cord Independence Measure-III (SCIM-III). The DKI metrics and SCIM-III were analysed using Spearman's rank correlation. RESULTS: This pilot study found a significant correlation between decreasing mean kurtosis values at the injury site of the spinal cord and higher grade of disability measured by the SCIM-III (p = 0.002). CONCLUSION: This pilot study found that DKI may be a valuable tool as a prognostic marker in the acute phase of SCI.

Microstructural changes in the brain after long-term post-concussion symptoms: A randomized trial.

A recent randomized controlled trial in young patients with long-term post-concussion symptoms showed that a novel behavioral intervention "Get going After concussIoN" is superior to enhanced usual care in terms of symptom reduction. It is unknown whether these interventional effects are associated with microstructural brain changes. The aim of this study was to examine whether diffusion-weighted MRI indices, which are sensitive to the interactions between cellular structures and water molecules' Brownian motion, respond differently to the interventions of the above-mentioned trial and whether such differences correlate with the improvement of post-concussion symptoms. Twenty-three patients from the intervention group (mean age 22.8, 18 females) and 19 patients from the control group (enhanced usual care) (mean age 23.9, 14 females) were enrolled. The primary outcome measure was the mean kurtosis tensor, which is sensitive to the microscopic complexity of brain tissue. The mean kurtosis tensor was significantly increased in the intervention group (p = 0.003) in the corpus callosum but not in the thalamus (p = 0.78) and the hippocampus (p = 0.34). An increase in mean kurtosis tensor in the corpus callosum tended to be associated with a reduction in symptoms, but this association did not reach significance (p = 0.059). Changes in diffusion tensor imaging metrics did not differ between intervention groups and were not associated with symptoms. The current study found different diffusion-weighted MRI responses from the microscopic cellular structures of the corpus callosum between patients receiving a novel behavioral intervention and patients receiving enhanced usual care. Correlations with improvement of post-concussion symptoms were not evident.

DeepControl: 2DRF pulses facilitating B1+ inhomogeneity and B0 off-resonance compensation in vivo at 7 T.

PURPOSE: Rapid 2DRF pulse design with subject-specific B1+ inhomogeneity and B0 off-resonance compensation at 7 T predicted from convolutional neural networks is presented. METHODS: The convolution neural network was trained on half a million single-channel transmit 2DRF pulses optimized with an optimal control method using artificial 2D targets, B1+ and B0 maps. Predicted pulses were tested in a phantom and in vivo at 7 T with measured B1+ and B0 maps from a high-resolution gradient echo sequence. RESULTS: Pulse prediction by the trained convolutional neural network was done on the fly during the MR session in approximately 9 ms for multiple hand-drawn regions of interest and the measured B1+ and B0 maps. Compensation of B1+ inhomogeneity and B0 off-resonances has been confirmed in the phantom and in vivo experiments. The reconstructed image data agree well with the simulations using the acquired B1+ and B0 maps, and the 2DRF pulse predicted by the convolutional neural networks is as good as the conventional RF pulse obtained by optimal control. CONCLUSION: The proposed convolutional neural network-based 2DRF pulse design method predicts 2DRF pulses with an excellent excitation pattern and compensated B1+ and B0 variations at 7 T. The rapid 2DRF pulse prediction (9 ms) enables subject-specific high-quality 2DRF pulses without the need to run lengthy optimizations.

The sensation of groove engages motor and reward networks.

The sensation of groove has been defined as the pleasurable desire to move to music, suggesting that both motor timing and reward processes are involved in this experience. Although many studies have investigated rhythmic timing and musical reward separately, none have examined whether the associated cortical and subcortical networks are engaged while participants listen to groove-based music. In the current study, musicians and non-musicians listened to and rated experimentally controlled groove-based stimuli while undergoing functional magnetic resonance imaging. Medium complexity rhythms elicited higher ratings of pleasure and wanting to move and were associated with activity in regions linked to beat perception and reward, as well as prefrontal and parietal regions implicated in generating and updating stimuli-based expectations. Activity in basal ganglia regions of interest, including the nucleus accumbens, caudate and putamen, was associated with ratings of pleasure and wanting to move, supporting their important role in the sensation of groove. We propose a model in which different cortico-striatal circuits interact to support the mechanisms underlying groove, including internal generation of the beat, beat-based expectations, and expectation-based affect. These results show that the sensation of groove is supported by motor and reward networks in the brain and, along with our proposed model, suggest that the basal ganglia are crucial nodes in networks that interact to generate this powerful response to music.

Language beyond the language system: Dorsal visuospatial pathways support processing of demonstratives and spatial language during naturalistic fast fMRI.

Spatial demonstratives are powerful linguistic tools used to establish joint attention. Identifying the meaning of semantically underspecified expressions like "this one" hinges on the integration of linguistic and visual cues, attentional orienting and pragmatic inference. This synergy between language and extralinguistic cognition is pivotal to language comprehension in general, but especially prominent in demonstratives. In this study, we aimed to elucidate which neural architectures enable this intertwining between language and extralinguistic cognition using a naturalistic fMRI paradigm. In our experiment, 28 participants listened to a specially crafted dialogical narrative with a controlled number of spatial demonstratives. A fast multiband-EPI acquisition sequence (TR = 388 m s) combined with finite impulse response (FIR) modelling of the hemodynamic response was used to capture signal changes at word-level resolution. We found that spatial demonstratives bilaterally engage a network of parietal areas, including the supramarginal gyrus, the angular gyrus, and precuneus, implicated in information integration and visuospatial processing. Moreover, demonstratives recruit frontal regions, including the right FEF, implicated in attentional orienting and reference frames shifts. Finally, using multivariate similarity analyses, we provide evidence for a general involvement of the dorsal ("where") stream in the processing of spatial expressions, as opposed to ventral pathways encoding object semantics. Overall, our results suggest that language processing relies on a distributed architecture, recruiting neural resources for perception, attention, and extra-linguistic aspects of cognition in a dynamic and context-dependent fashion.

Rapid solution of the Bloch-Torrey equation in anisotropic tissue: Application to dynamic susceptibility contrast MRI of cerebral white matter.

Blood vessel related magnetic resonance imaging (MRI) contrast provides a window into the brain's metabolism and function. Here, we show that the spin echo dynamic susceptibility contrast (DSC) MRI signal of the brain's white matter (WM) strongly depends on the angle between WM tracts and the main magnetic field. The apparent cerebral blood flow and volume are 20% larger in fibres perpendicular to the main magnetic field compared to parallel fibres. We present a rapid numerical framework for the solution of the Bloch-Torrey equation that allows us to explore the isotropic and anisotropic components of the vascular tree. By fitting the simulated spin echo DSC signal to the measured data, we show that half of the WM vascular volume is comprised of vessels running in parallel with WM fibre tracts. The WM blood volume corresponding to the best fit to the experimental data was 2.82%, which is close to the PET gold standard of 2.6%.

Ultrafast (milliseconds), multidimensional RF pulse design with deep learning.

PURPOSE: Some advanced RF pulses, like multidimensional RF pulses, are often long and require substantial computation time because of a number of constraints and requirements, sometimes hampering clinical use. However, the pulses offer opportunities of reduced-FOV imaging, regional flip-angle homogenization, and localized spectroscopy, e.g., of hyperpolarized metabolites. Proposed herein is a novel deep learning approach to ultrafast design of multidimensional RF pulses with intention of real-time pulse updates. METHODS: The proposed neural network considers input maps of the desired excitation region of interest and outputs a single-channel, multidimensional RF pulse. The training library is, e.g., retrieved from a large image database, and the target RF pulses trained upon are calculated with a method of choice. RESULTS: A relatively simple neural network is enough to produce reliable 2D spatial-selective RF pulses of comparable performance to the teaching method. For binary regions of interest, the training library does not need to be vast; hence, reestablishment of the training library is not necessarily cumbersome. The predicted pulses were tested numerically and experimentally at 3 T. CONCLUSION: Relatively effortless training of multidimensional RF pulses, based on non-MRI-related inputs, but working in an MRI setting still, has been demonstrated. The prediction time of a few milliseconds renders real-time updates of advanced RF pulses possible.

Brain inflammation accompanies amyloid in the majority of mild cognitive impairment cases due to Alzheimer's disease.

See Kreisl (doi:10.1093/awx151) for a scientific commentary on this article.Subjects with mild cognitive impairment associated with cortical amyloid-ß have a greatly increased risk of progressing to Alzheimer's disease. We hypothesized that neuroinflammation occurs early in Alzheimer's disease and would be present in most amyloid-positive mild cognitive impairment cases. 11C-Pittsburgh compound B and 11C-(R)-PK11195 positron emission tomography was used to determine the amyloid load and detect the extent of neuroinflammation (microglial activation) in 42 mild cognitive impairment cases. Twelve age-matched healthy control subjects had 11C-Pittsburgh compound B and 10 healthy control subjects had 11C-(R)-PK11195 positron emission tomography for comparison. Amyloid-positivity was defined as 11C-Pittsburgh compound B target-to-cerebellar ratio above 1.5 within a composite cortical volume of interest. Supervised cluster analysis was used to generate parametric maps of 11C-(R)-PK11195 binding potential. Levels of 11C-(R)-PK11195 binding potential were measured in a selection of cortical volumes of interest and at a voxel level. Twenty-six (62%) of 42 mild cognitive impairment cases showed a raised cortical amyloid load compared to healthy controls. Twenty-two (85%) of the 26 amyloid-positive mild cognitive impairment cases showed clusters of increased cortical microglial activation accompanying the amyloid. There was a positive correlation between levels of amyloid load and 11C-(R)-PK11195 binding potentials at a voxel level within subregions of frontal, parietal and temporal cortices. 11C-(R)-PK11195 positron emission tomography reveals increased inflammation in a majority of amyloid positive mild cognitive impairment cases, its cortical distribution overlapping that of amyloid deposition.

White matter biomarkers from fast protocols using axially symmetric diffusion kurtosis imaging.

White matter tract integrity (WMTI) can characterize brain microstructure in areas with highly aligned fiber bundles. Several WMTI biomarkers have now been validated against microscopy and provided promising results in studies of brain development and aging, as well as in a number of brain disorders. Currently, WMTI is mostly used in dedicated animal studies and clinical studies of slowly progressing diseases, and has not yet emerged as a routine clinical tool. To this end, a less data intensive experimental method would be beneficial by enabling high resolution validation studies, and ease clinical applications by speeding up data acquisition compared with typical diffusion kurtosis imaging (DKI) protocols utilized as part of WMTI imaging. Here, we evaluate WMTI based on recently introduced axially symmetric DKI, which has lower data demand than conventional DKI. We compare WMTI parameters derived from conventional DKI with those calculated analytically from axially symmetric DKI. We employ numerical simulations, as well as data from fixed rat spinal cord (one sample) and in vivo human (three subjects) and rat brain (four animals). Our analysis shows that analytical WMTI based on axially symmetric DKI with sparse data sets (19 images) produces WMTI metrics that correlate strongly with estimates based on traditional DKI data sets (60 images or more). We demonstrate the preclinical potential of the proposed WMTI technique in in vivo rat brain (300 µm isotropic resolution with whole brain coverage in a 1 h acquisition). WMTI parameter estimates are subject to a duality leading to two solution branches dependent on a sign choice, which is currently debated. Results from both of these branches are presented and discussed throughout our analysis. The proposed fast WMTI approach may be useful for preclinical research and e.g. clinical evaluation of patients with traumatic white matter injuries or symptoms of neurovascular or neuroinflammatory disorders.

Experimental considerations for fast kurtosis imaging.

PURPOSE: The clinical use of kurtosis imaging is impeded by long acquisitions and postprocessing. Recently, estimation of mean kurtosis tensor W¯ and mean diffusivity ( D¯) was made possible from 13 distinct diffusion weighted MRI acquisitions (the 1-3-9 protocol) with simple postprocessing. Here, we analyze the effects of noise and nonideal diffusion encoding, and propose a new correction strategy. We also present a 1-9-9 protocol with increased robustness to experimental imperfections and minimal additional scan time. This refinement does not affect computation time and also provides a fast estimate of fractional anisotropy (FA). THEORY AND METHODS: 1-3-9/1-9-9 data are acquired in rat and human brains, and estimates of D¯, FA, W¯ from human brains are compared with traditional estimates from an extensive diffusion kurtosis imaging data set. Simulations are used to evaluate the influence of noise and diffusion encodings deviating from the scheme, and the performance of the correction strategy. Optimal b-values are determined from simulations and data. RESULTS: Accuracy and precision in D¯ and W¯ are comparable to nonlinear least squares estimation, and is improved with the 1-9-9 protocol. The compensation strategy vastly improves parameter estimation in nonideal data. CONCLUSION: The framework offers a robust and compact method for estimating several diffusion metrics. The protocol is easily implemented. Magn Reson Med 76:1455-1468, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

A NO way to BOLD? Dietary nitrate alters the hemodynamic response to visual stimulation.

Neurovascular coupling links neuronal activity to vasodilation. Nitric oxide (NO) is a potent vasodilator, and in neurovascular coupling NO production from NO synthases plays an important role. However, another pathway for NO production also exists, namely the nitrate-nitrite-NO pathway. On this basis, we hypothesized that dietary nitrate (NO3-) could influence the brain's hemodynamic response to neuronal stimulation. In the present study, 20 healthy male participants were given either sodium nitrate (NaNO3) or sodium chloride (NaCl) (saline placebo) in a crossover study and were shown visual stimuli based on the retinotopic characteristics of the visual cortex. Our primary measure of the hemodynamic response was the blood oxygenation level dependent (BOLD) response measured with high-resolution functional magnetic resonance imaging (0.64×0.64×1.8 mm) in the visual cortex. From this response, we made a direct estimate of key parameters characterizing the shape of the BOLD response (i.e. lag and amplitude). During elevated nitrate intake, corresponding to the nitrate content of a large plate of salad, both the hemodynamic lag and the BOLD amplitude decreased significantly (7.0±2% and 7.9±4%, respectively), and the variation across activated voxels of both measures decreased (12.3±4% and 15.3±7%, respectively). The baseline cerebral blood flow was not affected by nitrate. Our experiments demonstrate, for the first time, that dietary nitrate may modulate the local cerebral hemodynamic response to stimuli. A faster and smaller BOLD response, with less variation across local cortex, is consistent with an enhanced hemodynamic coupling during elevated nitrate intake. These findings suggest that dietary patterns, via the nitrate-nitrite-NO pathway, may be a potential way to affect key properties of neurovascular coupling. This could have major clinical implications, which remain to be explored.

From Vivaldi to Beatles and back: predicting lateralized brain responses to music.

We aimed at predicting the temporal evolution of brain activity in naturalistic music listening conditions using a combination of neuroimaging and acoustic feature extraction. Participants were scanned using functional Magnetic Resonance Imaging (fMRI) while listening to two musical medleys, including pieces from various genres with and without lyrics. Regression models were built to predict voxel-wise brain activations which were then tested in a cross-validation setting in order to evaluate the robustness of the hence created models across stimuli. To further assess the generalizability of the models we extended the cross-validation procedure by including another dataset, which comprised continuous fMRI responses of musically trained participants to an Argentinean tango. Individual models for the two musical medleys revealed that activations in several areas in the brain belonging to the auditory, limbic, and motor regions could be predicted. Notably, activations in the medial orbitofrontal region and the anterior cingulate cortex, relevant for self-referential appraisal and aesthetic judgments, could be predicted successfully. Cross-validation across musical stimuli and participant pools helped identify a region of the right superior temporal gyrus, encompassing the planum polare and the Heschl's gyrus, as the core structure that processed complex acoustic features of musical pieces from various genres, with or without lyrics. Models based on purely instrumental music were able to predict activation in the bilateral auditory cortices, parietal, somatosensory, and left hemispheric primary and supplementary motor areas. The presence of lyrics on the other hand weakened the prediction of activations in the left superior temporal gyrus. Our results suggest spontaneous emotion-related processing during naturalistic listening to music and provide supportive evidence for the hemispheric specialization for categorical sounds with realistic stimuli. We herewith introduce a powerful means to predict brain responses to music, speech, or soundscapes across a large variety of contexts.

Experimentally and computationally fast method for estimation of a mean kurtosis.

PURPOSE: Results from several recent studies suggest the magnetic resonance diffusion-derived metric mean kurtosis (MK) to be a sensitive marker for tissue pathology; however, lengthy acquisition and postprocessing time hamper further exploration. The purpose of this study is to introduce and evaluate a new MK metric and a rapid protocol for its estimation. METHODS: The protocol requires acquisition of 13 standard diffusion-weighted images, followed by linear combination of log diffusion signals, thus avoiding nonlinear optimization. The method was evaluated on an ex vivo rat brain and an in vivo human brain. Parameter maps were compared with MK estimated from a standard diffusion kurtosis imaging (DKI) data set comprising 160 diffusion-weighted images. RESULTS: The new MK displays remarkably similar contrast to MK, and the proposed protocol acquires the necessary data in less than 1 min for full human brain coverage, with a postprocessing time of a few seconds. Scan-rescan reproducibility was comparable with MK. CONCLUSION: The framework offers a robust and rapid method for estimating MK, with a protocol easily adapted on commercial scanners, as it requires only minimal modification of standard diffusion-weighting protocols. These properties make the method feasible in practically any clinical setting.

Clipped DeepControl: Deep neural network two-dimensional pulse design with an amplitude constraint layer.

Advanced radio-frequency pulse design used in magnetic resonance imaging has recently been demonstrated with deep learning of (convolutional) neural networks and reinforcement learning. For two-dimensionally selective radio-frequency pulses, the (convolutional) neural network pulse prediction time (a few milliseconds) was in comparison more than three orders of magnitude faster than the conventional optimal control computation. The network pulses were from the supervised training capable of compensating scan-subject dependent inhomogeneities of B0 and B1+ fields. Unfortunately, the network presented with a small percentage of pulse amplitude overshoots in the test subset, despite the optimal control pulses used in training were fully constrained. Here, we have extended the convolutional neural network with a custom-made clipping layer that completely eliminates the risk of pulse amplitude overshoots, while preserving the ability to compensate for the inhomogeneous field conditions.

Executive Control and Associated Brain Activity in Children With Familial High-Risk of Schizophrenia or Bipolar Disorder: A Danish Register-based Study.

BACKGROUND AND HYPOTHESES: Impaired executive control is a potential prognostic and endophenotypic marker of schizophrenia (SZ) and bipolar disorder (BP). Assessing children with familial high-risk (FHR) of SZ or BP enables characterization of early risk markers and we hypothesize that they express impaired executive control as well as aberrant brain activation compared to population-based control (PBC) children. STUDY DESIGN: Using a flanker task, we examined executive control together with functional magnetic resonance imaging (fMRI) in 11- to 12-year-old children with FHR of SZ (FHR-SZ) or FHR of BP (FHR-BP) and PBC children as part of a register-based, prospective cohort-study; The Danish High Risk and Resilience study-VIA 11. STUDY RESULTS: We included 85 (44% female) FHR-SZ, 63 (52% female) FHR-BP and 98 (50% female) PBC in the analyses. Executive control effects, caused by the spatial visuomotor conflict, showed no differences between groups. Bayesian ANOVA of reaction time (RT) variability, quantified by the coefficient of variation (CVRT), revealed a group effect with similarly higher CVRT in FHR-BP and FHR-SZ compared to PBC (BF10 = 6.82). The fMRI analyses revealed no evidence for between-group differences in task-related brain activation. Post hoc analyses excluding children with psychiatric illness yielded same results. CONCLUSION: FHR-SZ and FHR-BP at age 11-12 show intact ability to resolve a spatial visuomotor conflict and neural efficacy. The increased variability in RT may reflect difficulties in maintaining sustained attention. Since variability in RT was independent of existing psychiatric illness, it may reflect a potential endophenotypic marker of risk.