BOLD Data Research Articles

Functional brain network architecture supporting the learning of social networks in humans

Most humans have the good fortune to live their lives embedded in richly structured social groups. Yet, it remains unclear how humans acquire knowledge about these social structures to successfully navigate social relationships. Here we address this knowledge gap with an interdisciplinary neuroimaging study drawing on recent advances in network science and statistical learning. Specifically, we collected BOLD MRI data while participants learned the community structure of both social and non-social networks, in order to examine whether the learning of these two types of networks was differentially associated with functional brain network topology. We found that participants learned the community structure of the networks, as evidenced by a slower reaction time when a trial moved between communities than when a trial moved within a community. Learning the community structure of social networks was also characterized by significantly greater functional connectivity of the hippocampus and temporoparietal junction when transitioning between communities than when transitioning within a community. Furthermore, temporoparietal regions of the default mode were more strongly connected to hippocampus, somatomotor, and visual regions for social networks than for non-social networks. Collectively, our results identify neurophysiological underpinnings of social versus non-social network learning, extending our knowledge about the impact of social context on learning processes. More broadly, this work offers an empirical approach to study the learning of social network structures, which could be fruitfully extended to other participant populations, various graph architectures, and a diversity of social contexts in future studies.

Correlation between blood oxygen level dependent fMRI signal and GABA content in anterior cingulate cortex after acupuncture of Hegu (LI4)

To explore the correlation between blood oxygen level dependent functional magnetic resonance imaging (BOLD-fMRI) signal and neurotransmitter γ-aminobutyric acid (GABA) concentration in the prefrontal cortex area after acupuncture or Von Frey filament stimulation (epidermal stimulation) at the right Hegu (LI4). A total of 76 healthy volunteers (23 men and 53 women, 24.5±1.4 years in age) were recruited in the pre-sent study. Each volunteer received two sessions of fMRI magnetic resonance scanning (MRS) examinations, with an interval of one week between two sessions. The MRI scan sequences included pre-task MRS, resting state BOLD and task MRS, BOLD. A region of Interest (ROI) of 35 mm×30 mm×25 mm was located at the bilateral medial prefrontal cortex areas. In the two sessions of examinations, the right LI4 point was stimulated by manual acupuncture or Von Frey filament-pressing. The tasks were designed as the block design. Each block contained 3 intermittent acupoint stimulations, lasting 30 s in each stimulation and with two minutes' pause between two stimulations. The MRS data were processed by using Linear Combination (LC) Model software (for assessing GABA content), and the BOLD data of fMRI was analyzed by using SPM12 software (comparison within each group), REST1.8 (comparison between two groups), separately. Extensive deactivations were induced by both stimulations, mainly involving the midline regions as the medial prefrontal lobe, and limbic lobe. The deactivation effect of manual acupuncture stimulation was more extensive and intensive than that of Von Frey filament stimulation, especially in the medial prefrontal lobe. Data from 66 volunteers (after exclusion of 10 participants due to bigger standard deviation of GABA/Glx) showed no marked correlation between the GABA concentration and BOLD activation in the anterior cingulate cortex area in both groups(manual acupuncture stimulation group: r=－0.07, －0.08, 0.04; P=0.57, 0.88, 0.74; Von Frey filament epidermal stimulation group: r=－0.10, －0.09, －0.01; P=0.43, 0.46, 0.96). Acupuncture of LI4 elicits a stronger and broader negative activation effect in the limbic-paralimbic-neocortical network including the medial prefrontal cortex in comparison with Von Frey filament stimulation, but no apparent correlation was found between the GABA concentration and BOLD activation in the anterior cingulate cortex after manual acupuncture and Von Frey stimulation.

Group representative brain connectivity model of episodic encoding using large fMRI dataset

Episodic memory is autobiographical memory crucial to human cognitive function. Brain connectivity modeling is an essential tool for describing brain function of interest. While a large body of research has focused on analyzing functional brain connectivity, most studies has focused on a connectivity of an individual. Brain connectivity studies are usually based on functional Magnetic Resonance Imaging (fMRI) which often involved many subjects. Only a few researches have focused on group level connectivity. We employ a framework called Tigramite to estimate causal interaction and model episodic memory connectivity on Human Connectome Project (HCP) BOLD data. Regions of interest are identified by performing fMRI univariate group subtraction analysis on working memory task-fMRI data using subsequent memory test paradigm. From each resulting individual connectivity graphs, we construct a group representative graph by performing median aggregation on each corresponding edges and nodes of each individual graphs. However, there is no established method to measure a quality of the group representative graph. So, we propose the use of Levenshtein distance as a measurement to validate the group representative graph if it represents general characteristics of each individual graphs in the population.

Alerting, Orienting, and Executive Control: The Effect of Bilingualism and Age on the Subcomponents of Attention.

Life-long experience of using two or more languages has been shown to enhance cognitive control abilities in young and elderly bilinguals in comparison to their monolingual peers. This advantage has been found to be larger in older adults in comparison to younger adults, suggesting that bilingualism provides advantages in cognitive control abilities. However, studies showing this effect have used a variety of tasks (Simon Task, Stroop task, Flanker Task), each measuring different subcomponents of attention and raising mixed results. At the same time, attention is not a unitary function but comprises of subcomponents which can be distinctively addressed within the Attention Network Test (ANT) (1, 2). The purpose of this work was to examine the neurofunctional correlates of the subcomponents of attention in healthy young and elderly bilinguals taking into account the L2 age of acquisition, language usage, and proficiency. Participants performed an fMRI version of the ANT task, and speed, accuracy, and BOLD data were collected. As expected, results show slower overall response times with increasing age. The ability to take advantage of the warning cues also decreased with age, resulting in reduced alerting and orienting abilities in older adults. fMRI results showed an increase in neurofunctional activity in the frontal and parietal areas in elderly bilinguals when compared to young bilinguals. Furthermore, higher L2 proficiency correlated negatively with activation in frontal area, and that faster RTs correlated negatively with activation in frontal and parietal areas. Such a correlation, especially with L2 proficiency was not present in young bilinguals and provides evidence for a bilingual advantage in the alerting subcomponent of attention that characterizes elderly bilinguals' performance. This study thus provides extra details about the bilingual advantage in the subcomponent of attention, in older bilinguals. Consequently, speaking more than one language impacts cognition and the brain later in life.

How to model the neurocognitive dynamics of decision making: A methodological primer with ACT-R.

Higher cognitive functions are the product of a dynamic interplay of perceptual, mnemonic, and other cognitive processes. Modeling the interplay of these processes and generating predictions about both behavioral and neural data can be achieved with cognitive architectures. However, such architectures are still used relatively rarely, likely because working with them comes with high entry-level barriers. To lower these barriers, we provide a methodological primer for modeling higher cognitive functions and their constituent cognitive subprocesses with arguably the most developed cognitive architecture today-ACT-R. We showcase a principled method of generating individual response time predictions, and demonstrate how neural data can be used to refine ACT-R models. To illustrate our approach, we develop a fully specified neurocognitive model of a prominent strategy for memory-based decisions-the take-the-best heuristic-modeling decision making as a dynamic interplay of perceptual, motor, and memory processes. This implementation allows us to predict the dynamics of behavior and the temporal and spatial patterns of brain activity. Moreover, we show that comparing the predictions for brain activity to empirical BOLD data allows us to differentiate competing ACT-R implementations of take the best.

Color contrast adaptation: fMRI fails to predict behavioral adaptation

fMRI-adaptation is a valuable tool for inferring the selectivity of neural responses. Here we use it in human color vision to test the selectivity of responses to S-cone opponent (blue-yellow), L/M-cone opponent (red-green), and achromatic (Ach) contrast across nine regions of interest in visual cortex. We measure psychophysical adaptation, using comparable stimuli to the fMRI-adaptation, and find significant selective adaptation for all three stimulus types, implying separable visual responses to each. For fMRI-adaptation, we find robust adaptation but, surprisingly, much less selectivity due to high levels of cross-stimulus adaptation in all conditions. For all BY and Ach test/adaptor pairs, selectivity is absent across all ROIs. For RG/Ach stimulus pairs, this paradigm has previously shown selectivity for RG in ventral areas and for Ach in dorsal areas. For chromatic stimulus pairs (RG/BY), we find a trend for selectivity in ventral areas. In conclusion, we find an overall lack of correspondence between BOLD and behavioral adaptation suggesting they reflect different aspects of the underlying neural processes. For example, raised cross-stimulus adaptation in fMRI may reflect adaptation of the broadly-tuned normalization pool. Finally, we also identify a longer-timescale adaptation (1h) in both BOLD and behavioral data. This is greater for chromatic than achromatic contrast. The longer-timescale BOLD effect was more evident in the higher ventral areas than in V1, consistent with increasing windows of temporal integration for higher-order areas.

Protracted Developmental Trajectory of Shape Processing along the Two Visual Pathways.

Studies of the emergence of shape representations in childhood have focused primarily on the ventral visual pathway. Importantly, however, there is increasing evidence that, in adults, the dorsal pathway also represents shape-based information. These dorsal representations follow a gradient with more posterior regions being more shape-sensitive than anterior regions and with representational similarity in some posterior regions that is equivalent to that observed in some ventral regions. To explore the emergence and nature of dorsal shape representations in development, we acquired both fMRI BOLD signals and behavioral data in children (aged 8-10 years) using a parametric image scrambling paradigm. Children exhibited adult-like large-scale organization of shape processing along both ventral and dorsal pathways. Also, as in adults, the activation profiles of children's posterior dorsal and ventral regions were correlated with recognition performance, reflecting a possible contribution of these signals to perception. There were age-related changes, however, with children being more affected by the distortion of shape information than adults, both behaviorally and neurally. These findings reveal that shape-processing mechanisms along both dorsal and ventral pathways are subject to a protracted developmental trajectory.

Improving the Assessment of Breath-Holding Induced Cerebral Vascular Reactivity Using a Multiband Multi-echo ASL/BOLD Sequence

Breath holding (BH) is a viable vasodilatory stimulus for calculating functional MRI-derived cerebral vascular reactivity (CVR). The BH technique suffers from reduced repeatability compared with gas inhalation techniques; however, extra equipment is needed to perform gas inhalation techniques, and this equipment is not available at all institutions. This study aimed to determine the sensitivity and repeatability of BH activation and CVR using a multiband multi-echo simultaneous arterial spin labelling/blood oxygenation level dependent (ASL/BOLD) sequence. Whole-brain images were acquired in 14 volunteers. Ten subjects returned for repeat imaging. Each subject performed four cycles of 16 s BH on expiration interleaved with paced breathing. Following standard preprocessing, the echoes were combined using a T2*-weighted approach. BOLD and ASL BH activation was computed, and CVR was then determined as the percent signal change related to the activation. The “M” parameter from the Davis Model was also computed by incorporating the ASL signal. Our results showed higher BH activation strength, volume, and repeatability for the combined multi-echo (MEC) data compared with the single-echo data. MEC CVR also had higher repeatability, sensitivity, specificity, and reliability compared with the single-echo BOLD data. These data support the usefulness of an MBME ASL/BOLD acquisition for BH CVR and M measurements.

Impaired brain white matter and functional networks in healthy individuals with auditory verbal hallucinations.

Impaired brain white matter and functional networks in healthy individuals with auditory verbal hallucinations.

250. A complete computational framework for simulating and inferring directed neuronal coupling under haemdynamic convolution

Purpose The use of Multivariate Granger Causality (MVGC) in estimating directed BOLD connectivity is still controversial, mostly because of the intrinsic low temporal resolution of BOLD data and the slow haemodynamic response of the neurovascular coupling. Characterizing MVGC detection performances in silico could allow us to understand the confidence of the results when applying MVGC in vivo. Methods and materials In this contribution we evaluate MVGC on synthetically generated BOLD data from complex network models based on Izhikevich neuronal populations interlinked by realistic neuronal fiber bundles which exert compounded directed influences and cascade into Baloon-like neurovascular coupling models. We use massively parallel computing to generate synthetic BOLD data from a family of 20-node networks. Each node represents a small cortical volume (see Fig. 1 for a graphical summary). MVGC was then assesed on in vivo fMRI data (HCP 100 unrelated subjects). After pre-processing the average BOLD signal was extracted in 116 regions of interest (ROIs) using the AAL atlas. Results In silico, top 1st percentile of a BOLD connectivity matrix has a PPV very close to 1. Fig. 2 shows the elements of the inter-subject median MVGC matrix between the 116 ROIs extracted from the AAL atlas and the inter-subject median of normalized MVGC. Conclusion We have shown in silico that the, and demonstrate in HCP data that functional interactions between parietal and prefrontal cortices are not symmetrical, but consists of directional connectivity from parietal areas to prefrontal cortices rather than vice versa [1] , [2] .

0137 Bold fMRI Correlates Of Intermittent Sympathetic Vasoconstriction During Light Sleep

Variations in sympathetic and parasympathetic activity during sleep can lead to fluctuations in heart rate and vascular tone, potentially confounding fMRI measurements of brain activity that rely on hemodynamic signals. To investigate this, photo-plethysmography (PPG) based measurements of peripheral vasoconstriction were correlated with fMRI signals acquired during an overnight sleep study. BOLD fMRI data was obtained at 3T with gradient-echo-EPI (flip-angle=900, repeatition-time=3s, echo-time=36ms, voxel-size=2.5x2.5x2mm3, matrix-size=96x70x50, acceleration-factor=2). EEG and ECG were acquired concurrently with the fMRI with a 64-channel recorder (61 EEG scalp, 2 electro-oculography, and 1 ECG electrodes), synchronized to the MRI system-clock. Heart rate (HR), vascular tone inferred from PPG signal amplitude (AMP), and respiratory volume (RV) were derived from the PPG and chest belt signals. Initial inspection of all data (n=16) showed, primarily during N1/N2 sleep, striking variations in AMP, consisting of intermittently occurring 10-15s drops accompanied by a biphasic change in HR. Based on this a subset of data was selected (~20% of the scans) that had a high incidence of AMP drops and fMRI without motion artifacts. AMP drops had a strong correlate in the fMRI signal in both grey-matter (GM) and white-matter (WM). The covariation of fMRI signal and PPG-AMP often exceeded that with the more conventional physiological measures of HR and RV. Voxel-vise correlations between PPG-AMP and fMRI signals showed a striking negative correlation in central WM and around medullary-veins at 0-lag, turning positive after about 3-6s. In GM, maximum positive correlation was observed at around 6s time-lags. Intermittent AMP drops are interpreted as systemic vasoconstrictive events, possibly relating to correlations between EEG measures of arousal and AMP drops, as previously observed during sleep (Ackner et al., 1957). The fMRI effects suggest that this vasoconstriction also involves the central-nervous-system vasculature. The lag-dependent characteristic of the WM signal can be explained by a temporal mismatch between blood-volume and blood-oxygenation effects originating from vascular transit delays. A similar mechanism may explain previous findings of WM fMRI signals during both task- and resting-state fMRI. Intramural Research Program of the NINDS.

Distribution of Trichaleurina javanica (Rehm) M. Carbone, Agnello & P. Alvarado (Chorioactidaceae) in India

During the recent field visits to Saurashtra regions of Western India, one of the interesting fungi i.e. Trichaleurina javanica (Rehm) M. Carbone, Agnello & P. Alvarado (Chorioactidaceae, order Pezizales) was collected from Sarkhadiya Hanuman and Sasan (Gir Forest, India). Further confirmation of the identity was carried out by using molecular methods with its DNA barcoding. Review of literature showed that this species was previously reported from India under a different name; the collection here studied is the first one molecularly confirmed. Nucleotide sequence obtained during molecular analysis is submitted into NCBI and is the first record at BOLD data system for its DNA barcode (BOLD ID KSRF-0019).

Spatial-temporal-spectral EEG patterns of BOLD functional network connectivity dynamics

Objective. Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during electroencephalogram (EEG) data analysis may leave part of the neural activity unrecognized. We propose an approach that blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. Approach. The blind decomposition of EEG spectrogram by parallel factor analysis has been shown to be a useful technique for uncovering patterns of neural activity. The simultaneously acquired BOLD fMRI data were decomposed by independent component analysis. Dynamic functional connectivity was computed on the component’s time series using a sliding window correlation, and between-network connectivity states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of between-network connectivity states and the fluctuations of EEG spectral patterns. Main results. We found three patterns related to the dynamics of between-network connectivity states. The first pattern has dominant peaks in the alpha, beta, and gamma bands and is related to the dynamics between the auditory, sensorimotor, and attentional networks. The second pattern, with dominant peaks in the theta and low alpha bands, is related to the visual and default mode network. The third pattern, also with peaks in the theta and low alpha bands, is related to the auditory and frontal network. Significance. Our previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. In this study, we suggest that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral constraints are applied on the EEG data.

Initiating DNA barcoding of Eastern Mediterranean deep-sea biota

Preliminary results of DNA barcoding survey of deep-sea mega-faunal biota are presented, collected by trawl and gillnet off the Israeli coast (SE Mediterranean, depths 700 to 1500 meters) during 2012-2013. 846 organisms were identified to 37 species, mainly fish and decapod crustaceans. The most abundant species were the blackmouth catshark Galeus melastomus, the cosmopolitan decapod Polycheles typhlops and the bivalve Abra longicallus. Two species were sampled for the first time from the southern Levant- the long armed chiroteuthid squid Chiroteuthis veranyi and the common mora, Mora moro. Four of the 18 fish species and two of the 10 crustacean species were abundant, representing 78% and 61%, respectively, of the organisms collected. Most other species are represented by fewer than 10 individuals. PCR products for the cytochrome c oxidase sub unit I (COI) gene for the 37 species were successfully sequenced. The identified and vouchered individuals are stored at the Steinhardt Museum of Natural History (Tel Aviv University, Israel) and their COI sequences were uploaded into the BoLD universal data center as part of the national marine barcoding project. The COI sequences of Acanthephyra eximia, Gryphus vitreus, Galeodea echinophora, Mesothuria intestinalis and Astropecten irregularis, constitute first records of these species in BoLD. When compared to the COI sequences in BoLD, the present results reveal some inconsistency in species identification, an outcome that should be taken into consideration primarily once the taxonomical verifications of collected taxa are elusive. This study is the first step in DNA barcoding of the Levant’s little-known benthic deep-sea fauna.

Multivariate Granger causality unveils directed parietal to prefrontal cortex connectivity during task-free MRI

While a large body of research has focused on the study of functional brain “connectivity”, few investigators have focused on directionality of brain-brain interactions which, in spite of the mostly bidirectional anatomical substrates, cannot be assumed to be symmetrical. We employ a multivariate Granger Causality-based approach to estimating directed in-network interactions and quantify its advantages using extensive realistic synthetic BOLD data simulations to match Human Connectome Project (HCP) data specification. We then apply our framework to resting state functional MRI (rs-fMRI) data provided by the HCP to estimate the directed connectome of the human brain. We show that the functional interactions between parietal and prefrontal cortices commonly observed in rs-fMRI studies are not symmetrical, but consists of directional connectivity from parietal areas to prefrontal cortices rather than vice versa. These effects are localized within the same hemisphere and do not generalize to cross-hemispheric functional interactions. Our data are consistent with neurophysiological evidence that posterior parietal cortices involved in processing and integration of multi-sensory information modulate the function of more anterior prefrontal regions implicated in action control and goal-directed behaviour. The directionality of functional connectivity can provide an additional layer of information in interpreting rs-fMRI studies both in health and disease.

T141. CHARACTERIZATION OF HEMODYNAMIC ALTERATIONS IN SCHIZOPHRENIA AND BIPOLAR DISORDER AND THEIR EFFECT ON RESTING-STATE FUNCTIONAL CONNECTIVITY

BackgroundSchizophrenia (SZ) and bipolar disorder (BP) have both common and distinct clinical symptomatology. Their neural bases have been explored using functional connectivity between brain regions using resting-state functional magnetic resonance imaging (rs-fMRI). However, fMRI is an indirect measure of neural activity and is modeled as a convolution of the hemodynamic response function (HRF) and latent neural activity. The HRF varies across both individuals and different brain regions within an individual. Consequently, it is plausible for two brain regions to appear synchronized in the BOLD space while being desynchronized in latent neural space and vice versa.MethodsIn order to address this issue, we estimated voxel-specific HRFs by deconvolving rs-fMRI time series obtained from SZ (N=19), BP (N=35) and matched healthy individuals (N=34). The shape of the HRF was significantly different between the three groups in many regions previously implicated in SZ and BP. Specifically, we found voxels within the mediodorsal, habenular and central lateral nuclei of the thalamus to have HRFs with aberrations in all three of its shape parameters: time to peak, response height and full width half max. Therefore, we defined this region as the seed, estimated seed-based functional connectivity maps in all three groups and characterized pairwise differences between them. Further, we performed a 2-way ANOVA and estimated regions exhibiting an interaction between the group and deconvolution factors.ResultsWe found voxels within the mediodorsal, habenular and central lateral nuclei of the thalamus to have HRFs with aberrations in all three of its shape parameters: time to peak, response height and full width half max. Results indicated that functional connectivity differences between the groups are inferred significantly differently with raw BOLD and deconvolved latent neural time series. Since the variability of the HRF could be driven by both neural and non-neural factors, we feel that it is preferable to estimate functional connectivity using deconvolved data.DiscussionNeurochemicals such as GABA, glutamate, serotonin and nitric oxide have a role in controlling neurosignaling pathways underlying neurovascular coupling and hence the HRF. Previously documented alterations of these neurochemicals in SZ and BP could, at least in part, explain the significant differences in HRF shapes observed between the groups. Functional connectivity group differences obtained from raw BOLD data must be interpreted cautiously in the light of systematic HRF differences between groups.

Gray and white matter integrity influence TMS signal propagation: a multimodal evaluation in cocaine-dependent individuals

Transcranial magnetic stimulation (TMS) can stimulate cortical and subcortical brain regions. However, in order to reach subcortical targets, intact monosynaptic connections are required. The goal of this investigation was to evaluate the contribution of white matter integrity and gray matter volume to frontal pole TMS-evoked striatal activity in a large cohort of chronic cocaine users. 49 cocaine users received single pulses of TMS to the frontal pole while BOLD data were acquired – a technique known as interleaved TMS/fMRI. Diffusion tensor imaging and voxel-based morphometry were used to quantify white matter integrity and gray matter volume (GMV), respectively. Stepwise regression was used to evaluate the contribution of clinical and demographic variables to TMS-evoked BOLD. Consistent with previous studies, frontal pole TMS evoked activity in striatum and salience circuitry. The size of the TMS-evoked response was related to fractional anisotropy between the frontal pole and putamen and GMV in the left frontal pole and left ACC. This is the first study to demonstrate that the effect of TMS on subcortical activity is dependent upon the structural integrity of the brain. These data suggest that these structural neuroimaging data types are biomarkers for TMS-induced mobilization of the striatum.

High-energy brain dynamics during anesthesia-induced unconsciousness.

Characterizing anesthesia-induced alterations to brain network dynamics provides a powerful framework to understand the neural mechanisms of unconsciousness. To this end, increased attention has been directed at how anesthetic drugs alter the functional connectivity between brain regions as defined through neuroimaging. However, the effects of anesthesia on temporal dynamics at functional network scales is less well understood. Here, we examine such dynamics in view of the free-energy principle, which postulates that brain dynamics tend to promote lower energy (more organized) states. We specifically engaged the hypothesis that such low-energy states play an important role in maintaining conscious awareness. To investigate this hypothesis, we analyzed resting-state BOLD fMRI data from human volunteers during wakefulness and under sevoflurane general anesthesia. Our approach, which extends an idea previously used in the characterization of neuron-scale populations, involves thresholding the BOLD time series and using a normalized Hamiltonian energy function derived from the Ising model. Our major finding is that the brain spends significantly more time in lower energy states during eyes-closed wakefulness than during general anesthesia. This effect is especially pronounced in networks thought to be critical for maintaining awareness, suggesting a crucial cognitive role for both the structure and the dynamical landscape of these networks.

Quantitative Measurement of Oxygen Extraction Fraction (OEF) Using Respiratory Modulated Perfusion MRI

Background: Measurement of oxygen consumption can give useful information of brain functionality in health and disease. To have a better understanding of normal physiology in all conditions (rest or functional tasks), development of accurate brain oxygen mapping is essential. This mapping could also be a great help in managing pathological conditions with disturbance in oxygen supply. One of the most important hemodynamic parameters of the brain is oxygen extraction fraction (OEF). By development of blood oxygen level dependent magnetic resonance imaging (BOLD MRI) in imaging, several methods have been proposed for measuring this parameter. The latest methods are mostly based on hypercapnic and hyperoxic stimulus. Objectives: Here, we presented a new method with hypercapnic and hyperoxic stimulus and using BOLD and dynamic susceptibility contrast (DSC) perfusion imaging instead of arterial spin labelling (ASL). Materials and Methods: A 3T Siemens Trio Tim Scanner was used for imaging five patients (three males and two females) who were recruited for this experiment. Four set of T1 data, BOLD data and two DSC-perfusions (two injections) were applied to each subject. Gas manipulation was applied while acquiring BOLD data and one of the DSC-perfusion was done in hyperoxic condition. Gas manipulation was a combination of hypercapnic, hyperoxic and normoxic conditions in a total of 13 minutes. The DSC data was analyzed using PMA (ASIST) software to calculate cerebral blood flow (CBF) and using its results with the BOLD data, OEF was calculated by MATLAB coding. All preprocessing was done with the SPM12 (MATLAB). Results: Comparable results were acquired for OEF with previous studies. The mean value of estimated OEF for gray matter (GM), white matter (WM) and whole brain is 0.46, 0.37, and 0.44, respectively which are within the expected range of normal condition. Conclusion: As the proposed method for OEF measurement uses a combination of hyperoxic and hypercapnic stimulus with BOLD and DSC-perfusion imaging, it could be considered the most available one in all MRI scanners and being a voxel wise method, it could give OEF value for any requested ROI.

Preterm birth leads to hyper-reactive cognitive control processing and poor white matter organization in adulthood

Individuals born preterm with very low birth weight (VLBW; birth weight ≤ 1500 g) are at high risk for perinatal brain injuries and deviant brain development, leading to increased chances of later cognitive, emotional, and behavioral problems. Here we investigated the neuronal underpinnings of both reactive and proactive cognitive control processes in adults with VLBW. We included 32 adults born preterm with VLBW (before 37th week of gestation) and 32 term-born controls (birth weight ≥10th percentile for gestational age) between 22 and 24 years of age that have been followed prospectively since birth. Participants performed a well-validated Not-X continuous performance test (CPT) adapted for use in a mixed block- and event-related fMRI protocol. BOLD fMRI and DTI data was acquired on a 3T scanner. Performance on the Not-X CPT was highly similar between groups. However, the VLBW group demonstrated hyper-reactive cognitive control processing and disrupted white matter organization. The hyper-reactive brain activation signature in VLBW adults was associated with lower gestational age, lower fluid intelligence score, and anxiety problems. Automated Multi-Atlas Tract Extraction (AutoMATE) analyses revealed that this disruption of normal brain function was accompanied by poorer white matter organization in the anterior thalamic radiation and the cingulum, as reflected in both reduced fractional anisotropy and increased mean diffusivity. These findings show that the preterm behavioral phenotype is associated with predominantly reactive-, rather than proactive cognitive control processing, as well as white matter abnormalities, that may underlie common difficulties that many preterm born individuals experience in everyday life.