Journal Sciences News
The Ocular Surface
1 May 2018
Probing the association between serotonin-1A autoreceptor binding and amygdala reactivity in healthy volunteers
Publication date: 1 May 2018
Source:NeuroImage, Volume 171 Author(s): Georg S. Kranz, Andreas Hahn, Christoph Kraus, Marie Spies, Verena Pichler, Johannes Jungwirth, Markus Mitterhauser, Wolfgang Wadsak, Christian Windischberger, Siegfried Kasper, Rupert Lanzenberger Introduction The serotonergic system modulates affect and is a target in the treatment of mood disorders. 5-HT1A autoreceptors in the raphe control serotonin release by means of negative feedback inhibition. Hence, 5-HT1A autoreceptor function should influence the serotonergic regulation of emotional reactivity in limbic regions. Previous findings suggest an inverse relationship between 5-HT1A autoreceptor binding and amygdala reactivity to facial emotional expressions. The aim of the current multimodal neuroimaging study was to replicate the previous finding in a larger cohort. Methods 31 healthy participants underwent fMRI as well as PET using the radioligand [carbonyl-11C]WAY-100635 to quantify 5-HT1A autoreceptor binding in the dorsal raphe. The binding potential (BPND) was quantified using the multilinear reference tissue model (MRTM2) and cerebellar white matter as reference tissue. Functional MRI was done at 3T using a well-established facial emotion discrimination task (EDT). Here, participants had to match the emotional valence of facial expressions, while in a control condition they had to match geometric shapes. Effects of 5-HT1A autoreceptor binding on amygdala reactivity were investigated using linear regression analysis with SPM8. Results Regression analysis between 5-HT1A autoreceptor binding and mean amygdala reactivity revealed no statistically significant associations. Investigating amygdala reactivity in a voxel-wise approach revealed a positive association in the right amygdala (peak-T
1 May 2018
False positive rates in surface-based anatomical analysis
Publication date: 1 May 2018
Source:NeuroImage, Volume 171 Author(s): Douglas N. Greve, Bruce Fischl The false positive rates (FPR) for surface-based group analysis of cortical thickness, surface area, and volume were evaluated for parametric and non-parametric clusterwise correction for multiple comparisons for a range of smoothing levels and cluster-forming thresholds (CFT) using real data under group assignments that should not yield significant results. For whole cortical surface analysis, thickness showed modest inflation in parametric FPRs above the nominal level (10% versus 5%). Surface area and volume FPRs were much higher (2030%). In the analysis of interhemispheric thickness asymmetries, FPRs were well controlled by parametric correction, but FPRs for surface area and volume asymmetries were still inflated. In all cases, non-parametric permutation adequately controlled the FPRs. It was found that inflated parametric FPRs were caused by violations in the parametric assumptions, namely a heavier-than-Gaussian spatial correlation. The non-Gaussian spatial correlation originates from anatomical features unique to individuals (e.g., a patch of cortex slightly thicker or thinner than average) and is not a by-product of scanning or processing. Thickness performed better than surface area and volume because thickness does not require a Jacobian correction.
1 May 2018
Altered reward learning and hippocampal connectivity following psychosocial stress
Publication date: 1 May 2018
Source:NeuroImage, Volume 171 Author(s): Onno Kruse, Isabell Tapia Le
1 May 2018
Human in-vivo brain magnetic resonance current density imaging (MRCDI)
Publication date: 1 May 2018
Source:NeuroImage, Volume 171 Author(s): Cihan G
1 May 2018
Predictive coding of visual object position ahead of moving objects revealed by time-resolved EEG decoding
Publication date: 1 May 2018
Source:NeuroImage, Volume 171 Author(s): Hinze Hogendoorn, Anthony N. Burkitt Due to the delays inherent in neuronal transmission, our awareness of sensory events necessarily lags behind the occurrence of those events in the world. If the visual system did not compensate for these delays, we would consistently mislocalize moving objects behind their actual position. Anticipatory mechanisms that might compensate for these delays have been reported in animals, and such mechanisms have also been hypothesized to underlie perceptual effects in humans such as the Flash-Lag Effect. However, to date no direct physiological evidence for anticipatory mechanisms has been found in humans. Here, we apply multivariate pattern classification to time-resolved EEG data to investigate anticipatory coding of object position in humans. By comparing the time-course of neural position representation for objects in both random and predictable apparent motion, we isolated anticipatory mechanisms that could compensate for neural delays when motion trajectories were predictable. As well as revealing an early neural position representation (lag 8090 ms) that was unaffected by the predictability of the object's trajectory, we demonstrate a second neural position representation at 140150 ms that was distinct from the first, and that was pre-activated ahead of the moving object when it moved on a predictable trajectory. The latency advantage for predictable motion was approximately 16
1 May 2018
Stereotypical modulations in dynamic functional connectivity explained by changes in BOLD variance
Publication date: 1 May 2018
Source:NeuroImage, Volume 171 Author(s): Katharina Glomb, Adri
1 May 2018
Convergence of spoken and written language processing in the superior temporal sulcus
Publication date: 1 May 2018
Source:NeuroImage, Volume 171 Author(s): Stephen M. Wilson, Alexa Bautista, Angelica McCarron Spoken and written language processing streams converge in the superior temporal sulcus (STS), but the functional and anatomical nature of this convergence is not clear. We used functional MRI to quantify neural responses to spoken and written language, along with unintelligible stimuli in each modality, and employed several strategies to segregate activations on the dorsal and ventral banks of the STS. We found that intelligible and unintelligible inputs in both modalities activated the dorsal bank of the STS. The posterior dorsal bank was able to discriminate between modalities based on distributed patterns of activity, pointing to a role in encoding of phonological and orthographic word forms. The anterior dorsal bank was agnostic to input modality, suggesting that this region represents abstract lexical nodes. In the ventral bank of the STS, responses to unintelligible inputs in both modalities were attenuated, while intelligible inputs continued to drive activation, indicative of higher level semantic and syntactic processing. Our results suggest that the processing of spoken and written language converges on the posterior dorsal bank of the STS, which is the first of a heterogeneous set of language regions within the STS, with distinct functions spanning a broad range of linguistic processes.
1 May 2018
Neural basis for reduced executive performance with hypoxic exercise
Publication date: 1 May 2018
Source:NeuroImage, Volume 171 Author(s): Genta Ochi, Yuhki Yamada, Kazuki Hyodo, Kazuya Suwabe, Takemune Fukuie, Kyeongho Byun, Ippeita Dan, Hideaki Soya While accumulating evidence suggests positive effects of exercise on executive function, such effects vary with environment. In particular, exercise in a hypoxic environment (hypobaric or normobaric hypoxia), leading to decreased oxygen supply, may dampen or cancel such effects. Thus, we further explore the relation between the effects of hypoxic exercise on executive function and their underlying neural mechanisms by monitoring changes of cortical activation patterns using functional near-infrared spectroscopy (fNIRS). Fifteen healthy participants performed color-word Stroop tasks (CWST) before and after a 10 min bout of moderate-intensity exercise (50%V
1 May 2018
Quenching of spontaneous fluctuations by attention in human visual cortex
Publication date: 1 May 2018
Source:NeuroImage, Volume 171 Author(s): Rotem Broday-Dvir, Shany Grossman, Edna Furman-Haran, Rafael Malach In the absence of a task, the human brain enters a mode of slow spontaneous fluctuations. A fundamental, unresolved question is whether these fluctuations are ongoing and thus persist during task engagement, or alternatively, are quenched and replaced by task-related activations. Here, we examined this issue in the human visual cortex, using fMRI. Participants were asked to either perform a recognition task of randomly appearing face and non-face targets (attended condition) or watch them passively (unattended condition). Importantly, in approximately half of the trials, all sensory stimuli were absent. Our results show that even in the absence of stimuli, spontaneous fluctuations were suppressed by attention. The effect occurred in early visual cortex as well as in fronto-parietal attention network regions. During unattended trials, the activity fluctuations were negatively linked to pupil diameter, arguing against attentional fluctuations as underlying the effect. The results demonstrate that spontaneous fluctuations do not remain unchanged with task performance, but are rather modulated according to behavioral and cognitive demands.
1 May 2018
Cortical hemodynamic changes during the Trier Social Stress Test: An fNIRS study
Publication date: 1 May 2018
Source:NeuroImage, Volume 171 Author(s): David Rosenbaum, Paula Hilsendegen, Mara Thomas, Florian B. Haeussinger, Florian G. Metzger, Hans-Christoph Nuerk, Andreas J. Fallgatter, Vanessa Nieratschker, Ann-Christine Ehlis The study of the stress response has been of great interest in the last decades due to its relationship to physical and mental health. Along with the technological progress in the neurosciences, different methods of stress induction have been developed for the special requirements regarding the acquisition of neuroimaging data. However, these paradigms often differ from ecologically valid stress inductions such as the Trier Social Stress Test (TSST) in substantial ways. In the study at hand, we used the rather robust optical imaging method of functional Near-infrared Spectroscopy (fNIRS) to assess brain activation during the TSST and two non-stressful control conditions. Additionally, we measured other stress parameters including the cortisol response and subjective stress ratings. As expected we found significant increases in subjective and physiological stress measures during the TSST in comparison to the baseline and control conditions. We found higher activation in parts of the cognitive control network (CCN) and dorsal attention network (DAN) comprising the dorsolateral prefrontal cortex, the inferior frontal gyrus and superior parietal cortex during the performance of the TSST in comparison to the control conditions. Further, calculation errors during the TSST as well as subjective and physiological stress parameters correlated significantly with the activation in the CCN. Our study confirms the validity of previous neuroimaging data obtained from adapted stress procedures by providing cortical activation data during a classical stress induction paradigm (i.e., the TSST) for the first time.
1 May 2018
Double dissociation of structure-function relationships in memory and fluid intelligence observed with magnetic resonance elastography
Publication date: 1 May 2018
Source:NeuroImage, Volume 171 Author(s): Curtis L. Johnson, Hillary Schwarb, Kevin M. Horecka, Matthew D.J. McGarry, Charles H. Hillman, Arthur F. Kramer, Neal J. Cohen, Aron K. Barbey Brain tissue mechanical properties, measured in vivo with magnetic resonance elastography (MRE), have proven to be sensitive metrics of neural tissue integrity. Recently, our group has reported on the positive relationship between viscoelasticity of the hippocampus and performance on a relational memory task in healthy young adults, which highlighted the potential of sensitive MRE measures for studying brain health and its relation to cognitive function; however, structure-function relationships outside of the hippocampus have not yet been explored. In this study, we examined the relationships between viscoelasticity of both the hippocampus and the orbitofrontal cortex and performance on behavioral assessments of relational memory and fluid intelligence. In a sample of healthy, young adults (N
1 May 2018
Predictive assessment of models for dynamic functional connectivity
Publication date: 1 May 2018
Source:NeuroImage, Volume 171 Author(s): S
1 May 2018
Brain state flexibility accompanies motor-skill acquisition
Publication date: 1 May 2018
Source:NeuroImage, Volume 171 Author(s): Pranav G. Reddy, Marcelo G. Mattar, Andrew C. Murphy, Nicholas F. Wymbs, Scott T. Grafton, Theodore D. Satterthwaite, Danielle S. Bassett Learning requires the traversal of inherently distinct cognitive states to produce behavioral adaptation. Yet, tools to explicitly measure these states with non-invasive imaging and to assess their dynamics during learning remain limited. Here, we describe an approach based on a distinct application of graph theory in which points in time are represented by network nodes, and similarities in brain states between two different time points are represented as network edges. We use a graph-based clustering technique to identify clusters of time points representing canonical brain states, and to assess the manner in which the brain moves from one state to another as learning progresses. We observe the presence of two primary states characterized by either high activation in sensorimotor cortex or high activation in a frontal-subcortical system. Flexible switching among these primary states and other less common states becomes more frequent as learning progresses, and is inversely correlated with individual differences in learning rate. These results are consistent with the notion that the development of automaticity is associated with a greater freedom to use cognitive resources for other processes. Taken together, our work offers new insights into the constrained, low dimensional nature of brain dynamics characteristic of early learning, which give way to less constrained, high-dimensional dynamics in later learning.
1 May 2018
Tracking behavioral and neural fluctuations during sustained attention: A robust replication and extension
Publication date: 1 May 2018
Source:NeuroImage, Volume 171 Author(s): Francesca C. Fortenbaugh, David Rothlein, Regina McGlinchey, Joseph DeGutis, Michael Esterman Novel paradigms have allowed for more precise measurements of sustained attention ability and fluctuations in sustained attention over time, as well as the neural basis of fluctuations and lapses in performance. However, in recent years, concerns have arisen over the replicability of neuroimaging studies and psychology more broadly, particularly given the typically small sample sizes. One recently developed paradigm, the gradual-onset continuous performance task (gradCPT) has been validated behaviorally in large samples of participants. Yet neuroimaging studies investigating the neural basis of performance on this task have only been collected in small samples. The present study completed both a robust replication of the original neuroimaging findings and extended previous results from the gradCPT task using a large sample of 140 Veteran participants. Results replicate findings that fluctuations in attentional stability are tracked over time by BOLD activity in task positive (e.g., dorsal and ventral attention networks) and task negative (e.g., default network) regions. Extending prior results, we relate this coupling between attentional stability and on-going brain activity to overall sustained attention ability and demonstrate that this coupling strength, along with across-network coupling, could be used to predict individual differences in performance. Additionally, the results extend previous findings by demonstrating that temporal dynamics across the default and dorsal attention networks are associated with lapse-likelihood on subsequent trials. This study demonstrates the reliability of the gradCPT, and underscores the utility of this paradigm in understanding attentional fluctuations, as well as individual variation and deficits in sustained attention.
1 May 2018
Seizure epicenter depth and translaminar field potential synchrony underlie complex variations in tissue oxygenation during ictal initiation
Publication date: 1 May 2018
Source:NeuroImage, Volume 171 Author(s): Samuel S. Harris, Luke W. Boorman, Aneurin J. Kennerley, Paul S. Sharp, Chris Martin, Peter Redgrave, Theodore H. Schwartz, Jason Berwick Whether functional hyperemia during epileptic activity is adequate to meet the heightened metabolic demand of such events is controversial. Whereas some studies have demonstrated hyperoxia during ictal onsets, other work has reported transient hypoxic episodes that are spatially dependent on local surface microvasculature. Crucially, how laminar differences in ictal evolution can affect subsequent cerebrovascular responses has not been thus far investigated, and is likely significant in view of possible laminar-dependent neurovascular mechanisms and angioarchitecture. We addressed this open question using a novel multi-modal methodology enabling concurrent measurement of cortical tissue oxygenation, blood flow and hemoglobin concentration, alongside laminar recordings of neural activity, in a urethane anesthetized rat model of recurrent seizures induced by 4-aminopyridine. We reveal there to be a close relationship between seizure epicenter depth, translaminar local field potential (LFP) synchrony and tissue oxygenation during the early stages of recurrent seizures, whereby deep layer seizures are associated with decreased cross laminar synchrony and prolonged periods of hypoxia, and middle layer seizures are accompanied by increased cross-laminar synchrony and hyperoxia. Through comparison with functional activation by somatosensory stimulation and graded hypercapnia, we show that these seizure-related cerebrovascular responses occur in the presence of conserved neural-hemodynamic and blood flow-volume coupling. Our data provide new insights into the laminar dependency of seizure-related neurovascular responses, which may reconcile inconsistent observations of seizure-related hypoxia in the literature, and highlight a potential layer-dependent vulnerability that may contribute to the harmful effects of clinical recurrent seizures. The relevance of our findings to perfusion-related functional neuroimaging techniques in epilepsy are also discussed.
1 May 2018
Longitudinal atlas for normative human brain development and aging over the lifespan using quantitative susceptibility mapping
Publication date: 1 May 2018
Source:NeuroImage, Volume 171 Author(s): Yuyao Zhang, Hongjiang Wei, Matthew J. Cronin, Naying He, Fuhua Yan, Chunlei Liu Longitudinal brain atlases play an important role in the study of human brain development and cognition. Existing atlases are mainly based on anatomical features derived from T1-and T2-weighted MRI. A 4D developmental quantitative susceptibility mapping (QSM) atlas may facilitate the estimation of age-related iron changes in deep gray matter nuclei and myelin changes in white matter. To this end, group-wise co-registered QSM templates were generated over various age intervals from age 183 years old. Registration was achieved by combining both T1-weighted and QSM images. Based on the proposed template, we created an accurate deep gray matter nuclei parcellation map (DGM map). Notably, we segmented thalamus into 5 sub-regions, i.e. the anterior nuclei, the median nuclei, the lateral nuclei, the pulvinar and the internal medullary lamina. Furthermore, we built a whole brain QSM parcellation map by combining existing cortical parcellation and white-matter atlases with the proposed DGM map. Based on the proposed QSM atlas, the segmentation accuracy of iron-rich nuclei using QSM is significantly improved, especially for children and adolescent subjects. The age-related progression of magnetic susceptibility in each of the deep gray matter nuclei, the hippocampus, and the amygdala was estimated. Our automated atlas-based analysis provided a systematic confirmation of previous findings on susceptibility progression with age resulting from manual ROI drawings in deep gray matter nuclei. The susceptibility development in the hippocampus and the amygdala follow an iron accumulation model; while in the thalamus sub-regions, the susceptibility development exhibits a variety of trends. It is envisioned that the newly developed 4D QSM atlas will serve as a template for studying brain iron deposition and myelination/demyelination in both normal aging and various brain diseases.
1 May 2018
Combined fMRI- and eye movement-based decoding of bistable plaid motion perception
Publication date: 1 May 2018
Source:NeuroImage, Volume 171 Author(s): Gregor Wilbertz, Madhura Ketkar, Matthias Guggenmos, Philipp Sterzer The phenomenon of bistable perception, in which perception alternates spontaneously despite constant sensory stimulation, has been particularly useful in probing the neural bases of conscious perception. The study of such bistability requires access to the observer's perceptual dynamics, which is usually achieved via active report. This report, however, constitutes a confounding factor in the study of conscious perception and can also be biased in the context of certain experimental manipulations. One approach to circumvent these problems is to track perceptual alternations using signals from the eyes or the brain instead of observers' reports. Here we aimed to optimize such decoding of perceptual alternations by combining eye and brain signals. Eye-tracking and functional magnetic resonance imaging (fMRI) was performed in twenty participants while they viewed a bistable visual plaid motion stimulus and reported perceptual alternations. Multivoxel pattern analysis (MVPA) for fMRI was combined with eye-tracking in a Support vector machine to decode participants' perceptual time courses from fMRI and eye-movement signals. While both measures individually already yielded high decoding accuracies (on average 86% and 88% correct, respectively) classification based on the two measures together further improved the accuracy (91% correct). These findings show that leveraging on both fMRI and eye movement data may pave the way for optimized no-report paradigms through improved decodability of bistable motion perception and hence for a better understanding of the neural correlates of consciousness.
1 May 2018
Polar-angle representation of saccadic eye movements in human superior colliculus
Publication date: 1 May 2018
Source:NeuroImage, Volume 171 Author(s): Ricky R. Savjani, Sucharit Katyal, Elizabeth Halfen, Jung Hwan Kim, David Ress The superior colliculus (SC) is a layered midbrain structure involved in directing both head and eye movements and coordinating visual attention. Although a retinotopic organization for the mediation of saccadic eye-movements has been shown in monkey SC, in human SC the topography of saccades has not been confirmed. Here, a novel experimental paradigm was performed by five participants (one female) while high-resolution (1.2-mm) functional magnetic resonance imaging was used to measure activity evoked by saccadic eye movements within human SC. Results provide three critical observations about the topography of the SC: (1) saccades along the superior-inferior visual axis are mapped across the medial-lateral anatomy of the SC; (2) the saccadic eye-movement representation is in register with the retinotopic organization of visual stimulation; and (3) activity evoked by saccades occurs deeper within SC than that evoked by visual stimulation. These approaches lay the foundation for studying the organization of human subcortical and enhanced cortical mapping of eye-movement mechanisms.

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1 April 2018
Subthalamic stimulation, oscillatory activity and connectivity reveal functional role of STN and network mechanisms during decision making under conflict
Publication date: 1 May 2018
Source:NeuroImage, Volume 171 Author(s): Franz Hell, Paul C.J. Taylor, Jan H. Mehrkens, Kai B
1 April 2018
Improved three-dimensional multi-echo gradient echo based myelin water fraction mapping with phase related artifact correction
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Hongpyo Lee, Yoonho Nam, Ho-Joon Lee, Jung-Jiin Hsu, Roland G. Henry, Dong-Hyun Kim Myelin water fraction (MWF) mapping with a multi-echo gradient echo (mGRE) sequence using complex-value based model fitting approach was recently described, in which the phase of the data plays an important role in the accuracy of the fitting results. Thus, influences coming from the undesirable phase components need to be reduced. Targeted for improved MWF mapping, methods to combat these phase related issues which include offset correction, main magnetic field (B0) inhomogeneity related correction, and flow compensation have been developed. For offset correction, a coil combine method with bipolar readout gradients has been devised. For B0 related artifact, a voxel spread function correction approach along with a navigator echo acquisition was utilized. Finally, flow compensation gradients were used to reduce the effects of flow from regions including the veins. The correction methods led to reduced residual fitting error and improved quality of the resultant MWF maps. Quantitative analysis shows increased reliability when the corrections were used. Data from normal volunteers showed improved MWF mapping with the integrated method developed in this work.
1 April 2018
A spatio-temporal reference model of the aging brain
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): W. Huizinga, D.H.J. Poot, M.W. Vernooij, G.V. Roshchupkin, E.E. Bron, M.A. Ikram, D. Rueckert, W.J. Niessen, S. Klein Both normal aging and neurodegenerative disorders such as Alzheimer's disease (AD) cause morphological changes of the brain. It is generally difficult to distinguish these two causes of morphological change by visual inspection of magnetic resonance (MR) images. To facilitate making this distinction and thus aid the diagnosis of neurodegenerative disorders, we propose a method for developing a spatio-temporal model of morphological differences in the brain due to normal aging. The method utilizes groupwise image registration to characterize morphological variation across brain scans of people with different ages. To extract the deformations that are due to normal aging we use partial least squares regression, which yields modes of deformations highly correlated with age, and corresponding scores for each input subject. Subsequently, we determine a distribution of morphologies as a function of age by fitting smooth percentile curves to these scores. This distribution is used as a reference to which a person's morphology score can be compared. We validate our method on two different datasets, using images from both cognitively normal subjects and patients with Alzheimer disease (AD). Results show that the proposed framework extracts the expected atrophy patterns. Moreover, the morphology scores of cognitively normal subjects are on average lower than the scores of AD subjects, indicating that morphology differences between AD subjects and healthy subjects can be partly explained by accelerated aging. With our methods we are able to assess accelerated brain aging on both population and individual level. A spatio-temporal aging brain model derived from 988 T1-weighted MR brain scans from a large population imaging study (age range 45.991.7y, mean age 68.3y) is made publicly available at www.agingbrain.nl.
1 April 2018
Adaptive cortical parcellations for source reconstructed EEG/MEG connectomes
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Seyedeh-Rezvan Farahibozorg, Richard N. Henson, Olaf Hauk There is growing interest in the rich temporal and spectral properties of the functional connectome of the brain that are provided by Electro- and Magnetoencephalography (EEG/MEG). However, the problem of leakage between brain sources that arises when reconstructing brain activity from EEG/MEG recordings outside the head makes it difficult to distinguish true connections from spurious connections, even when connections are based on measures that ignore zero-lag dependencies. In particular, standard anatomical parcellations for potential cortical sources tend to over- or under-sample the real spatial resolution of EEG/MEG. By using information from cross-talk functions (CTFs) that objectively describe leakage for a given sensor configuration and distributed source reconstruction method, we introduce methods for optimising the number of parcels while simultaneously minimising the leakage between them. More specifically, we compare two image segmentation algorithms: 1) a split-and-merge (SaM) algorithm based on standard anatomical parcellations and 2) a region growing (RG) algorithm based on all the brain vertices with no prior parcellation. Interestingly, when applied to minimum-norm reconstructions for EEG/MEG configurations from real data, both algorithms yielded approximately 70 parcels despite their different starting points, suggesting that this reflects the resolution limit of this particular sensor configuration and reconstruction method. Importantly, when compared against standard anatomical parcellations, resolution matrices of adaptive parcellations showed notably higher sensitivity and distinguishability of parcels. Furthermore, extensive simulations of realistic networks revealed significant improvements in network reconstruction accuracies, particularly in reducing false leakage-induced connections. Adaptive parcellations therefore allow a more accurate reconstruction of functional EEG/MEG connectomes.

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1 April 2018
Perturbation of whole-brain dynamics in silico reveals mechanistic differences between brain states
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Gustavo Deco, Joana Cabral, Victor M. Saenger, Melanie Boly, Enzo Tagliazucchi, Helmut Laufs, Eus Van Someren, Beatrice Jobst, Angus Stevner, Morten L. Kringelbach Human neuroimaging research has revealed that wakefulness and sleep involve very different activity patterns. Yet, it is not clear why brain states differ in their dynamical complexity, e.g. in the level of integration and segregation across brain networks over time. Here, we investigate the mechanisms underlying the dynamical stability of brain states using a novel off-line in silico perturbation protocol. We first adjust a whole-brain computational model to the basal dynamics of wakefulness and deep sleep recorded with fMRI in two independent human fMRI datasets. Then, the models of sleep and awake brain states are perturbed using two distinct multifocal protocols either promoting or disrupting synchronization in randomly selected brain areas. Once perturbation is halted, we use a novel measure, the Perturbative Integration Latency Index (PILI), to evaluate the recovery back to baseline. We find a clear distinction between models, consistently showing larger PILI in wakefulness than in deep sleep, corroborating previous experimental findings. In the models, larger recoveries are associated to a critical slowing down induced by a shift in the model's operation point, indicating that the awake brain operates further from a stable equilibrium than deep sleep. This novel approach opens up for a new level of artificial perturbative studies unconstrained by ethical limitations allowing for a deeper investigation of the dynamical properties of different brain states.
1 April 2018
High-density EEG characterization of brain responses to auditory rhythmic stimuli during wakefulness and NREM sleep
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Caroline Lustenberger, Yogi A. Patel, Sankaraleengam Alagapan, Jessica M. Page, Betsy Price, Michael R. Boyle, Flavio Fr
1 April 2018
The effects of dopaminergic D2-like receptor stimulation upon behavioral and neural correlates of renewal depend on individual context processing propensities
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Silke Lissek, Benjamin Glaubitz, Anne Klass, Martin Tegenthoff Renewal is defined as the recovery of an extinguished response when the contexts of extinction and recall differ. Prominent hippocampal activity during context-related extinction can predict renewal. Dopaminergic antagonism during extinction learning impaired extinction and reduced hippocampal activation, without affecting renewal. However, to what extent dopaminergic stimulation during extinction influences hippocampal processing and renewal is as yet unknown. In this fMRI study, we investigated the effects of the dopamine D2-like agonist bromocriptine upon renewal in an associative learning task, in hippocampus and ventromedial PFC. We observed significant differences between bromocriptine (BROMO) and placebo (PLAC) treatments in the subgroups showing (REN) and lacking (NoREN) renewal: the renewal level of BROMO REN was significantly higher, and associated with more prominent hippocampal activation during extinction and recall, compared to PLAC REN and BROMO NoREN. Results suggest that an interaction between D2like-agonist-induced enhancement of hippocampal activity and a pre-existing tendency favoring context processing contributed to the higher renewal levels. In contrast, ventromedial prefrontal activation was unchanged, indicating that increased hippocampal context processing and not prefrontal response selection constituted the central driving force behind the high renewal levels. The findings demonstrate that hippocampal dopamine is important for encoding and providing of context information, and thus crucially involved in the renewal effect.
1 April 2018
Domain-general and domain-specific neural changes underlying visual expertise
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Farah Martens, Jessica Bulth
1 April 2018
Evidence for spatiotemporally distinct effects of image repetition and perceptual expectations as measured by event-related potentials
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Daniel Feuerriegel, Owen Churches, Scott Coussens, Hannah A.D. Keage Repeated stimulus presentation leads to reductions in responses of cortical neurons, known as repetition suppression or stimulus-specific adaptation. Circuit-based models of repetition suppression provide a framework for investigating patterns of repetition effects that propagate through cortical hierarchies. To further develop such models it is critical to determine whether (and if so, when) repetition effects are modulated by factors such as expectation and attention. We investigated whether repetition effects are influenced by perceptual expectations, and whether the time courses of each effect are similar or distinct, by presenting pairs of repeated and alternating face images and orthogonally manipulating expectations regarding the likelihood of stimulus repetition. Event-related potentials (ERPs) were recorded from n
1 April 2018
A digital 3D atlas of the marmoset brain based on multi-modal MRI
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Cirong Liu, Frank Q. Ye, Cecil Chern-Chyi Yen, John D. Newman, Daniel Glen, David A. Leopold, Afonso C. Silva The common marmoset (Callithrix jacchus) is a New-World monkey of growing interest in neuroscience. Magnetic resonance imaging (MRI) is an essential tool to unveil the anatomical and functional organization of the marmoset brain. To facilitate identification of regions of interest, it is desirable to register MR images to an atlas of the brain. However, currently available atlases of the marmoset brain are mainly based on 2D histological data, which are difficult to apply to 3D imaging techniques. Here, we constructed a 3D digital atlas based on high-resolution ex-vivo MRI images, including magnetization transfer ratio (a T1-like contrast), T2w images, and multi-shell diffusion MRI. Based on the multi-modal MRI images, we manually delineated 54 cortical areas and 16 subcortical regions on one hemisphere of the brain (the core version). The 54 cortical areas were merged into 13 larger cortical regions according to their locations to yield a coarse version of the atlas, and also parcellated into 106 sub-regions using a connectivity-based parcellation method to produce a refined atlas. Finally, we compared the new atlas set with existing histology atlases and demonstrated its applications in connectome studies, and in resting state and stimulus-based fMRI. The atlas set has been integrated into the widely-distributed neuroimaging data analysis software AFNI and SUMA, providing a readily usable multi-modal template space with multi-level anatomical labels (including labels from the Paxinos atlas) that can facilitate various neuroimaging studies of marmosets.

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1 April 2018
A transferable high-intensity intermittent exercise improves executive performance in association with dorsolateral prefrontal activation in young adults
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Sylwester Kujach, Kyeongho Byun, Kazuki Hyodo, Kazuya Suwabe, Takemune Fukuie, Radoslaw Laskowski, Ippeita Dan, Hideaki Soya Although growing attention has been drawn to attainable, high-intensity intermittent exercise (HIE)-based intervention, which can improve cardiovascular and metabolic health, for sedentary individuals, there is limited information on the impact and potential benefit of an easily attainable HIE intervention for cognitive health. We aimed to reveal how acute HIE affects executive function focusing on underlying neural substrates. To address this issue, we examined the effects of acute HIE on executive function using the color-word matching Stroop task (CWST), which produces a cognitive conflict in the decision-making process, and its neural substrate using functional near infrared spectroscopy (fNIRS). Twenty-five sedentary young adults (mean age: 21.01.6 years; 9 females) participated in two counter-balanced sessions: HIE and resting control. The HIE session consisted of two minutes of warm-up exercise (50W load at 60rpm) and eight sets of 30s of cycling exercise at 60% of maximal aerobic power (mean: 127W29.5 load at 100rpm) followed by 30s of rest on a recumbent-ergometer. Participants performed a CWST before and after the 10-minute exercise session, during both of which cortical hemodynamic changes in the prefrontal cortex were monitored using fNIRS. Acute HIE led to improved Stroop performance reflected by a shortening of the response time related to Stroop interference. It also evoked cortical activation related to Stroop interference on the left-dorsal-lateral prefrontal cortex (DLPFC), which corresponded significantly with improved executive performance. These results provide the first empirical evidence using a neuroimaging method, to our knowledge, that acute HIE improves executive function, probably mediated by increased activation of the task-related area of the prefrontal cortex including the left-DLPFC.
1 April 2018
Investigation of the pulsatility of cerebrospinal fluid using cardiac-gated Intravoxel Incoherent Motion imaging
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Anton S. Becker, Andreas Boss, Markus Klarhoefer, Tim Finkenstaedt, Moritz C. Wurnig, Cristina Rossi The quantitative and non-invasive monitoring of cerebrospinal fluid (CSF) dynamics and composition may have high clinical relevance in the management of CSF disorders. In this study, we propose the use of the Intravoxel Incoherent Motion (IVIM) MRI for obtaining simultaneous measurements of CSF self-diffusion and fluid circulation. The rationale for this study was that turbulent fluid and mesoscopic fluid fluctuations can be modeled in a first approximation as a fast diffusion process. In this case, we expect that the fast fluid circulation and slower molecular diffusion dynamics can be quantified, assuming a bi-exponential attenuation pattern of the diffusion-weighted signal in MRI. IVIM indexes of fast and slow diffusion measured at different sites of the CSF system were systematically evaluated depending on both the phase of the heart cycle and the direction of the diffusion-encoding. The IVIM measurements were compared to dynamic measurements of fluid circulation performed by phase-contrast MRI. Concerning the dependence on the diffusion/flow-encoding direction, similar patterns were found both in the fraction of fast diffusion, f, and in the fluid velocity. Generally, we observed a moderate to high correlation between the fraction of fast diffusion and the maximum fluid velocity along the high-flow directions. Exploratory data analysis detected similarities in the dependency of the fraction of fast diffusion and of the velocity from the phase of the cardiac cycle. However, no significant differences were found between parameters measured during different phases of the cardiac cycle. Our results suggest that the fraction of fast diffusion may reflect CSF circulation. The bi-exponential IVIM model potentially allows us to disentangle the two diffusion components of the CSF dynamics by providing measurements of fluid cellularity (via the slow-diffusion coefficient) and circulation (via the fraction of fast-diffusion index).

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1 April 2018
An unbiased data-driven age-related structural brain parcellation for the identification of intrinsic brain volume changes over the adult lifespan
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Epifanio Bagarinao, Hirohisa Watanabe, Satoshi Maesawa, Daisuke Mori, Kazuhiro Hara, Kazuya Kawabata, Noritaka Yoneyama, Reiko Ohdake, Kazunori Imai, Michihito Masuda, Takamasa Yokoi, Aya Ogura, Toshihiko Wakabayashi, Masafumi Kuzuya, Norio Ozaki, Minoru Hoshiyama, Haruo Isoda, Shinji Naganawa, Gen Sobue This study aims to elucidate age-related intrinsic brain volume changes over the adult lifespan using an unbiased data-driven structural brain parcellation. Anatomical brain images from a cohort of 293 healthy volunteers ranging in age from 21 to 86 years were analyzed using independent component analysis (ICA). ICA-based parcellation identified 192 component images, of which 174 (90.6%) showed a significant negative correlation with age and with some components being more vulnerable to aging effects than others. Seven components demonstrated a convex slope with aging; 3 components had an inverted U-shaped trajectory, and 4 had a U-shaped trajectory. Linear combination of 86 components provided reliable prediction of chronological age with a mean absolute prediction error of approximately 7.2 years. Structural co-variation analysis showed strong interhemispheric, short-distance positive correlations and long-distance, inter-lobar negative correlations. Estimated network measures either exhibited a U- or an inverted U-shaped relationship with age, with the vertex occurring at approximately 4550 years. Overall, these findings could contribute to our knowledge about healthy brain aging and could help provide a framework to distinguish the normal aging processes from that associated with age-related neurodegenerative diseases.
1 April 2018
Detecting white matter activity using conventional 3Tesla fMRI: An evaluation of standard field strength and hemodynamic response function
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Matthew J. Courtemanche, Carolyn J. Sparrey, Xiaowei Song, Alex MacKay, Ryan C.N. D'Arcy Detection of functional magnetic resonance imaging (fMRI) activation in white matter has been increasingly reported despite historically being controversial. Much of the development work to-date has used high-field 4T MRI and specialized pulse sequences. In the current study, we utilized conventional 3T MRI and a commonly applied gradient-echo-planar imaging sequence to evaluate white matter (WM) fMRI sensitivity within a common framework. Functional WM activity was replicated in target regions of interest within the corpus callosum, at the group and individual levels. As expected there was a reduction in overall WM activation sensitivity. Individual analyses revealed that 8 of the 13 individuals showed white matter activation, showing a lower percentage of individuals with WM activation detected. Importantly, WM activation results were sensitive to analyses that applied alternate hemodynamic response functions, with an increase in the group level cluster when hemodynamic response function (HRF) onset slope was reduced. The findings supported the growing evidence that WM activation is detectable, with activation levels are closer to thresholds used for routine 3T MRI studies. Optimization factors, such as the HRF model, appear to be important to further enhance the characterization of WM activity in fMRI.
1 April 2018
The neural network for face recognition: Insights from an fMRI study on developmental prosopagnosia
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Yuanfang Zhao, Zonglei Zhen, Xiqin Liu, Yiying Song, Jia Liu Face recognition is supported by collaborative work of multiple face-responsive regions in the brain. Based on findings from individuals with normal face recognition ability, a neural model has been proposed with the occipital face area (OFA), fusiform face area (FFA), and face-selective posterior superior temporal sulcus (pSTS) as the core face network (CFN) and the rest of the face-responsive regions as the extended face network (EFN). However, little is known about how these regions work collaboratively for face recognition in our daily life. Here we focused on individuals suffering developmental prosopagnosia (DP), a neurodevelopmental disorder specifically impairing face recognition, to shed light on the infrastructure of the neural model of face recognition. Specifically, we used a variant of global brain connectivity method to comprehensively explore resting-state functional connectivity (FC) among face-responsive regions in a large sample of DPs (N=64). We found that both the FCs within the CFN and those between the CFN and EFN were largely reduced in DP. Importantly, the right OFA and FFA served as the dysconnectivity hubs within the CFN, i.e., FCs concerning these two regions within the CFN were largely disrupted. In addition, DPs' right FFA also showed reduced FCs with the EFN. Moreover, these disrupted FCs were related to DP's behavioral deficit in face recognition, with the FCs from the FFA to the anterior temporal lobe (ATL) and pSTS the most predictive. Based on these findings, we proposed a revised neural model of face recognition demonstrating the relatedness of interactions among face-responsive regions to face recognition.
1 April 2018
Affective and non-affective touch evoke differential brain responses in 2-month-old infants
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Emma H. J
1 April 2018
Considering factors affecting the connectome-based identification process: Comment on Waller etal.
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Corey Horien, Stephanie Noble, Emily S. Finn, Xilin Shen, Dustin Scheinost, R. Todd Constable A recent study by Waller and colleagues evaluated the reliability, specificity, and generalizability of using functional connectivity data to identify individuals from a group. The authors note they were able to replicate identification rates in a larger version of the original Human Connectome Project (HCP) dataset. However, they also report lower identification accuracies when using historical neuroimaging acquisitions with low spatial and temporal resolution. The authors suggest that their results indicate connectomes derived from historical imaging data may be similar across individuals, to the extent that this connectome-based approach may be inappropriate for precision psychiatry and the goal of drawing inferences based on subject-level data. Here we note that the authors did not take into account factors affecting data quality and hence identification rates, independent of whether a low spatiotemporal resolution acquisition or a high spatiotemporal resolution acquisition is used. Specifically, we show here that the amount of data collected per subject and in-scanner motion are the predominant factors influencing identification rates, not the spatiotemporal resolution of the acquisition. To do this, we investigated identification rates in the HCP dataset as a function of the amount of data and motion. Using a dataset from the Consortium for Reliability and Reproducibility (CoRR), we investigated the impact of multiband versus non-multiband imaging parameters; that is, high spatiotemporal resolution versus low spatiotemporal resolution acquisitions. We show scan length and motion affect identification, whereas the imaging protocol does not affect these rates. Our results suggest that motion and amount of data per subject are the primary factors impacting individual connectivity profiles, but that within these constraints, individual differences in the connectome are readily observable.
1 April 2018
Gas-free calibrated fMRI with a correction for vessel-size sensitivity
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Avery J.L. Berman, Erin L. Mazerolle, M. Ethan MacDonald, Nicholas P. Blockley, Wen-Ming Luh, G. Bruce Pike Calibrated functional magnetic resonance imaging (fMRI) is a method to independently measure the metabolic and hemodynamic contributions to the blood oxygenation level dependent (BOLD) signal. This technique typically requires the use of a respiratory challenge, such as hypercapnia or hyperoxia, to estimate the calibration constant, M. There has been a recent push to eliminate the gas challenge from the calibration procedure using asymmetric spin echo (ASE) based techniques. This study uses simulations to better understand spin echo (SE) and ASE signals, analytical modelling to characterize the signal evolution, and in vivo imaging to validate the modelling. Using simulations, it is shown how ASE imaging generally underestimates M and how this depends on several parameters of the acquisition, including echo time and ASE offset, as well as the vessel size. This underestimation is the result of imperfect SE refocusing due to diffusion of water through the extravascular environment surrounding the microvasculature. By empirically characterizing this SE attenuation as an exponential decay that increases with echo time, we have proposed a quadratic ASE biophysical signal model. This model allows for the characterization and compensation of the SE attenuation if SE and ASE signals are acquired at multiple echo times. This was tested in healthy subjects and was found to significantly increase the estimates of M across grey matter. These findings show promise for improved gas-free calibration and can be extended to other relaxation-based imaging studies of brain physiology.
1 April 2018
Affective value, intensity and quality of liquid tastants/food discernment in the human brain: An activation likelihood estimation meta-analysis
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Andy Wai Kan Yeung, Tazuko K. Goto, W. Keung Leung The primary dimensions of taste are affective value, intensity and quality. Numerous studies have reported the role of the insula in evaluating these dimensions of taste; however, the results were inconsistent. Therefore, in the current study, we performed meta-analyses of published data to identify locations consistently activated across studies and evaluate whether different regions of the human brain could be responsible for processing different dimensions of taste. Meta-analyses were performed on 39 experiments, with 846 total healthy subjects (without psychiatric/neurological disorders) in 34 studies reporting whole-brain results. The aim was to establish the activation likelihood estimation (ALE) of taste-mediated regional activation across the whole brain. Apart from one meta-analysis for all studies in general, three analyses were performed to reveal the clusters of activation that were attributable to processing the affective value (data from 323 foci), intensity (data from 43 foci) and quality (data from 45 foci) of taste. The ALE revealed eight clusters of activation outside the insula for processing affective value, covering the middle and posterior cingulate, pre-/post-central gyrus, caudate and thalamus. The affective value had four clusters of activation (two in each hemisphere) in the insula. The intensity and quality activated only the insula, each with one cluster on the right. The concurrence between studies was moderate; at best, 53% of the experiments contributed to the significant clusters attributable to the affective value, 60% to intensity and 50% to quality. The affective value was processed bilaterally in the anterior to middle insula, whereas intensity was processed in the right antero-middle insula, and quality was processed in the right middle insula. The right middle dorsal insula was responsible for processing both the affective value and quality of taste. The exploratory analysis on taste quality did not have a significant result if the studies using liquid food stimuli were excluded. Results from the meta-analyses on studies involving the oral delivery of liquid tastants or liquid food stimuli confirmed that the insula is involved in processing all three dimensions of taste. More experimental studies are required to investigate whether brain activations differ between liquid tastants and food. The coordinates of activated brain areas and brain maps are provided to serve as references for future taste/food studies.
1 April 2018
Contrasting functional imaging parametric maps: The mislocation problem and alternative solutions
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Mathieu Bourguignon, Nicola Molinaro, Vincent Wens In the field of neuroimaging, researchers often resort to contrasting parametric maps to identify differences between conditions or populations. Unfortunately, contrast patterns mix effects related to amplitude and location differences and tend to peak away from sources of genuine brain activity to an extent that scales with the smoothness of the maps. Here, we illustrate this mislocation problem on source maps reconstructed from magnetoencephalographic recordings and propose a novel, dedicated location-comparison method. In realistic simulations, contrast mislocation was on average
1 April 2018
Multiple time courses of somatosensory responses in human cortex
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): P. Avanzini, V. Pelliccia, G. Lo Russo, G.A. Orban, G. Rizzolatti Here we show how anatomical and functional data recorded from patients undergoing stereo-EEG can be used to decompose the cortical processing following nerve stimulation in different stages characterized by specific topography and time course. Tibial, median and trigeminal nerves were stimulated in 96 patients, and the increase in gamma power was evaluated over 11878 cortical sites. All three nerve datasets exhibited similar clusters of time courses: phasic, delayed/prolonged and tonic, which differed in topography, temporal organization and degree of spatial overlap. Strong phasic responses of the three nerves followed the classical somatotopic organization of SI, with no overlap in either time or space. Delayed responses presented overlaps between pairs of body parts in both time and space, and were confined to the dorsal motor cortices. Finally, tonic responses occurred in the perisylvian region including posterior insular cortex and were evoked by the stimulation of all three nerves, lacking any spatial and temporal specificity. These data indicate that the somatosensory processing following nerve stimulation is a multi-stage hierarchical process common to all three nerves, with the different stages likely subserving different functions. While phasic responses represent the neural basis of tactile perception, multi-nerve tonic responses may represent the neural signature of processes sustaining the capacity to become aware of tactile stimuli.
1 April 2018
A probabilistic atlas of human brainstem pathways based on connectome imaging data
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Yuchun Tang, Wei Sun, Arthur W. Toga, John M. Ringman, Yonggang Shi The brainstem is a critical structure that regulates vital autonomic functions, houses the cranial nerves and their nuclei, relays motor and sensory information between the brain and spinal cord, and modulates cognition, mood, and emotions. As a primary relay center, the fiber pathways of the brainstem include efferent and afferent connections among the cerebral cortex, spinal cord, and cerebellum. While diffusion MRI has been successfully applied to map various brain pathways, its application for the in vivo imaging of the brainstem pathways has been limited due to inadequate resolution and large susceptibility-induced distortion artifacts. With the release of high-resolution data from the Human Connectome Project (HCP), there is increasing interest in mapping human brainstem pathways. Previous works relying on HCP data to study brainstem pathways, however, did not consider the prevalence (>80%) of large distortions in the brainstem even after the application of correction procedures from the HCP-Pipeline. They were also limited in the lack of adequate consideration of subject variability in either fiber pathways or region of interests (ROIs) used for bundle reconstruction. To overcome these limitations, we develop in this work a probabilistic atlas of 23 major brainstem bundles using high-quality HCP data passing rigorous quality control. For the large-scale data from the 500-Subject release of HCP, we conducted extensive quality controls to exclude subjects with severe distortions in the brainstem area. After that, we developed a systematic protocol to manually delineate 1300 ROIs on 20 HCP subjects (10 males; 10 females) for the reconstruction of fiber bundles using tractography techniques. Finally, we leveraged our novel connectome modeling techniques including high order fiber orientation distribution (FOD) reconstruction from multi-shell diffusion imaging and topography-preserving tract filtering algorithms to successfully reconstruct the 23 fiber bundles for each subject, which were then used to calculate the probabilistic atlases in the MNI152 space for public release. In our experimental results, we demonstrate that our method yielded anatomically faithful reconstruction of the brainstem pathways and achieved improved performance in comparison with an existing atlas of cerebellar peduncles based on HCP data. These atlases have been publicly released on NITRIC (https://www.nitrc.org/projects/brainstem_atlas/) and can be readily used by brain imaging researchers interested in studying brainstem pathways.
1 April 2018
3D spatially-adaptive canonical correlation analysis: Local and global methods
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Zhengshi Yang, Xiaowei Zhuang, Karthik Sreenivasan, Virendra Mishra, Tim Curran, Richard Byrd, Rajesh Nandy, Dietmar Cordes Local spatially-adaptive canonical correlation analysis (local CCA) with spatial constraints has been introduced to fMRI multivariate analysis for improved modeling of activation patterns. However, current algorithms require complicated spatial constraints that have only been applied to 2D local neighborhoods because the computational time would be exponentially increased if the same method is applied to 3D spatial neighborhoods. In this study, an efficient and accurate line search sequential quadratic programming (SQP) algorithm has been developed to efficiently solve the 3D local CCA problem with spatial constraints. In addition, a spatially-adaptive kernel CCA (KCCA) method is proposed to increase accuracy of fMRI activation maps. With oriented 3D spatial filters anisotropic shapes can be estimated during the KCCA analysis of fMRI time courses. These filters are orientation-adaptive leading to rotational invariance to better match arbitrary oriented fMRI activation patterns, resulting in improved sensitivity of activation detection while significantly reducing spatial blurring artifacts. The kernel method in its basic form does not require any spatial constraints and analyzes the whole-brain fMRI time series to construct an activation map. Finally, we have developed a penalized kernel CCA model that involves spatial low-pass filter constraints to increase the specificity of the method. The kernel CCA methods are compared with the standard univariate method and with two different local CCA methods that were solved by the SQP algorithm. Results show that SQP is the most efficient algorithm to solve the local constrained CCA problem, and the proposed kernel CCA methods outperformed univariate and local CCA methods in detecting activations for both simulated and real fMRI episodic memory data.
1 April 2018
The role of the cerebellum in explicit and incidental processing of facial emotional expressions: A study with transcranial magnetic stimulation
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Chiara Ferrari, Viola Oldrati, Marcello Gallucci, Tomaso Vecchi, Zaira Cattaneo Growing evidence suggests that the cerebellum plays a critical role in non-motor functions, contributing to cognitive and affective processing. In particular, the cerebellum might represent an important node of the limbic network, underlying not only emotion regulation but also emotion perception and recognition. Here, we used transcranial magnetic stimulation (TMS) to shed further light on the role of the cerebellum in emotional perception by specifically testing cerebellar contribution to explicit and incidental emotional processing. In particular, in three different experiments, we found that TMS over the (left) cerebellum impaired participants ability to categorize facial emotional expressions (explicit task) and to classify the gender of emotional faces (incidental emotional processing task), but not the gender of neutral faces. Overall, our results indicate that the cerebellum is involved in perceiving the emotional content of facial stimuli, even when this is task irrelevant.
1 April 2018
Intracranial high-
1 April 2018
Non-invasive estimation of [11C]PBR28 binding potential
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Martin Schain, Francesca Zanderigo, R. Todd Ogden, William C. Kreisl [11C]PBR28 is a PET radioligand used to estimate densities of the 18kDa translocator protein (TSPO) in vivo. Since there is no suitable reference region, arterial blood samples are required for full quantification. Here, we evaluate a methodology for full quantification of [11C]PBR28 PET data that does not require either a reference region or blood samples. Simultaneous estimation (SIME) uses time-activity curves from several brain regions to estimate binding potential (BP ND), a theoretically more sensitive outcome measure than total distribution volume. SIME can be employed with either a measured arterial input function (AIF) or a template input function (tIF) that has similar shape as the AIF, but with arbitrary amplitude. We evaluated the ability of SIME to detect group differences in TSPO densities using PET and arterial plasma data from 21 Alzheimer's disease (AD) patients and 15 controls that underwent [11C]PBR28 imaging. Regional BP ND obtained with tIFs were compared to those obtained using measured AIFs. Standard kinetic modeling was also employed for comparison. The sensitivity of each method to detect group differences in TSPO densities were assessed by comparing estimated effect sizes between AD patients and controls. For this purpose, BP ND estimated for one region with high pathological burden (inferior temporal cortex), and for one region with low pathological burden (cerebellum) was used. BP ND estimates obtained with SIME and tIFs were close to identical to those obtained with AIF (3.021% difference, r 2 =0.78). In this dataset, the effect sizes between AD patients and controls for both SIME with AIF and SIME with tIF were similar (30.3%, p=0.001 and 31.0%, p=0.004, respectively) and were each greater than the effect size observed using the two-tissue compartment model (16.1%, p=0.12). None of the tested methods showed difference in TSPO binding in cerebellum. These results demonstrate that BP ND can be estimated for [11C]PBR28 using SIME, and may be useful in clinical studies. In addition, arterial sampling may not be necessary if tIFs can be reliably estimated.
1 April 2018
Neural phase locking predicts BOLD response in human auditory cortex
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Hiroyuki Oya, Phillip E. Gander, Christopher I. Petkov, Ralph Adolphs, Kirill V. Nourski, Hiroto Kawasaki, Matthew A. Howard, Timothy D. Griffiths Natural environments elicit both phase-locked and non-phase-locked neural responses to the stimulus in the brain. The interpretation of the BOLD signal to date has been based on an association of the non-phase-locked power of high-frequency local field potentials (LFPs), or the related spiking activity in single neurons or groups of neurons. Previous studies have not examined the prediction of the BOLD signal by phase-locked responses. We examined the relationship between the BOLD response and LFPs in the same nine human subjects from multiple corresponding points in the auditory cortex, using amplitude modulated pure tone stimuli of a duration to allow an analysis of phase locking of the sustained time period without contamination from the onset response. The results demonstrate that both phase locking at the modulation frequency and its harmonics, and the oscillatory power in gamma/high-gamma bands are required to predict the BOLD response. Biophysical models of BOLD signal generation in auditory cortex therefore require revision and the incorporation of both phase locking to rhythmic sensory stimuli and power changes in the ensemble neural activity.
1 April 2018
Transcranial magnetic stimulation of the precuneus enhances memory and neural activity in prodromal Alzheimer's disease
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Giacomo Koch, Sonia Bonn
1 April 2018
Serotonergic and cholinergic modulation of functional brain connectivity: A comparison between young and older adults
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Bernadet L. Klaassens, Joop M.A. van Gerven, Erica S. Klaassen, Jeroen van der Grond, Serge A.R.B. Rombouts Aging is accompanied by changes in neurotransmission. To advance our understanding of how aging modifies specific neural circuitries, we examined serotonergic and cholinergic stimulation with resting state functional magnetic resonance imaging (RS-fMRI) in young and older adults. The instant response to the selective serotonin reuptake inhibitor citalopram (30
1 April 2018
Chronic nicotine exposure impairs uncertainty modulation on reinforcement learning in anterior cingulate cortex and serotonin system
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Zhengde Wei, Long Han, Xiuying Zhong, Ying Liu, Rujing Zha, Ying Wang, Li-Zhuang Yang, Junjie Bu, Hongwen Song, Wenjuan Wang, Yifeng Zhou, Ping Gao, Xiaochu Zhang Deficits in the computational processes of reinforcement learning have been suggested to underlie addiction. Additionally, environmental uncertainty, which is encoded in the anterior cingulate cortex (ACC), modulates reward prediction errors (RPEs) during reinforcement learning and exacerbates addiction. The present study tested whether and how the ACC would have an essential role in drug addiction by failing to use uncertainty to modulate the RPEs during reinforcement learning. In Experiment I, we found that the ACC/medial prefrontal cortex (MPFC) did not modulate RPE learning according to uncertainty in smokers. The effect of uncertainty
1 April 2018
Transformation from independent to integrative coding of multi-object arrangements in human visual cortex
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): Daniel Kaiser, Marius V. Peelen To optimize processing, the human visual system utilizes regularities present in naturalistic visual input. One of these regularities is the relative position of objects in a scene (e.g., a sofa in front of a television), with behavioral research showing that regularly positioned objects are easier to perceive and to remember. Here we use fMRI to test how positional regularities are encoded in the visual system. Participants viewed pairs of objects that formed minimalistic two-object scenes (e.g., a living room consisting of a sofa and television) presented in their regularly experienced spatial arrangement or in an irregular arrangement (with interchanged positions). Additionally, single objects were presented centrally and in isolation. Multi-voxel activity patterns evoked by the object pairs were modeled as the average of the response patterns evoked by the two single objects forming the pair. In two experiments, this approximation in object-selective cortex was significantly less accurate for the regularly than the irregularly positioned pairs, indicating integration of individual object representations. More detailed analysis revealed a transition from independent to integrative coding along the posterior-anterior axis of the visual cortex, with the independent component (but not the integrative component) being almost perfectly predicted by object selectivity across the visual hierarchy. These results reveal a transitional stage between individual object and multi-object coding in visual cortex, providing a possible neural correlate of efficient processing of regularly positioned objects in natural scenes.

Artificial scotoma estimation based on population receptive field mapping
Publication date: 1 April 2018
Source:NeuroImage, Volume 169 Author(s): A. Hummer, M. Ritter, M. Woletz, A.A. Ledolter, M. Tik, S.O. Dumoulin, G.E. Holder, U. Schmidt-Erfurth, C. Windischberger Population receptive field (pRF) mapping based on functional magnetic resonance imaging (fMRI) is an ideal method for obtaining detailed retinotopic information. One particularly promising application of pRF mapping is the estimation and quantification of visual field effects, for example scotomata in patients suffering from macular dysfunction or degeneration (MD) or hemianopic defects in patients with intracranial dysfunction. However, pRF mapping performance is influenced by a number of factors including spatial and temporal resolution, distribution of dural venous sinuses and patient performance. This study addresses the ability of current pRF methodology to assess the size of simulated scotomata in healthy individuals. The data demonstrate that central scotomata down to a radius of 2.35 (4.7 diameter) visual angle can be reliably estimated in single subjects using high spatial resolution protocols and multi-channel receive array coils.
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