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Hansol Lee, Sun-Yong Baek, Se Young Chun, Jae-Hyeok Lee, HyungJoon Cho
Neuromelanin (NM) is an endogenous iron chelating molecule of pigmented neurons in the human substantia nigra (SN). Along with the increase in iron deposition, the reduction in NM-containing dopaminergic neurons and the variation of iron load on NM are generally considered to be important factors participating to pathogenesis of Parkinson's disease (PD). The aim of this study was to non-invasively delineate the spatial distributions of paramagnetic magnetic susceptibility perturbers, such as NM-iron complex and ferric iron in SN...
November 18, 2017: NeuroImage
Michał Bola, Adam B Barrett, Andrea Pigorini, Lino Nobili, Anil K Seth, Artur Marchewka
Loss of consciousness can result from a wide range of causes, including natural sleep and pharmacologically induced anesthesia. Important insights might thus come from identifying neuronal mechanisms of loss and re-emergence of consciousness independent of a specific manipulation. Therefore, to seek neuronal signatures of loss of consciousness common to sleep and anesthesia we analyzed spontaneous electrophysiological activity recorded in two experiments. First, electrocorticography (ECoG) acquired from 4 macaque monkeys anesthetized with different anesthetic agents (ketamine, medetomidine, propofol) and, second, stereo-electroencephalography (sEEG) from 10 epilepsy patients in different wake-sleep stages (wakefulness, NREM, REM)...
November 18, 2017: NeuroImage
Ting-Ting Chang, Pei-Hong Lee, Arron W S Metcalfe
The neural substrates of children's reading and arithmetic skills have long been of great interest to cognitive neuroscientists. However, most previous studies have focused on the contrast between these skills as specific domains. Here, we investigate the potentially shared processes across these domains by focusing on how the neural circuits associated with cognitive control influence reading and arithmetic proficiency in 8-to-10-year-old children. Using a task-free resting state approach, we correlated the intrinsic functional connectivity of the right anterior insula (rAI) network with performance on assessments of Chinese character recognition, reading comprehension, subtraction, and multiplication performance...
November 18, 2017: NeuroImage
Hae-Jeong Park, Karl Friston, Chongwon Pae, Bumhee Park, Adeel Razi
Context-sensitive and activity-dependent fluctuations in connectivity underlie functional integration in the brain and have been studied widely in terms of synaptic plasticity, learning and condition-specific (e.g., attentional) modulations of synaptic efficacy. This dynamic aspect of brain connectivity has recently attracted a lot of attention in the resting state fMRI community. To explain dynamic functional connectivity in terms of directed effective connectivity among brain regions, we introduce a novel method to identify dynamic effective connectivity using spectral dynamic causal modelling (spDCM)...
November 17, 2017: NeuroImage
Zhong-Xu Liu, Cheryl Grady, Morris Moscovitch
It is known that prior knowledge can facilitate memory acquisition. It is unclear, however, whether prior knowledge can affect post-encoding brain activity to facilitate memory consolidation. In this fMRI study, we asked participants to associate novel houses with famous/nonfamous faces and investigated how associative-encoding tasks with/without prior knowledge differentially affected post-encoding brain connectivity during rest. Besides memory advantages in the famous condition, we found that post-encoding hippocampal connectivity with the fusiform face area (FFA) and ventral-medial-prefrontal cortex (vmPFC) was stronger following encoding of associations with famous than non-famous faces...
November 17, 2017: NeuroImage
Jean-Philippe Fortin, Nicholas Cullen, Yvette I Sheline, Warren D Taylor, Irem Aselcioglu, Philip A Cook, Phil Adams, Crystal Cooper, Maurizio Fava, Patrick J McGrath, Melvin McInnis, Mary L Phillips, Madhukar H Trivedi, Myrna M Weissman, Russell T Shinohara
With the proliferation of multi-site neuroimaging studies, there is a greater need for handling non-biological variance introduced by differences in MRI scanners and acquisition protocols. Such unwanted sources of variation, which we refer to as "scanner effects", can hinder the detection of imaging features associated with clinical covariates of interest and cause spurious findings. In this paper, we investigate scanner effects in two large multi-site studies on cortical thickness measurements across a total of 11 scanners...
November 16, 2017: NeuroImage
Marco Palombo, Noam Shemesh, Itamar Ronen, Julien Valette
Many developmental processes, such as plasticity and aging, or pathological processes such as neurological diseases are characterized by modulations of specific cellular types and their microstructures. Diffusion-weighted Magnetic Resonance Imaging (DW-MRI) is a powerful technique for probing microstructure, yet its information arises from the ubiquitous, non-specific water signal. By contrast, diffusion-weighted Magnetic Resonance Spectroscopy (DW-MRS) allows specific characterizations of tissues such as brain and muscle in vivo by quantifying the diffusion properties of MR-observable metabolites...
November 16, 2017: NeuroImage
Lauren E Welbourne, Antony B Morland, Alex R Wade
The spatial sensitivity of the human visual system depends on stimulus color: achromatic gratings can be resolved at relatively high spatial frequencies while sensitivity to isoluminant color contrast tends to be more low-pass. Models of early spatial vision often assume that the receptive field size of pattern-sensitive neurons is correlated with their spatial frequency sensitivity - larger receptive fields are typically associated with lower optimal spatial frequency. A strong prediction of this model is that neurons coding isoluminant chromatic patterns should have, on average, a larger receptive field size than neurons sensitive to achromatic patterns...
November 14, 2017: NeuroImage
Frank de Vos, Marisa Koini, Tijn M Schouten, Stephan Seiler, Jeroen van der Grond, Anita Lechner, Reinhold Schmidt, Mark de Rooij, Serge A R B Rombouts
Alzheimer's disease (AD) patients show altered patterns of functional connectivity (FC) on resting state functional magnetic resonance imaging (RSfMRI) scans. It is yet unclear which RSfMRI measures are most informative for the individual classification of AD patients. We investigated this using RSfMRI scans from 77 AD patients (MMSE = 20.4 ± 4.5) and 173 controls (MMSE = 27.5 ± 1.8). We calculated i) FC matrices between resting state components as obtained with independent component analysis (ICA), ii) the dynamics of these FC matrices using a sliding window approach, iii) the graph properties (e...
November 14, 2017: NeuroImage
Nima Noury, Markus Siegel
Transcranial Electric Stimulation (tES) is a widely used non-invasive brain stimulation technique. However, strong stimulation artifacts complicate the investigation of neural activity with EEG or MEG during tES. Thus, studying brain signals during tES requires detailed knowledge about the properties of these artifacts. Recently, we characterized the phase- and amplitude-relationship between tES stimulation currents and tES artifacts in EEG and MEG and provided a mathematical model of these artifacts (Noury and Siegel, 2017, and Noury et al...
November 14, 2017: NeuroImage
Maria Fatima Silva, Jan W Brascamp, Sónia Ferreira, Miguel Castelo-Branco, Serge O Dumoulin, Ben M Harvey
Human visual cortex does not represent the whole visual field with the same detail. Changes in receptive field size, population receptive field (pRF) size and cortical magnification factor (CMF) with eccentricity are well established, and associated with changes in visual acuity with eccentricity. Visual acuity also changes across polar angle. However, it remains unclear how RF size, pRF size and CMF change across polar angle. Here, we examine differences in pRF size and CMF across polar angle in V1, V2 and V3 using pRF modeling of human fMRI data...
November 14, 2017: NeuroImage
Vittoria De Angelis, Federico De Martino, Michelle Moerel, Roberta Santoro, Lars Hausfeld, Elia Formisano
Pitch is a perceptual attribute related to the fundamental frequency (or periodicity) of a sound. So far, the cortical processing of pitch has been investigated mostly using synthetic sounds. However, the complex harmonic structure of natural sounds may require different mechanisms for the extraction and analysis of pitch. This study investigated the neural representation of pitch in human auditory cortex using model-based encoding and decoding analyses of high field (7 T) functional magnetic resonance imaging (fMRI) data collected while participants listened to a wide range of real-life sounds...
November 13, 2017: NeuroImage
G Spinelli, G Tieri, E F Pavone, S M Aglioti
EEG studies show that observing errors in one's own or others' actions triggers specific electro-cortical signatures in the onlooker's brain, but whether the brain error-monitoring system operates according to graded or discrete rules is still largely unknown. To explore this issue, we combined immersive virtual reality with EEG recording in participants who observed an avatar reaching-to-grasp a glass from a first-person perspective. The avatar could perform correct or erroneous actions. Erroneous grasps were defined as small or large depending on the magnitude of the trajectory deviation from the to-be-grasped glass...
November 13, 2017: NeuroImage
Chris M Foster, Kristen M Kennedy, Marci M Horn, David A Hoagey, Karen M Rodrigue
Beta-amyloid (Aβ) positive individuals hyper-activate brain regions compared to those not at-risk; however, hyperactivation is then thought to diminish as Alzheimer's disease symptomatology begins, evidencing eventual hypoactivation. It remains unclear when in the disease staging this transition occurs. We hypothesized that differential levels of amyloid burden would be associated with both increased and decreased activation (i.e., a quadratic trajectory) in cognitively-normal adults. Participants (N = 62; aged 51-94) underwent an fMRI spatial distance-judgment task and Amyvid-PET scanning...
November 13, 2017: NeuroImage
Christian Kames, Vanessa Wiggermann, Alexander Rauscher
Quantitative susceptibility mapping (QSM) is a post-processing technique of gradient echo phase data that attempts to map the spatial distribution of local tissue magnetic susceptibilities. To obtain these maps, an ill-posed field-to-source inverse problem must be solved to remove non-local magnetic field perturbations. Current state-of-the-art algorithms which aim to solve the dipole inversion problem are plagued by the trade-off between reconstruction speed and accuracy. A two-step dipole inversion algorithm is proposed to bridge this gap...
November 11, 2017: NeuroImage
Kanad Mandke, Jil Meier, Matthew J Brookes, Reuben D O'Dea, Piet Van Mieghem, Cornelis J Stam, Arjan Hillebrand, Prejaas Tewarie
There is an increasing awareness of the advantages of multi-modal neuroimaging. Networks obtained from different modalities are usually treated in isolation, which is however contradictory to accumulating evidence that these networks show non-trivial interdependencies. Even networks obtained from a single modality, such as frequency-band specific functional networks measured from magnetoencephalography (MEG) are often treated independently. Here, we discuss how a multilayer network framework allows for integration of multiple networks into a single network description and how graph metrics can be applied to quantify multilayer network organisation for group comparison...
November 11, 2017: NeuroImage
Ankit N Khambhati, Marcelo G Mattar, Nicholas F Wymbs, Scott T Grafton, Danielle S Bassett
The human brain is in constant flux, as distinct areas engage in transient communication to support basic behaviors as well as complex cognition. The collection of interactions between cortical and subcortical areas forms a functional brain network whose topology evolves with time. Despite the nontrivial dynamics that are germane to this networked system, experimental evidence demonstrates that functional interactions organize into putative brain systems that facilitate different facets of cognitive computation...
November 11, 2017: NeuroImage
Xinlin Zhou, Mengyi Li, Leinian Li, Yiyun Zhang, Jiaxin Cui, Jie Liu, Chuansheng Chen
Numerous studies have shown that the brain regions around bilateral intraparietal cortex are critical for number processing and arithmetical computation. However, the neural circuits for more advanced mathematics such as mathematical problem solving (with little routine arithmetical computation) remain unclear. Using functional magnetic resonance imaging (fMRI), this study (N = 24 undergraduate students) compared neural bases of mathematical problem solving (i.e., number series completion, mathematical word problem solving, and geometric problem solving) and arithmetical computation...
November 10, 2017: NeuroImage
Bibek Dhital, Elias Kellner, Valerij G Kiselev, Marco Reisert
Understanding diffusion-weighted MR signal in brain white matter (WM) has been a long-sought-after goal. Modern research pursuits this goal by focusing on the biological compartments that contributes essentially to the signal. In this study, we experimentally address the apparent presence of a compartment in which water motion is restricted in all spatial directions. Using isotropic diffusion encoding, we establish an upper bound on the fraction of such a compartment, which is shown to be about 2% of the unweighted signal for moderate diffusion times...
November 9, 2017: NeuroImage
Jing Yuan, Xiang Li, Jinhe Zhang, Liao Luo, Qinglin Dong, Jinglei Lv, Yu Zhao, Xi Jiang, Shu Zhang, Wei Zhang, Tianming Liu
Many recent literature studies have revealed interesting dynamics patterns of functional brain networks derived from fMRI data. However, it has been rarely explored how functional networks spatially overlap (or interact) and how such connectome-scale network interactions temporally evolve. To explore these unanswered questions, this paper presents a novel framework for spatio-temporal modeling of connectome-scale functional brain network interactions via two main effective computational methodologies. First, to integrate, pool and compare brain networks across individuals and their cognitive states under task performances, we designed a novel group-wise dictionary learning scheme to derive connectome-scale consistent brain network templates that can be used to define the common reference space of brain network interactions...
November 9, 2017: NeuroImage
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