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David J Schaeffer, Kyle M Gilbert, Maryam Ghahremani, Joseph S Gati, Ravi S Menon, Stefan Everling
The common marmoset (Callithrix jacchus) has garnered recent attention as a potentially powerful preclinical model and complement to other canonical mammalian models of human brain diseases (e.g., rodents and Old World non-human primates). With a granular frontal cortex and the advent of transgenic modifications, marmosets are well positioned to serve as neuropsychiatric models of prefrontal cortex dysfunction. A critical step in the development of marmosets for such models is to characterize functional network topologies of frontal cortex in healthy, normally functioning marmosets...
November 9, 2018: NeuroImage
Luke Baxter, Sean Fitzgibbon, Fiona Moultrie, Sezgi Goksan, Mark Jenkinson, Stephen Smith, Jesper Andersson, Eugene Duff, Rebeccah Slater
The infant brain is unlike the adult brain, with considerable differences in morphological, neurodynamic, and haemodynamic features. As the majority of current MRI analysis tools were designed for use in adults, a primary objective of the Developing Human Connectome Project (dHCP) is to develop optimised methodological pipelines for the analysis of neonatal structural, resting state, and diffusion MRI data. Here, in an independent neonatal dataset we have extended and optimised the dHCP fMRI preprocessing pipeline for the analysis of stimulus-response fMRI data...
November 8, 2018: NeuroImage
Kaitlin Cassady, Holly Gagnon, Poortata Lalwani, Molly Simmonite, Bradley Foerster, Denise Park, Scott J Peltier, Myria Petrou, Stephan F Taylor, Daniel H Weissman, Rachael D Seidler, Thad A Polk
Aging is typically associated with declines in sensorimotor performance. Previous studies have linked some age-related behavioral declines to reductions in network segregation. For example, compared to young adults, older adults typically exhibit weaker functional connectivity within the same functional network but stronger functional connectivity between different networks. Based on previous animal studies, we hypothesized that such reductions of network segregation are linked to age-related reductions in the brain's major inhibitory transmitter, gamma aminobutyric acid (GABA)...
November 8, 2018: NeuroImage
Raffaele Cacciaglia, Jordi Costa-Faidella, Katarzyna Zarnowiec, Sabine Grimm, Carles Escera
Perception is a highly active process relying on the continuous formulation of predictive inferences using short-term sensory memory templates, which are recursively adjusted based on new input. According to this idea, earlier studies have shown that novel stimuli preceded by a higher number of repetitions yield greater novelty responses, indexed by larger mismatch negativity (MMN). However, it is not clear whether this MMN memory trace effect is driven by more adapted responses to prior stimulation or rather by a heightened processing of the unexpected deviant, and only few studies have so far attempted to characterize the functional neuroanatomy of these effects...
November 8, 2018: NeuroImage
Bradley T Baker, Anees Abrol, Rogers F Silva, Eswar Damaraju, Anand D Sarwate, Vince D Calhoun, Sergey M Plis
The field of neuroimaging has recently witnessed a strong shift towards data sharing; however, current collaborative research projects may be unable to leverage institutional architectures that collect and store data in local, centralized data centers. Additionally, though research groups are willing to grant access for collaborations, they often wish to maintain control of their data locally. These concerns may stem from research culture as well as privacy and accountability concerns. In order to leverage the potential of these aggregated larger data sets, we require tools that perform joint analyses without transmitting the data...
November 5, 2018: NeuroImage
Tianhao Zhang, Qi Huang, Chunxiang Jiao, Hua Liu, Binbin Nie, Shengxiang Liang, Panlong Li, Xi Sun, Ting Feng, Lin Xu, Baoci Shan
Metabolic brain network, which is based on functional correlation patterns of 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET) images, has been widely applied in both basic and clinical neuroscience. Exploring the properties of the metabolic brain network can provide valuable insight to the physiologic and pathologic processes of the brain. Based on the network theory, modular architecture has the ability to limit the spread of local perturbation impact and therefore modular networks are more robust against external damage...
November 5, 2018: NeuroImage
Noam Goldway, Jacob Ablin, Omer Lubin, Yoav Zamir, Jackob Nimrod Keynan, Ayelet Or-Borichev, Marc Cavazza, Fred Charles, Nathan Intrator, Silviu Brill, Eti Ben-Simon, Haggai Sharon, Talma Hendler
Volitional neural modulation using neurofeedback has been indicated as a potential treatment for chronic conditions that involve peripheral and central neural dysregulation. Here we utilized neurofeedback in patients suffering from Fibromyalgia - a chronic pain syndrome that involves sleep disturbance and emotion dysregulation. These ancillary symptoms, which have an amplification effect on pain, are known to be mediated by heightened limbic activity. In order to reliably probe limbic activity in a scalable manner fit for EEG-neurofeedback training, we utilized an Electrical Finger Print (EFP) model of amygdala-BOLD signal (termed Amyg-EFP), that has been successfully validated in our lab in the context of volitional neuromodulation...
November 5, 2018: NeuroImage
Kirsten Petras, Sanne Ten Ten Oever, Christianne Jacobs, Valerie Goffaux
Coarse-to-fine theories of vision propose that the coarse information carried by the low spatial frequencies (LSF) of visual input guides the integration of finer, high spatial frequency (HSF) detail. Whether and how LSF modulates HSF processing in naturalistic broad-band stimuli is still unclear. Here we used multivariate decoding of EEG signals to separate the respective contribution of LSF and HSF to the neural response evoked by broad-band images. Participants viewed images of human faces, monkey faces and phase-scrambled versions that were either broad-band or filtered to contain LSF or HSF...
November 4, 2018: NeuroImage
Claude J Bajada, Jan Schreiber, Svenja Caspers
There has been a recent increased interest in the structural connectivity of the cortex. However, an important feature of connectivity remains relatively unexplored; tract length. In this article, we develop an approach to characterize fiber length distributions across the human cerebral cortex. We used data from 76 participants of the Adult WU-Minn Human Connectome Project using probabilistic tractography. We found that connections of different lengths are not evenly distributed across the cortex. They form patterns where certain areas have a high density of fibers of a specific length while other areas have very low density...
November 3, 2018: NeuroImage
Prejaas Tewarie, Romesh Abeysuriya, Áine Byrne, George C O'Neill, Stamatios N Sotiropoulos, Matthew J Brookes, Stephen Coombes
Functional networks obtained from magnetoencephalography (MEG) from different frequency bands show distinct spatial patterns. It remains to be elucidated how distinct spatial patterns in MEG networks emerge given a single underlying structural network. Recent work has suggested that the eigenmodes of the structural network might serve as a basis set for functional network patterns in the case of functional MRI. Here, we take this notion further in the context of frequency band specific MEG networks. We show that a selected set of eigenmodes of the structural network can predict different frequency band specific networks in the resting state, ranging from delta (1-4 Hz) to the high gamma band (40-70 Hz)...
November 3, 2018: NeuroImage
Spencer A Arbuckle, Atsushi Yokoi, J Andrew Pruszynski, Jörn Diedrichsen
Fine-grained activity patterns, as measured with functional magnetic resonance imaging (fMRI), are thought to reflect underlying neural representations. Multivariate analysis techniques, such as representational similarity analysis (RSA), can be used to test models of brain representation by quantifying the representational geometry (the collection of pair-wise dissimilarities between activity patterns). One important caveat, however, is that non-linearities in the coupling between neural activity and the fMRI signal may lead to significant distortions in the representational geometry estimated from fMRI activity patterns...
November 2, 2018: NeuroImage
Steven W McNair, Stephanie J Kayser, Christoph Kayser
As we get older, perception in cluttered environments becomes increasingly difficult as a result of changes in peripheral and central neural processes. Given the aging society, it is important to understand the neural mechanisms constraining perception in the elderly. In young participants, the state of rhythmic brain activity prior to a stimulus has been shown to modulate the neural encoding and perceptual impact of this stimulus - yet it remains unclear whether, and if so, how, the perceptual relevance of pre-stimulus activity changes with age...
November 2, 2018: NeuroImage
Mengqi Xing, Hyekyoung Lee, Zachery Morrissey, Moo K Chung, K Luan Phan, Heide Klumpp, Alex Leow, Olusola Ajilore
Emotion regulation deficits are commonly observed in social anxiety disorder (SAD). We used manifold-learning to learn the phase-space connectome manifold of EEG brain dynamics in twenty SAD participants and twenty healthy controls. The purpose of the present study was to utilize manifold-learning to understand EEG brain dynamics associated with emotion regulation processes. Our emotion regulation task (ERT) contains three conditions: Neutral, Maintain and Reappraise. For all conditions and subjects, EEG connectivity data was converted into series of temporally-consecutive connectomes and aggregated to yield this phase-space manifold...
November 1, 2018: NeuroImage
Maximilian Pietsch, Daan Christiaens, Jana Hutter, Lucilio Cordero-Grande, Anthony N Price, Emer Hughes, A David Edwards, Joseph V Hajnal, Serena J Counsell, J-Donald Tournier
We describe a framework for creating a time-resolved group average template of the developing brain using advanced multi-shell high angular resolution diffusion imaging data, for use in group voxel or fixel-wise analysis, atlas-building, and related applications. This relies on the recently proposed multi-shell multi-tissue constrained spherical deconvolution (MSMT-CSD) technique. We decompose the signal into one isotropic component and two anisotropic components, with response functions estimated from cerebrospinal fluid and white matter in the youngest and oldest participant groups, respectively...
November 1, 2018: NeuroImage
Kate Ergo, Esther De Loof, Clio Janssens, Tom Verguts
Reward prediction errors (RPEs) are crucial to learning. Whereas these mismatches between reward expectation and reward outcome are known to drive procedural learning, their role in declarative learning remains underexplored. Earlier work from our lab addressed this, and consistently found that signed reward prediction errors (SRPEs; "better-than-expected" signals) boost declarative learning. In the current EEG study, we sought to explore the neural signatures of SRPEs. Participants studied 60 Dutch-Swahili word pairs while RPE magnitudes were parametrically manipulated...
November 2, 2018: NeuroImage
Miguel R Chuapoco, Mankin Choy, Florian Schmid, Ben A Duffy, Hyun Joo Lee, Jin Hyung Lee
Extracellular electrophysiology and functional MRI are complementary techniques that provide information about cellular and network-level neural activity, respectively. However, electrodes for electrophysiology are typically made from metals, which cause significant susceptibility artifacts on MR images. Previous work has demonstrated that insulated carbon fiber bundle electrodes reduce the volume of magnetic susceptibility artifacts and can be used to record local field potentials (LFP), but the relatively large diameter of the probes make them unsuitable for multi- and single-unit recordings...
November 1, 2018: NeuroImage
Enrico De Martino, David A Seminowicz, Siobhan M Schabrun, Laura Petrini, Thomas Graven-Nielsen
Based on reciprocal connections between the dorsolateral prefrontal cortex (DLPFC) and basal-ganglia regions associated with sensorimotor cortical excitability, it was hypothesized that repetitive transcranial magnetic stimulation (rTMS) of the left DLPFC would modulate sensorimotor cortical excitability induced by muscle pain. Muscle pain was provoked by injections of nerve growth factor (end of Day-0 and Day-2) into the right extensor carpi radialis brevis (ECRB) muscle in two groups of 15 healthy participants receiving 5 daily sessions (Day-0 to Day-4) of active or sham rTMS...
November 1, 2018: NeuroImage
I Pappas, R M Adapa, D K Menon, E A Stamatakis
The precise mechanism of anaesthetic action on a neural level remains unclear. Recent approaches suggest that anaesthetics attenuate the complexity of interactions (connectivity) however evidence remains insufficient. We used tools from network and information theory to show that, during propofol-induced sedation, a collection of brain regions displayed decreased complexity in their connectivity patterns, especially so if they were sparsely connected. Strikingly, we found that, despite their low connectivity strengths, these regions exhibited an inordinate role in network integration...
October 31, 2018: NeuroImage
Giancarlo Valente, Amanda Kaas, Elia Formisano, Rainer Goebel
Functional Magnetic Resonance Imaging (fMRI) has been successfully used for Brain Computer Interfacing (BCI) to classify (imagined) movements of different limbs. However, reliable classification of more subtle signals originating from co-localized neural networks in the sensorimotor cortex, e.g. individual movements of fingers of the same hand, has proved to be more challenging, especially when taking into account the requirement for high single trial reliability in the BCI context. In recent years, Multi Voxel Pattern Analysis (MVPA) has gained momentum as a suitable method to disclose such weak, distributed activation patterns...
October 31, 2018: NeuroImage
Wei Liu, Nils Kohn, Guillén Fernández
Personality is a central high-level psychological concept that defines individual human beings and has been associated with a variety of real-world outcomes (e.g., mental health and academic performance). Using 2 h, high resolution, functional magnetic resonance imaging (fMRI) resting state data of 984 (primary dataset N = 801, hold-out dataset N = 183) participants from the Human Connectome Project (HCP), we investigated the relationship between personality (five-factor model, FFM) and intrinsic whole-brain functional connectome...
October 30, 2018: NeuroImage
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