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Yohan Yee, Darren J Fernandes, Leon French, Jacob Ellegood, Lindsay S Cahill, Dulcie A Vousden, Leigh Spencer Noakes, Jan Scholz, Matthijs C van Eede, Brian J Nieman, John G Sled, Jason P Lerch
An organizational pattern seen in the brain, termed structural covariance, is the statistical association of pairs of brain regions in their anatomical properties. These associations, measured across a population as covariances or correlations usually in cortical thickness or volume, are thought to reflect genetic and environmental underpinnings. Here, we examine the biological basis of structural volume covariance in the mouse brain. We first examined large scale associations between brain region volumes using an atlas-based approach that parcellated the entire mouse brain into 318 regions over which correlations in volume were assessed, for volumes obtained from 153 mouse brain images via high-resolution MRI...
May 18, 2018: NeuroImage
Yuan Wang, Yao Wang, Yvonne W Lui
Dynamic Causal Modeling (DCM) is an advanced biophysical model which explicitly describes the entire process from experimental stimuli to functional magnetic resonance imaging (fMRI) signals via neural activity and cerebral hemodynamics. To conduct a DCM study, one needs to represent the experimental stimuli as a compact vector-valued function of time, which is hard in complex tasks such as book reading and natural movie watching. Deep learning provides the state-of-the-art signal representation solution, encoding complex signals into compact dense vectors while preserving the essence of the original signals...
May 18, 2018: NeuroImage
Tavia E Evans, Hieab H H Adams, Silvan Licher, Frank J Wolters, Aad van der Lugt, M Kamran Ikram, Michael J O'Sullivan, Meike W Vernooij, M Arfan Ikram
BACKGROUND: Total hippocampal volume has been consistently linked to cognitive function and dementia. Yet, given its complex and parcellated internal structure, the role of subregions of the hippocampus in cognition and risk of dementia remains relatively underexplored. We studied subregions of the hippocampus in a large population-based cohort to further understand their role in cognitive impairment and dementia risk. METHODS: We studied 5035 dementia- and stroke-free persons from the Rotterdam Study, aged over 45 years...
May 17, 2018: NeuroImage
Adora M DSouza, Anas Z Abidin, Udaysankar Chockanathan, Giovanni Schifitto, Axel Wismüller
Functional connectivity analysis of functional MRI (fMRI) can represent brain networks and reveal insights into interactions amongst different brain regions. However, most connectivity analysis approaches adopted in practice are linear and non-directional. In this paper, we demonstrate the advantage of a data-driven, directed connectivity analysis approach called Mutual Connectivity Analysis using Local Models (MCA-LM) that approximates connectivity by modeling nonlinear dependencies of signal interaction, over more conventionally used approaches, such as Pearson's and partial correlation, Patel's conditional dependence measures, etcetera...
May 16, 2018: NeuroImage
Hanna Keren, Gang Chen, Brenda Benson, Monique Ernst, Ellen Leibenluft, Nathan A Fox, Daniel S Pine, Argyris Stringaris
Reward Prediction Errors (RPEs), defined as the difference between the expected and received outcomes, are integral to reinforcement learning models and play an important role in development and psychopathology. In humans, RPE encoding can be estimated using fMRI recordings, however, a basic measurement property of RPE signals, their test-retest reliability across different time scales, remains an open question. In this paper, we examine the 3-month and 3-year reliability of RPE encoding in youth (mean age at baseline = 10...
May 16, 2018: NeuroImage
Nicole Proulx, Ali-Akbar Samadani, Tom Chau
Event-related potentials (ERPs) have previously been used to confirm the existence of the fast optical signal (FOS) but validation methods have mainly been limited to exploring the temporal correspondence of FOS peaks to those of ERPs. The purpose of this study was to systematically quantify the relationship between FOS and ERP responses to a visual oddball task in both time and frequency domains. Near-infrared spectroscopy (NIRS) and electroencephalography (EEG) sensors were co-located over the prefrontal cortex while participants performed a visual oddball task...
May 16, 2018: NeuroImage
B B Bankson, M N Hebart, I I A Groen, C I Baker
Visual object representations are commonly thought to emerge rapidly, yet it has remained unclear to what extent early brain responses reflect purely low-level visual features of these objects and how strongly those features contribute to later categorical or conceptual representations. Here, we aimed to estimate a lower temporal bound for the emergence of conceptual representations by defining two criteria that characterize such representations: 1) conceptual object representations should generalize across different exemplars of the same object, and 2) these representations should reflect high-level behavioral judgments...
May 16, 2018: NeuroImage
Peter Fransson, Björn C Schiffler, William Hedley Thompson
The characterization of brain subnetwork segregation and integration has previously focused on changes that are detectable at the level of entire sessions or epochs of imaging data. In this study, we applied time-varying functional connectivity analysis together with temporal network theory to calculate point-by-point estimates in subnetwork segregation and integration during an epoch-based (2-back, 0-back, baseline) working memory fMRI experiment as well as during resting-state. This approach allowed us to follow task-related changes in subnetwork segregation and integration at a high temporal resolution...
May 16, 2018: NeuroImage
Sathesan Thavabalasingam, Edward B O'Neil, Andy C H Lee
Recent rodent work suggests the hippocampus may provide a temporal representation of event sequences, in which the order of events and the interval durations between them are encoded. There is, however, limited human evidence for the latter, in particular whether the hippocampus processes duration information pertaining to the passage of time rather than qualitative or quantitative changes in event content. We scanned participants while they made match/mismatch judgements on each trial between a study sequence of events and a subsequent test sequence...
May 15, 2018: NeuroImage
Yi Pu, Brian R Cornwell, Douglas Cheyne, Blake W Johnson
In rodents, hippocampal cell assemblies formed during learning of a navigation task are observed to re-emerge during resting (offline) periods, accompanied by high-frequency oscillations (HFOs). This phenomenon is believed to reflect mechanisms for strengthening newly-formed memory traces. Using magnetoencephalography recordings and a beamforming source location algorithm (synthetic aperture magnetometry), we investigated high-gamma (80-140 Hz) oscillations in the hippocampal region in 18 human participants during inter-trial rest periods in a virtual navigation task...
May 14, 2018: NeuroImage
Begoña Díaz, Helen Blank, Katharina von Kriegstein
The cerebral cortex modulates early sensory processing via feed-back connections to sensory pathway nuclei. The functions of this top-down modulation for human behavior are poorly understood. Here, we show that top-down modulation of the visual sensory thalamus (the lateral geniculate body, LGN) is involved in visual-speech recognition. In two independent functional magnetic resonance imaging (fMRI) studies, LGN response increased when participants processed fast-varying features of articulatory movements required for visual-speech recognition, as compared to temporally more stable features required for face identification with the same stimulus material...
May 14, 2018: NeuroImage
Rudolf Nieuwenhuys
Morphological and genoarchitectonic studies have conclusively shown that the human brain (and that of all vertebrates) is segmented i. e. is fundamentally composed of a number of rostrocaudally arranged brain segments or neuromeres. However in the current neuroimaging literature the term segmentation, derived initially from computer graphics technology, is used instead to indicate the neuroanatomical parcellation or subdivision of neural structures in the fully formed brain, especially the cortex. The neuroimaging community should be aware of the prior use of this term in the parallel discipline of neuroembryology, and should use a different one e...
May 14, 2018: NeuroImage
Yaakov Stern, Yunglin Gazes, Qolomreza Razlighi, Jason Steffener, Christian Habeck
The concept of cognitive reserve (CR) can explain individual differences in susceptibility to cognitive or functional impairment in the presence of age or disease-related brain changes. Epidemiologic evidence indicates that CR helps maintain performance in the face of pathology across multiple cognitive domains. We therefore tried to identify a single, "task-invariant" CR network that is active during the performance of many disparate tasks. In imaging data acquired from 255 individuals age 20-80 while performing 12 different cognitive tasks, we used an iterative approach to derive a multivariate network that was expressed during the performance of all tasks, and whose degree of expression correlated with IQ, a proxy for CR...
May 14, 2018: NeuroImage
Madeleine Verriotis, Laura Jones, Kimberley Whitehead, Pureza Laudiano-Dray, Ismini Panayotidis, Hemani Patel, Judith Meek, Lorenzo Fabrizi, Maria Fitzgerald
In adults, there are differences between male and female structural and functional brain connectivity, specifically for those regions involved in pain processing. This may partly explain the observed sex differences in pain sensitivity, tolerance, and inhibitory control, and in the development of chronic pain. However, it is not known if these differences exist from birth. Cortical activity in response to a painful stimulus can be observed in the human neonatal brain, but this nociceptive activity continues to develop in the postnatal period and is qualitatively different from that of adults, partly due to the considerable cortical maturation during this time...
May 12, 2018: NeuroImage
Dushyant Kumar, Hari Hariharan, Tobias D Faizy, Patrick Borchert, Susanne Siemonsen, Jens Fiehler, Ravinder Reddy, Jan Sedlacik
PURPOSE: We present a computationally feasible and iterative multi-voxel spatially regularized algorithm for myelin water fraction (MWF) reconstruction. This method utilizes 3D spatial correlations present in anatomical/pathological tissues and underlying B1+ -inhomogeneity or flip angle inhomogeneity to enhance the noise robustness of the reconstruction while intrinsically accounting for stimulated echo contributions using T2-distribution data alone. METHODS: Simulated data and in vivo data acquired using 3D non-selective multi-echo spin echo (3DNS-MESE) were used to compare the reconstruction quality of the proposed approach against those of the popular algorithm (the method by Prasloski et al...
May 12, 2018: NeuroImage
Fang-Cheng Yeh, Sandip Panesar, David Fernandes, Antonio Meola, Masanori Yoshino, Juan C Fernandez-Miranda, Jean M Vettel, Timothy Verstynen
A comprehensive map of the structural connectome in the human brain has been a coveted resource for understanding macroscopic brain networks. Here we report an expert-vetted, population-averaged atlas of the structural connectome derived from diffusion MRI data (N = 842). This was achieved by creating a high-resolution template of diffusion patterns averaged across individual subjects and using tractography to generate 550,000 trajectories of representative white matter fascicles annotated by 80 anatomical labels...
May 11, 2018: NeuroImage
Mathilde Spiess, Giulio Bernardi, Salome Kurth, Maya Ringli, Flavia M Wehrle, Oskar G Jenni, Reto Huber, Francesca Siclari
INTRODUCTION: Slow waves, the hallmarks of non-rapid eye-movement (NREM) sleep, are thought to reflect maturational changes that occur in the cerebral cortex throughout childhood and adolescence. Recent work in adults has revealed evidence for two distinct synchronization processes involved in the generation of slow waves, which sequentially come into play in the transition to sleep. In order to understand how these two processes are affected by developmental changes, we compared slow waves between children and young adults in the falling asleep period...
May 11, 2018: NeuroImage
Thomas D Sambrook, Ben Hardwick, Andy J Wills, Jeremy Goslin
Learning theorists posit two reinforcement learning systems: model-free and model-based. Model-based learning incorporates knowledge about structure and contingencies in the world to assign candidate actions with an expected value. Model-free learning is ignorant of the world's structure; instead, actions hold a value based on prior reinforcement, with this value updated by expectancy violation in the form of a reward prediction error. Because they use such different learning mechanisms, it has been previously assumed that model-based and model-free learning are computationally dissociated in the brain...
May 11, 2018: NeuroImage
Lucia Amoruso, Alessandra Finisguerra, Cosimo Urgesi
Context facilitates the recognition of forthcoming actions by pointing to which intention is likely to drive them. This intention is thought to be estimated in a ventral pathway linking MTG with frontal regions and to further impact on the implementation of sensory predictions within the action observation network (AON). Additionally, when conflicting intentions are estimated from context, the DLPFC may bias action selection. However, direct evidence for the contribution of these areas to context-embedded action representations in the AON is still lacking...
May 10, 2018: NeuroImage
Matthew F Glasser, Timothy S Coalson, Janine D Bijsterbosch, Samuel J Harrison, Michael P Harms, Alan Anticevic, David C Van Essen, Stephen M Smith
Temporal fluctuations in functional Magnetic Resonance Imaging (fMRI) have been profitably used to study brain activity and connectivity for over two decades. Unfortunately, fMRI data also contain structured temporal "noise" from a variety of sources, including subject motion, subject physiology, and the MRI equipment. Recently, methods have been developed to automatically and selectively remove spatially specific structured noise from fMRI data using spatial Independent Components Analysis (ICA) and machine learning classifiers...
May 10, 2018: NeuroImage
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