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https://www.readbyqxmd.com/read/28527694/voluntary-wheel-running-ameliorates-depression-like-behaviors-and-brain-blood-oxygen-level-dependent-signals-in-chronic-unpredictable-mild-stress-mice
#1
Peng Huang, Zhaoyang Dong, Weiliang Huang, Chuying Zhou, Weichao Zhong, Peiqian Hu, Ge Wen, Xuegang Sun, Heyu Hua, Huihui Cao, Lei Gao, Zhiping Lv
BACKGROUND: Physical exercise has been long recognized for its therapeutic effects on depressive disorders, but the underlying mechanisms remain largely unknown. In the study, we investigated whether the physical exercise by voluntary wheel running (VWR) alters depression-like behaviors and its impact on brain blood oxygen level-dependent (BOLD) signals in mice. METHODS: Adult male C57BL/6 mice were assigned to one of the following groups; (1) no exercise control (noEx), housed in a standard cage; (2) exercise (Ex), 2hours/day in a running wheel apparatus; (3) chronic unpredictable mild stress (CUMS), which was imitating adult stress; and (4) CUMS+Ex...
May 17, 2017: Behavioural Brain Research
https://www.readbyqxmd.com/read/28505152/a-predictive-coding-account-of-bistable-perception-a-model-based-fmri-study
#2
Veith Weilnhammer, Heiner Stuke, Guido Hesselmann, Philipp Sterzer, Katharina Schmack
In bistable vision, subjective perception wavers between two interpretations of a constant ambiguous stimulus. This dissociation between conscious perception and sensory stimulation has motivated various empirical studies on the neural correlates of bistable perception, but the neurocomputational mechanism behind endogenous perceptual transitions has remained elusive. Here, we recurred to a generic Bayesian framework of predictive coding and devised a model that casts endogenous perceptual transitions as a consequence of prediction errors emerging from residual evidence for the suppressed percept...
May 15, 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28503664/fixing-the-stimulus-as-fixed-effect-fallacy-in-task-fmri
#3
Jacob Westfall, Thomas E Nichols, Tal Yarkoni
Most functional magnetic resonance imaging (fMRI) experiments record the brain's responses to samples of stimulus materials (e.g., faces or words). Yet the statistical modeling approaches used in fMRI research universally fail to model stimulus variability in a manner that affords population generalization, meaning that researchers' conclusions technically apply only to the precise stimuli used in each study, and cannot be generalized to new stimuli. A direct consequence of this stimulus-as-fixed-effect fallacy is that the majority of published fMRI studies have likely overstated the strength of the statistical evidence they report...
December 9, 2016: Wellcome Open Research
https://www.readbyqxmd.com/read/28498564/spatial-bayesian-latent-factor-regression-modeling-of-coordinate-based-meta-analysis-data
#4
Silvia Montagna, Tor Wager, Lisa Feldman Barrett, Timothy D Johnson, Thomas E Nichols
Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA...
May 12, 2017: Biometrics
https://www.readbyqxmd.com/read/28497802/data-driven-subgroups-in-depression-derived-from-directed-functional-connectivity-paths-at-rest
#5
Rebecca B Price, Kathleen Gates, Thomas E Kraynak, Michael E Thase, Greg J Siegle
Depressed patients show abnormalities in brain connectivity at rest, including hyperconnectivity within the Default Mode Network (DMN). However, there is well-known heterogeneity in the clinical presentation of depression that is overlooked when averaging connectivity data. We used data-driven parsing of neural connectivity to reveal subgroups among 80 depressed patients completing resting state fMRI. Directed functional connectivity paths (eg, region A influences region B) within a depression-relevant network were characterized using Group Iterative Multiple Model Estimation, a method shown to accurately recover the direction and presence of connectivity paths in individual participants...
May 12, 2017: Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology
https://www.readbyqxmd.com/read/28491032/topological-filtering-of-dynamic-functional-brain-networks-unfolds-informative-chronnectomics-a-novel-data-driven-thresholding-scheme-based-on-orthogonal-minimal-spanning-trees-omsts
#6
Stavros I Dimitriadis, Christos Salis, Ioannis Tarnanas, David E Linden
The human brain is a large-scale system of functionally connected brain regions. This system can be modeled as a network, or graph, by dividing the brain into a set of regions, or "nodes," and quantifying the strength of the connections between nodes, or "edges," as the temporal correlation in their patterns of activity. Network analysis, a part of graph theory, provides a set of summary statistics that can be used to describe complex brain networks in a meaningful way. The large-scale organization of the brain has features of complex networks that can be quantified using network measures from graph theory...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28487746/depression-disorder-classification-of-fmri-data-using-sparse-low-rank-functional-brain-network-and-graph-based-features
#7
Xin Wang, Yanshuang Ren, Wensheng Zhang
Study of functional brain network (FBN) based on functional magnetic resonance imaging (fMRI) has proved successful in depression disorder classification. One popular approach to construct FBN is Pearson correlation. However, it only captures pairwise relationship between brain regions, while it ignores the influence of other brain regions. Another common issue existing in many depression disorder classification methods is applying only single local feature extracted from constructed FBN. To address these issues, we develop a new method to classify fMRI data of patients with depression and healthy controls...
2017: Computational and Mathematical Methods in Medicine
https://www.readbyqxmd.com/read/28484402/to-resolve-or-not-to-resolve-that-is-the-question-the-dual-path-model-of-incongruity-resolution-and-absurd-verbal-humor-by-fmri
#8
Ru H Dai, Hsueh-Chih Chen, Yu C Chan, Ching-Lin Wu, Ping Li, Shu L Cho, Jon-Fan Hu
It is well accepted that the humor comprehension processing involves incongruity detection and resolution and then induces a feeling of amusement. However, this three-stage model of humor processing does not apply to absurd humor (so-called nonsense humor). Absurd humor contains an unresolvable incongruity but can still induce a feeling of mirth. In this study, we used functional magnetic resonance imaging (fMRI) to identify the neural mechanisms of absurd humor. Specifically, we aimed to investigate the neural substrates associated with the complete resolution of incongruity resolution humor and partial resolution of absurd humor...
2017: Frontiers in Psychology
https://www.readbyqxmd.com/read/28476213/reprint-of-using-neuroimaging-to-individualize-tms-treatment-for-depression-toward-a-new-paradigm-for-imaging-guided-intervention
#9
Bruce M Luber, Simon Davis, Elisabeth Bernhardt, Andrada Neacsiu, Lori Kwapil, Sarah H Lisanby, Timothy J Strauman
The standard clinical technique for using repetitive transcranial magnetic stimulation (rTMS) for major depressive disorder (MDD) is associated with limited efficacy to date. Such limited efficacy may be due to reliance on scalp-based targeting rather than state-of-the-science methods which incorporate fMRI-guided neuronavigation based on a specific model of neurocircuit dysfunction. In this review, we examine such a specific model drawn from regulatory focus theory, which postulates two brain/behavior systems, the promotion and prevention systems, underlying goal pursuit...
May 1, 2017: NeuroImage
https://www.readbyqxmd.com/read/28466439/high-sensitivity-neuroimaging-biomarkers-for-the-identification-of-amnestic-mild-cognitive-impairment-based-on-resting-state-fmri-and-a-triple-network-model
#10
Enyan Yu, Zhengluan Liao, Yunfei Tan, Yaju Qiu, Junpeng Zhu, Zhang Han, Jue Wang, Xinwei Wang, Hong Wang, Yan Chen, Qi Zhang, Yumei Li, Dewang Mao, Zhongxiang Ding
Many functional magnetic resonance imaging (fMRI) studies have indicated that Granger causality analysis (GCA) is a suitable method for revealing causal effects between brain regions. The purpose of the present study was to identify neuroimaging biomarkers with a high sensitivity to amnestic mild cognitive impairment (aMCI). The resting-state fMRI data of 30 patients with Alzheimer's disease (AD), 14 patients with aMCI, and 18 healthy controls (HC) were evaluated using GCA. This study focused on the "triple networks" concept, a recently proposed higher-order functioning-related brain network model that includes the default-mode network (DMN), salience network (SN), and executive control network (ECN)...
May 3, 2017: Brain Imaging and Behavior
https://www.readbyqxmd.com/read/28461061/optimization-of-functional-mri-for-detection-decoding-and-high-resolution-imaging-of-the-response-patterns-of-cortical-columns
#11
Denis Chaimow, Kâmil Uğurbil, Amir Shmuel
The capacity of functional MRI (fMRI) to resolve cortical columnar organizations depends on several factors, e.g. the spatial scale of the columnar pattern, the point-spread of the fMRI response, the voxel size, and the SNR considering thermal and physiological noise. How these factors combine, and what is the voxel size that optimizes fMRI of cortical columns remain unknown. Here we combine current knowledge into a quantitative model of fMRI of realistic patterns of cortical columns of different spatial scales and degrees of irregularity...
April 28, 2017: NeuroImage
https://www.readbyqxmd.com/read/28450541/spatial-attention-motor-intention-and-bayesian-cue-predictability-in-the-human-brain
#12
Anna B Kuhns, Pascasie L Dombert, Paola Mengotti, Gereon R Fink, Simone Vossel
Predictions about upcoming events influence how we perceive and respond to our environment. There is increasing evidence that predictions may be generated based upon previous observations following Bayesian principles, but little is known about the underlying cortical mechanisms and their specificity for different cognitive subsystems. The present study aimed at identifying common and distinct neural signatures of predictive processing in the spatial attentional and motor intentional systems. Twenty-three female and male healthy human volunteers performed two probabilistic cueing tasks with either spatial or motor cues while lying in the fMRI scanner...
April 27, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28439231/informing-the-structure-of-executive-function-in-children-a-meta-analysis-of-functional-neuroimaging-data
#13
Róisín McKenna, T Rushe, Kate A Woodcock
The structure of executive function (EF) has been the focus of much debate for decades. What is more, the complexity and diversity provided by the developmental period only adds to this contention. The development of executive function plays an integral part in the expression of children's behavioral, cognitive, social, and emotional capabilities. Understanding how these processes are constructed during development allows for effective measurement of EF in this population. This meta-analysis aims to contribute to a better understanding of the structure of executive function in children...
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/28439014/brain-networks-for-confidence-weighting-and-hierarchical-inference-during-probabilistic-learning
#14
Florent Meyniel, Stanislas Dehaene
Learning is difficult when the world fluctuates randomly and ceaselessly. Classical learning algorithms, such as the delta rule with constant learning rate, are not optimal. Mathematically, the optimal learning rule requires weighting prior knowledge and incoming evidence according to their respective reliabilities. This "confidence weighting" implies the maintenance of an accurate estimate of the reliability of what has been learned. Here, using fMRI and an ideal-observer analysis, we demonstrate that the brain's learning algorithm relies on confidence weighting...
April 24, 2017: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/28434861/representation-of-multiple-body-parts-in-the-missing-hand-territory-of-congenital-one-handers
#15
Avital Hahamy, Scott N Macdonald, Fiona van den Heiligenberg, Paullina Kieliba, Uzay Emir, Rafael Malach, Heidi Johansen-Berg, Peter Brugger, Jody C Culham, Tamar R Makin
Individuals born without one hand (congenital one-handers) provide a unique model for understanding the relationship between focal reorganization in the sensorimotor cortex and everyday behavior. We previously reported that the missing hand's territory of one-handers becomes utilized by its cortical neighbor (residual arm representation), depending on residual arm usage in daily life to substitute for the missing hand's function [1, 2]. However, the repertoire of compensatory behaviors may involve utilization of other body parts that do not cortically neighbor the hand territory...
May 8, 2017: Current Biology: CB
https://www.readbyqxmd.com/read/28431740/getting-a-grip-on-reality-grasping-movements-directed-to-real-objects-and-images-rely-on-dissociable-neural-representations
#16
Erez Freud, Scott N Macdonald, Juan Chen, Derek J Quinlan, Melvyn A Goodale, Jody C Culham
In the current era of touchscreen technology, humans commonly execute visually guided actions directed to two-dimensional (2D) images of objects. Although real, three-dimensional (3D), objects and images of the same objects share high degree of visual similarity, they differ fundamentally in the actions that can be performed on them. Indeed, previous behavioral studies have suggested that simulated grasping of images relies on different representations than actual grasping of real 3D objects. Yet the neural underpinnings of this phenomena have not been investigated...
March 18, 2017: Cortex; a Journal Devoted to the Study of the Nervous System and Behavior
https://www.readbyqxmd.com/read/28426802/decoding-the-infant-mind-multivariate-pattern-analysis-mvpa-using-fnirs
#17
Lauren L Emberson, Benjamin D Zinszer, Rajeev D S Raizada, Richard N Aslin
The MRI environment restricts the types of populations and tasks that can be studied by cognitive neuroscientists (e.g., young infants, face-to-face communication). FNIRS is a neuroimaging modality that records the same physiological signal as fMRI but without the constraints of MRI, and with better spatial localization than EEG. However, research in the fNIRS community largely lacks the analytic sophistication of analogous fMRI work, restricting the application of this imaging technology. The current paper presents a method of multivariate pattern analysis for fNIRS that allows the authors to decode the infant mind (a key fNIRS population)...
2017: PloS One
https://www.readbyqxmd.com/read/28420788/reconstructing-the-spectrotemporal-modulations-of-real-life-sounds-from-fmri-response-patterns
#18
Roberta Santoro, Michelle Moerel, Federico De Martino, Giancarlo Valente, Kamil Ugurbil, Essa Yacoub, Elia Formisano
Ethological views of brain functioning suggest that sound representations and computations in the auditory neural system are optimized finely to process and discriminate behaviorally relevant acoustic features and sounds (e.g., spectrotemporal modulations in the songs of zebra finches). Here, we show that modeling of neural sound representations in terms of frequency-specific spectrotemporal modulations enables accurate and specific reconstruction of real-life sounds from high-resolution functional magnetic resonance imaging (fMRI) response patterns in the human auditory cortex...
May 2, 2017: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/28413706/basic-taste-processing-recruits-bilateral-anteroventral-and-middle-dorsal-insulae-an-activation-likelihood-estimation-meta-analysis-of-fmri-studies
#19
Andy Wai Kan Yeung, Tazuko K Goto, Wai Keung Leung
BACKGROUND AND PURPOSE: Numerous task-based functional magnetic resonance imaging (fMRI) studies have reported the locations of basic taste representations in the human brain, but they usually employed a limited number of subjects (<20) with different methodologies and stimuli. Moreover, the reported brain regions were sometimes inconsistent. Thus, we aimed at performing a meta-analysis of the published data to identify locations consistently activated across studies, and performed a connectivity analysis to reveal how these taste processing regions connect with other brain regions...
April 2017: Brain and Behavior
https://www.readbyqxmd.com/read/28403383/neural-signatures-of-cognitive-flexibility-and-reward-sensitivity-following-nicotinic-receptor-stimulation-in-dependent-smokers-a-randomized-trial
#20
Elise Lesage, Sarah E Aronson, Matthew T Sutherland, Thomas J Ross, Betty Jo Salmeron, Elliot A Stein
Importance: Withdrawal from nicotine is an important contributor to smoking relapse. Understanding how reward-based decision making is affected by abstinence and by pharmacotherapies such as nicotine replacement therapy and varenicline tartrate may aid cessation treatment. Objective: To independently assess the effects of nicotine dependence and stimulation of the nicotinic acetylcholine receptor on the ability to interpret valence information (reward sensitivity) and subsequently alter behavior as reward contingencies change (cognitive flexibility) in a probabilistic reversal learning task...
April 12, 2017: JAMA Psychiatry
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