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https://www.readbyqxmd.com/read/28641247/modeling-task-fmri-data-via-deep-convolutional-autoencoder
#1
Heng Huang, Xintao Hu, Yu Zhao, Milad Makkie, Qinglin Dong, Shijie Zhao, Lei Guo, Tianming Liu
Task-based fMRI (tfMRI) has been widely used to study functional brain networks under task performance. Modeling tfMRI data is challenging due to at least two problems: the lack of the ground truth of underlying neural activity and the highly complex intrinsic structure of tfMRI data. To better understand brain networks based on fMRI data, data-driven approaches have been proposed, for instance, Independent Component Analysis (ICA) and Sparse Dictionary Learning (SDL). However, both ICA and SDL only build shallow models, and they are under the strong assumption that original fMRI signal could be linearly decomposed into time series components with their corresponding spatial maps...
June 15, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28641239/automatic-recognition-of-fmri-derived-functional-networks-using-3d-convolutional-neural-networks
#2
Yu Zhao, Qinglin Dong, Shu Zhang, Wei Zhang, Hanbo Chen, Xi Jiang, Lei Guo, Xintao Hu, Junwei Han, Tianming Liu
Current fMRI data modeling techniques such as Independent Component Analysis (ICA) and Sparse Coding methods can effectively reconstruct dozens or hundreds of concurrent interacting functional brain networks simultaneously from the whole brain fMRI signals. However, such reconstructed networks have no correspondences across different subjects. Thus, automatic, effective and accurate classification and recognition of these large numbers of fMRI-derived functional brain networks are very important for subsequent steps of functional brain analysis in cognitive and clinical neuroscience applications...
June 15, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28638316/a-new-generation-of-brain-computer-interfaces-driven-by-discovery-of-latent-eeg-fmri-linkages-using-tensor-decomposition
#3
Gopikrishna Deshpande, D Rangaprakash, Luke Oeding, Andrzej Cichocki, Xiaoping P Hu
A Brain-Computer Interface (BCI) is a setup permitting the control of external devices by decoding brain activity. Electroencephalography (EEG) has been extensively used for decoding brain activity since it is non-invasive, cheap, portable, and has high temporal resolution to allow real-time operation. Due to its poor spatial specificity, BCIs based on EEG can require extensive training and multiple trials to decode brain activity (consequently slowing down the operation of the BCI). On the other hand, BCIs based on functional magnetic resonance imaging (fMRI) are more accurate owing to its superior spatial resolution and sensitivity to underlying neuronal processes which are functionally localized...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28637279/high-dimensional-multivariate-mediation-with-application-to-neuroimaging-data
#4
Oliver Y Chén, Ciprian Crainiceanu, Elizabeth L Ogburn, Brian S Caffo, Tor D Wager, Martin A Lindquist
Mediation analysis is an important tool in the behavioral sciences for investigating the role of intermediate variables that lie in the path between a treatment and an outcome variable. The influence of the intermediate variable on the outcome is often explored using a linear structural equation model (LSEM), with model coefficients interpreted as possible effects. While there has been significant research on the topic, little work has been done when the intermediate variable (mediator) is a high-dimensional vector...
June 15, 2017: Biostatistics
https://www.readbyqxmd.com/read/28626019/neural-mechanisms-of-updating-under-reducible-and-irreducible-uncertainty
#5
Kenji Kobayashi, Ming Hsu
Adaptive decision-making depends on agents' ability to make use of environmental signals to reduce uncertainty. However, because there exist multiple types of uncertainty, agents should take into account not only the extent to which signals violate prior expectancy but also whether uncertainty can be reduced in the first place. Here we studied how the human brain of both sexes responds to signals under conditions of reducible and irreducible uncertainty. We show behaviorally that subjects' value updating was sensitivity to the reducibility of uncertainty, and could be quantitative characterized by a Bayesian model where agents ignore expectancy violations that do not update beliefs or values...
June 16, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28619656/the-large-scale-functional-connectivity-correlates-of-consciousness-and-arousal-during-the-healthy-and-pathological-human-sleep-cycle
#6
REVIEW
Enzo Tagliazucchi, Eus J W van Someren
Advances in neuroimaging have greatly improved our understanding of human sleep from a systems neuroscience perspective. However, cognition and awareness are reduced during sleep, hindering the applicability of standard task-based paradigms. Methods recently developed to study spontaneous brain activity fluctuations have proven useful to overcome this limitation. In this review, we focus on the concept of functional connectivity (FC, i.e. statistical covariance between brain activity signals) and its application to functional magnetic resonance imaging (fMRI) data acquired during sleep...
June 12, 2017: NeuroImage
https://www.readbyqxmd.com/read/28615426/modulation-of-intrinsic-resting-state-fmri-networks-in-women-with-chronic-migraine
#7
X Michelle Androulakis, Kaitlin Krebs, B Lee Peterlin, Tianming Zhang, Nasim Maleki, Souvik Sen, Chris Rorden, Priyantha Herath
OBJECTIVE: To evaluate the intrinsic resting functional connectivity of the default mode network (DMN), salience network (SN), and central executive network (CEN) network in women with chronic migraine (CM), and whether clinical features are associated with such abnormalities. METHODS: We analyzed resting-state connectivity in 29 women with CM as compared to age- and sex-matched controls. Relationships between clinical characteristics and changes in targeted networks connectivity were evaluated using a multivariate linear regression model...
June 14, 2017: Neurology
https://www.readbyqxmd.com/read/28606805/decision-ambiguity-is-mediated-by-a-late-positive-potential-originating-from-cingulate-cortex
#8
Sai Sun, Shanshan Zhen, Zhongzheng Fu, Daw-An Wu, Shinsuke Shimojo, Ralph Adolphs, Rongjun Yu, Shuo Wang
People often make decisions in the face of ambiguous information, but it remains unclear how ambiguity is represented in the brain. We used three types of ambiguous stimuli and combined EEG and fMRI to examine the neural representation of perceptual decisions under ambiguity. We identified a late positive potential, the LPP, which differentiated levels of ambiguity, and which was specifically associated with behavioral judgments about choices that were ambiguous, rather than passive perception of ambiguous stimuli...
June 9, 2017: NeuroImage
https://www.readbyqxmd.com/read/28602945/the-energy-landscape-underpinning-module-dynamics-in-the-human-brain-connectome
#9
Arian Ashourvan, Shi Gu, Marcelo G Mattar, Jean M Vettel, Danielle S Bassett
Human brain dynamics can be viewed through the lens of statistical mechanics, where neurophysiological activity evolves around and between local attractors representing mental states. Many physically-inspired models of these dynamics define brain states based on instantaneous measurements of regional activity. Yet, recent work in network neuroscience has provided evidence that the brain might also be well-characterized by time-varying states composed of locally coherent activity or functional modules. We study this network-based notion of brain state to understand how functional modules dynamically interact with one another to perform cognitive functions...
June 7, 2017: NeuroImage
https://www.readbyqxmd.com/read/28600737/extendable-supervised-dictionary-learning-for-exploring-diverse-and-concurrent-brain-activities-in-task-based-fmri
#10
Shijie Zhao, Junwei Han, Xintao Hu, Xi Jiang, Jinglei Lv, Tuo Zhang, Shu Zhang, Lei Guo, Tianming Liu
Recently, a growing body of studies have demonstrated the simultaneous existence of diverse brain activities, e.g., task-evoked dominant response activities, delayed response activities and intrinsic brain activities, under specific task conditions. However, current dominant task-based functional magnetic resonance imaging (tfMRI) analysis approach, i.e., the general linear model (GLM), might have difficulty in discovering those diverse and concurrent brain responses sufficiently. This subtraction-based model-driven approach focuses on the brain activities evoked directly from the task paradigm, thus likely overlooks other possible concurrent brain activities evoked during the information processing...
June 9, 2017: Brain Imaging and Behavior
https://www.readbyqxmd.com/read/28600253/robust-granger-analysis-in-lp-norm-space-for-directed-eeg-network-analysis
#11
PeiYang Li, Xiaoye Huang, Fali Li, Xurui Wang, Weiwei Zhou, Huan Liu, Teng Ma, Tao Zhang, Daqing Guo, Dezhong Yao, Peng Xu
Granger analysis (GA) is widely used to construct directed brain networks based on various physiological recordings, such as functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), etc. However, in real applications, EEGs are inevitably contaminated by unexpected artifacts that may distort the networks because of the L2 norm structure utilized in GAs when estimating directed links. Compared with the L2 norm, the Lp (p ≤ 1) norm can compress outlier effects. In this study, an extended GA is constructed by applying the Lp (p ≤ 1) norm strategy to estimate robust causalities under outlier conditions, and a feasible iteration procedure is utilized to solve the new GA model...
June 5, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28598734/does-psychosocial-stress-impact-cognitive-reappraisal-behavioral-and-neural-evidence
#12
Maheen Shermohammed, Pranjal H Mehta, Joan Zhang, Cassandra M Brandes, Luke J Chang, Leah H Somerville
Cognitive reappraisal (CR) is regarded as an effective emotion regulation strategy. Acute stress, however, is believed to impair the functioning of prefrontal-based neural systems, which could result in lessened effectiveness of CR under stress. This study tested the behavioral and neurobiological impact of acute stress on CR. While undergoing fMRI, adult participants ( n = 54) passively viewed or used CR to regulate their response to negative and neutral pictures and provided ratings of their negative affect in response to each picture...
June 9, 2017: Journal of Cognitive Neuroscience
https://www.readbyqxmd.com/read/28598432/neural-correlates-of-evidence-accumulation-during-value-based-decisions-revealed-via-simultaneous-eeg-fmri
#13
M Andrea Pisauro, Elsa Fouragnan, Chris Retzler, Marios G Philiastides
Current computational accounts posit that, in simple binary choices, humans accumulate evidence in favour of the different alternatives before committing to a decision. Neural correlates of this accumulating activity have been found during perceptual decisions in parietal and prefrontal cortex; however the source of such activity in value-based choices remains unknown. Here we use simultaneous EEG-fMRI and computational modelling to identify EEG signals reflecting an accumulation process and demonstrate that the within- and across-trial variability in these signals explains fMRI responses in posterior-medial frontal cortex...
June 9, 2017: Nature Communications
https://www.readbyqxmd.com/read/28588065/the-hierarchical-cortical-organization-of-human-speech-processing
#14
Wendy A de Heer, Alexander G Huth, Thomas L Griffiths, Jack L Gallant, Frédéric E Theunissen
Speech comprehension requires that the brain extract semantic meaning from the spectral features represented at the cochlea. To investigate this process, we performed an fMRI experiment in which five men and two women passively listened to several hours of natural narrative speech. We then used voxel-wise modeling to predict BOLD responses based on three different feature spaces that represent the spectral, articulation, and semantic properties of speech. The amount of variance explained by each feature space was then assessed using a separate validation dataset...
June 6, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28581478/reinstated-episodic-context-guides-sampling-based-decisions-for-reward
#15
Aaron M Bornstein, Kenneth A Norman
How does experience inform decisions? In episodic sampling, decisions are guided by a few episodic memories of past choices. This process can yield choice patterns similar to model-free reinforcement learning; however, samples can vary from trial to trial, causing decisions to vary. Here we show that context retrieved during episodic sampling can cause choice behavior to deviate sharply from the predictions of reinforcement learning. Specifically, we show that, when a given memory is sampled, choices (in the present) are influenced by the properties of other decisions made in the same context as the sampled event...
June 5, 2017: Nature Neuroscience
https://www.readbyqxmd.com/read/28580693/changes-in-brain-activity-following-intensive-voice-treatment-in-children-with-cerebral-palsy
#16
Reyhaneh Bakhtiari, Jacqueline Cummine, Alesha Reed, Cynthia M Fox, Brea Chouinard, Ivor Cribben, Carol A Boliek
Eight children (3 females; 8-16 years) with motor speech disorders secondary to cerebral palsy underwent 4 weeks of an intensive neuroplasticity-principled voice treatment protocol, LSVT LOUD(®) , followed by a structured 12-week maintenance program. Children were asked to overtly produce phonation (ah) at conversational loudness, cued-phonation at perceived twice-conversational loudness, a series of single words, and a prosodic imitation task while being scanned using fMRI, immediately pre- and post-treatment and 12 weeks following a maintenance program...
June 5, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28579965/neural-correlates-of-psychotherapeutic-treatment-of-post-traumatic-stress-disorder-a-systematic-literature-review
#17
Kathrin Malejko, Birgit Abler, Paul L Plener, Joana Straub
OBJECTIVES: Post-traumatic stress disorder (PTSD) is a common psychiatric disease with changes in neural circuitries. Neurobiological models conceptualize the symptoms of PTSD as correlates of a dysfunctional stress reaction to traumatic events. Functional imaging studies showed an increased amygdala and a decreased prefrontal cortex response in PTSD patients. As psychotherapeutic approaches represent the gold standard for PTSD treatment, it is important to examine its underlying neurobiological correlates...
2017: Frontiers in Psychiatry
https://www.readbyqxmd.com/read/28579187/functional-mri-bold-response-in-sickle-mice-with-hyperalgesia
#18
Ying Wang, Xiao Wang, Wei Chen, Kalpna Gupta, Xiao-Hong Zhu
Patients with sickle cell anemia (SCA) have abnormal hemoglobin (sickle hemoglobin S) leading to the crystallization of hemoglobin chains in red blood cells (RBCs), which assume sickle shape and display reduced flexibility. Sickle RBCs (sRBCs) adhere to vessel walls and block blood flow, thus preventing oxygen delivery to the tissues leading to vaso-occlusive crises (VOC), acute pain and organ damage. SCA patients often have chronic pain that can be attributed to inflammation, vasculopathy, neuropathy, ischemia-reperfusion injury and organ damage...
June 2017: Blood Cells, Molecules & Diseases
https://www.readbyqxmd.com/read/28575424/association-between-habenula-dysfunction-and-motivational-symptoms-in-unmedicated-major-depressive-disorder
#19
Wen-Hua Liu, Vincent Valton, Ling-Zhi Wang, Yu-Hua Zhu, Jonathan P Roiser
The lateral habenula plays a central role in reward and punishment processing and has been suggested to drive the cardinal symptom of anhedonia in depression. This hypothesis is largely based on observations of habenula hypermetabolism in animal models of depression, but the activity of habenula and its relationship with clinical symptoms in patients with depression remains unclear. High-resolution functional magnetic resonance imaging (fMRI) and computational modelling were used to investigate the activity of the habenula during a probabilistic reinforcement learning task with rewarding and punishing outcomes in 21 unmedicated patients with major depression and 17 healthy participants...
May 29, 2017: Social Cognitive and Affective Neuroscience
https://www.readbyqxmd.com/read/28567171/a-functional-mri-based-model-for-individual-memory-assessment-in-patients-eligible-for-anterior-temporal-lobe-resection
#20
Maria Strandberg, Peter Mannfolk, Lars Stenberg, Hanna Ljung, Ia Rorsman, Elna-Marie Larsson, Danielle van Westen, Kristina Källén
TITLE: A functional (f) MRI-based model for individual memory assessment in patients eligible for temporal lobe resection. AIM: To investigate if pre-operative fMRI memory paradigms, add predictive information with regard to post-surgical memory deficits. METHODS: Fourteen pharmacoresistant Temporal Lobe Epilepsy (TLE) patients accepted for Anterior Temporal Lobe Resection (ATLR) were included. A clinical risk assessment score (RAS 0-3) was constructed from structural MRI, neuropsychological testing and hemisphere dominance...
2017: Open Neuroimaging Journal
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