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Large scale brain networks

Sylvain Baillet
We review the aspects that uniquely characterize magnetoencephalography (MEG) among the techniques available to explore and resolve brain function and dysfunction. While emphasizing its specific strengths in terms of millisecond source imaging, we also identify and discuss current practical challenges, in particular in signal extraction and interpretation. We also take issue with some perceived disadvantages of MEG, including the misconception that the technique is redundant with electroencephalography. Overall, MEG contributes uniquely to our deeper comprehension of both regional and large-scale brain dynamics: from the functions of neural oscillations and the nature of event-related brain activation, to the mechanisms of functional connectivity between regions and the emergence of modes of network communication in brain systems...
February 23, 2017: Nature Neuroscience
Yu Meng, Gang Li, Li Wang, Weili Lin, John H Gilmore, Dinggang Shen
The cortical folding of the human brain is highly complex and variable across individuals. Mining the major patterns of cortical folding from modern large-scale neuroimaging datasets is of great importance in advancing techniques for neuroimaging analysis and understanding the inter-individual variations of cortical folding and its relationship with cognitive function and disorders. As the primary cortical folding is genetically influenced and has been established at term birth, neonates with the minimal exposure to the complicated postnatal environmental influence are the ideal candidates for understanding the major patterns of cortical folding...
October 2016: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
Shaoyu Qiao, Kevin A Brown, Amy L Orsborn, Breonna Ferrentino, Bijan Pesaran, Shaoyu Qiao, Kevin A Brown, Amy L Orsborn, Breonna Ferrentino, Bijan Pesaran, Shaoyu Qiao, Amy L Orsborn, Breonna Ferrentino, Kevin A Brown, Bijan Pesaran
The development of novel neurotechnologies for treating refractory neuropsychiatry disorders depends on understanding and manipulating the dynamics of neural circuits across large-scale brain networks. The mesolimbic pathway plays an essential role in reward processing and mood regulation and disorders of this pathway underlie many neuropsychiatric disorders. Here, we present the design of a customized semi-chronic microdrive array that precisely targets the anatomical structures of non-human primate (NHP) mesolimbic and basal ganglia systems...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Maria Anastasiadou, Avgis Hadjipapas, Manolis Christodoulakis, Eleftherios S Papathanasiou, Savvas S Papacostas, Georgios D Mitsis, Maria Anastasiadou, Avgis Hadjipapas, Manolis Christodoulakis, Eleftherios S Papathanasiou, Savvas S Papacostas, Georgios D Mitsis, Maria Anastasiadou, Avgis Hadjipapas, Manolis Christodoulakis, Savvas S Papacostas, Eleftherios S Papathanasiou, Georgios D Mitsis
We investigated the correlation of epileptic seizure onset times with long term EEG functional brain network properties. To do so, we constructed binary functional brain networks from long-term, multichannel electroencephalographic data recorded from nine patients with epilepsy. The corresponding network properties were quantified using the average network degree. It was found that the network degree (as well as other network properties such as the network efficiency and clustering coefficient) exhibited large fluctuations over time; however, it also exhibited specific periodic temporal structure over different time scales (1...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Han Yuan, Jerzy Bodurka, Lei Ding, Han Yuan, Jerzy Bodurka, Lei Ding, Han Yuan, Lei Ding, Jerzy Bodurka
Functional magnetic resonance imaging (fMRI) studies utilizing measures of hemodynamic signal, such as the blood-oxygenation-level dependent (BOLD) signal, have discovered that resting-state brain activities are organized into multiple large-scale functional networks, coined as resting state networks (RSNs). However, an important limitation of the available fMRI studies is that hemodynamic signals only provide an indirect measure of neuronal activity and that the neurobiological basis of the fMRI RSNs is not clear...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Angela R Laird, Michael C Riedel, Mershack Okoe, Radu Jianu, Kimberly L Ray, Simon B Eickhoff, Stephen M Smith, Peter T Fox, Matthew T Sutherland
Computational cognitive neuroimaging approaches can be leveraged to characterize the hierarchical organization of distributed, functionally specialized networks in the human brain. To this end, we performed large-scale mining across the BrainMap database of coordinate-based activation locations from over 10,000 task-based experiments. Meta-analytic coactivation networks were identified by jointly applying independent component analysis (ICA) and meta-analytic connectivity modeling (MACM) across a wide range of model orders (i...
February 18, 2017: NeuroImage
Soo-Eun Chang, Michael Angstadt, Ho Ming Chow, Andrew C Etchell, Emily O Garnett, Ai Leen Choo, Daniel Kessler, Robert C Welsh, Chandra Sripada
PURPOSE: We combined a large longitudinal neuroimaging dataset that includes children who do and do not stutter and a whole-brain network analysis in order to examine the intra- and inter-network connectivity changes associated with stuttering. Additionally, we asked whether whole brain connectivity patterns observed at the initial year of scanning could predict persistent stuttering in later years. METHODS: A total of 224 high-quality resting state fMRI scans collected from 84 children (42 stuttering, 42 controls) were entered into an independent component analysis (ICA), yielding a number of distinct network connectivity maps ("components") as well as expression scores for each component that quantified the degree to which it is expressed for each child...
January 25, 2017: Journal of Fluency Disorders
Tomoyasu Horikawa, Yukiyasu Kamitani
Dreaming is generally thought to be generated by spontaneous brain activity during sleep with patterns common to waking experience. This view is supported by a recent study demonstrating that dreamed objects can be predicted from brain activity during sleep using statistical decoders trained with stimulus-induced brain activity. However, it remains unclear whether and how visual image features associated with dreamed objects are represented in the brain. In this study, we used a deep neural network (DNN) model for object recognition as a proxy for hierarchical visual feature representation, and DNN features for dreamed objects were analyzed with brain decoding of fMRI data collected during dreaming...
2017: Frontiers in Computational Neuroscience
Ishan C Walpola, Timothy Nest, Leor Roseman, David Erritzoe, Amanda Feilding, David J Nutt, Robin L Carhart-Harris
Recent work with noninvasive human brain imaging has started to investigate the effects of 3, 4-methylenedioxymethamphetamine (MDMA) on large-scale patterns of brain activity. MDMA, a potent monoamine-releaser with particularly pronounced serotonin- releasing properties, has unique subjective effects that include: marked positive mood, pleasant/unusual bodily sensations and pro-social, empathic feelings. However, the neurobiological basis for these effects is not properly understood, and the present analysis sought to address this knowledge gap...
February 14, 2017: Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology
Daniel von Rhein, Christian F Beckmann, Barbara Franke, Jaap Oosterlaan, Dirk J Heslenfeld, Pieter J Hoekstra, Catharina A Hartman, Marjolein Luman, Stephen V Faraone, Roshan Cools, Jan K Buitelaar, Maarten Mennes
INTRODUCTION: Reward processing is a key aspect of cognitive control processes, putatively instantiated by mesolimbic and mesocortical brain circuits. Deficient signaling within these circuits has been associated with psychopathology. We applied a network discovery approach to assess specific functional networks associated with reward processing in participants with attention-deficit/hyperactivity disorder (ADHD). METHODS: To describe task-related processes in terms of integrated functional networks, we applied independent component analysis (ICA) to task response maps of 60 healthy participants who performed a monetary incentive delay (MID) task...
February 8, 2017: Human Brain Mapping
Micaela Y Chan, Fahd H Alhazmi, Denise C Park, Neil K Savalia, Gagan S Wig
: Brain network connectivity differs across individuals. For example, older adults exhibit less segregated resting-state sub-networks relative to younger adults (e.g., Chan et al., 2014). It has been hypothesized that individual differences in network connectivity impact the recruitment of brain areas during task execution. While recent studies have described the spatial overlap between resting-state functional correlation (RSFC) sub-networks and task-evoked activity, it is unclear whether individual variations in the connectivity pattern of a brain area (topology) relates to its activity during task execution...
February 7, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
David S Grayson, Damien A Fair
The development of human cognition results from the emergence of coordinated brain activity betweeen distant brain areas. Network science, combined with non-invasive functional imaging, has generated unprecedented insights regarding the adult brain's functional organization, and promises to help elucidate the development of functional architectures supporting complex behavior. Here we review what is known about functional network development from birth until adulthood, particularly as understood through the use of resting-state functional connectivity MRI (rs-fcMRI)...
February 1, 2017: NeuroImage
Marek Havlík
Consciousness still stands as one of the most interesting and the most elusive problems of neuroscience. Finding its correlates is the first step toward its satisfactory explanation. Several theories have proposed its correlates but none of them seem to be generally accepted even though most of them share some very similar elements. These elements are the activity of the thalamus, which is considered by some as the central region for consciousness, and gamma synchronization, which should be the general principal for the emergence of conscious experience...
February 1, 2017: Consciousness and Cognition
Lubin Wang, Hui Shen, Yu Lei, Ling-Li Zeng, Fenglin Cao, Linyan Su, Zheng Yang, Shuqiao Yao, Dewen Hu
Internet addiction (IA) is a condition characterized by loss of control over Internet use, leading to a variety of negative psychosocial consequences. Recent neuroimaging studies have begun to identify IA-related changes in specific brain regions and connections. However, whether and how the interactions within and between the large-scale brain networks are disrupted in individuals with IA remain largely unexplored. Using group independent component analysis, we extracted five intrinsic connectivity networks (ICNs) from the resting-state fMRI data of 26 adolescents with IA and 43 controls, including the anterior and posterior default mode network (DMN), left and right fronto-parietal network (FPN), and salience network (SN)...
January 15, 2017: Addictive Behaviors
Tong Wu, Joanes Grandjean, Simone C Bosshard, Markus Rudin, David Reutens, Tianzi Jiang
Studies in mice using resting-state functional magnetic resonance imaging (rs-fMRI) have provided opportunities to investigate the effects of pharmacological manipulations on brain function and map the phenotypes of mouse models of human brain disorders. Mouse rs-fMRI is typically performed under anaesthesia, which induces both regional suppression of brain activity and disruption of large-scale neural networks. Previous comparative studies using rodents investigating various drug effects on long-distance functional connectivity (FC) have reported agent-specific FC patterns, however, effects of regional suppression are sparsely explored...
February 1, 2017: NeuroImage
Carl D Hacker, Abraham Z Snyder, Mrinal Pahwa, Maurizio Corbetta, Eric C Leuthardt
Resting state functional MRI (R-fMRI) studies have shown that slow (<0.1Hz), intrinsic fluctuations of the blood oxygen level dependent (BOLD) signal are temporally correlated within hierarchically organized functional systems known as resting state networks (RSNs) (Doucet et al., 2011). Most broadly, this hierarchy exhibits a dichotomy between two opposed systems (Fox et al., 2005). One system engages with the environment and includes the visual, auditory, and sensorimotor (SMN) networks as well as the dorsal attention network (DAN), which controls spatial attention...
January 31, 2017: NeuroImage
Janosch P Heller, Piotr Michaluk, Kohtaroh Sugao, Dmitri A Rusakov
Astroglia are essential for brain development, homeostasis, and metabolic support. They also contribute actively to the formation and regulation of synaptic circuits, by successfully handling, integrating, and propagating physiological signals of neural networks. The latter occurs mainly by engaging a versatile mechanism of internal Ca(2+) fluctuations and regenerative waves prompting targeted release of signaling molecules into the extracellular space. Astroglia also show substantial structural plasticity associated with age- and use-dependent changes in neural circuitry...
February 2, 2017: Journal of Neuroscience Research
Daniela Zöller, Marie Schaer, Elisa Scariati, Maria Carmela Padula, Stephan Eliez, Dimitri Van De Ville
Although often ignored in fMRI studies, moment-to-moment variability of blood oxygenation level dependent (BOLD) signals reveals important information about brain function. Indeed, higher brain signal variability has been associated with better cognitive performance in young adults compared to children and elderly adults. Functional connectivity, a very common approach in resting-state fMRI analysis, is scaled for variance. Thus, alterations might be confounded or driven by BOLD signal variance alterations...
January 29, 2017: NeuroImage
Jorge F Mejias, John D Murray, Henry Kennedy, Xiao-Jing Wang
Interactions between top-down and bottom-up processes in the cerebral cortex hold the key to understanding attentional processes, predictive coding, executive control, and a gamut of other brain functions. However, the underlying circuit mechanism remains poorly understood and represents a major challenge in neuroscience. We approached this problem using a large-scale computational model of the primate cortex constrained by new directed and weighted connectivity data. In our model, the interplay between feedforward and feedback signaling depends on the cortical laminar structure and involves complex dynamics across multiple (intralaminar, interlaminar, interareal, and whole cortex) scales...
November 2016: Science Advances
David Bernal-Casas, Hyun Joo Lee, Andrew J Weitz, Jin Hyung Lee
Defining the large-scale behavior of brain circuits with cell type specificity is a major goal of neuroscience. However, neuronal circuit diagrams typically draw upon anatomical and electrophysiological measurements acquired in isolation. Consequently, a dynamic and cell-type-specific connectivity map has never been constructed from simultaneous measurements across the brain. Here, we introduce dynamic causal modeling (DCM) for optogenetic fMRI experiments-which uniquely allow cell-type-specific, brain-wide functional measurements-to parameterize the causal relationships among regions of a distributed brain network with cell type specificity...
February 8, 2017: Neuron
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