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dynamic brain connectivity

U Olcese
The scientific study of the neural correlates of consciousness (NCC) has long relied on comparing conditions in which consciousness is normally present with others in which it is impaired. Brain lesions offer a unique opportunity to understand which anatomical networks are needed to sustain consciousness, but provide limited insights on the patterns of neural activity that can support conscious processing. Non-REM sleep, on the other hand, has long epitomized the typical case of a non-conscious yet fully active brain...
September 1, 2018: Archives Italiennes de Biologie
Hongming Li, Yong Fan
Dynamic functional connectivity analysis provides valuable information for understanding brain functional activity underlying different cognitive processes. Besides sliding window based approaches, a variety of methods have been developed to automatically split the entire functional MRI scan into segments by detecting change points of functional signals to facilitate better characterization of temporally dynamic functional connectivity patterns. However, these methods are based on certain assumptions for the functional signals, such as Gaussian distribution, which are not necessarily suitable for the fMRI data...
September 2018: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
Jonni Hirvonen, Simo Monto, Sheng H Wang, J Matias Palva, Satu Palva
Sensory-guided actions entail the processing of sensory information, generation of perceptual decisions, and the generation of appropriate actions. Neuronal activity underlying these processes is distributed into sensory, fronto-parietal, and motor brain areas, respectively. How the neuronal processing is coordinated across these brain areas to support functions from perception to action remains unknown. We investigated whether phase synchronization in large-scale networks coordinate these processes. We recorded human cortical activity with magnetoencephalography (MEG) during a task in which weak somatosensory stimuli remained unperceived or were perceived...
2018: Network neuroscience
Jian Zhang, Xiaonan Dong, Luyao Wang, Lun Zhao, Zizheng Weng, Tianyu Zhang, Junyu Sui, Ritsu Go, Qiang Huang, Jinglong Wu, Tianyi Yan
To investigate gender differences in functional connectivity during the unattended processing of facial expressions, we recorded visual mismatch negativity (vMMN) in 34 adults using a deviant-standard reverse oddball paradigm. Using wavelet analysis, we calculated the time-frequency (TF) power at each electrode associated with happy-deviant, sad-deviant, happy-standard and sad-standard conditions. We also calculated the phase lag index (PLI) between electrode pairs and analyzed the dynamic network topologies of the functional connectivity for happy and sad vMMNs in the delta (0...
2018: Frontiers in Behavioral Neuroscience
Fatemeh Mokhtari, Paul J Laurienti, W Jack Rejeski, Grey Ballard
As brain network organization likely fluctuates over time to react to internal and external stimuli, the validity of conventional static brain connectivity models are being questioned. Thus, there is a growing interest in using so-called dynamic network analyses. Brain network analyses yield complex network data that is difficult to analyze and interpret. To deal with the complex structures, data reduction techniques that simplify the data are often used. For dynamic network analyses, data simplification is even of greater importance, as dynamic connectivity analyses result in a time series of complex networks...
October 15, 2018: Brain Connectivity
R Peyron, C Fauchon
Brain functional imaging has been applied to the study of pain since 1991. Then, a plethora of studies around the world looking at pain sensations and their brain correlates was published. Four kinds of studies can be distinguished: i) A first set investigated brain responses to noxious heat stimulations (above the pain threshold) relative to an equivalent warm innocuous stimulation (below the pain threshold). The aim of these studies was to identify the pattern of brain regions involved in the nociceptive processes and they may be considered as descriptive studies rather than explanative studies...
October 11, 2018: Revue Neurologique
Bo Chen
OBJECTIVES: Schizophrenia is a predominant product of pathological alterations distributed throughout interconnected neural systems. Designing new objectively diagnostic methods are burning questions. Dynamical functional connectivity (DFCs) methodology based on fMRI data is an effective lever to investigate changeability evolution in macroscopic neural activity patterns underlying critical aspects of cognition and behavior. However, region properties of brain architecture have been less investigated by special indexes of dynamical graph in general mental disorders...
October 11, 2018: Journal of Neuroscience Methods
Andrew P Salzwedel, Rebecca L Stephens, Barbara D Goldman, Weili Lin, John H Gilmore, Wei Gao
BACKGROUND: The amygdala represents a core node in the human brain's emotional signal processing circuitry. Given its critical role, both the typical and atypical functional connectivity patterns of the amygdala have been extensively studied in adults. However, the development of amygdala functional connectivity during infancy is less well studied; thus, our understanding of the normal growth trajectory of key emotion-related brain circuits during a critical period is limited. METHODS: In this study, we used resting-state functional magnetic resonance imaging (N = 233 subjects with 334 datasets) to delineate the spatiotemporal dynamics of amygdala functional connectivity development during the first 2 years of life...
August 30, 2018: Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
Patrick J Drew, Aaron T Winder, Qingguang Zhang
Animals and humans continuously engage in small, spontaneous motor actions, such as blinking, whisking, and postural adjustments ("fidgeting"). These movements are accompanied by changes in neural activity in sensory and motor regions of the brain. The frequency of these motions varies in time, is affected by sensory stimuli, arousal levels, and pathology. These fidgeting behaviors can be entrained by sensory stimuli. Fidgeting behaviors will cause distributed, bilateral functional activation in the 0...
October 12, 2018: Neuroscientist: a Review Journal Bringing Neurobiology, Neurology and Psychiatry
Philippa J Karoly, Levin Kuhlmann, Daniel Soudry, David B Grayden, Mark J Cook, Dean R Freestone
We present the results of a model inversion algorithm for electrocorticography (ECoG) data recorded during epileptic seizures. The states and parameters of neural mass models were tracked during a total of over 3000 seizures from twelve patients with focal epilepsy. These models provide an estimate of the effective connectivity within intracortical circuits over the time course of seizures. Observing the dynamics of effective connectivity provides insight into mechanisms of seizures. Estimation of patients seizure dynamics revealed: 1) a highly stereotyped pattern of evolution for each patient, 2) distinct sub-groups of onset mechanisms amongst patients, and 3) different offset mechanisms for long and short seizures...
October 11, 2018: PLoS Computational Biology
Jiayue Cai, Aiping Liu, Taomian Mi, Saurabh Garg, Wade Trappe, Martin J McKeown, Z Jane Wang
Graph theoretical analysis is a powerful tool for quantitatively understanding the topological properties of complex networks, such as system-level descriptions of brain connectivity. In conventional functional connectivity analysis, brain connectivity is assumed to be temporally stationary, while increasing evidence suggests that functional connectivity exhibits temporal variations during dynamic brain activity. Although a number of methods have been developed to estimate time-dependent brain connectivity, there is a paucity of studies examining the utility of brain dynamics for assessing brain disease states...
October 11, 2018: IEEE Journal of Biomedical and Health Informatics
Arseny A Sokolov, Peter Zeidman, Michael Erb, Philippe Ryvlin, Marina A Pavlova, Karl J Friston
Despite the potential for better understanding functional neuroanatomy, the complex relationship between neuroimaging measures of brain structure and function has confounded integrative, multimodal analyses of brain connectivity. This is particularly true for task-related effective connectivity, which describes the causal influences between neuronal populations. Here, we assess whether measures of structural connectivity may usefully inform estimates of effective connectivity in larger scale brain networks...
October 9, 2018: Brain Structure & Function
Barnaly Rashid, Jiayu Chen, Ishtiaque Rashid, Eswar Damaraju, Jingyu Liu, Robyn Miller, Oktay Agcaoglu, Theo G M van Erp, Kelvin O Lim, Jessica A Turner, Daniel H Mathalon, Judith M Ford, James Voyvodic, Bryon A Mueller, Aysenil Belger, Sarah McEwen, Steven G Potkin, Adrian Preda, Juan R Bustillo, Godfrey D Pearlson, Vince D Calhoun
Multimodal, imaging-genomics techniques offer a platform for understanding genetic influences on brain abnormalities in psychiatric disorders. Such approaches utilize the information available from both imaging and genomics data and identify their association. Particularly for complex disorders such as schizophrenia, the relationship between imaging and genomic features may be better understood by incorporating additional information provided by advanced multimodal modeling. In this study, we propose a novel framework to combine features corresponding to functional magnetic resonance imaging (functional) and single nucleotide polymorphism (SNP) data from 61 schizophrenia (SZ) patients and 87 healthy controls (HC)...
October 6, 2018: NeuroImage
B Q Rosen, G Krishnan, P Sanda, M Komarov, T Sejnowski, N Rulkov, I Ulbert, L Eross, J Madsen, O Devinsky, W Doyle, D Fabo, S Cash, M Bazhenov, E Halgren
BACKGROUND: Although they form a unitary phenomenon, the relationship between extracranial M/EEG and transmembrane ion flows is understood only as a general principle rather than as a well-articulated and quantified causal chain. METHOD: We present an integrated multiscale model, consisting of a neural simulation of thalamus and cortex during stage N2 sleep and a biophysical model projecting cortical current densities to M/EEG fields. Sleep spindles were generated through the interactions of local and distant network connections and intrinsic currents within thalamocortical circuits...
October 6, 2018: Journal of Neuroscience Methods
Adam Gorlewicz, Leszek Kaczmarek
Chemical synapses are specialized interfaces between neurons in the brain that transmit and modulate information, thereby integrating cells into multiplicity of interacting neural circuits. Cell adhesion molecules (CAMs) might form trans-synaptic complexes that are crucial for the appropriate identification of synaptic partners and further for the establishment, properties, and dynamics of synapses. When affected, trans-synaptic adhesion mechanisms play a role in synaptopathies in a variety of neuropsychiatric disorders including epilepsy...
2018: Frontiers in Cell and Developmental Biology
Han Wang, Kun Xie, Zhichao Lian, Yan Cui, Yaowu Chen, Jing Zhang, Li Xie, Joe Tsien, Tianming Liu
Brain dynamics has recently received increasing interest due to its significant importance in basic and clinical neurosciences. However, due to inherent difficulties in both data acquisition and data analysis methods, studies on large-scale brain dynamics of mouse with local field potential (LFP) recording are very rare. In this paper, we did a series of works on modeling large-scale mouse brain dynamic activities responding to fearful earthquake. Based on LFP recording data from thirteen brain regions which are closely related to fear learning and memory and the effective Bayesian connectivity change point model (BCCPM), we divided the response time series into four stages: "Before", "Earthquake", "Recovery", and "After"...
October 5, 2018: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Katarzyna Stachowicz
Synaptic plasticity simply put, is the activity‑dependent modification of the strength or efficacy of synaptic transmission in the network of synapses in the brain. The role of synaptic plasticity in disease is an active area of research. Changes in plasticity translate to the release of neurotransmitters at the synapse and subsequently, the way humans see the world. It is known that neuropsychiatric disorders such as depression, posttraumatic stress disorder (PTSD), and Alzheimer's disease (AD) are related to pathological changes in dynamic processes in synapses, dialogue between neurons, and finally, changes in overall plasticity...
2018: Acta Neurobiologiae Experimentalis
N Toschi, R Riccelli, I Indovina, A Terracciano, L Passamonti
A key objective of the emerging field of personality neuroscience is to link the great variety of the enduring dispositions of human behaviour with reliable markers of brain function. This can be achieved by analyzing large sets of data with methods that model whole-brain connectivity patterns. To meet these expectations, we exploited a large repository of personality and neuroimaging measures made publicly available via the Human Connectome Project. Using connectomic analyses based on graph theory, we computed global and local indices of functional connectivity (e...
2018: Personality neuroscience
Elisa Ryyppö, Enrico Glerean, Elvira Brattico, Jari Saramäki, Onerva Korhonen
The properties of functional brain networks strongly depend on how their nodes are chosen. Commonly, nodes are defined by Regions of Interest (ROIs), predetermined groupings of fMRI measurement voxels. Earlier, we demonstrated that the functional homogeneity of ROIs, captured by their spatial consistency , varies widely across ROIs in commonly used brain atlases. Here, we ask how ROIs behave as nodes of dynamic brain networks. To this end, we use two measures: spatiotemporal consistency measures changes in spatial consistency across time and network turnover quantifies the changes in the local network structure around an ROI...
2018: Network neuroscience
R Devon Hjelm, Eswar Damaraju, Kyunghyun Cho, Helmut Laufs, Sergey M Plis, Vince D Calhoun
We introduce a novel recurrent neural network (RNN) approach to account for temporal dynamics and dependencies in brain networks observed via functional magnetic resonance imaging (fMRI). Our approach directly parameterizes temporal dynamics through recurrent connections, which can be used to formulate blind source separation with a conditional (rather than marginal) independence assumption, which we call RNN-ICA. This formulation enables us to visualize the temporal dynamics of both first order (activity) and second order (directed connectivity) information in brain networks that are widely studied in a static sense, but not well-characterized dynamically...
2018: Frontiers in Neuroscience
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