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Object Familiarity Modulates Effective Connectivity During Haptic Shape Perception

Deshpande, Gopikrishna; Hu, Xiaoping; Lacey, Simon; Stilla, Randall; Sathian, K.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
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In the preceding paper (Lacey et al., 2009), we showed that the activations evoked by visual imagery overlapped more extensively, and their magnitudes were more correlated, with those evoked during haptic shape perception of familiar, compared to unfamiliar, objects. Here we used task-specific analyses of functional and effective connectivity to provide convergent evidence. These analyses showed that the visual imagery and familiar haptic shape tasks activated similar networks, whereas the unfamiliar haptic shape task activated a different network. Multivariate Granger causality analyses of effective connectivity, in both a conventional form and one purged of zero-lag correlations, showed that the visual imagery and familiar haptic shape networks involved top-down paths from prefrontal cortex into the lateral occipital complex (LOC), whereas the unfamiliar haptic shape network was characterized by bottom-up, somatosensory inputs into the LOC. We conclude that shape representations in the LOC are flexibly accessible, either top-down or bottom-up, according to task demands, and that visual imagery is more involved in LOC activation during haptic shape perception when objects are familiar, compared to unfamiliar.

Dissociating hippocampal and basal ganglia contributions to category learning using stimulus novelty and subjective judgments

Seger, Carol A.; Dennison, Christina S.; Lopez-Paniagua, Dan; Peterson, Erik J.; Roark, Aubrey A.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
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26.13%
We identified factors leading to hippocampal and basal ganglia recruitment during categorization learning. Subjects alternated between blocks of a standard trial and error category learning task and a subjective judgment task. In the subjective judgments task subjects categorized the stimulus and then instead of receiving feedback they indicated the basis of their response using 4 options: Remember: Conscious episodic memory of previous trials. Know-Automatic: Automatic, rapid response accompanied by conscious awareness of category membership. Know-Intuition: A “gut feeling” without fully conscious knowledge of category membership. Guess: Guessing. In addition, new stimuli were introduced throughout the experiment to examine effects of novelty. Categorization overall recruited both the basal ganglia and posterior hippocampus. However, basal ganglia activity was found during Know judgments (both Automatic and Intuition), whereas posterior hippocampus activity was found during Remember judgments. Granger causality mapping indicated interactions between the basal ganglia and hippocampus, with the putamen exerting directed influence on the posterior hippocampus, which in turn exerted directed influence on the posterior caudate nucleus. We also found a region of anterior hippocampus that showed decreased activity relative to baseline during categorization overall...

Robustness and fault tolerance make brains harder to study

Srinivasan, Shyam; Stevens, Charles F
Fonte: BioMed Central Publicador: BioMed Central
Tipo: Artigo de Revista Científica
Publicado em 29/06/2011 Português
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Brains increase the survival value of organisms by being robust and fault tolerant. That is, brain circuits continue to operate as the organism needs, even when the circuit properties are significantly perturbed. Kispersky and colleagues, in a recent paper in Neural Systems & Circuits, have found that Granger Causality analysis, an important method used to infer circuit connections from the behavior of neurons within the circuit, is defeated by the mechanisms that give rise to this robustness and fault tolerance.

Driving and Driven Architectures of Directed Small-World Human Brain Functional Networks

Yan, Chaogan; He, Yong
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 12/08/2011 Português
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Recently, increasing attention has been focused on the investigation of the human brain connectome that describes the patterns of structural and functional connectivity networks of the human brain. Many studies of the human connectome have demonstrated that the brain network follows a small-world topology with an intrinsically cohesive modular structure and includes several network hubs in the medial parietal regions. However, most of these studies have only focused on undirected connections between regions in which the directions of information flow are not taken into account. How the brain regions causally influence each other and how the directed network of human brain is topologically organized remain largely unknown. Here, we applied linear multivariate Granger causality analysis (GCA) and graph theoretical approaches to a resting-state functional MRI dataset with a large cohort of young healthy participants (n = 86) to explore connectivity patterns of the population-based whole-brain functional directed network. This directed brain network exhibited prominent small-world properties, which obviously improved previous results of functional MRI studies showing weak small-world properties in the directed brain networks in terms of a kernel-based GCA and individual analysis. This brain network also showed significant modular structures associated with 5 well known subsystems: fronto-parietal...

Multimodal Functional Network Connectivity: An EEG-fMRI Fusion in Network Space

Lei, Xu; Ostwald, Dirk; Hu, Jiehui; Qiu, Chuan; Porcaro, Camillo; Bagshaw, Andrew P.; Yao, Dezhong
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 22/09/2011 Português
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EEG and fMRI recordings measure the functional activity of multiple coherent networks distributed in the cerebral cortex. Identifying network interaction from the complementary neuroelectric and hemodynamic signals may help to explain the complex relationships between different brain regions. In this paper, multimodal functional network connectivity (mFNC) is proposed for the fusion of EEG and fMRI in network space. First, functional networks (FNs) are extracted using spatial independent component analysis (ICA) in each modality separately. Then the interactions among FNs in each modality are explored by Granger causality analysis (GCA). Finally, fMRI FNs are matched to EEG FNs in the spatial domain using network-based source imaging (NESOI). Investigations of both synthetic and real data demonstrate that mFNC has the potential to reveal the underlying neural networks of each modality separately and in their combination. With mFNC, comprehensive relationships among FNs might be unveiled for the deep exploration of neural activities and metabolic responses in a specific task or neurological state.

Fronto-parietal regulation of media violence exposure in adolescents: a multi-method study

Strenziok, Maren; Krueger, Frank; Deshpande, Gopikrishna; Lenroot, Rhoshel K.; van der Meer, Elke; Grafman, Jordan
Fonte: Oxford University Press Publicador: Oxford University Press
Tipo: Artigo de Revista Científica
Português
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Adolescents spend a significant part of their leisure time watching TV programs and movies that portray violence. It is unknown, however, how the extent of violent media use and the severity of aggression displayed affect adolescents’ brain function. We investigated skin conductance responses, brain activation and functional brain connectivity to media violence in healthy adolescents. In an event-related functional magnetic resonance imaging experiment, subjects repeatedly viewed normed videos that displayed different degrees of aggressive behavior. We found a downward linear adaptation in skin conductance responses with increasing aggression and desensitization towards more aggressive videos. Our results further revealed adaptation in a fronto-parietal network including the left lateral orbitofrontal cortex (lOFC), right precuneus and bilateral inferior parietal lobules, again showing downward linear adaptations and desensitization towards more aggressive videos. Granger causality mapping analyses revealed attenuation in the left lOFC, indicating that activation during viewing aggressive media is driven by input from parietal regions that decreased over time, for more aggressive videos. We conclude that aggressive media activates an emotion–attention network that has the capability to blunt emotional responses through reduced attention with repeated viewing of aggressive media contents...

Identifying brain effective connectivity patterns from EEG: performance of Granger Causality, DTF, PDC and PSI on simulated data

Haufe, Stefan; Nikulin, Vadim; Nolte, Guido
Fonte: BioMed Central Publicador: BioMed Central
Tipo: Artigo de Revista Científica
Publicado em 18/07/2011 Português
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26.13%

Use of Granger causality analysis and artificial spike trains to examine pause coding in Purkinje cell spike activity related to rhythmic licking

Maran, Selva K; Cao, Ying; Dhamala, Mukesh; Heck, Detlef; Jaeger, Dieter
Fonte: BioMed Central Publicador: BioMed Central
Tipo: Artigo de Revista Científica
Publicado em 18/07/2011 Português
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26.13%

Interlaminar Granger causality and alpha oscillations in a model of macaque cortex

Kerr, Cliff C; Mo, Jue; Neymotin, Samuel; Ding, Mingzhou; Lytton, William W
Fonte: BioMed Central Publicador: BioMed Central
Tipo: Artigo de Revista Científica
Publicado em 18/07/2011 Português
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26.13%

How to infer gene networks from expression profiles, revisited

Penfold, Christopher A.; Wild, David L.
Fonte: The Royal Society Publicador: The Royal Society
Tipo: Artigo de Revista Científica
Português
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26.13%
Inferring the topology of a gene-regulatory network (GRN) from genome-scale time-series measurements of transcriptional change has proved useful for disentangling complex biological processes. To address the challenges associated with this inference, a number of competing approaches have previously been used, including examples from information theory, Bayesian and dynamic Bayesian networks (DBNs), and ordinary differential equation (ODE) or stochastic differential equation. The performance of these competing approaches have previously been assessed using a variety of in silico and in vivo datasets. Here, we revisit this work by assessing the performance of more recent network inference algorithms, including a novel non-parametric learning approach based upon nonlinear dynamical systems. For larger GRNs, containing hundreds of genes, these non-parametric approaches more accurately infer network structures than do traditional approaches, but at significant computational cost. For smaller systems, DBNs are competitive with the non-parametric approaches with respect to computational time and accuracy, and both of these approaches appear to be more accurate than Granger causality-based methods and those using simple ODEs models.

Interaction of catechol O-methyltransferase and serotonin transporter genes modulates effective connectivity in a facial emotion-processing circuitry

Surguladze, S A; Radua, J; El-Hage, W; Gohier, B; Sato, J R; Kronhaus, D M; Proitsi, P; Powell, J; Phillips, M L
Fonte: Nature Publishing Group Publicador: Nature Publishing Group
Tipo: Artigo de Revista Científica
Português
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Imaging genetic studies showed exaggerated blood oxygenation level-dependent response in limbic structures in carriers of low activity alleles of serotonin transporter-linked promoter region (5-HTTLPR) as well as catechol O-methyltransferase (COMT) genes. This was suggested to underlie the vulnerability to mood disorders. To better understand the mechanisms of vulnerability, it is important to investigate the genetic modulation of frontal-limbic connectivity that underlies emotional regulation and control. In this study, we have examined the interaction of 5-HTTLPR and COMT genetic markers on effective connectivity within neural circuitry for emotional facial expressions. A total of 91 healthy Caucasian adults underwent functional magnetic resonance imaging experiments with a task presenting dynamic emotional facial expressions of fear, sadness, happiness and anger. The effective connectivity within the facial processing circuitry was assessed with Granger causality method. We have demonstrated that in fear processing condition, an interaction between 5-HTTLPR (S) and COMT (met) low activity alleles was associated with reduced reciprocal connectivity within the circuitry including bilateral fusiform/inferior occipital regions, right superior temporal gyrus/superior temporal sulcus...

EEG-Based Automatic Classification of ‘Awake’ versus ‘Anesthetized’ State in General Anesthesia Using Granger Causality

Nicolaou, Nicoletta; Hourris, Saverios; Alexandrou, Pandelitsa; Georgiou, Julius
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 22/03/2012 Português
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Functional connectivity in a rhythmic inhibitory circuit using Granger causality

Kispersky, Tilman; Gutierrez, Gabrielle J; Marder, Eve
Fonte: BioMed Central Publicador: BioMed Central
Tipo: Artigo de Revista Científica
Publicado em 25/05/2011 Português
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26.13%

Laterality of Temporoparietal Causal Connectivity during the Prestimulus Period Correlates with Phonological Decoding Task Performance in Dyslexic and Typical Readers

Frye, Richard E.; Liederman, Jacqueline; McGraw Fisher, Janet; Wu, Meng-Hung
Fonte: Oxford University Press Publicador: Oxford University Press
Tipo: Artigo de Revista Científica
Português
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26.13%
We examined how effective connectivity into and out of the left and right temporoparietal areas (TPAs) to/from other key cortical areas affected phonological decoding in 7 dyslexic readers (DRs) and 10 typical readers (TRs) who were young adults. Granger causality was used to compute the effective connectivity of the preparatory network 500 ms prior to presentation of nonwords that required phonological decoding. Neuromagnetic activity was analyzed within the low, medium, and high beta and gamma subbands. A mixed-model analysis determined whether connectivity to or from the left and right TPAs differed across connectivity direction (in vs. out), brain areas (right and left inferior frontal and ventral occipital–temporal and the contralateral TPA), reading group (DR vs. TR), and/or task performance. Within the low beta subband, better performance was associated with increased influence of the left TPA on other brain areas across both reading groups and poorer performance was associated with increased influence of the right TPA on other brain areas for DRs only. DRs were also found to have an increase in high gamma connectivity between the left TPA and other brain areas. This study suggests that hierarchal network structure rather than connectivity per se is important in determining phonological decoding performance.

Model-Free Reconstruction of Excitatory Neuronal Connectivity from Calcium Imaging Signals

Stetter, Olav; Battaglia, Demian; Soriano, Jordi; Geisel, Theo
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Português
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26.13%
A systematic assessment of global neural network connectivity through direct electrophysiological assays has remained technically infeasible, even in simpler systems like dissociated neuronal cultures. We introduce an improved algorithmic approach based on Transfer Entropy to reconstruct structural connectivity from network activity monitored through calcium imaging. We focus in this study on the inference of excitatory synaptic links. Based on information theory, our method requires no prior assumptions on the statistics of neuronal firing and neuronal connections. The performance of our algorithm is benchmarked on surrogate time series of calcium fluorescence generated by the simulated dynamics of a network with known ground-truth topology. We find that the functional network topology revealed by Transfer Entropy depends qualitatively on the time-dependent dynamic state of the network (bursting or non-bursting). Thus by conditioning with respect to the global mean activity, we improve the performance of our method. This allows us to focus the analysis to specific dynamical regimes of the network in which the inferred functional connectivity is shaped by monosynaptic excitatory connections, rather than by collective synchrony. Our method can discriminate between actual causal influences between neurons and spurious non-causal correlations due to light scattering artifacts...

Information Flow in Networks and the Law of Diminishing Marginal Returns: Evidence from Modeling and Human Electroencephalographic Recordings

Marinazzo, Daniele; Wu, Guorong; Pellicoro, Mario; Angelini, Leonardo; Stramaglia, Sebastiano
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 18/09/2012 Português
Relevância na Pesquisa
26.13%
We analyze simple dynamical network models which describe the limited capacity of nodes to process the input information. For a proper range of their parameters, the information flow pattern in these models is characterized by exponential distribution of the incoming information and a fat-tailed distribution of the outgoing information, as a signature of the law of diminishing marginal returns. We apply this analysis to effective connectivity networks from human EEG signals, obtained by Granger Causality, which has recently been given an interpretation in the framework of information theory. From the distributions of the incoming versus the outgoing values of the information flow it is evident that the incoming information is exponentially distributed whilst the outgoing information shows a fat tail. This suggests that overall brain effective connectivity networks may also be considered in the light of the law of diminishing marginal returns. Interestingly, this pattern is reproduced locally but with a clear modulation: a topographic analysis has also been made considering the distribution of incoming and outgoing values at each electrode, suggesting a functional role for this phenomenon.

Neuronal Mechanisms and Attentional Modulation of Corticothalamic Alpha Oscillations

Bollimunta, Anil; Mo, Jue; Schroeder, Charles E.; Ding, Mingzhou
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em 30/03/2011 Português
Relevância na Pesquisa
26.13%
Field potential oscillations in the ~10 Hz range are known as the alpha rhythm. The genesis and function of alpha has been the subject of intense investigation for the past 80 years. Whereas early work focused on the thalamus as the pacemaker of alpha rhythm, subsequent slice studies revealed that pyramidal neurons in the deep layers of sensory cortices are capable of oscillating in the alpha frequency range independently. How thalamic and cortical generating mechanisms in the intact brain might interact to shape the organization and function of alpha oscillations remains unclear. We addressed this problem by analyzing laminar profiles of local field potential (LFP) and multi-unit activity (MUA) recorded with linear array multielectrodes from the striate cortex of two macaque monkeys performing an intermodal selective attention task. Current source density (CSD) analysis was combined with CSD-MUA coherence to identify intracortical alpha current generators and assess their potential for pacemaking. Coherence and Granger causality analysis was applied to delineate the patterns of interaction among different alpha current generators. We found that: (1) separable alpha current generators are located in superficial, granular and deep layers...

Identification of a Metabolic Reaction Network from Time-Series Data of Metabolite Concentrations

Sriyudthsak, Kansuporn; Shiraishi, Fumihide; Hirai, Masami Yokota
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 10/01/2013 Português
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26.13%
Recent development of high-throughput analytical techniques has made it possible to qualitatively identify a number of metabolites simultaneously. Correlation and multivariate analyses such as principal component analysis have been widely used to analyse those data and evaluate correlations among the metabolic profiles. However, these analyses cannot simultaneously carry out identification of metabolic reaction networks and prediction of dynamic behaviour of metabolites in the networks. The present study, therefore, proposes a new approach consisting of a combination of statistical technique and mathematical modelling approach to identify and predict a probable metabolic reaction network from time-series data of metabolite concentrations and simultaneously construct its mathematical model. Firstly, regression functions are fitted to experimental data by the locally estimated scatter plot smoothing method. Secondly, the fitted result is analysed by the bivariate Granger causality test to determine which metabolites cause the change in other metabolite concentrations and remove less related metabolites. Thirdly, S-system equations are formed by using the remaining metabolites within the framework of biochemical systems theory. Finally...

MEG-SIM: A Web Portal for Testing MEG Analysis Methods using Realistic Simulated and Empirical Data

Aine, C. J.; Sanfratello, L.; Ranken, D.; Best, E.; MacArthur, J. A.; Wallace, T.; Gilliam, K.; Donahue, C. H.; Montaño, R.; Bryant, J. E.; Scott, A.; Stephen, J. M.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em /04/2012 Português
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26.13%
MEG and EEG measure electrophysiological activity in the brain with exquisite temporal resolution. Because of this unique strength relative to noninvasive hemodynamic-based measures (fMRI, PET), the complementary nature of hemodynamic and electrophysiological techniques is becoming more widely recognized (e.g., Human Connectome Project). However, the available analysis methods for solving the inverse problem for MEG and EEG have not been compared and standardized to the extent that they have for fMRI/PET. A number of factors, including the non-uniqueness of the solution to the inverse problem for MEG/EEG, have led to multiple analysis techniques which have not been tested on consistent datasets, making direct comparisons of techniques challenging (or impossible). Since each of the methods is known to have their own set of strengths and weaknesses, it would be beneficial to quantify them. Toward this end, we are announcing the establishment of a website containing an extensive series of realistic simulated data for testing purposes (http://cobre.mrn.org/megsim/). Here, we present: 1) a brief overview of the basic types of inverse procedures; 2) the rationale and description of the testbed created; and 3) cases emphasizing functional connectivity (e.g....

Altered Effective Connectivity Network of the Basal Ganglia in Low-Grade Hepatic Encephalopathy: A Resting-State fMRI Study with Granger Causality Analysis

Qi, Rongfeng; Zhang, Long Jiang; Zhong, Jianhui; Zhang, Zhiqiang; Ni, Ling; Jiao, Qing; Liao, Wei; Zheng, Gang; Lu, Guangming
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 11/01/2013 Português
Relevância na Pesquisa
26.13%