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An Analysis Approach for High-Field fMRI Data from Awake Non-Human Primates

Stoewer, Steffen; Goense, Jozien; Keliris, Georgios A.; Bartels, Andreas; Logothetis, Nikos K.; Duncan, John; Sigala, Natasha
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 06/01/2012 Português
Relevância na Pesquisa
26.84%
fMRI experiments with awake non-human primates (NHP) have seen a surge of applications in recent years. However, the standard fMRI analysis tools designed for human experiments are not optimal for analysis of NHP fMRI data collected at high fields. There are several reasons for this, including the trial-based nature of NHP experiments, with inter-trial periods being of no interest, and segmentation artefacts and distortions that may result from field changes due to movement. We demonstrate an approach that allows us to address some of these issues consisting of the following steps: 1) Trial-based experimental design. 2) Careful control of subject movement. 3) Computer-assisted selection of trials devoid of artefacts and animal motion. 4) Nonrigid between-trial and rigid within-trial realignment of concatenated data from temporally separated trials and sessions. 5) Linear interpolation of inter-trial intervals and high-pass filtering of temporally continuous data 6) Removal of interpolated data and reconcatenation of datasets before statistical analysis with SPM. We have implemented a software toolbox, fMRI Sandbox (http://code.google.com/p/fmri-sandbox/), for semi-automated application of these processing steps that interfaces with SPM software. Here...

fMRI Repetition Suppression: Neuronal Adaptation or Stimulus Expectation?

Larsson, Jonas; Smith, Andrew T.
Fonte: Oxford University Press Publicador: Oxford University Press
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.84%
Measurements of repetition suppression with functional magnetic resonance imaging (fMRI adaptation) have been used widely to probe neuronal population response properties in human cerebral cortex. fMRI adaptation techniques assume that fMRI repetition suppression reflects neuronal adaptation, an assumption that has been challenged on the basis of evidence that repetition-related response changes may reflect unrelated factors, such as attention and stimulus expectation. Specifically, Summerfield et al. (Summerfield C, Trittschuh EH, Monti JM, Mesulam MM, Egner T. 2008. Neural repetition suppression reflects fulfilled perceptual expectations. Nat Neurosci. 11:1004–1006) reported that the relative frequency of stimulus repetitions and non-repetitions influenced the magnitude of repetition suppression in the fusiform face area, suggesting that stimulus expectation accounted for most of the effect of repetition. We confirm that stimulus expectation can significantly influence fMRI repetition suppression throughout visual cortex and show that it occurs with long as well as short adaptation durations. However, the effect was attention dependent: When attention was diverted away from the stimuli, the effects of stimulus expectation completely disappeared. Nonetheless...

Automated classification of fMRI during cognitive control identifies more severely disorganized subjects with schizophrenia

Yoon, Jong H.; Nguyen, Danh V.; McVay, Lindsey M.; Deramo, Paul; Minzenberg, Michael J.; Ragland, J. Daniel; Niendham, Tara; Solomon, Marjorie; Carter, Cameron S.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.84%
The establishment of a neurobiologically based nosological system is one of the ultimate goals of modern biological psychiatry research. Developments in neuroimaging and statistical/machine learning have provided useful basic tools for these efforts. Recent studies have demonstrated the utility of fMRI as input data for the classification of schizophrenia, but none, to date, has used fMRI of cognitive control for this purpose. In this study, we evaluated the accuracy of an unbiased classification method on fMRI data from a large cohort of subjects with first episode schizophrenia and a cohort of age matched healthy control subjects while they completed the AX version of the Continuous Performance Task (AX-CPT). We compared these results to classifications based on AX-CPT behavioral data. Classification accuracy for DSM-IV defined schizophrenia using fMRI data was modest and comparable to classifications conducted with behavioral data. Interestingly fMRI classifications did however identify a distinct subgroup of patients with greater behavioral disorganization, whereas behavioral data classifications did not. These results suggest that fMRI-based classification could be a useful tool in defining a neurobiologically distinct subgroup within the clinically defined syndrome of schizophrenia...

Visual inspection of independent components: Defining a procedure for artifact removal from fMRI data

Kelly, Robert E.; Alexopoulos, George S.; Wang, Zhishun; Gunning, Faith M.; Murphy, Christopher F.; Morimoto, Sarah Shizuko; Kanellopoulos, Dora; Jia, Zhiru; Lim, Kelvin O.; Hoptman, Matthew J.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.84%
Artifacts in fMRI data, primarily those related to motion and physiological sources, negatively impact the functional signal-to-noise ratio in fMRI studies, even after conventional fMRI preprocessing. Independent component analysis’ demonstrated capacity to separate sources of neural signal, structured noise, and random noise into separate components might be utilized in improved procedures to remove artifacts from fMRI data. Such procedures require a method for labeling independent components (ICs) as representing artifacts to be removed or neural signals of interest to be spared. Visual inspection is often considered an accurate method for such labeling as well as a standard to which automated labeling methods are compared. However, detailed descriptions of methods for visual inspection of ICs are lacking in the literature. Here we describe the details of, and the rationale for, an operationalized fMRI data denoising procedure that involves visual inspection of ICs (96% inter-rater agreement). We estimate that dozens of subjects/sessions can be processed within a few hours using the described method of visual inspection. Our hope is that continued scientific discussion of and testing of visual inspection methods will lead to the development of improved...

Variability of the Relationship between Electrophysiology and BOLD-fMRI across Cortical Regions in Humans

Conner, Christopher R.; Ellmore, Timothy M.; Pieters, Thomas A.; DiSano, Michael A.; Tandon, Nitin
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em 07/09/2011 Português
Relevância na Pesquisa
26.84%
The relationship between blood oxygenation level-dependent (BOLD) functional MRI (fMRI) signal and the underlying neural electrical activity in humans is a topic of intense interest to systems neuroscience. This relationship has generally been assumed to be invariant regardless of the brain region and the cognitive task being studied. We critically evaluated these assumptions by comparing the BOLD-fMRI response with local field potential (LFP) measurements during visually cued common noun and verb generation in 11 humans in whom 1210 subdural electrodes were implanted. As expected, power in the mid-gamma band (60 –120 Hz) correlated positively (r2 = 0.16, p < 10−16) and power in the beta band (13–30 Hz) correlated negatively (r2 = 0.09, p < 10−16) with the BOLD signal change. Beta and mid-gamma band activity independently explain different components of the observed BOLD signal. Importantly, we found that the location (i.e., lobe) of the recording site modulates the relationship between the electrocorticographic (ECoG) signal and the observed fMRI response (p < 10−16, F21,1830 = 52.7), while the type of language task does not. Across all brain regions, ECoG activity in the gamma and beta bands explains 22% of the fMRI response...

Scale-Free and Multifractal Time Dynamics of fMRI Signals during Rest and Task

Ciuciu, P.; Varoquaux, G.; Abry, P.; Sadaghiani, S.; Kleinschmidt, A.
Fonte: Frontiers Research Foundation Publicador: Frontiers Research Foundation
Tipo: Artigo de Revista Científica
Publicado em 15/06/2012 Português
Relevância na Pesquisa
26.84%
Scaling temporal dynamics in functional MRI (fMRI) signals have been evidenced for a decade as intrinsic characteristics of ongoing brain activity (Zarahn et al., 1997). Recently, scaling properties were shown to fluctuate across brain networks and to be modulated between rest and task (He, 2011): notably, Hurst exponent, quantifying long memory, decreases under task in activating and deactivating brain regions. In most cases, such results were obtained: First, from univariate (voxelwise or regionwise) analysis, hence focusing on specific cognitive systems such as Resting-State Networks (RSNs) and raising the issue of the specificity of this scale-free dynamics modulation in RSNs. Second, using analysis tools designed to measure a single scaling exponent related to the second order statistics of the data, thus relying on models that either implicitly or explicitly assume Gaussianity and (asymptotic) self-similarity, while fMRI signals may significantly depart from those either of those two assumptions (Ciuciu et al., 2008; Wink et al., 2008). To address these issues, the present contribution elaborates on the analysis of the scaling properties of fMRI temporal dynamics by proposing two significant variations. First, scaling properties are technically investigated using the recently introduced Wavelet Leader-based Multifractal formalism (WLMF; Wendt et al....

The Story of the Initial dip in fMRI

Hu, Xiaoping; Yacoub, Essa
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.84%
Over the past 20 years much attention has been given to characterizing the spatial accuracy of fMRI based signals and to techniques that improve on its co-localization with neuronal activity. While the vast majority of fMRI studies have always used the conventional positive BOLD signal, alternative contrast options have demonstrated superior spatial specificity. One of these options surfaced shortly after the initial BOLD fMRI demonstrations and was motivated by optical imaging studies which revealed an early signal change that was much smaller but spatially more specific than the delayed positive response. This early signal change was attributed to oxygenation changes prior to any subsequent blood flow increases. After observation of this biphasic hemodynamic response in fMRI, because this early response resulted in a small MR signal decrease prior to the onset of the large signal increase, it became known as the “initial dip”. While the initial dip in fMRI was subsequently reported by many studies, including those in humans, monkeys, and cats, there were conflicting views about the associated mechanisms and whether it could be generalized across brain regions or species, in addition to whether or not it would prove fruitful for neuroscience. These discrepancies...

The Rapid Development of High Speed, Resolution and Precision in fMRI

Feinberg, David A.; Yacoub, Essa
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.84%
MRI pulse sequences designed to increase the speed and spatial resolution of fMRI have always been a hot topic. Here, we review and chronicle the history behind some of the pulse sequence ideas that have contributed not only to the enhancement of fMRI acquisition but also to diffusion imaging. (i) Partial Fourier EPI allows lengthening echo trains for higher spatial resolution while maintaining optimal TE and BOLD sensitivity. (ii) Inner-volume EPI renamed zoomed-EPI, achieves extremely high spatial resolution and has been applied to fMRI at 7 Tesla to resolve cortical layer activity and columnar level fMRI. (iii) An early non-BOLD approach while unsuccessful for fMRI created a diffusion sequence of bipolar pulses called ‘twice refocused spin echo’ now widely used for high resolution DTI and HARDI neuronal fiber track imaging. (iv) Multiplexed EPI shortens TR to a few hundred millisecond, increasing sampling rates and statistical power in fMRI.

fMRI Resting Slow Fluctuations Correlate with the Activity of Fast Cortico-Cortical Physiological Connections

Koch, Giacomo; Bozzali, Marco; Bonnì, Sonia; Giacobbe, Viola; Caltagirone, Carlo; Cercignani, Mara
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 20/12/2012 Português
Relevância na Pesquisa
26.84%
Recording of slow spontaneous fluctuations at rest using functional magnetic resonance imaging (fMRI) allows distinct long-range cortical networks to be identified. The neuronal basis of connectivity as assessed by resting-state fMRI still needs to be fully clarified, considering that these signals are an indirect measure of neuronal activity, reflecting slow local variations in de-oxyhaemoglobin concentration. Here, we combined fMRI with multifocal transcranial magnetic stimulation (TMS), a technique that allows the investigation of the causal neurophysiological interactions occurring in specific cortico-cortical connections. We investigated whether the physiological properties of parieto-frontal circuits mapped with short-latency multifocal TMS at rest may have some relationship with the resting-state fMRI measures of specific resting-state functional networks (RSNs). Results showed that the activity of fast cortico-cortical physiological interactions occurring in the millisecond range correlated selectively with the coupling of fMRI slow oscillations within the same cortical areas that form part of the dorsal attention network, i.e., the attention system believed to be involved in reorientation of attention. We conclude that resting-state fMRI ongoing slow fluctuations likely reflect the interaction of underlying physiological cortico-cortical connections.

A receptor-based model for dopamine-induced fMRI signal

Mandeville, Joseph. B.; Sander, Christin Y. M.; Jenkins, Bruce G.; Hooker, Jacob M.; Catana, Ciprian; Vanduffel, Wim; Alpert, Nathaniel M.; Rosen, Bruce R.; Normandin, Marc D.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.84%
This report describes a multi-receptor physiological model of the fMRI temporal response and signal magnitude evoked by drugs that elevate synaptic dopamine in basal ganglia. The model is formulated as a summation of dopamine’s effects at D1-like and D2-like receptor families, which produce functional excitation and inhibition, respectively, as measured by molecular indicators like adenylate cyclase or neuroimaging techniques like fMRI. Functional effects within the model are described in terms of relative changes in receptor occupancies scaled by receptor densities and neuro-vascular coupling constants. Using literature parameters, the model reconciles many discrepant observations and interpretations of pre-clinical data. Additionally, we present data showing that amphetamine stimulation produces fMRI inhibition at low doses and a biphasic response at higher doses in the basal ganglia of non-human primates (NHP), in agreement with model predictions based upon the respective levels of evoked dopamine. Because information about dopamine release is required to inform the fMRI model, we simultaneously acquired PET 11C-raclopride data in several studies to evaluate the relationship between raclopride displacement and assumptions about dopamine release. At high levels of dopamine release...

Is Granger Causality a Viable Technique for Analyzing fMRI Data?

Wen, Xiaotong; Rangarajan, Govindan; Ding, Mingzhou
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 04/07/2013 Português
Relevância na Pesquisa
26.84%
Multivariate neural data provide the basis for assessing interactions in brain networks. Among myriad connectivity measures, Granger causality (GC) has proven to be statistically intuitive, easy to implement, and generate meaningful results. Although its application to functional MRI (fMRI) data is increasing, several factors have been identified that appear to hinder its neural interpretability: (a) latency differences in hemodynamic response function (HRF) across different brain regions, (b) low-sampling rates, and (c) noise. Recognizing that in basic and clinical neuroscience, it is often the change of a dependent variable (e.g., GC) between experimental conditions and between normal and pathology that is of interest, we address the question of whether there exist systematic relationships between GC at the fMRI level and that at the neural level. Simulated neural signals were convolved with a canonical HRF, down-sampled, and noise-added to generate simulated fMRI data. As the coupling parameters in the model were varied, fMRI GC and neural GC were calculated, and their relationship examined. Three main results were found: (1) GC following HRF convolution is a monotonically increasing function of neural GC; (2) this monotonicity can be reliably detected as a positive correlation when realistic fMRI temporal resolution and noise level were used; and (3) although the detectability of monotonicity declined due to the presence of HRF latency differences...

Best Current Practice for Obtaining High Quality EEG Data During Simultaneous fMRI

Mullinger, Karen J.; Castellone, Pierluigi; Bowtell, Richard
Fonte: MyJove Corporation Publicador: MyJove Corporation
Tipo: Artigo de Revista Científica
Publicado em 03/06/2013 Português
Relevância na Pesquisa
26.84%
Simultaneous EEG-fMRI allows the excellent temporal resolution of EEG to be combined with the high spatial accuracy of fMRI. The data from these two modalities can be combined in a number of ways, but all rely on the acquisition of high quality EEG and fMRI data. EEG data acquired during simultaneous fMRI are affected by several artifacts, including the gradient artefact (due to the changing magnetic field gradients required for fMRI), the pulse artefact (linked to the cardiac cycle) and movement artifacts (resulting from movements in the strong magnetic field of the scanner, and muscle activity). Post-processing methods for successfully correcting the gradient and pulse artifacts require a number of criteria to be satisfied during data acquisition. Minimizing head motion during EEG-fMRI is also imperative for limiting the generation of artifacts.

Poststimulus undershoots in cerebral blood flow and BOLD fMRI responses are modulated by poststimulus neuronal activity

Mullinger, Karen J.; Mayhew, Stephen D.; Bagshaw, Andrew P.; Bowtell, Richard; Francis, Susan T.
Fonte: National Academy of Sciences Publicador: National Academy of Sciences
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.84%
fMRI is the foremost technique for noninvasive measurement of human brain function. However, its utility is limited by an incomplete understanding of the relationship between neuronal activity and the hemodynamic response. Though the primary peak of the hemodynamic response is modulated by neuronal activity, the origin of the typically negative poststimulus signal is poorly understood and its amplitude assumed to covary with the primary response. We use simultaneous recordings of EEG with blood oxygenation level-dependent (BOLD) and cerebral blood flow (CBF) fMRI during unilateral median nerve stimulation to show that the poststimulus fMRI signal is neuronally modulated. We observe high spatial agreement between concurrent BOLD and CBF responses to median nerve stimulation, with primary signal increases in contralateral sensorimotor cortex and primary signal decreases in ipsilateral sensorimotor cortex. During the poststimulus period, the amplitude and directionality (positive/negative) of the BOLD signal in both contralateral and ipsilateral sensorimotor cortex depends on the poststimulus synchrony of 8–13 Hz EEG neuronal activity, which is often considered to reflect cortical inhibition, along with concordant changes in CBF and metabolism. Therefore we present conclusive evidence that the fMRI time course represents a hemodynamic signature of at least two distinct temporal phases of neuronal activity...

High-Speed Real-Time Resting-State fMRI Using Multi-Slab Echo-Volumar Imaging

Posse, Stefan; Ackley, Elena; Mutihac, Radu; Zhang, Tongsheng; Hummatov, Ruslan; Akhtari, Massoud; Chohan, Muhammad; Fisch, Bruce; Yonas, Howard
Fonte: Frontiers Media S.A. Publicador: Frontiers Media S.A.
Tipo: Artigo de Revista Científica
Publicado em 26/08/2013 Português
Relevância na Pesquisa
26.84%
We recently demonstrated that ultra-high-speed real-time fMRI using multi-slab echo-volumar imaging (MEVI) significantly increases sensitivity for mapping task-related activation and resting-state networks (RSNs) compared to echo-planar imaging (Posse et al., 2012). In the present study we characterize the sensitivity of MEVI for mapping RSN connectivity dynamics, comparing independent component analysis (ICA) and a novel seed-based connectivity analysis (SBCA) that combines sliding-window correlation analysis with meta-statistics. This SBCA approach is shown to minimize the effects of confounds, such as movement, and CSF and white matter signal changes, and enables real-time monitoring of RSN dynamics at time scales of tens of seconds. We demonstrate highly sensitive mapping of eloquent cortex in the vicinity of brain tumors and arterio-venous malformations, and detection of abnormal resting-state connectivity in epilepsy. In patients with motor impairment, resting-state fMRI provided focal localization of sensorimotor cortex compared with more diffuse activation in task-based fMRI. The fast acquisition speed of MEVI enabled segregation of cardiac-related signal pulsation using ICA, which revealed distinct regional differences in pulsation amplitude and waveform...

Integrated MEG/fMRI Model Validated Using Real Auditory Data

Babajani-Feremi, Abbas; Soltanian-Zadeh, Hamid; Moran, John E.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.84%
The main objective of this paper is to present methods and results for the estimation of parameters of our proposed integrated magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) model. We use real auditory MEG and fMRI datasets from 7 normal subjects to estimate the parameters of the model. The MEG and fMRI data were acquired at different times, but the stimulus profile was the same for both techniques. We use independent component analysis (ICA) to extract activation-related signal from the MEG data. The stimulus-correlated ICA component is used to estimate MEG parameters of the model. The temporal and spatial information of the fMRI datasets are used to estimate fMRI parameters of the model. The estimated parameters have reasonable means and standard deviations for all subjects. Goodness of fit of the real data to our model shows the possibility of using the proposed model to simulate realistic datasets for evaluation of integrated MEG/fMRI analysis methods.

Boosting BOLD fMRI by K-Space Density Weighted Echo Planar Imaging

Zeller, Mario; Müller, Alexander; Gutberlet, Marcel; Nichols, Thomas; Hahn, Dietbert; Köstler, Herbert; Bartsch, Andreas J.
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 10/09/2013 Português
Relevância na Pesquisa
26.84%
Functional magnetic resonance imaging (fMRI) has become a powerful and influential method to non-invasively study neuronal brain activity. For this purpose, the blood oxygenation level-dependent (BOLD) effect is most widely used. T2* weighted echo planar imaging (EPI) is BOLD sensitive and the prevailing fMRI acquisition technique. Here, we present an alternative to its standard Cartesian recordings, i.e. k-space density weighted EPI, which is expected to increase the signal-to-noise ratio in fMRI data. Based on in vitro and in vivo pilot measurements, we show that fMRI by k-space density weighted EPI is feasible and that this new acquisition technique in fact boosted spatial and temporal SNR as well as the detection of local fMRI activations. Spatial resolution, spatial response function and echo time were identical for density weighted and conventional Cartesian EPI. The signal-to-noise ratio gain of density weighting can improve activation detection and has the potential to further increase the sensitivity of fMRI investigations.

Fusion of fNIRS and fMRI data: identifying when and where hemodynamic signals are changing in human brains

Yuan, Zhen; Ye, JongChul
Fonte: Frontiers Media S.A. Publicador: Frontiers Media S.A.
Tipo: Artigo de Revista Científica
Publicado em 16/10/2013 Português
Relevância na Pesquisa
26.84%
In this study we implemented a new imaging method to fuse functional near infrared spectroscopy (fNIRS) measurements and functional magnetic resonance imaging (fMRI) data to reveal the spatiotemporal dynamics of the hemodynamic responses with high spatiotemporal resolution across the brain. We evaluated this method using multimodal data acquired from human right finger tapping tasks. And we found the proposed method is able to clearly identify from the linked components of fMRI and fNIRS where and when the hemodynamic signals are changing. In particular, the estimated associations between fNIRS and fMRI will be displayed as time varying spatial fMRI maps along with the fNIRS time courses. In addition, the joint components between fMRI and fNIRS are combined together to generate full spatiotemporal “snapshots” and movies, which provides an excellent way to examine the dynamic interplay between hemodynamic fNIRS and fMRI measurements.

Multisensory integration of dynamic emotional faces and voices: method for simultaneous EEG-fMRI measurements

Schelenz, Patrick D.; Klasen, Martin; Reese, Barbara; Regenbogen, Christina; Wolf, Dhana; Kato, Yutaka; Mathiak, Klaus
Fonte: Frontiers Media S.A. Publicador: Frontiers Media S.A.
Tipo: Artigo de Revista Científica
Publicado em 14/11/2013 Português
Relevância na Pesquisa
26.84%
Combined EEG-fMRI analysis correlates time courses from single electrodes or independent EEG components with the hemodynamic response. Implementing information from only one electrode, however, may miss relevant information from complex electrophysiological networks. Component based analysis, in turn, depends on a priori knowledge of the signal topography. Complex designs such as studies on multisensory integration of emotions investigate subtle differences in distributed networks based on only a few trials per condition. Thus, they require a sensitive and comprehensive approach which does not rely on a-priori knowledge about the underlying neural processes. In this pilot study, feasibility and sensitivity of source localization-driven analysis for EEG-fMRI was tested using a multisensory integration paradigm. Dynamic audiovisual stimuli consisting of emotional talking faces and pseudowords with emotional prosody were rated in a delayed response task. The trials comprised affectively congruent and incongruent displays. In addition to event-locked EEG and fMRI analyses, induced oscillatory EEG responses at estimated cortical sources and in specific temporo-spectral windows were correlated with the corresponding BOLD responses. EEG analysis showed high data quality with less than 10% trial rejection. In an early time window...

Multiple Time Scale Complexity Analysis of Resting State FMRI

Smith, Robert X.; Yan, Lirong; Wang, Danny J.J.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.84%
The present study explored multi-scale entropy (MSE) analysis to investigate the entropy of resting state fMRI signals across multiple time scales. MSE analysis was developed to distinguish random noise from complex signals since the entropy of the former decreases with longer time scales while the latter signal maintains its entropy due to a self-resemblance” across time scales. A long resting state BOLD fMRI (rs-fMRI) scan with 1000 data points was performed on five healthy young volunteers to investigate the spatial and temporal characteristics of entropy across multiple time scales. A shorter rs-fMRI scan with 240 data points was performed on a cohort of subjects consisting of healthy young (age 23±2 years, n=8) and aged volunteers (age 66±3 years, n=8) to investigate the effect of healthy aging on the entropy of rs-fMRI. The results showed that MSE of gray matter, rather than white matter, resembles closely that of f−1 noise over multiple time scales. By filtering out high frequency random fluctuations, MSE analysis is able to reveal enhanced contrast in entropy between gray and white matter, as well as between age groups at longer time scales. Our data support the use of MSE analysis as a validation metric for quantifying the complexity of rs-fMRI signals.

Multimodal Functional Imaging Using fMRI-Informed Regional EEG/MEG Source Estimation

Ou, Wanmei; Nummenmaa, Aapo; Golland, Polina; Hämäläinen, Matti S.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em //2009 Português
Relevância na Pesquisa
26.84%
We propose a novel method, fMRI-Informed Regional Estimation (FIRE), which utilizes information from fMRI in E/MEG source reconstruction. FIRE takes advantage of the spatial alignment between the neural and the vascular activities, while allowing for substantial differences in their dynamics. Furthermore, with the regional approach, FIRE can be efficiently applied to a dense grid of sources. Inspection of our optimization procedure reveals that FIRE is related to the re-weighted minimum-norm algorithms, the difference being that the weights in the proposed approach are computed from both the current estimates and fMRI data. Analysis of both simulated and human fMRI-MEG data shows that FIRE reduces the ambiguities in source localization present in the minimum-norm estimates. Comparisons with several joint fMRI-E/MEG algorithms demonstrate robustness of FIRE in the presence of sources silent to either fMRI or E/MEG measurements.