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Determining Functional Connectivity using fMRI Data with Diffusion-Based Anatomical Weighting

Bowman, F. DuBois; Zhang, Lijun; Derado, Gordana; Chen, Shuo
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.79%
There is strong interest in investigating both functional connectivity (FC) using functional magnetic resonance imaging (fMRI) and structural connectivity (SC) using diffusion tensor imaging (DTI). There is also emerging evidence of correspondence between functional and structural pathways within many networks (Skudlarski et al., 2008; van den Heuvel et al., 2009; Greicius, et al., 2009), although some regions without SC exhibit strong FC (Honey et al., 2009). These findings suggest that FC may be mediated by (direct or indirect) anatomical connections, offering an opportunity to supplement fMRI data with DTI data when determining FC. We develop a novel statistical method for determining FC, called anatomically-weighted FC (awFC), which combines fMRI and DTI data. Our awFC approach implements a hierarchical clustering algorithm that establishes neural processing networks using a new distance measure consisting of two components, a primary functional component that captures correlations between fMRI signals from different regions and a secondary anatomical weight reflecting probabilities of SC. The awFC approach defaults to conventional unweighted clustering for specific parameter settings. We optimize awFC parameters using a strictly functional criterion...

Spatiotemporal characteristics and vascular sources of neural-specific and -nonspecific fMRI signals at submillimeter columnar resolution

Moon, Chan Hong; Fukuda, Mitsuhiro; Kim, Seong-Gi
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.79%
The neural specificity of hemodynamic-based functional magnetic resonance imaging (fMRI) signals are dependent on both the vascular regulation and the sensitivity of the applied fMRI technique to different types and sizes of blood vessels. In order to examine the specificity of MRI-detectable hemodynamic responses, submillimeter blood oxygenation-level dependent (BOLD) and cerebral blood volume (CBV) fMRI studies were performed in a well-established cat orientation column model at 9.4 Tesla. Neural-nonspecific and -specific signals were separated by comparing the fMRI responses of orthogonal orientation stimuli. The BOLD response was dominantly neural-nonspecific, mostly originating from pial and intracortical emerging veins, and thus was highly correlated with baseline blood volume. Uneven baseline CBV may displace or distort small functional domains in high-resolution BOLD maps. The CBV response in the parenchyma exhibited dual spatiotemporal characteristics, a fast and early neural-nonspecific response (with 4.3-s time constant) and a slightly slower and delayed neural-specific response (with 9.4-s time constant). The nonspecific CBV signal originates from early-responding arteries and arterioles, while the specific CBV response...

Sources of fMRI signal fluctuations in the human brain at rest: a 7T study

Bianciardi, Marta; Fukunaga, Masaki; van Gelderen, Peter; Horovitz, Silvina G.; de Zwart, Jacco A.; Shmueli, Karin; Duyn, Jeff H.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.79%
Signal fluctuations in functional magnetic resonance imaging (fMRI) can result from a number of sources that may have a neuronal, physiologic, or instrumental origin. To determine the relative contribution of these sources we recorded physiological (respiration and cardiac) signals simultaneously with fMRI in human volunteers at rest with their eyes closed. State-of-the-art technology was used including high magnetic field (7T), a multi-channel detector array, and high resolution (3 mm3) echo-planar imaging (EPI). We investigated the relative contribution of thermal noise and other sources of variance to the observed fMRI signal fluctuations both in the visual cortex and in the whole brain gray matter. The following sources of variance were evaluated separately: low frequency drifts due to scanner instability, effects correlated with respiratory and cardiac cycles, effects due to variability in the respiratory flow rate and cardiac rate, and other sources, tentatively attributed to spontaneous neuronal activity. We found that low-frequency drifts are the most significant source of fMRI signal fluctuations (3.0% signal change in the visual cortex, TE = 32 ms), followed by spontaneous neuronal activity (2.9%), thermal noise (2.1%) and effects due to variability in physiological rates (respiration 0.9%...

An electrophysiological validation of stochastic DCM for fMRI

Daunizeau, J.; Lemieux, L.; Vaudano, A. E.; Friston, K. J.; Stephan, K. E.
Fonte: Frontiers Media S.A. Publicador: Frontiers Media S.A.
Tipo: Artigo de Revista Científica
Publicado em 18/01/2013 Português
Relevância na Pesquisa
26.79%
In this note, we assess the predictive validity of stochastic dynamic causal modeling (sDCM) of functional magnetic resonance imaging (fMRI) data, in terms of its ability to explain changes in the frequency spectrum of concurrently acquired electroencephalography (EEG) signal. We first revisit the heuristic model proposed in Kilner et al. (2005), which suggests that fMRI activation is associated with a frequency modulation of the EEG signal (rather than an amplitude modulation within frequency bands). We propose a quantitative derivation of the underlying idea, based upon a neural field formulation of cortical activity. In brief, dense lateral connections induce a separation of time scales, whereby fast (and high spatial frequency) modes are enslaved by slow (low spatial frequency) modes. This slaving effect is such that the frequency spectrum of fast modes (which dominate EEG signals) is controlled by the amplitude of slow modes (which dominate fMRI signals). We then use conjoint empirical EEG-fMRI data—acquired in epilepsy patients—to demonstrate the electrophysiological underpinning of neural fluctuations inferred from sDCM for fMRI.

ICA analysis of fMRI with real-time constraints: an evaluation of fast detection performance as function of algorithms, parameters and a priori conditions

Soldati, Nicola; Calhoun, Vince D.; Bruzzone, Lorenzo; Jovicich, Jorge
Fonte: Frontiers Media S.A. Publicador: Frontiers Media S.A.
Tipo: Artigo de Revista Científica
Publicado em 01/02/2013 Português
Relevância na Pesquisa
26.79%
Independent component analysis (ICA) techniques offer a data-driven possibility to analyze brain functional MRI data in real-time. Typical ICA methods used in functional magnetic resonance imaging (fMRI), however, have been until now mostly developed and optimized for the off-line case in which all data is available. Real-time experiments are ill-posed for ICA in that several constraints are added: limited data, limited analysis time and dynamic changes in the data and computational speed. Previous studies have shown that particular choices of ICA parameters can be used to monitor real-time fMRI (rt-fMRI) brain activation, but it is unknown how other choices would perform. In this rt-fMRI simulation study we investigate and compare the performance of 14 different publicly available ICA algorithms systematically sampling different growing window lengths (WLs), model order (MO) as well as a priori conditions (none, spatial or temporal). Performance is evaluated by computing the spatial and temporal correlation to a target component as well as computation time. Four algorithms are identified as best performing (constrained ICA, fastICA, amuse, and evd), with their corresponding parameter choices. Both spatial and temporal priors are found to provide equal or improved performances in similarity to the target compared with their off-line counterpart...

A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping

Eggebrecht, Adam T.; White, Brian R.; Ferradal, Silvina L.; Chen, Chunxiao; Zhan, Yuxuan; Snyder, Abraham Z.; Dehghani, Hamid; Culver, Joseph P.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.79%
Functional neuroimaging commands a dominant role in current neuroscience research. However its use in bedside clinical and certain neuro-scientific studies has been limited because the current tools lack the combination of being non-invasive, non-ionizing and portable while maintaining moderate resolution and localization accuracy. Optical neuroimaging satisfies many of these requirements, but, until recent advances in high-density diffuse optical tomography (HD-DOT), has been hampered by limited resolution. While early results of HD-DOT have been promising, a quantitative voxel-wise comparison and validation of HD-DOT against the gold standard of functional magnetic resonance imaging (fMRI) has been lacking. Herein, we provide such an analysis within the visual cortex using matched visual stimulation protocols in a single group of subjects (n=5) during separate HD-DOT and fMRI scanning sessions. To attain the needed voxel-to-voxel co-registration between HD-DOT and fMRI image spaces, we implemented subject-specific head modeling that incorporated MRI anatomy, detailed segmentation, and alignment of source and detector positions. Comparisons of the visual responses found an average localization error between HD-DOT and fMRI of 4.4 +/− 1 mm...

Comparison of semantic and episodic memory BOLD fMRI activation in predicting cognitive decline in older adults

Hantke, Nathan; Nielson, Kristy A.; Woodard, John L.; Guidotti Breting, Leslie M.; Butts, Alissa; Seidenberg, Michael; Smith, J. Carson; Durgerian, Sally; Lancaster, Melissa; Matthews, Monica; Sugarman, Michael A.; Rao, Stephen M.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.79%
Previous studies suggest that task-activated fMRI can predict future cognitive decline among healthy older adults. The present fMRI study examined the relative sensitivity of semantic memory (SM) versus episodic memory (EM) activation tasks for predicting cognitive decline. Seventy-eight cognitively intact elders underwent neuropsychological testing at entry and after an 18-month interval, with participants classified as cognitively “Stable” or “Declining” based on ≥1.0 SD decline in performance. Baseline fMRI scanning involved SM (famous name discrimination) and EM (name recognition) tasks. SM and EM fMRI activation, along with APOE ε4 status, served as predictors of cognitive outcome using a logistic regression analysis. Twenty-seven (34.6%) participants were classified as Declining and 51 (65.4%) as Stable. APOE ε4 status alone significantly predicted cognitive decline (R2 = .106; C index = .642). Addition of SM activation significantly improved prediction accuracy (R2 = .285; C index = .787), whereas the addition of EM did not (R2 = .212; C index = .711). In combination with APOE status, SM task activation predicts future cognitive decline better than EM activation. These results have implications for use of fMRI in prevention clinical trials involving the identification of persons at-risk for age-associated memory loss and Alzheimer’s disease.

Functional Topography of Human Corpus Callosum: An fMRI Mapping Study

Fabri, Mara; Polonara, Gabriele
Fonte: Hindawi Publishing Corporation Publicador: Hindawi Publishing Corporation
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.79%
The concept of a topographical map of the corpus callosum (CC) has emerged from human lesion studies and from electrophysiological and anatomical tracing investigations in other mammals. Over the last few years a rising number of researchers have been reporting functional magnetic resonance imaging (fMRI) activation in white matter, particularly the CC. In this study the scope for describing CC topography with fMRI was explored by evoking activation through simple sensory stimulation and motor tasks. We reviewed our published and unpublished fMRI and diffusion tensor imaging data on the cortical representation of tactile, gustatory, auditory, and visual sensitivity and of motor activation, obtained in 36 normal volunteers and in 6 patients with partial callosotomy. Activation foci were consistently detected in discrete CC regions: anterior (taste stimuli), central (motor tasks), central and posterior (tactile stimuli), and splenium (auditory and visual stimuli). Reconstruction of callosal fibers connecting activated primary gustatory, motor, somatosensory, auditory, and visual cortices by diffusion tensor tracking showed bundles crossing, respectively, through the genu, anterior and posterior body, and splenium, at sites harboring fMRI foci. These data confirm that the CC commissure has a topographical organization and demonstrate that its functional topography can be explored with fMRI.

Measuring Relative Timings of Brain Activities Using FMRI

Katwal, Santosh B.; Gore, John C.; Gatenby, J. Christopher; Rogers, Baxter P.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.79%
Functional MRI (fMRI) has previously been shown to be able to measure hundreds of milliseconds differences in timings of activities in different brain regions, even though the underlying blood oxygenation level-dependent (BOLD) response is delayed and dispersed on the order of seconds. This capability may contribute towards the study of communication within the brain by assessing the temporal sequences of various brain processes (mental chronometry). The practical limit of fMRI for detecting the relative timings of brain activities is not known. We aimed to detect fine differences in the timings of brain activities beyond those previously measured from fMRI data in human subjects. We introduced known delays between the onsets of visual stimuli in a controlled, sparse event-related design and investigated if the temporal shifts in the corresponding average BOLD signals were detectable. To maximize sensitivity, we used high spatial and temporal resolution fMRI at ultrahigh field (7 Tesla), in conjunction with a novel data-driven technique for voxel selection using graph-based visualizations of self-organizing maps and Granger causality to measure relative timing. This approach detected timing differences as small as 28 ms in visual cortex in individual subjects. For signal extraction...

Assessing hippocampal functional reserve in temporal lobe epilepsy: A multi-voxel pattern analysis of fMRI data

Bonnici, Heidi M.; Sidhu, Meneka; Chadwick, Martin J.; Duncan, John S.; Maguire, Eleanor A.
Fonte: Elsevier Science Publishers Publicador: Elsevier Science Publishers
Tipo: Artigo de Revista Científica
Publicado em /07/2013 Português
Relevância na Pesquisa
26.79%
Assessing the functional reserve of key memory structures in the medial temporal lobes (MTL) of pre-surgical patients with intractable temporal lobe epilepsy (TLE) remains a challenge. Conventional functional MRI (fMRI) memory paradigms have yet to fully convince of their ability to confidently assess the risk of a post-surgical amnesia. An alternative fMRI analysis method, multi-voxel pattern analysis (MVPA), focuses on the patterns of activity across voxels in specific brain regions that are associated with individual memory traces. This method makes it possible to investigate whether the hippocampus and related structures contralateral to any proposed surgery are capable of laying down and representing specific memories. Here we used MVPA-fMRI to assess the functional integrity of the hippocampi and MTL in patients with long-standing medically refractory TLE associated with unilateral hippocampal sclerosis (HS). Patients were exposed to movie clips of everyday events prior to scanning, which they subsequently recalled during high-resolution fMRI. MTL structures were delineated and pattern classifiers were trained to learn the patterns of brain activity across voxels associated with each memory. Predictable patterns of activity across voxels associated with specific memories could be detected in MTL structures...

A Model-Based fMRI Analysis with Hierarchical Bayesian Parameter Estimation

Ahn, Woo-Young; Krawitz, Adam; Kim, Woojae; Busmeyer, Jerome R.; Brown, Joshua W.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em /05/2011 Português
Relevância na Pesquisa
26.79%
A recent trend in decision neuroscience is the use of model-based fMRI using mathematical models of cognitive processes. However, most previous model-based fMRI studies have ignored individual differences due to the challenge of obtaining reliable parameter estimates for individual participants. Meanwhile, previous cognitive science studies have demonstrated that hierarchical Bayesian analysis is useful for obtaining reliable parameter estimates in cognitive models while allowing for individual differences. Here we demonstrate the application of hierarchical Bayesian parameter estimation to model-based fMRI using the example of decision making in the Iowa Gambling Task. First we use a simulation study to demonstrate that hierarchical Bayesian analysis outperforms conventional (individual- or group-level) maximum likelihood estimation in recovering true parameters. Then we perform model-based fMRI analyses on experimental data to examine how the fMRI results depend upon the estimation method.

The Perception of Dynamic and Static Facial Expressions of Happiness and Disgust Investigated by ERPs and fMRI Constrained Source Analysis

Trautmann-Lengsfeld, Sina Alexa; Domínguez-Borràs, Judith; Escera, Carles; Herrmann, Manfred; Fehr, Thorsten
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 20/06/2013 Português
Relevância na Pesquisa
26.79%
A recent functional magnetic resonance imaging (fMRI) study by our group demonstrated that dynamic emotional faces are more accurately recognized and evoked more widespread patterns of hemodynamic brain responses than static emotional faces. Based on this experimental design, the present study aimed at investigating the spatio-temporal processing of static and dynamic emotional facial expressions in 19 healthy women by means of multi-channel electroencephalography (EEG), event-related potentials (ERP) and fMRI-constrained regional source analyses. ERP analysis showed an increased amplitude of the LPP (late posterior positivity) over centro-parietal regions for static facial expressions of disgust compared to neutral faces. In addition, the LPP was more widespread and temporally prolonged for dynamic compared to static faces of disgust and happiness. fMRI constrained source analysis on static emotional face stimuli indicated the spatio-temporal modulation of predominantly posterior regional brain activation related to the visual processing stream for both emotional valences when compared to the neutral condition in the fusiform gyrus. The spatio-temporal processing of dynamic stimuli yielded enhanced source activity for emotional compared to neutral conditions in temporal (e.g....

An Automated Method for Identifying Artifact in Independent Component Analysis of Resting-State fMRI

Bhaganagarapu, Kaushik; Jackson, Graeme D.; Abbott, David F.
Fonte: Frontiers Media S.A. Publicador: Frontiers Media S.A.
Tipo: Artigo de Revista Científica
Publicado em 10/07/2013 Português
Relevância na Pesquisa
26.79%
An enduring issue with data-driven analysis and filtering methods is the interpretation of results. To assist, we present an automatic method for identification of artifact in independent components (ICs) derived from functional MRI (fMRI). The method was designed with the following features: does not require temporal information about an fMRI paradigm; does not require the user to train the algorithm; requires only the fMRI images (additional acquisition of anatomical imaging not required); is able to identify a high proportion of artifact-related ICs without removing components that are likely to be of neuronal origin; can be applied to resting-state fMRI; is automated, requiring minimal or no human intervention. We applied the method to a MELODIC probabilistic ICA of resting-state functional connectivity data acquired in 50 healthy control subjects, and compared the results to a blinded expert manual classification. The method identified between 26 and 72% of the components as artifact (mean 55%). About 0.3% of components identified as artifact were discordant with the manual classification; retrospective examination of these ICs suggested the automated method had correctly identified these as artifact. We have developed an effective automated method which removes a substantial number of unwanted noisy components in ICA analyses of resting-state fMRI data. Source code of our implementation of the method is available.

Task modulation of brain responses in visual word recognition as studied using EEG/MEG and fMRI

Chen, Y.; Davis, M. H.; Pulvermüller, F.; Hauk, O.
Fonte: Frontiers Media S.A. Publicador: Frontiers Media S.A.
Tipo: Artigo de Revista Científica
Publicado em 23/07/2013 Português
Relevância na Pesquisa
26.79%
Do task demands change the way we extract information from a stimulus, or only how we use this information for decision making? In order to answer this question for visual word recognition, we used EEG/MEG as well as fMRI to determine the latency ranges and spatial areas in which brain activation to words is modulated by task demands. We presented letter strings in three tasks (lexical decision, semantic decision, silent reading), and measured combined EEG/MEG as well as fMRI responses in two separate experiments. EEG/MEG sensor statistics revealed the earliest reliable task effects at around 150 ms, which were localized, using minimum norm estimates (MNE), to left inferior temporal, right anterior temporal and left precentral gyri. Later task effects (250 and 480 ms) occurred in left middle and inferior temporal gyri. Our fMRI data showed task effects in left inferior frontal, posterior superior temporal and precentral cortices. Although there was some correspondence between fMRI and EEG/MEG localizations, discrepancies predominated. We suggest that fMRI may be less sensitive to the early short-lived processes revealed in our EEG/MEG data. Our results indicate that task-specific processes start to penetrate word recognition already at 150 ms...

Resting-state FMRI confounds and cleanup

Murphy, Kevin; Birn, Rasmus M.; Bandettini, Peter A.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.79%
The goal of resting-state functional magnetic resonance imaging (FMRI) is to investigate the brain’s functional connections by using the temporal similarity between blood oxygenation level dependent (BOLD) signals in different regions of the brain “at rest” as an indicator of synchronous neural activity. Since this measure relies on the temporal correlation of FMRI signal changes between different parts of the brain, any non-neural activity-related process that affects the signals will influence the measure of functional connectivity, yielding spurious results. To understand the sources of these resting-state FMRI confounds, this article describes the origins of the BOLD signal in terms of MR physics and cerebral physiology. Potential confounds arising from motion, cardiac and respiratory cycles, arterial CO2 concentration, blood pressure/cerebral autoregulation, and vasomotion are discussed. Two classes of techniques to remove confounds from resting-state BOLD time series are reviewed: 1) those utilising external recordings of physiology and 2) data-based cleanup methods that only use the resting-state FMRI data itself. Further methods that remove noise from functional connectivity measures at a group level are also discussed. For successful interpretation of resting-state FMRI comparisons and results...

Ultra high-resolution fMRI and electrophysiology of the rat primary somatosensory cortex✰

Shih, Yen-Yu Ian; Chen, You-Yin; Lai, Hsin-Yi; Kao, Yu-Chieh Jill; Shyu, Bai-Chuang; Duong, Timothy Q.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.79%
High-resolution functional-magnetic-resonance-imaging (fMRI) has been used to study brain functions at increasingly finer scale, but whether fMRI can accurately reflect layer-specific neuronal activities is less well understood. The present study investigated layer-specific cerebral-blood-volume (CBV) fMRI and electrophysiological responses in the rat cortex. CBV fMRI at 40×40 µm in-plane resolution was performed on an 11.7-T scanner. Electrophysiology used a 32-channel electrode array that spanned the entire cortical depth. Graded electrical stimulation was used to study activations in different cortical layers, exploiting the notion that most of the sensory-specific neurons are in layers II–V and most of the nociceptive-specific neurons are in layers V–VI. CBV response was strongest in layer IV of all stimulus amplitudes. Current source density analysis showed strong sink currents at cortical layers IV and VI. Multi-unit activities mainly appeared at layers IV–VI and peaked at layer V. Although our measures showed scaled activation profiles during modulation of stimulus amplitude and failed to detect specific recruitment at layers V and VI during noxious electrical stimuli, there appears to be discordance between CBV fMRI and electrophysiological peak responses...

fMRI orientation decoding in V1 does not require global maps or globally coherent orientation stimuli

Alink, Arjen; Krugliak, Alexandra; Walther, Alexander; Kriegeskorte, Nikolaus
Fonte: Frontiers Media S.A. Publicador: Frontiers Media S.A.
Tipo: Artigo de Revista Científica
Publicado em 12/08/2013 Português
Relevância na Pesquisa
26.79%
The orientation of a large grating can be decoded from V1 functional magnetic resonance imaging (fMRI) data, even at low resolution (3-mm isotropic voxels). This finding has suggested that columnar-level neuronal information might be accessible to fMRI at 3T. However, orientation decodability might alternatively arise from global orientation-preference maps. Such global maps across V1 could result from bottom-up processing, if the preferences of V1 neurons were biased toward particular orientations (e.g., radial from fixation, or cardinal, i.e., vertical or horizontal). Global maps could also arise from local recurrent or top-down processing, reflecting pre-attentive perceptual grouping, attention spreading, or predictive coding of global form. Here we investigate whether fMRI orientation decoding with 2-mm voxels requires (a) globally coherent orientation stimuli and/or (b) global-scale patterns of V1 activity. We used opposite-orientation gratings (balanced about the cardinal orientations) and spirals (balanced about the radial orientation), along with novel patch-swapped variants of these stimuli. The two stimuli of a patch-swapped pair have opposite orientations everywhere (like their globally coherent parent stimuli). However...

The Nuisance of Nuisance Regression: Spectral Misspecification in a Common Approach to Resting-State fMRI Preprocessing Reintroduces Noise and Obscures Functional Connectivity

Hallquist, Michael N.; Hwang, Kai; Luna, Beatriz
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.79%
Recent resting-state functional connectivity fMRI (RS-fcMRI) research has demonstrated that head motion during fMRI acquisition systematically influences connectivity estimates despite bandpass filtering and nuisance regression, which are intended to reduce such nuisance variability. We provide evidence that the effects of head motion and other nuisance signals are poorly controlled when the fMRI time series are bandpass-filtered but the regressors are unfiltered, resulting in the inadvertent reintroduction of nuisance-related variation into frequencies previously suppressed by the bandpass filter, as well as suboptimal correction for noise signals in the frequencies of interest. This is important because many RS-fcMRI studies, including some focusing on motion-related artifacts, have applied this approach. In two cohorts of individuals (n = 117 and 22) who completed resting-state fMRI scans, we found that the bandpass-regress approach consistently overestimated functional connectivity across the brain, typically on the order of r = .10 – .35, relative to a simultaneous bandpass filtering and nuisance regression approach. Inflated correlations under the bandpass-regress approach were associated with head motion and cardiac artifacts. Furthermore...

fMRI in the awake marmoset: Somatosensory-evoked responses, functional connectivity, and comparison with propofol anesthesia

Liu, Junjie V.; Hirano, Yoshiyuki; Nascimento, George C.; Stefanovic, Bojana; Leopold, David A.; Silva, Afonso C.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.79%
Functional neuroimaging in animal models is essential for understanding the principles of neurovascular coupling and the physiological basis of fMRI signals that are widely used to study sensory and cognitive processing in the human brain. While hemodynamic responses to sensory stimuli have been characterized in humans, animal studies are able to combine very high resolution imaging with invasive measurements and pharmacological manipulation. To date, most high-resolution studies of neurovascular coupling in small animals have been carried out in anesthetized rodents. Here we report fMRI experiments in conscious, awake common marmosets (Callithrix jacchus), and compare responses to animals anesthetized with propofol. In conscious marmosets, robust BOLD fMRI responses to somatosensory stimulation of the forearm were found in contralateral and ipsilateral regions of the thalamus, primary (SI) and secondary (SII) somatosensory cortex, and the caudate nucleus. These responses were markedly stronger than those in anesthetized marmosets and showed a monotonic increase in the amplitude of the BOLD response with stimulus frequency. On the other hand, anesthesia significantly attenuated responses in thalamus, SI and SII, and abolished responses in caudate and ipsilateral SI. Moreover...

Physiological Noise in Brainstem fMRI

Brooks, Jonathan C. W.; Faull, Olivia K.; Pattinson, Kyle T. S.; Jenkinson, Mark
Fonte: Frontiers Media S.A. Publicador: Frontiers Media S.A.
Tipo: Artigo de Revista Científica
Publicado em 04/10/2013 Português
Relevância na Pesquisa
26.79%
The brainstem is directly involved in controlling blood pressure, respiration, sleep/wake cycles, pain modulation, motor, and cardiac output. As such it is of significant basic science and clinical interest. However, the brainstem’s location close to major arteries and adjacent pulsatile cerebrospinal fluid filled spaces, means that it is difficult to reliably record functional magnetic resonance imaging (fMRI) data from. These physiological sources of noise generate time varying signals in fMRI data, which if left uncorrected can obscure signals of interest. In this Methods Article we will provide a practical introduction to the techniques used to correct for the presence of physiological noise in time series fMRI data. Techniques based on independent measurement of the cardiac and respiratory cycles, such as retrospective image correction (RETROICOR, Glover et al., 2000), will be described and their application and limitations discussed. The impact of a physiological noise model, implemented in the framework of the general linear model, on resting fMRI data acquired at 3 and 7 T is presented. Data driven approaches based such as independent component analysis (ICA) are described. MR acquisition strategies that attempt to either minimize the influence of physiological fluctuations on recorded fMRI data...