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Wavelet correlation between subjects: A time-scale data driven analysis for brain mapping using fMRI

LESSA, Patricia S.; SATO, Joao R.; CARDOSO, Elisson F.; NETO, Carlos G.; VALADARES, Ana Paula; AMARO JR., Edson
Fonte: ELSEVIER SCIENCE BV Publicador: ELSEVIER SCIENCE BV
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.73%
Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.; FAPESP; UNIEMP/Brazil

Método de análise de componentes dependentes para o processamento, caracterização e extração de componentes de sinais biomédicos; Dependent Component Analysis for processing, characterization and extraction of biomedical signal components.

Montesco, Carlos Alberto Estombelo
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Tese de Doutorado Formato: application/pdf
Publicado em 10/12/2007 Português
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Na área de processamento de sinais biomédicos a extração de informação, baseada em um conjunto de medidas adquiridas no tempo, é considerada de suma importância. A qualidade desta informação extraída permite avaliar o funcionamento dos diversos órgãos. Objetivos: (1) propor o método de análise de componentes dependentes para auxiliar a extração de componentes de interesse, a partir de medidas multivariadas; (2) caraterizar as componentes extraídas através de representações em termos de tempo e freqüência, e espectro de potência; e, (3) aplicar o método e avaliar as componentes de interesse extraídas no contexto real MCGf, MGG e fMRI. A proposta para a extração fundamenta-se no método chamado de Análise de Componentes Dependentes ACD. As medidas a serem processadas são multivariadas a partir de sensores distribuídos, espacialmente, no corpo humano dando origem a um conjunto de dados correlacionados no tempo e/ou no espaço. Observa-se que os sinais de interesse raramente são registrados de forma isolada, e sim misturados com outros sinais superpostos, ruído e artefatos fisiológicos ou ambientais, onde a relação sinal-ruído é geralmente baixa. Nesse contexto, a estratégia a ser utilizada baseia-se na ACD...

BrainCAT : a tool for automated and combined functional magnetic resonance imaging and diffusion tensor imaging brain connectivity analysis

Marques, Paulo César Gonçalves; Soares, José Miguel; Alves, Victor; Sousa, Nuno
Fonte: Universidade do Minho Publicador: Universidade do Minho
Tipo: Artigo de Revista Científica
Publicado em 21/11/2013 Português
Relevância na Pesquisa
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Multimodal neuroimaging studies have recently become a trend in the neuroimaging field and are certainly a standard for the future. Brain connectivity studies combining functional activation patterns using resting-state or task-related functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) tractography have growing popularity. However, there is a scarcity of solutions to perform optimized, intuitive, and consistent multimodal fMRI/DTI studies. Here we propose a new tool, brain connectivity analysis tool (Brain CAT), for an automated and standard multimodal analysis of combined fMRI/DTI data, using freely available tools. With a friendly graphical user interface, BrainCAT aims to make data processing easier and faster, implementing a fully automated data processing pipeline and minimizing the need for user intervention, which hopefully will expand the use of combined fMRI/DTI studies. Its validity was tested in an aging study of the default mode network (DMN) white matter connectivity. The results evidenced the cingulum bundle as the structural connector of the precuneus/posterior cingulate cortex and the medial frontal cortex, regions of the DMN. Moreover, mean fractional anisotropy (FA) values along the cingulum extracted with BrainCAT showed a strong correlation with FA values from the manual selection of the same bundle. Taken together...

Cerebral energetics and spiking frequency: The neurophysiological basis of fMRI

Smith, Arien J.; Blumenfeld, Hal; Behar, Kevin L.; Rothman, Douglas L.; Shulman, Robert G.; Hyder, Fahmeed
Fonte: National Academy of Sciences Publicador: National Academy of Sciences
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.73%
Functional MRI (fMRI) is widely assumed to measure neuronal activity, but no satisfactory mechanism for this linkage has been identified. Here we derived the changes in the energetic component from the blood oxygenation level-dependent (BOLD) fMRI signal and related it to changes in the neuronal spiking frequency in the activated voxels. Extracellular recordings were used to measure changes in cerebral spiking frequency (Δν/ν) of a neuronal ensemble during forepaw stimulation in the α-chloralose anesthetized rat. Under the same conditions localized changes in brain energy metabolism (ΔCMRO2/CMRO2) were obtained from BOLD fMRI data in conjunction with measured changes in cerebral blood flow (ΔCBF/CBF), cerebral blood volume (ΔCBV/CBV), and transverse relaxation rates of tissue water (Tdocumentclass[10pt]{article} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{pmc} usepackage[Euler]{upgreek} pagestyle{empty} oddsidemargin -1.0in egin{document} egin{equation*}_{2}^{*}end{equation*}end{document} and T2) by MRI methods at 7T. On stimulation from two different depths of anesthesia ΔCMRO2/CMRO2 ≈ Δν/ν. Previous 13C magnetic resonance spectroscopy studies...

Mapping the MRI Voxel Volume in Which Thermal Noise Matches Physiological Noise-Implications for fMRI.

Bodurka, J.; Ye, F.; Petridou, N.; Murphy, K.; Bandettini, P.A.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.73%
This work addresses the choice of the imaging voxel volume in blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI). Noise of physiological origin that is present in the voxel time course is a prohibitive factor in the detection of small activation-induced BOLD signal changes. If the physiological noise contribution dominates over the temporal fluctuation contribution in the imaging voxel, further increases in the voxel signal-to-noise ratio (SNR) will have diminished corresponding increases in temporal signal-to-noise (TSNR), resulting in reduced corresponding increases in the ability to detect activation induced signal changes.. On the other hand, if the thermal and system noise dominate(suggesting a relatively low SNR) further decreases in SNR can prohibit detection of activation-induced signal changes. Here we have proposed and called the “suggested” voxel volume for fMRI the volume where thermal plus system-related and physiological noise variances are equal. Based on this condition we have created maps of fMRI suggested voxel volume from our experimental data at 3T, since this value will spatially vary depending on the contribution of physiologic noise in each voxel. Based on our fast EPI segmentation technique we have found that for gray matter (GM)...

Functional Cortical Source Imaging from Simultaneously Recorded ERP and fMRI

Im, Chang-Hwan; Liu, Zhongming; Zhang, Nanyin; Chen, Wei; He, Bin
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.73%
Feasibility of continuously and simultaneously recording visual evoked potentials (VEPs) with fMRI was assessed by quantitatively comparing cortical source images by means of receiver operating characteristic (ROC) curve analysis. The averaged EEG source images coincided well with simultaneously acquired fMRI activations. Strong correlation was found between the cortical source images of VEPs recorded inside and outside the scanner, despite slight difference in latencies and amplitudes of P1 peak existed in waveforms. Application of fMRI prior information strengthened correlation between estimated source images as well as resulted in source estimates with higher spatial resolution. The present results demonstrate that reliable cortical source images can be acquired during simultaneous fMRI scanning and they may be used for multimodal functional source imaging studies.

Fusing EEG and fMRI based on a bottom-up model: inferring activation and effective connectivity in neural masses

Riera, J; Aubert, E; Iwata, K; Kawashima, R; Wan, X; Ozaki, T
Fonte: The Royal Society Publicador: The Royal Society
Tipo: Artigo de Revista Científica
Português
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26.73%
The elucidation of the complex machinery used by the human brain to segregate and integrate information while performing high cognitive functions is a subject of imminent future consequences. The most significant contributions to date in this field, known as cognitive neuroscience, have been achieved by using innovative neuroimaging techniques, such as electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI), which measure variations in both the time and the space of some interpretable physical magnitudes. Extraordinary maps of cerebral activation involving function-restricted brain areas, as well as graphs of the functional connectivity between them, have been obtained from EEG and fMRI data by solving some spatio-temporal inverse problems, which constitutes a top-down approach. However, in many cases, a natural bridge between these maps/graphs and the causal physiological processes is lacking, leading to some misunderstandings in their interpretation. Recent advances in the comprehension of the underlying physiological mechanisms associated with different cerebral scales have provided researchers with an excellent scenario to develop sophisticated biophysical models that permit an integration of these neuroimage modalities...

Test-retest study of fMRI signal change evoked by electro-acupuncture stimulation

Kong, Jian; Gollub, Randy L; Webb, J. Megan; Kong, Jiang-Ti; Vangel, Mark G; Kwong, Kenneth
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.73%
Recent efforts to use fMRI to investigate the effects of acupuncture needle manipulation on the brain have yielded discrepant results. This study was designed to test the reliability of fMRI signal changes evoked by acupuncture stimulation. Six subjects participated in six identical scanning sessions consisting of four functional scans, one for each of the four conditions: electroacupuncture stimulation (2Hz) at GB 37, UB 60, non-acupoint (NP), and a control task of the finger-tapping. In the group analysis across all subjects and sessions, both the average ratings on a subjective acupuncture sensation scale and fMRI signal changes (increases and decreases) were similar for GB37, UB 60 and NP. Visual inspection of the activation maps from individual sessions and ICC analysis revealed that fMRI signal changes evoked by electroacupuncture stimulation were significantly more variable than those from the control finger-tapping task. The relatively large variability across different sessions within the same subject suggests multiple sessions should be used to accurately capture the activation patterns evoked by acupuncture stimulation at a particular point for a specific subject.

fMRI responses in medial frontal cortex that depend on the temporal frequency of visual input

Srinivasan, Ramesh; Fornari, Eleonora; Knyazeva, Maria G.; Meuli, Reto; Maeder, Philippe
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.73%
Functional networks in the human brain have been investigated using electrophysiological methods (EEG/MEG, LFP, and MUA) and steady-state paradigms that apply periodic luminance or contrast modulation to drive cortical networks. We have used this approach with fMRI to characterize a cortical network driven by a checkerboard reversing at a fixed frequency. We found that the fMRI signals in voxels located in occipital cortex were increased by checkerboard reversal at frequencies ranging from 3 to 14 Hz. In contrast, the response of a cluster of voxels centered on basal medial frontal cortex depended strongly on the reversal frequency, consistently exhibiting a peak in the response for specific reversal frequencies between 3 and 5 Hz in each subject. The fMRI signals at the frontal voxels were positively correlated indicating a homogeneous cluster. Some of the occipital voxels were positively correlated to the frontal voxels apparently forming a large-scale functional network. Other occipital voxels were negatively correlated to the frontal voxels, suggesting a functionally distinct network. The results provide preliminary fMRI evidence that during visual stimulation, input frequency can be varied to engage different functional networks.

How long to scan? The relationship between fMRI temporal signal to noise and necessary scan duration

Murphy, Kevin; Bodurka, Jerzy; Bandettini, Peter A.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.73%
Recent advances in MRI receiver and coil technologies have significantly improved image signal-to-noise ratios (SNR) and thus temporal SNR (TSNR). These gains in SNR and TSNR have allowed the detection of fMRI signal changes at higher spatial resolution and therefore have increased the potential to localize small brain structures such as cortical layers and columns. The majority of current fMRI processing strategies employ multi-subject averaging and therefore require spatial smoothing and normalization, effectively negating these gains in spatial resolution higher than about 10mm3. Reliable detection of activation in single subjects at high resolution is becoming a more common desire among fMRI researchers who are interested in comparing individuals rather than populations. Since TSNR decreases with voxel volume, detection of activation at higher resolutions requires longer scan durations. The relationship between TSNR, voxel volume and detectability is highly non-linear. In this study, the relationship between TSNR and the necessary fMRI scan duration required to obtain significant results at varying P values is determined both experimentally and theoretically. The results demonstrate that, with a TSNR of 50, detection of activation of above 2% requires at most 350 scan volumes (when steps are taken to remove the influence of physiological noise from the data). Importantly...

fMRI Brain-Computer Interface: A Tool for Neuroscientific Research and Treatment

Sitaram, Ranganatha; Caria, Andrea; Veit, Ralf; Gaber, Tilman; Rota, Giuseppina; Kuebler, Andrea; Birbaumer, Niels
Fonte: Hindawi Publishing Corporation Publicador: Hindawi Publishing Corporation
Tipo: Artigo de Revista Científica
Português
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26.73%
Brain-computer interfaces based on functional magnetic resonance imaging (fMRI-BCI) allow volitional control of anatomically specific regions of the brain. Technological advancement in higher field MRI scanners, fast data acquisition sequences, preprocessing algorithms, and robust statistical analysis are anticipated to make fMRI-BCI more widely available and applicable. This noninvasive technique could potentially complement the traditional neuroscientific experimental methods by varying the activity of the neural substrates of a region of interest as an independent variable to study its effects on behavior. If the neurobiological basis of a disorder (e.g., chronic pain, motor diseases, psychopathy, social phobia, depression) is known in terms of abnormal activity in certain regions of the brain, fMRI-BCI can be targeted to modify activity in those regions with high specificity for treatment. In this paper, we review recent results of the application of fMRI-BCI to neuroscientific research and psychophysiological treatment.

Origins of Spatial Working Memory Deficits in Schizophrenia: An Event-Related fMRI and Near-Infrared Spectroscopy Study

Lee, Junghee; Folley, Bradley S.; Gore, John; Park, Sohee
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 12/03/2008 Português
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26.73%
Abnormal prefrontal functioning plays a central role in the working memory (WM) deficits of schizophrenic patients, but the nature of the relationship between WM and prefrontal activation remains undetermined. Using two functional neuroimaging methods, we investigated the neural correlates of remembering and forgetting in schizophrenic and healthy participants. We focused on the brain activation during WM maintenance phase with event-related functional magnetic resonance imaging (fMRI). We also examined oxygenated hemoglobin changes in relation to memory performance with the near-infrared spectroscopy (NIRS) using the same spatial WM task. Distinct types of correct and error trials were segregated for analysis. fMRI data indicated that prefrontal activation was increased during WM maintenance on correct trials in both schizophrenic and healthy subjects. However, a significant difference was observed in the functional asymmetry of frontal activation pattern. Healthy subjects showed increased activation in the right frontal, temporal and cingulate regions. Schizophrenic patients showed greater activation compared with control subjects in left frontal, temporal and parietal regions as well as in right frontal regions. We also observed increased ‘false memory’ errors in schizophrenic patients...

Continuous ASL perfusion fMRI investigation of higher cognition: Quantification of tonic CBF changes during sustained attention and working memory tasks

Kim, Junghoon; Whyte, John; Wang, Jiongjiong; Rao, Hengyi; Tang, Kathy Z.; Detre, John A.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.73%
Arterial spin labeling (ASL) perfusion fMRI is an emerging method in clinical neuroimaging. Its non-invasiveness, absence of low frequency noise, and ability to quantify the absolute level of cerebral blood flow (CBF) make the method ideal for longitudinal designs or low frequency paradigms. Despite the usefulness in the study of cognitive dysfunctions in clinical populations, perfusion activation studies to date have been conducted for simple sensorimotor paradigms or with single-slice acquisition, mainly due to technical challenges. Using our recently developed amplitude-modulated continuous ASL (CASL) perfusion fMRI protocol, we assessed the feasibility of a higher level cognitive activation study in twelve healthy subjects. Taking advantage of the ASL noise properties, we were able to study tonic CBF changes during uninterrupted 6-min continuous performance of working memory and sustained attention tasks. For the visual sustained attention task, regional CBF increases (6-12 ml/100 g/min) were detected in the right middle frontal gyrus, the bilateral occipital gyri, and the anterior cingulate/medial frontal gyri. During the 2-back working memory task, significantly increased activations (7-11 ml/100 g/min) were found in the left inferior frontal/precentral gyri...

Automatic Independent Component Labeling for Artifact Removal in fMRI

Tohka, Jussi; Foerde, Karin; Aron, Adam R.; Tom, Sabrina M.; Toga, Arthur W.; Poldrack, Russell A.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.73%
Blood oxygenation level dependent (BOLD) signals in functional magnetic resonance imaging (fMRI) are often small compared to the level of noise in the data. The sources of noise are numerous including different kinds of motion artifacts and physiological noise with complex patterns. This complicates the statistical analysis of the fMRI data. In this study, we propose an automatic method to reduce fMRI artifacts based on independent component analysis (ICA). We trained a supervised classifier to distinguish between independent components relating to a potentially task related signal and independent components clearly relating to structured noise. After the components had been classified as either signal or noise, a denoised fMR timeseries was reconstructed based only on the independent components classified as potentially task related. The classifier was a novel global (fixed structure) decision tree trained in a Neyman-Pearson (NP) framework, which allowed the shape of the decision regions to be controlled effectively. Additionally, the conservativeness of the classifier could be tuned by modifying the NP threshold. The classifier was tested against the component classifications by an expert with the data from a category learning task. The test set as well as the expert were different from the data used for classifier training and the expert labeling the training set. The misclassification rate was between 0.2 and 0.3 for both the event related and blocked designs and it was consistent among variety of different NP thresholds. The effects of denoising on the group level statistical analyses were as expected: The denoising generally decreased Z-scores in the white matter...

Improved cortical-layer specificity of Vascular Space Occupancy fMRI with slab inversion relative to spin-echo BOLD at 9.4 T

Jin, Tao; Kim, Seong-Gi
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.73%
Cerebral blood volume (CBV)-weighted endogenous functional contrast can be obtained by the vascular space occupancy (VASO) technique. VASO relies on nonselective inversion for nulling blood signals, but the implementation of VASO at magnetic fields higher than 3 T is difficult due to similar T1 values of tissue and blood water and a stronger counteracting blood oxygen level-dependent (BOLD) effect. To improve functional CBV sensitivity, we proposed to use VASO with slab-selective inversion (SI-VASO). Computer simulations showed that the SI-VASO approach significantly increases functional sensitivity compared to the original VASO in a stronger magnetic field with a shorter repetition time. To examine layer-dependent specificity, SI-VASO and spin-echo BOLD (SE-BOLD) functional magnetic resonance imaging (fMRI) experiments were performed on isoflurane-anesthetized cats during visual stimulation at 9.4 T. Unlike simultaneously acquired SE-BOLD signal, the SI-VASO signal peaked at 0.9 mm from the surface of the cortex and was localized to the middle cortical layer. The full-width at half maximal response across the cortex was narrower for SI-VASO than for SE-BOLD (1.7 mm vs. 2.5 mm, respectively), suggesting that SI-VASO is better localized to neuronally active sites than SE-BOLD fMRI. The magnitude of the SI-VASO change in the middle cortex was −1.45% with our experimental parameters...

Effect of Retrieval Effort and Switching Demand on fMRI Activation During Semantic Word Generation in Schizophrenia

Ragland, JD; Moelter, ST; Bhati, MT; Valdez, JN; Kohler, CG; Siegel, SJ; Gur, RC; Gur, RE
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.73%
Verbal fluency deficits in schizophrenia are difficult to interpret because the tasks are multi-factorial and groups differ in total words generated. We manipulated retrieval and switching demands by requiring alternation between over-learned sequences in which retrieval is relatively automatic (OS) and semantic categories requiring increased retrieval effort (SC). Controlled processing was also manipulated by including switching and non-switching conditions, and formal thought disorder (FTD) was assessed with the communication disorders index (CDI). The OS/SC semantic fluency paradigm was administered during fMRI to 13 patients with schizophrenia and 14 matched controls. Images were acquired on a 3 Tesla Siemens scanner using compressed image acquisition to allow for cued overt word production. Subjects alternated between OS, SC, OS-switch, SC-switch, and baseline blocks. Images were pre-processed in SPM-2, and a two-stage random effects analysis tested within and between group contrasts. There were no group performance differences. fMRI analysis did not reveal any group differences during the OS non-switching condition. Both groups produced expected activation in bilateral prefrontal and inferior parietal regions. However, during the SC condition patients had greater activation than controls in left prefrontal...

Evidence for a vascular contribution to diffusion FMRI at high b value

Miller, Karla L.; Bulte, Daniel P.; Devlin, Hannah; Robson, Matthew D.; Wise, Richard G.; Woolrich, Mark W.; Jezzard, Peter; Behrens, Timothy E. J.
Fonte: National Academy of Sciences Publicador: National Academy of Sciences
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.73%
Recent work has suggested that diffusion-weighted functional magnetic resonance imaging (FMRI) with strong diffusion weighting (high b value) detects neuronal swelling that is directly related to neuronal firing. This would constitute a much more direct measure of brain activity than current methods and represent a major advance in neuroimaging. However, it has not been firmly established that the observed signal changes do not reflect residual vascular effects, which are known to exist at low b value. This study measures the vascular component of diffusion FMRI directly by using hypercapnia, which induces blood flow changes in the absence of a change in neuronal firing. Hypercapnia elicits a similar diffusion FMRI response to a visual stimulus including a rise in percent signal change with increasing b value, which was reported for visual activation. Analysis of the response timing found no evidence for an early response at high b value, which has been reported as evidence for a nonhemodynamic response. These results suggest that a large component of the diffusion FMRI signal at high b value is vascular rather than neuronal.

High Spatial Resolution Increases the Specificity of Block-Design BOLD fMRI Studies of Overt Vowel Production

Soltysik, David A.; Hyde, James S.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.73%
Functional MRI (fMRI) studies of tasks involving orofacial motion, such as speech, are prone to problems related to motion-induced magnetic field variations. Orofacial motion perturbs the static magnetic field, leading to signal changes that correlate with the task and corrupt activation maps with false positives or signal loss. These motion-induced signal changes represent a contraindication for the implementation of fMRI to study the neurophysiology of orofacial motion. An fMRI experiment of a structured, non-semantic vowel production task was performed using four different voxel volumes and three different slice orientations in an attempt to find a set of acquisition parameters leading to activation maps with maximum specificity. Results indicate that the use of small voxel volumes (2×2×3 mm3) yielded a significantly higher percentage of true positive activation compared to the use of larger voxel volumes. Slice orientation did not have as great an impact as spatial resolution, although coronal slices appeared superior at high spatial resolutions. Furthermore, it was found that combining the strategy of high spatial resolution with an optimum task duration and post-processing methods for separating true and false positives greatly improved the specificity of single-subject...

Pictures of a thousand words: Investigating the neural mechanisms of reading with extremely rapid event-related fMRI

Yarkoni, Tal; Speer, Nicole K.; Balota, David A.; McAvoy, Mark P.; Zacks, Jeffrey M.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
26.73%
Reading is one of the most important skills human beings can acquire, but has proven difficult to study naturalistically using functional magnetic resonance imaging (fMRI). We introduce a novel Event-Related Reading (ERR) fMRI approach that enables reliable estimation of the neural correlates of single-word processing during reading of rapidly presented narrative text (200–300 ms / word). Application to an fMRI experiment in which subjects read coherent narratives and made no overt responses revealed widespread effects of orthographic, phonological, contextual, and semantic variables on brain activation. Word-level variables predicted activity in classical language areas as well as the inferotemporal visual word form area, specifically supporting a role for the latter in mapping visual forms onto articulatory or acoustic representations. Additional analyses demonstrated that ERR results replicate across experiments and predict reading comprehension. The ERR approach represents a powerful and extremely flexible new approach for studying reading and language behavior with fMRI.

Partner-Matching for the Automated Identification of Reproducible ICA Components from fMRI Datasets: Algorithm and Validation

Wang, Zhishun; Peterson, Bradley S.
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em /08/2008 Português
Relevância na Pesquisa
26.73%
The analysis of functional magnetic resonance imaging (fMRI) data is complicated by the presence of a mixture of many sources of signal and noise. Independent component analysis (ICA) can separate these mixtures into independent components, each of which contains maximal information from a single, independent source of signal, whether from noise or from a discrete physiological or neural system. ICA typically generates a large number of components for each subject imaged, however, and therefore it generates a vast number of components across all of the subjects imaged in an fMRI dataset. The practical implementation of ICA has been limited by the difficulty in discerning which of these many components are spurious and which are reproducible, either within or across individuals of the dataset. We have developed a novel clustering algorithm, termed “Partner-Matching” (PM), which identifies automatically the independent components that are reproducible either within or between subjects. It identifies those components by clustering them according to robust measures of similarity in their spatial configurations either across different subjects of an fMRI dataset, within a single subject scanned across multiple scanning sessions, or within an individual subject scanned across multiple runs within a single scanning session. We demonstrate the face validity of our algorithm by applying it to the analysis of three fMRI datasets acquired in 13 healthy adults performing simple auditory...