Detection of cortical activation during averaged single trials of a cognitive task using functional magnetic resonance imaging

Functional neuroimaging studies in human subjects using positron emission tomography or functional magnetic resonance imaging (fMRI) are typically conducted by collecting data over extended time periods that contain many similar trials of a task. Here methods for acquiring fMRI data from single trials of a cognitive task are reported. In experiment one, whole brain fMRI was used to reliably detect single-trial responses in a prefrontal region within single subjects. In experiment two, higher temporal sampling of a more limited spatial field was used to measure temporal offsets between regions. Activation maps produced solely from the single-trial data were comparable to those produced from blocked runs. These findings suggest that single-trial paradigms will be able to exploit the high temporal resolution of fMRI. Such paradigms will provide experimental flexibility and time-resolved data for individual brain regions on a trial-by-trial basis.

Principal component analysis and assessment of language network activation patterns in pediatric epilepsy

This dissertation establishes a novel data-driven method to identify language network activation patterns in pediatric epilepsy through the use of the Principal Component Analysis (PCA) on functional magnetic resonance imaging (fMRI). A total of 122 subjects’ data sets from five different hospitals were included in the study through a web-based repository site designed here at FIU. Research was conducted to evaluate different classification and clustering techniques in identifying hidden activation patterns and their associations with meaningful clinical variables. The results were assessed through agreement analysis with the conventional methods of lateralization index (LI) and visual rating. What is unique in this approach is the new mechanism designed for projecting language network patterns in the PCA-based decisional space. Synthetic activation maps were randomly generated from real data sets to uniquely establish nonlinear decision functions (NDF) which are then used to classify any new fMRI activation map into typical or atypical. The best nonlinear classifier was obtained on a 4D space with a complexity (nonlinearity) degree of 7. Based on the significant association of language dominance and intensities with the top eigenvectors of the PCA decisional space, a new algorithm was deployed to delineate primary cluster members without intensity normalization. In this case, three distinct activations patterns (groups) were identified (averaged kappa with rating 0.65, with LI 0.76) and were characterized by the regions of: (1) the left inferior frontal Gyrus (IFG) and left superior temporal gyrus (STG), considered typical for the language task; (2) the IFG, left mesial frontal lobe, right cerebellum regions, representing a variant left dominant pattern by higher activation; and (3) the right homologues of the first pattern in Broca's and Wernicke's language areas. Interestingly, group 2 was found to reflect a different language compensation mechanism than reorganization. Its high intensity activation suggests a possible remote effect on the right hemisphere focus on traditionally left-lateralized functions. In retrospect, this data-driven method provides new insights into mechanisms for brain compensation/reorganization and neural plasticity in pediatric epilepsy.

Principal Component Analysis and Assessment of Language Network Activation Patterns in Pediatric Epilepsy

This dissertation establishes a novel data-driven method to identify language network activation patterns in pediatric epilepsy through the use of the Principal Component Analysis (PCA) on functional magnetic resonance imaging (fMRI). A total of 122 subjects’ data sets from five different hospitals were included in the study through a web-based repository site designed here at FIU. Research was conducted to evaluate different classification and clustering techniques in identifying hidden activation patterns and their associations with meaningful clinical variables. The results were assessed through agreement analysis with the conventional methods of lateralization index (LI) and visual rating. What is unique in this approach is the new mechanism designed for projecting language network patterns in the PCA-based decisional space. Synthetic activation maps were randomly generated from real data sets to uniquely establish nonlinear decision functions (NDF) which are then used to classify any new fMRI activation map into typical or atypical. The best nonlinear classifier was obtained on a 4D space with a complexity (nonlinearity) degree of 7. Based on the significant association of language dominance and intensities with the top eigenvectors of the PCA decisional space, a new algorithm was deployed to delineate primary cluster members without intensity normalization. In this case, three distinct activations patterns (groups) were identified (averaged kappa with rating 0.65, with LI 0.76) and were characterized by the regions of: 1) the left inferior frontal Gyrus (IFG) and left superior temporal gyrus (STG), considered typical for the language task; 2) the IFG, left mesial frontal lobe, right cerebellum regions, representing a variant left dominant pattern by higher activation; and 3) the right homologues of the first pattern in Broca's and Wernicke's language areas. Interestingly, group 2 was found to reflect a different language compensation mechanism than reorganization. Its high intensity activation suggests a possible remote effect on the right hemisphere focus on traditionally left-lateralized functions. In retrospect, this data-driven method provides new insights into mechanisms for brain compensation/reorganization and neural plasticity in pediatric epilepsy.

Cognitive control associated with irritability induction: an autobiographical recall fMRI study

OBJECTIVE: Despite the relevance of irritability emotions to the treatment, prognosis and classification of psychiatric disorders, the neurobiological basis of this emotional state has been rarely investigated to date. We assessed the brain circuitry underlying personal script-driven irritability in healthy subjects (n = 11) using functional magnetic resonance imaging. METHOD: Blood oxygen level-dependent signal changes were recorded during auditory presentation of personal scripts of irritability in contrast to scripts of happiness or neutral emotional content. Self-rated emotional measurements and skin conductance recordings were also obtained. Images were acquired using a 1,5T magnetic resonance scanner. Brain activation maps were constructed from individual images, and between-condition differences in the mean power of experimental response were identified by using cluster-wise nonparametric tests. RESULTS: Compared to neutral scripts, increased blood oxygen level-dependent signal during irritability scripts was detected in the left subgenual anterior cingulate cortex, and in the left medial, anterolateral and posterolateral dorsal prefrontal cortex (cluster-wise p-value < 0.05). While the involvement of the subgenual cingulate and dorsal anterolateral prefrontal cortices was unique to the irritability state, increased blood oxygen level-dependent signal in dorsomedial and dorsal posterolateral prefrontal regions were also present during happiness induction. CONCLUSION: Irritability induction is associated with functional changes in a limited set of brain regions previously implicated in the mediation of emotional states. Changes in prefrontal and cingulate areas may be related to effortful cognitive control aspects that gain salience during the emergence of irritability.

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

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.

The impact of functional connectivity changes on support vector machines mapping of fMRI data

Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.

Comparison of epicardial mapping and noncontact endocardial mapping in dog experiments and computer simulations

La fibrillation auriculaire, l'arythmie la plus fréquente en clinique, affecte 2.3 millions de patients en Amérique du Nord. Pour en étudier les mécanismes et les thérapies potentielles, des modèles animaux de fibrillation auriculaire ont été développés. La cartographie électrique épicardique à haute densité est une technique expérimentale bien établie pour suivre in vivo l'activité des oreillettes en réponse à une stimulation électrique, à du remodelage, à des arythmies ou à une modulation du système nerveux autonome. Dans les régions qui ne sont pas accessibles par cartographie épicardique, la cartographie endocardique sans contact réalisée à l'aide d'un cathéter en forme de ballon pourrait apporter une description plus complète de l'activité auriculaire. Dans cette étude, une expérience chez le chien a été conçue et analysée. Une reconstruction électro-anatomique, une cartographie épicardique (103 électrodes), une cartographie endocardique sans contact (2048 électrodes virtuelles calculées à partir un cathéter en forme de ballon avec 64 canaux) et des enregistrements endocardiques avec contact direct ont été réalisés simultanément. Les systèmes d'enregistrement ont été également simulés dans un modèle mathématique d'une oreillette droite de chien. Dans les simulations et les expériences (après la suppression du nœud atrio-ventriculaire), des cartes d'activation ont été calculées pendant le rythme sinusal. La repolarisation a été évaluée en mesurant l'aire sous l'onde T auriculaire (ATa) qui est un marqueur de gradient de repolarisation. Les résultats montrent un coefficient de corrélation épicardique-endocardique de 0.8 (expérience) and 0.96 (simulation) entre les cartes d'activation, et un coefficient de corrélation de 0.57 (expérience) and 0.92 (simulation) entre les valeurs de ATa. La cartographie endocardique sans contact apparait comme un instrument expérimental utile pour extraire de l'information en dehors des régions couvertes par les plaques d'enregistrement épicardique.

How does spatial extent of fMRI datasets affect independent component analysis decomposition?

Spatial independent component analysis (sICA) of functional magnetic resonance imaging (fMRI) time series can generate meaningful activation maps and associated descriptive signals, which are useful to evaluate datasets of the entire brain or selected portions of it. Besides computational implications, variations in the input dataset combined with the multivariate nature of ICA may lead to different spatial or temporal readouts of brain activation phenomena. By reducing and increasing a volume of interest (VOI), we applied sICA to different datasets from real activation experiments with multislice acquisition and single or multiple sensory-motor task-induced blood oxygenation level-dependent (BOLD) signal sources with different spatial and temporal structure. Using receiver operating characteristics (ROC) methodology for accuracy evaluation and multiple regression analysis as benchmark, we compared sICA decompositions of reduced and increased VOI fMRI time-series containing auditory, motor and hemifield visual activation occurring separately or simultaneously in time. Both approaches yielded valid results; however, the results of the increased VOI approach were spatially more accurate compared to the results of the decreased VOI approach. This is consistent with the capability of sICA to take advantage of extended samples of statistical observations and suggests that sICA is more powerful with extended rather than reduced VOI datasets to delineate brain activity.

Avaliação de linguagem por ressonância magnética funcional em pacientes com epilepsia associada à esclerose mesial temporal unilateral: correlação com avaliação clínica de linguagem

Introdução: A esclerose mesial temporal (EMT) é a principal causa de epilepsia resistente ao tratamento medicamentoso. Pacientes com EMT apresentam dificuldades no processamento semântico e fonológico de linguagem e maior incidência de reorganização cerebral da linguagem (bilateral ou à direita) em relação à população geral. A ressonância magnética funcional (RMf) permite avaliar a reorganização cerebral das redes de linguagem, comparando padrões de ativação cerebral entre diversas regiões cerebrais. Objetivo: Investigar o desempenho linguístico de pacientes com EMT unilateral esquerda e direita e a ocorrência de reorganização das redes de linguagem com RMf para avaliar se a reorganização foi benéfica para a linguagem nestes pacientes. Métodos: Utilizamos provas clínicas de linguagem e paradigmas de nomeação visual e responsiva para RMf, desenvolvidos para este estudo. Foram avaliados 24 pacientes com EMTe, 22 pacientes com EMTd e 24 controles saudáveis, submetidos a provas de linguagem (fluência semântica e fonológica, nomeação de objetos, verbos, nomes próprios e responsiva, e compreensão de palavras) e a três paradigmas de linguagem por RMf [nomeação por confrontação visual (NCV), nomeação responsiva à leitura (NRL) e geração de palavras (GP)]. Seis regiões cerebrais de interesse (ROI) foram selecionadas (giro frontal inferior, giro frontal médio, giro frontal superior, giro temporal inferior, giro temporal médio e giro temporal superior). Índices de Lateralidade (ILs) foram calculados com dois métodos: bootstrap, do programa LI-Toolbox, independe de limiar, e PSC, que indica a intensidade da ativação cerebral de cada voxel. Cada grupo de pacientes (EMTe e EMTd) foi dividido em dois subgrupos, de acordo com o desempenho em relação aos controles na avaliação clinica de linguagem. O <= -1,5 foi utilizado como nota de corte para dividir os grupos em pacientes com bom e com mau desempenho de linguagem. Em seguida, comparou-se o desempenho linguístico dos subgrupos ao índices IL-boot. Resultados: Pacientes com EMT esquerda e direita mostraram pior desempenho que controles nas provas clínicas de nomeação de verbos, nomeação de nomes próprios, nomeação responsiva e fluência verbal. Os mapas de ativação cerebral por RMf mostraram efeito BOLD em regiões frontais e temporoparietais de linguagem. Os mapas de comparação de ativação cerebral entre os grupos revelaram que pacientes com EMT esquerda e direita apresentam maior ativação em regiões homólogas do hemisfério direito em relação aos controles. Os ILs corroboraram estes resultados, mostrando valores médios menores para os pacientes em relação aos controles e, portanto, maior simetria na representação da linguagem. A comparação entre o IL-boot e o desempenho nas provas clínicas de linguagem indicou que, no paradigma de nomeação responsiva à leitura, a reorganização funcional no giro temporal médio, e possivelmente, nos giros temporal inferior e superior associou-se a desempenho preservado em provas de nomeação. Conclusão: Pacientes com EMT direita e esquerda apresentam comprometimento de nomeação e fluência verbal e reorganização da rede cerebral de linguagem. A reorganização funcional de linguagem em regiões temporais, especialmente o giro temporal médio associou-se a desempenho preservado em provas de nomeação em pacientes com EMT esquerda no paradigma de RMf de nomeação responsiva à leitura

A novel method for studying the cortical processing of human swallowing using Synthetic Aperture Magnetometry(SAM)

Background/Aims: Positron emission tomography has been applied to study cortical activation during human swallowing, but employs radio-isotopes precluding repeated experiments and has to be performed supine, making the task of swallowing difficult. Here we now describe Synthetic Aperture Magnetometry (SAM) as a novel method of localising and imaging the brain's neuronal activity from magnetoencephalographic (MEG) signals to study the cortical processing of human volitional swallowing in the more physiological prone position. Methods: In 3 healthy male volunteers (age 28–36), 151-channel whole cortex MEG (Omega-151, CTF Systems Inc.) was recorded whilst seated during the conditions of repeated volitional wet swallowing (5mls boluses at 0.2Hz) or rest. SAM analysis was then performed using varying spatial filters (5–60Hz) before co-registration with individual MRI brain images. Activation areas were then identified using standard sterotactic space neuro-anatomical maps. In one subject repeat studies were performed to confirm the initial study findings. Results: In all subjects, cortical activation maps for swallowing could be generated using SAM, the strongest activations being seen with 10–20Hz filter settings. The main cortical activations associated with swallowing were in: sensorimotor cortex (BA 3,4), insular cortex and lateral premotor cortex (BA 6,8). Of relevance, each cortical region displayed consistent inter-hemispheric asymmetry, to one or other hemisphere, this being different for each region and for each subject. Intra-subject comparisons of activation localisation and asymmetry showed impressive reproducibility. Conclusion: SAM analysis using MEG is an accurate, repeatable, and reproducible method for studying the brain processing of human swallowing in a more physiological manner and provides novel opportunities for future studies of the brain-gut axis in health and disease.

Design and implementation of a multisite data repository for pediatric epilepsy

This dissertation established a software-hardware integrated design for a multisite data repository in pediatric epilepsy. A total of 16 institutions formed a consortium for this web-based application. This innovative fully operational web application allows users to upload and retrieve information through a unique human-computer graphical interface that is remotely accessible to all users of the consortium. A solution based on a Linux platform with My-SQL and Personal Home Page scripts (PHP) has been selected. Research was conducted to evaluate mechanisms to electronically transfer diverse datasets from different hospitals and collect the clinical data in concert with their related functional magnetic resonance imaging (fMRI). What was unique in the approach considered is that all pertinent clinical information about patients is synthesized with input from clinical experts into 4 different forms, which were: Clinical, fMRI scoring, Image information, and Neuropsychological data entry forms. A first contribution of this dissertation was in proposing an integrated processing platform that was site and scanner independent in order to uniformly process the varied fMRI datasets and to generate comparative brain activation patterns. The data collection from the consortium complied with the IRB requirements and provides all the safeguards for security and confidentiality requirements. An 1-MR1-based software library was used to perform data processing and statistical analysis to obtain the brain activation maps. Lateralization Index (LI) of healthy control (HC) subjects in contrast to localization-related epilepsy (LRE) subjects were evaluated. Over 110 activation maps were generated, and their respective LIs were computed yielding the following groups: (a) strong right lateralization: (HC=0%, LRE=18%), (b) right lateralization: (HC=2%, LRE=10%), (c) bilateral: (HC=20%, LRE=15%), (d) left lateralization: (HC=42%, LRE=26%), e) strong left lateralization: (HC=36%, LRE=31%). Moreover, nonlinear-multidimensional decision functions were used to seek an optimal separation between typical and atypical brain activations on the basis of the demographics as well as the extent and intensity of these brain activations. The intent was not to seek the highest output measures given the inherent overlap of the data, but rather to assess which of the many dimensions were critical in the overall assessment of typical and atypical language activations with the freedom to select any number of dimensions and impose any degree of complexity in the nonlinearity of the decision space.

Comparison of Methods and Co-Registration Maps of EEG and fMRI in Occipital Lobe Epilepsy

Clinically childhood occipital lobe epilepsy (OLE) manifests itself with distinct syndromes. The traditional EEG recordings have not been able to overcome the difficulty in correlating the ictal clinical symptoms to the onset in particular areas of the occipital lobes. To understand these syndromes it is important to map with more precision the epileptogenic cortical regions in OLE. Experimentally, we studied three idiopathic childhood OLE patients with EEG source analysis and with the simultaneous acquisition of EEG and fMRI, to map the BOLD effect associated with EEG spikes. The spatial overlap between the EEG and BOLD results was not very good, but the fMRI suggested localizations more consistent with the ictal clinical manifestations of each type of epileptic syndrome. Since our first results show that by associating the BOLD effect with interictal spikes the epileptogenic areas are mapped to localizations different from those calculated from EEG sources and that by using different EEG/fMRI processing methods our results differ to some extent, it is very important to compare the different methods of processing the localization of activation and develop a good methodology for obtaining co-registration maps of high resolution EEG with BOLD localizations.

Abnormal cortical network activation in human amnesia: A high-resolution evoked potential study.

Little is known about how human amnesia affects the activation of cortical networks during memory processing. In this study, we recorded high-density evoked potentials in 12 healthy control subjects and 11 amnesic patients with various types of brain damage affecting the medial temporal lobes, diencephalic structures, or both. Subjects performed a continuous recognition task composed of meaningful designs. Using whole-scalp spatiotemporal mapping techniques, we found that, during the first 200 ms following picture presentation, map configuration of amnesics and controls were indistinguishable. Beyond this period, processing significantly differed. Between 200 and 350 ms, amnesic patients expressed different topographical maps than controls in response to new and repeated pictures. From 350 to 550 ms, healthy subjects showed modulation of the same maps in response to new and repeated items. In amnesics, by contrast, presentation of repeated items induced different maps, indicating distinct cortical processing of new and old information. The study indicates that cortical mechanisms underlying memory formation and re-activation in amnesia fundamentally differ from normal memory processing.

RNA polymerase subunit RPB5 plays a role in transcriptional activation

A mutation in RPB5 (rpb5–9), an essential RNA polymerase subunit assembled into RNA polymerases I, II, and III, revealed a role for this subunit in transcriptional activation. Activation by GAL4-VP16 was impaired upon in vitro transcription with mutant whole-cell extracts. In vivo experiments using inducible reporter plasmids and Northern analysis support the in vitro data and demonstrate that RPB5 influences activation at some, but not all, promoters. Remarkably, this mutation maps to a conserved region of human RPB5 implicated by others to play a role in activation. Chimeric human-yeast RPB5 containing this conserved region now can function in place of its yeast counterpart. The defects noted with rpb5–9 are similar to those seen in truncation mutants of the RPB1-carboxyl terminal domain (CTD). We demonstrate that RPB5 and the RPB1-CTD have overlapping roles in activation because the double mutant is synthetically lethal and has exacerbated activation defects at the GAL1/10 promoter. These studies demonstrate that there are multiple activation targets in RNA polymerase II and that RPB5 and the CTD have similar roles in activation.

The influence of interhemispheric connections on ongoing and evoked orientation preference maps and spiking activity in the cat primary visual cortex

In the primary visual cortex, neurons with similar physiological features are clustered together in columns extending through all six cortical layers. These columns form modular orientation preference maps. Long-range lateral fibers are associated to the structure of orientation maps since they do not connect columns randomly; they rather cluster in regular intervals and interconnect predominantly columns of neurons responding to similar stimulus features. Single orientation preference maps – the joint activation of domains preferring the same orientation - were observed to emerge spontaneously and it was speculated whether this structured ongoing activation could be caused by the underlying patchy lateral connectivity. Since long-range lateral connections share many features, i.e. clustering, orientation selectivity, with visual inter-hemispheric connections (VIC) through the corpus callosum we used the latter as a model for long-range lateral connectivity. In order to address the question of how the lateral connectivity contributes to spontaneously generated maps of one hemisphere we investigated how these maps react to the deactivation of VICs originating from the contralateral hemisphere. To this end, we performed experiments in eight adult cats. We recorded voltage-sensitive dye (VSD) imaging and electrophysiological spiking activity in one brain hemisphere while reversible deactivating the other hemisphere with a cooling technique. In order to compare ongoing activity with evoked activity patterns we first presented oriented gratings as visual stimuli. Gratings had 8 different orientations distributed equally between 0º and 180º. VSD imaged frames obtained during ongoing activity conditions were then compared to the averaged evoked single orientation maps in three different states: baseline, cooling and recovery. Kohonen self-organizing maps were also used as a means of analysis without prior assumption (like the averaged single condition maps) on ongoing activity. We also evaluated if cooling had a differential effect on evoked and ongoing spiking activity of single units. We found that deactivating VICs caused no spatial disruption on the structure of either evoked or ongoing activity maps. The frequency with which a cardinally preferring (0º or 90º) map would emerge, however, decreased significantly for ongoing but not for evoked activity. The same result was found by training self-organizing maps with recorded data as input. Spiking activity of cardinally preferring units also decreased significantly for ongoing when compared to evoked activity. Based on our results we came to the following conclusions: 1) VICs are not a determinant factor of ongoing map structure. Maps continued to be spontaneously generated with the same quality, probably by a combination of ongoing activity from local recurrent connections, thalamocortical loop and feedback connections. 2) VICs account for a cardinal bias in the temporal sequence of ongoing activity patterns, i.e. deactivating VIC decreases the probability of cardinal maps to emerge spontaneously. 3) Inter- and intrahemispheric long-range connections might serve as a grid preparing primary visual cortex for likely junctions in a larger visual environment encompassing the two hemifields.