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

Depression in Parkinson`s disease: Convergence from voxel-based morphometry and functional magnetic resonance imaging in the limbic thalamus

Depression is the most frequent psychiatric disorder in Parkinson`s disease (PD). Although evidence Suggests that depression in PD is related to the degenerative process that underlies the disease, further studies are necessary to better understand the neural basis of depression in this population of patients. In order to investigate neuronal alterations underlying the depression in PD, we studied thirty-six patients with idiopathic PD. Twenty of these patients had the diagnosis of major depression disorder and sixteen did not. The two groups were matched for PD motor severity according to Unified Parkinson Disease Rating Scale (UPDRS). First we conducted a functional magnetic resonance imaging (fMRI) using an event-related parametric emotional perception paradigm with test retest design. Our results showed decreased activation in the left mediodorsal (MD) thalamus and in medial prefrontall cortex in PD patients with depression compared to those without depression. Based upon these results and the increased neuron count in MD thalamus found in previous studies, we conducted a region of interest (ROI) guided voxel-based morphometry (VBM) study comparing the thalamic volume. Our results showed an increased volume in mediodorsal thalamic nuclei bilaterally. Converging morphological changes and functional emotional processing in mediodorsal thalamus highlight the importance of limbic thalamus in PD depression. In addition this data supports the link between neurodegenerative alterations and mood regulation. (C) 2009 Elsevier Inc. All rights reserved.

Are glutamate and lactate increases ubiquitous to physiological activation? A (1)H functional MR spectroscopy study during motor activation in human brain at 7Tesla.

Recent studies at high field (7Tesla) have reported small metabolite changes, in particular lactate and glutamate (below 0.3μmol/g) during visual stimulation. These studies have been limited to the visual cortex because of its high energy metabolism and good magnetic resonance spectroscopy (MRS) sensitivity using surface coil. The aim of this study was to extend functional MRS (fMRS) to investigate for the first time the metabolite changes during motor activation at 7T. Small but sustained increases in lactate (0.17μmol/g±0.05μmol/g, p<0.001) and glutamate (0.17μmol/g±0.09μmol/g, p<0.005) were detected during motor activation followed by a return to the baseline after the end of activation. The present study demonstrates that increases in lactate and glutamate during motor stimulation are small, but similar to those observed during visual stimulation. From the observed glutamate and lactate increase, we inferred that these metabolite changes may be a general manifestation of the increased neuronal activity. In addition, we propose that the measured metabolite concentration increases imply an increase in ΔCMRO2 that is transiently below that of ΔCMRGlc during the first 1 to 2min of the stimulation.

Confirmation of functional zones within the human subthalamic nucleus: patterns of connectivity and sub-parcellation using diffusion weighted imaging.

The subthalamic nucleus (STN) is a small, glutamatergic nucleus situated in the diencephalon. A critical component of normal motor function, it has become a key target for deep brain stimulation in the treatment of Parkinson's disease. Animal studies have demonstrated the existence of three functional sub-zones but these have never been shown conclusively in humans. In this work, a data driven method with diffusion weighted imaging demonstrated that three distinct clusters exist within the human STN based on brain connectivity profiles. The STN was successfully sub-parcellated into these regions, demonstrating good correspondence with that described in the animal literature. The local connectivity of each sub-region supported the hypothesis of bilateral limbic, associative and motor regions occupying the anterior, mid and posterior portions of the nucleus respectively. This study is the first to achieve in-vivo, non-invasive anatomical parcellation of the human STN into three anatomical zones within normal diagnostic scan times, which has important future implications for deep brain stimulation surgery.

Principal components of functional connectivity: A new approach to study dynamic brain connectivity during rest.

Functional connectivity (FC) as measured by correlation between fMRI BOLD time courses of distinct brain regions has revealed meaningful organization of spontaneous fluctuations in the resting brain. However, an increasing amount of evidence points to non-stationarity of FC; i.e., FC dynamically changes over time reflecting additional and rich information about brain organization, but representing new challenges for analysis and interpretation. Here, we propose a data-driven approach based on principal component analysis (PCA) to reveal hidden patterns of coherent FC dynamics across multiple subjects. We demonstrate the feasibility and relevance of this new approach by examining the differences in dynamic FC between 13 healthy control subjects and 15 minimally disabled relapse-remitting multiple sclerosis patients. We estimated whole-brain dynamic FC of regionally-averaged BOLD activity using sliding time windows. We then used PCA to identify FC patterns, termed "eigenconnectivities", that reflect meaningful patterns in FC fluctuations. We then assessed the contributions of these patterns to the dynamic FC at any given time point and identified a network of connections centered on the default-mode network with altered contribution in patients. Our results complement traditional stationary analyses, and reveal novel insights into brain connectivity dynamics and their modulation in a neurodegenerative disease.

Asymmetry of Functional Connectivity in Schizophrenia at Different Spatial Scales

Introduction: The interhemispheric asymmetries that originate from connectivity-related structuring of the cerebral cortex are compromised in schizophrenia (SZ). Recently, we have revealed the whole-head topography of EEG synchronization in SZ (Jalili et al. 2007; Knyazeva et al. 2008). Here we extended the analysis to assess the abnormality in the asymmetry of synchronization, which is further motivated by the evidence that the interhemispheric asymmetries suspected to be abnormal in SZ originate from the connectivity-related structuring of the cortex. Methods: Thirteen right-handed SZ patients and thirteen matched controls, participated in this study and the multichannel (128) EEGs were recorded for 3-5 minutes at rest. Then, Laplacian EEG (LEEG) were calculated using a 2-D spline. The LEEGs were analysis through calculating the power spectral density using Welch's average periodogram method. Furthermore, using a state-space based multivariate synchronization measure, S-estimator, we analyzed the correlate of the functional cortico-cortical connectivity in SZ patients compared to the controls. The values of S-estimator were obtained at three different special scales: first-order neighbors for each sensor location, second-order neighbors, and the whole hemisphere. The synchronization measures based on LEEG of alpha and beta bands were applied and tuned to various spatial scales including local, intraregional, and long-distance levels. To assess the between-group differences, we used a permutation version of Hotelling's T2 test. For correlation analysis, Spearman Rank Correlation was calculated. Results: Compared to the controls, who had rightward asymmetry at a local level (LEEG power), rightward anterior and leftward posterior asymmetries at an intraregional level (first- and second-order S-estimator), and rightward global asymmetry (hemispheric S-estimator), SZ patients showed generally attenuated asymmetry, the effect being strongest for intraregional synchronization. This deviation in asymmetry across the anterior-to-posterior axis is consistent with the cerebral form of the so-called Yakovlevian or anticlockwise cerebral torque. Moreover, the negative occipital and positive frontal asymmetry values suggest higher regional synchronization among the left occipital and the right frontal locations relative to their symmetrical counterparts. Correlation analysis linked the posterior intraregional and hemispheric abnormalities to the negative SZ symptoms, whereas the asymmetry of LEEG power appeared to be weakly coupled to clinical ratings. The posterior intraregional abnormalities of asymmetry were shown to increase with the duration of the disease. The tentative links between these findings and gross anatomical asymmetries, including the cerebral torque and gyrification pattern in normal subjects and SZ patients, are discussed. Conclusions: Overall, our findings reveal the abnormalities in the synchronization asymmetry in SZ patients and heavy involvement of the right hemisphere in these abnormalities. These results indicate that anomalous asymmetry of cortico-cortical connections in schizophrenia is amenable to electrophysiological analysis.

Regional reproducibility of calibrated BOLD functional MRI: implications for the study of cognition and plasticity.

Calibrated BOLD fMRI is a promising alternative to the classic BOLD contrast due to its reduced venous sensitivity and greater physiological specificity. The delayed adoption of this technique for cognitive studies may stem partly from a lack of information on the reproducibility of these measures in the context of cognitive tasks. In this study we have explored the applicability and reproducibility of a state-of-the-art calibrated BOLD technique using a complex functional task at 7 tesla. Reproducibility measures of BOLD, CBF, CMRO2 flow-metabolism coupling n and the calibration parameter M were compared and interpreted for three ROIs. We found an averaged intra-subject variation of CMRO2 of 8% across runs and 33% across days. BOLD (46% across runs, 36% across days), CBF (33% across runs, 46% across days) and M (41% across days) showed significantly higher intra-subject variability. Inter-subject variability was found to be high for all quantities, though CMRO2 was the most consistent across brain regions. The results of this study provide evidence that calibrated BOLD may be a viable alternative for longitudinal and cognitive MRI studies.

Alpha-band suppression in the visual word form area as a functional bottleneck to consciousness.

The current state of empirical investigations refers to consciousness as an all-or-none phenomenon. However, a recent theoretical account opens up this perspective by proposing a partial level (between nil and full) of conscious perception. In the well-studied case of single-word reading, short-lived exposure can trigger incomplete word-form recognition wherein letters fall short of forming a whole word in one's conscious perception thereby hindering word-meaning access and report. Hence, the processing from incomplete to complete word-form recognition straightforwardly mirrors a transition from partial to full-blown consciousness. We therefore hypothesized that this putative functional bottleneck to consciousness (i.e. the perceptual boundary between partial and full conscious perception) would emerge at a major key hub region for word-form recognition during reading, namely the left occipito-temporal junction. We applied a real-time staircase procedure and titrated subjective reports at the threshold between partial (letters) and full (whole word) conscious perception. This experimental approach allowed us to collect trials with identical physical stimulation, yet reflecting distinct perceptual experience levels. Oscillatory brain activity was monitored with magnetoencephalography and revealed that the transition from partial-to-full word-form perception was accompanied by alpha-band (7-11 Hz) power suppression in the posterior left occipito-temporal cortex. This modulation of rhythmic activity extended anteriorly towards the visual word form area (VWFA), a region whose selectivity for word-forms in perception is highly debated. The current findings provide electrophysiological evidence for a functional bottleneck to consciousness thereby empirically instantiating a recently proposed partial perspective on consciousness. Moreover, the findings provide an entirely new outlook on the functioning of the VWFA as a late bottleneck to full-blown conscious word-form perception.

Classifying minimally disabled multiple sclerosis patients from resting state functional connectivity.

Multiple sclerosis (MS), a variable and diffuse disease affecting white and gray matter, is known to cause functional connectivity anomalies in patients. However, related studies published to-date are post hoc; our hypothesis was that such alterations could discriminate between patients and healthy controls in a predictive setting, laying the groundwork for imaging-based prognosis. Using functional magnetic resonance imaging resting state data of 22 minimally disabled MS patients and 14 controls, we developed a predictive model of connectivity alterations in MS: a whole-brain connectivity matrix was built for each subject from the slow oscillations (<0.11Hz) of region-averaged time series, and a pattern recognition technique was used to learn a discriminant function indicating which particular functional connections are most affected by disease. Classification performance using strict cross-validation yielded a sensitivity of 82% (above chance at p<0.005) and specificity of 86% (p<0.01) to distinguish between MS patients and controls. The most discriminative connectivity changes were found in subcortical and temporal regions, and contralateral connections were more discriminative than ipsilateral connections. The pattern of decreased discriminative connections can be summarized post hoc in an index that correlates positively (ρ=0.61) with white matter lesion load, possibly indicating functional reorganisation to cope with increasing lesion load. These results are consistent with a subtle but widespread impact of lesions in white matter and in gray matter structures serving as high-level integrative hubs. These findings suggest that predictive models of resting state fMRI can reveal specific anomalies due to MS with high sensitivity and specificity, potentially leading to new non-invasive markers.

Prospective motion correction of 3D echo-planar imaging data for functional MRI using optical tracking.

We evaluated the performance of an optical camera based prospective motion correction (PMC) system in improving the quality of 3D echo-planar imaging functional MRI data. An optical camera and external marker were used to dynamically track the head movement of subjects during fMRI scanning. PMC was performed by using the motion information to dynamically update the sequence's RF excitation and gradient waveforms such that the field-of-view was realigned to match the subject's head movement. Task-free fMRI experiments on five healthy volunteers followed a 2×2×3 factorial design with the following factors: PMC on or off; 3.0mm or 1.5mm isotropic resolution; and no, slow, or fast head movements. Visual and motor fMRI experiments were additionally performed on one of the volunteers at 1.5mm resolution comparing PMC on vs PMC off for no and slow head movements. Metrics were developed to quantify the amount of motion as it occurred relative to k-space data acquisition. The motion quantification metric collapsed the very rich camera tracking data into one scalar value for each image volume that was strongly predictive of motion-induced artifacts. The PMC system did not introduce extraneous artifacts for the no motion conditions and improved the time series temporal signal-to-noise by 30% to 40% for all combinations of low/high resolution and slow/fast head movement relative to the standard acquisition with no prospective correction. The numbers of activated voxels (p<0.001, uncorrected) in both task-based experiments were comparable for the no motion cases and increased by 78% and 330%, respectively, for PMC on versus PMC off in the slow motion cases. The PMC system is a robust solution to decrease the motion sensitivity of multi-shot 3D EPI sequences and thereby overcome one of the main roadblocks to their widespread use in fMRI studies.

Clustered functional MRI of overt speech production

To investigate the neural network of overt speech production, eventrelated fMRI was performed in 9 young healthy adult volunteers. A clustered image acquisition technique was chosen to minimize speechrelated movement artifacts. Functional images were acquired during the production of oral movements and of speech of increasing complexity (isolated vowel as well as monosyllabic and trisyllabic utterances). This imaging technique and behavioral task enabled depiction of the articulo-phonologic network of speech production from the supplementary motor area at the cranial end to the red nucleus at the caudal end. Speaking a single vowel and performing simple oral movements involved very similar activation of the corticaland subcortical motor systems. More complex, polysyllabic utterances were associated with additional activation in the bilateral cerebellum,reflecting increased demand on speech motor control, and additional activation in the bilateral temporal cortex, reflecting the stronger involvement of phonologic processing.

Epoch-specific functional networks involved in working memory

Working memory (WM) is not a unitary construct. There are distinct processes involved in encoding information, maintaining it on-line, and using it to guide responses. The anatomical configurations of these processes are more accurately analyzed as functionally connected networks than collections of individual regions. In the current study we analyzed event-related functional magnetic resonance imaging (fMRI) data from a Sternberg Item Recognition Paradigm WM task using a multivariate analysis method that allowed the linking of functional networks to temporally-separated WM epochs. The length of the delay epochs was varied to optimize isolation of the hemodynamic response (HDR) for each task epoch. All extracted functional networks displayed statistically significant sensitivity to delay length. Novel information extracted from these networks that was not apparent in the univariate analysis of these data included involvement of the hippocampus in encoding/probe, and decreases in BOLD signal in the superior temporal gyrus (STG), along with default-mode regions, during encoding/delay. The bilateral hippocampal activity during encoding/delay fits with theoretical models of WM in which memoranda held across the short term are activated long-term memory representations. The BOLD signal decreases in the STG were unexpected, and may reflect repetition suppression effects invoked by internal repetition of letter stimuli. Thus, analysis methods focusing on how network dynamics relate to experimental conditions allowed extraction of novel information not apparent in univariate analyses, and are particularly recommended for WM experiments for which task epochs cannot be randomized.

Whole-brain functional connectivity during emotional word classification in medication-free Major Depressive Disorder: abnormal salience circuitry and relations to positive emotionality

Major Depressive Disorder (MDD) has been associated with biased processing and abnormal regulation of negative and positive information, which may result from compromised coordinated activity of prefrontal and subcortical brain regions involved in evaluating emotional information. We tested whether patients with MDD show distributed changes in functional connectivity with a set of independently derived brain networks that have shown high correspondence with different task demands, including stimulus salience and emotional processing. We further explored if connectivity during emotional word processing related to the tendency to engage in positive or negative emotional states. In this study, 25 medication-free MDD patients without current or past comorbidity and matched controls (n=25) performed an emotional word-evaluation task during functional MRI. Using a dual regression approach, individual spatial connectivity maps representing each subject’s connectivity with each standard network were used to evaluate between-group differences and effects of positive and negative emotionality (extraversion and neuroticism, respectively, as measured with the NEO-FFI). Results showed decreased functional connectivity of the medial prefrontal cortex, ventrolateral prefrontal cortex, and ventral striatum with the fronto-opercular salience network in MDD patients compared to controls. In patients, abnormal connectivity was related to extraversion, but not neuroticism. These results confirm the hypothesis of a relative (para)limbic-cortical decoupling that may explain dysregulated affect in MDD. As connectivity of these regions with the salience network was related to extraversion, but not to general depression severity or negative emotionality, dysfunction of this network may be responsible for the failure to sustain engagement in rewarding behavior.

Antidepressant medications reduce subcortical-cortical resting-state functional connectivity in healthy volunteers

Studies have revealed abnormalities in resting-state functional connectivity in those with major depressive disorder specifically in areas such as the dorsal anterior cingulate, thalamus, amygdala, the pallidostriatum and subgenual cingulate. However, the effect of antidepressant medications on human brain function is less clear and the effect of these drugs on resting-state functional connectivity is unknown. Forty volunteers matched for age and gender with no previous psychiatric history received either citalopram (SSRI; selective serotonergic reuptake inhibitor), reboxetine (SNRI; selective noradrenergic reuptake inhibitor) or placebo for 7 days in a double-blind design. Using resting-state functional magnetic resonance imaging and seed based connectivity analysis we selected the right nucleus accumbens, the right amygdala, the subgenual cingulate and the dorsal medial prefrontal cortex as seed regions. Mood and subjective experience were also measured before and after drug administration using self-report scales. Despite no differences in mood across the three groups, we found reduced connectivity between the amygdala and the ventral medial prefrontal cortex in the citalopram group and the amygdala and the orbitofrontal cortex for the reboxetine group. We also found reduced striatal-orbitofrontal cortex connectivity in the reboxetine group. These data suggest that antidepressant medications can decrease resting-state functional connectivity independent of mood change and in areas known to mediate reward and emotional processing in the brain. We conclude that hypothesis-driven seed based analysis of resting-state fMRI supports the proposition that antidepressant medications might work by normalising the elevated resting-state functional connectivity seen in depressed patients.

Heart rate variability is associated with amygdala functional connectivity with MPFC across younger and older adults

The ability to regulate emotion is crucial to promote well-being. Evidence suggests that the medial prefrontal cortex (mPFC) and adjacent anterior cingulate (ACC) modulate amygdala activity during emotion regulation. Yet less is known about whether the amygdala-mPFC circuit is linked with regulation of the autonomic nervous system and whether the relationship differs across the adult lifespan. The current study tested the hypothesis that heart rate variability (HRV) reflects the strength of mPFC-amygdala interaction across younger and older adults. We recorded participants’ heart rates at baseline and examined whether baseline HRV was associated with amygdala-mPFC functional connectivity during rest. We found that higher HRV was associated with stronger functional connectivity between the amygdala and the mPFC during rest across younger and older adults. In addition to this age-invariant pattern, there was an age-related change, such that greater HRV was linked with stronger functional connectivity between amygdala and ventrolateral PFC (vlPFC) in younger than in older adults. These results are in line with past evidence that vlPFC is involved in emotion regulation especially in younger adults. Taken together, our results support the neurovisceral integration model and suggest that higher heart rate variability is associated with neural mechanisms that support successful emotional regulation across the adult lifespan.