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.

From EEG to BOLD: Brain mapping and estimating transfer functions in simultaneous EEG-fMRI acquisitions

Simultaneous acquisition of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) aims to disentangle the description of brain processes by exploiting the advantages of each technique. Most studies in this field focus on exploring the relationships between fMRI signals and the power spectrum at some specific frequency bands (alpha, beta, etc.). On the other hand, brain mapping of EEG signals (e.g., interictal spikes in epileptic patients) usually assumes an haemodynamic response function for a parametric analysis applying the GLM, as a rough approximation. The integration of the information provided by the high spatial resolution of MR images and the high temporal resolution of EEG may be improved by referencing them by transfer functions, which allows the identification of neural driven areas without strong assumptions about haemodynamic response shapes or brain haemodynamic`s homogeneity. The difference on sampling rate is the first obstacle for a full integration of EEG and fMRI information. Moreover, a parametric specification of a function representing the commonalities of both signals is not established. In this study, we introduce a new data-driven method for estimating the transfer function from EEG signal to fMRI signal at EEG sampling rate. This approach avoids EEG subsampling to fMRI time resolution and naturally provides a test for EEG predictive power over BOLD signal fluctuations, in a well-established statistical framework. We illustrate this concept in resting state (eyes closed) and visual simultaneous fMRI-EEG experiments. The results point out that it is possible to predict the BOLD fluctuations in occipital cortex by using EEG measurements. (C) 2010 Elsevier Inc. All rights reserved.

EEG-based functional brain networks: does the network size matter?

Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. These networks--whose nodes can vary from tens to hundreds--are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which various graph metrics depend upon the network size. To this end, EEGs from 32 normal subjects were recorded and functional networks of three different sizes were extracted. A state-space based method was used to calculate cross-correlation matrices between different brain regions. These correlation matrices were used to construct binary adjacency connectomes, which were assessed with regards to a number of graph metrics such as clustering coefficient, modularity, efficiency, economic efficiency, and assortativity. We showed that the estimates of these metrics significantly differ depending on the network size. Larger networks had higher efficiency, higher assortativity and lower modularity compared to those with smaller size and the same density. These findings indicate that the network size should be considered in any comparison of networks across studies.

Structural and functional brain changes in middle-aged type 2 diabetic patients: a cross-sectional study.

BACKGROUND Type 2 diabetes mellitus (T2DM) is an emerging risk factor for cognitive impairment. Whether this impairment is a direct effect of this metabolic disorder on brain function, a consequence of vascular disease, or both, remains unknown. Structural and functional neuroimaging studies in patients with T2DM could help to elucidate this question. OBJECTIVE We designed a cross-sectional study comparing 25 T2DM patients with 25 age- and gender-matched healthy control participants. Clinical information, APOE genotype, lipid and glucose analysis, structural cerebral magnetic resonance imaging including voxel-based morphometry, and F-18 fluorodeoxyglucose positron emission tomography were obtained in all subjects. METHODS Gray matter densities and metabolic differences between groups were analyzed using statistical parametric mapping. In addition to comparing the neuroimaging profiles of both groups, we correlated neuroimaging findings with HbA1c levels, duration of T2DM, and insulin resistance measurement (HOMA-IR) in the diabetic patients group. Results: Patients with T2DM presented reduced gray matter densities and reduced cerebral glucose metabolism in several fronto-temporal brain regions after controlling for various vascular risk factors. Furthermore, within the T2DM group, longer disease duration, and higher HbA1c levels and HOMA-IR were associated with lower gray matter density and reduced cerebral glucose metabolism in fronto-temporal regions. CONCLUSION In agreement with previous reports, our findings indicate that T2DM leads to structural and metabolic abnormalities in fronto-temporal areas. Furthermore, they suggest that these abnormalities are not entirely explained by the role of T2DM as a cardiovascular risk factor.

Functional MRI Mapping of the Human Auditory Cortex

Mapping the human auditory cortex with standard functional imaging techniques is difficult because of its small size and angular position along the Sylvian fissure. As a result, the exact number and location of auditory cortex areas in the human remains unknown. In a first experiment, we measured the two largest tonotopic areas of primary auditory cortex (PAC, Al and R) using high-resolution functional MRI at 7 Tesla relative to the underlying anatomy of Heschl's gyrus (HG). The data reveals a clear anatomical- functional relationship that indicates the location of PAC across the range of common morphological variants of HG (single gyri, partial duplication and complete duplication). Human PAC tonotopic areas are oriented along an oblique posterior-to-anterior axis with mirror-symmetric frequency gradients perpendicular to HG, as in the macaque. In a second experiment, we tested whether these primary frequency-tuned units were modulated by selective attention to preferred vs. non-preferred sound frequencies in the dynamic manner needed to account for human listening abilities in noisy environments, such as cocktail parties or busy streets. We used a dual-stream selective attention experiment where subjects attended to one of two competing tonal streams presented simultaneously to different ears. Attention to low-frequency tones (250 Hz) enhanced neural responses within low-frequency-tuned voxels relative to high (4000 Hz), and vice versa when at-tention switched from high to low. Human PAC is able to tune into attended frequency channels and can switch frequencies on demand, like a radio. In a third experiment, we investigated repetition suppression effects to environmental sounds within primary and non-primary early-stage auditory areas, identified with the tonotopic mapping design. Repeated presentations of sounds from the same sources, as compared to different sources, gave repetition suppression effects within posterior and medial non-primary areas of the right hemisphere, reflecting their potential involvement in semantic representations. These three studies were conducted at 7 Tesla with high-resolution imaging. However, 7 Tesla scanners are, for the moment, not yet used for clinical diagnosis and mostly reside in institutions external to hospitals. Thus, hospital-based clinical functional and structural studies are mainly performed using lower field systems (1.5 or 3 Tesla). In a fourth experiment, we acquired tonotopic maps at 3 and 7 Tesla and evaluated the consistency of a tonotopic mapping paradigm between scanners. Mirror-symmetric gradients within PAC were highly similar at 7 and 3 Tesla across renderings at different spatial resolutions. We concluded that the tonotopic mapping paradigm is robust and suitable for definition of primary tonotopic areas, also at 3 Tesla. Finally, in a fifth study, we considered whether focal brain lesions alter tonotopic representations in the intact ipsi- and contralesional primary auditory cortex in three patients with hemispheric or cerebellar lesions, without and with auditory complaints. We found evidence for tonotopic reorganisation at the level of the primary auditory cortex in cases of brain lesions independently of auditory complaints. Overall, these results reflect a certain degree of plasticity within primary auditory cortex in different populations of subjects, assessed at different field strengths. - La cartographie du cortex auditif chez l'humain est difficile à réaliser avec des techniques d'imagerie fonctionnelle standard, étant donné sa petite taille et position angulaire le long de la fissure sylvienne. En conséquence, le nombre et l'emplacement exacts des différentes aires du cortex auditif restent inconnus chez l'homme. Lors d'une première expérience, nous avons mesuré, avec de l'imagerie par résonance magnétique à haute intensité (IRMf à 7 Tesla) chez des sujets humains sains, deux larges aires au sein du cortex auditif primaire (PAC; Al et R) avec une représentation spécifique des fréquences pures préférées - ou tonotopie. Nos résultats ont démontré une relation anatomico- fonctionnelle qui définit clairement la position du PAC à travers toutes les variantes du gyrus d'Heschl's (HG). Les aires tonotopiques du PAC humain sont orientées le long d'un axe postéro-antérieur oblique avec des gradients de fréquences spécifiques perpendiculaires à HG, d'une manière similaire à celles mesurées chez le singe. Dans une deuxième expérience, nous avons testé si ces aires primaires pouvaient être modulées, de façon dynamique, par une attention sélective pour des fréquences préférées par rapport à celles non-préférées. Cette modulation est primordiale lors d'interactions sociales chez l'humain en présence de bruits distracteurs tels que d'autres discussions ou un environnement sonore nuisible (comme par exemple, dans la circulation routière). Dans cette étude, nous avons utilisé une expérience d'attention sélective où le sujet devait être attentif à une des deux voies sonores présentées simultanément à chaque oreille. Lorsque le sujet portait était attentif aux sons de basses fréquences (250 Hz), la réponse neuronale relative à ces fréquences augmentait par rapport à celle des hautes fréquences (4000 Hz), et vice versa lorsque l'attention passait des hautes aux basses fréquences. De ce fait, nous pouvons dire que PAC est capable de focaliser sur la fréquence attendue et de changer de canal selon la demande, comme une radio. Lors d'une troisième expérience, nous avons étudié les effets de suppression due à la répétition de sons environnementaux dans les aires auditives primaires et non-primaires, d'abord identifiées via le protocole de la première étude. La présentation répétée de sons provenant de la même source sonore, par rapport à de sons de différentes sources sonores, a induit un effet de suppression dans les aires postérieures et médiales auditives non-primaires de l'hémisphère droite, reflétant une implication de ces aires dans la représentation de la catégorie sémantique. Ces trois études ont été réalisées avec de l'imagerie à haute résolution à 7 Tesla. Cependant, les scanners 7 Tesla ne sont pour le moment utilisés que pour de la recherche fondamentale, principalement dans des institutions externes, parfois proches du patient mais pas directement à son chevet. L'imagerie fonctionnelle et structurelle clinique se fait actuellement principalement avec des infrastructures cliniques à 1.5 ou 3 Tesla. Dans le cadre dune quatrième expérience, nous avons avons évalués la cohérence du paradigme de cartographie tonotopique à travers différents scanners (3 et 7 Tesla) chez les mêmes sujets. Nos résultats démontrent des gradients de fréquences définissant PAC très similaires à 3 et 7 Tesla. De ce fait, notre paradigme de définition des aires primaires auditives est robuste et applicable cliniquement. Finalement, nous avons évalués l'impact de lésions focales sur les représentations tonotopiques des aires auditives primaires des hémisphères intactes contralésionales et ipsilésionales chez trois patients avec des lésions hémisphériques ou cérébélleuses avec ou sans plaintes auditives. Nous avons trouvé l'évidence d'une certaine réorganisation des représentations topographiques au niveau de PAC dans le cas de lésions cérébrales indépendamment des plaintes auditives. En conclusion, nos résultats démontrent une certaine plasticité du cortex auditif primaire avec différentes populations de sujets et différents champs magnétiques.

Laser Doppler imaging for intraoperative human brain mapping

The identification and accurate location of centers of brain activity are vital both in neuro-surgery and brain research. This study aimed to provide a non-invasive, non-contact, accurate, rapid and user-friendly means of producing functional images intraoperatively. To this end a full field Laser Doppler imager was developed and integrated within the surgical microscope and perfusion images of the cortical surface were acquired during awake surgery whilst the patient performed a predetermined task. The regions of brain activity showed a clear signal (10-20% with respect to the baseline) related to the stimulation protocol which lead to intraoperative functional brain maps of strong statistical significance and which correlate well with the preoperative fMRI and intraoperative cortical electro-stimulation. These initial results achieved with a prototype device and wavelet based regressor analysis (the hemodynamic response function being derived from MRI applications) demonstrate the feasibility of LDI as an appropriate technique for intraoperative functional brain imaging.

Functional brain network efficiency predicts intelligence

The neuronal causes of individual differences in mental abilities such as intelligence are complex and profoundly important. Understanding these abilities has the potential to facilitate their enhancement. The purpose of this study was to identify the functional brain network characteristics and their relation to psychometric intelligence. In particular, we examined whether the functional network exhibits efficient small-world network attributes (high clustering and short path length) and whether these small-world network parameters are associated with intellectual performance. High-density resting state electroencephalography (EEG) was recorded in 74 healthy subjects to analyze graph-theoretical functional network characteristics at an intracortical level. Ravens advanced progressive matrices were used to assess intelligence. We found that the clustering coefficient and path length of the functional network are strongly related to intelligence. Thus, the more intelligent the subjects are the more the functional brain network resembles a small-world network. We further identified the parietal cortex as a main hub of this resting state network as indicated by increased degree centrality that is associated with higher intelligence. Taken together, this is the first study that substantiates the neural efficiency hypothesis as well as the Parieto-Frontal Integration Theory (P-FIT) of intelligence in the context of functional brain network characteristics. These theories are currently the most established intelligence theories in neuroscience. Our findings revealed robust evidence of an efficiently organized resting state functional brain network for highly productive cognitions.

Functional brain perfusion evaluation with Arterial Spin Labeling at 3 Tesla

Dissertation submitted in Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa for the degree of Master of Biomedical Engineering

Properties of functional brain networks correlate with frequency of psychogenic non-epileptic seizures.

Abnormalities in the topology of brain networks may be an important feature and etiological factor for psychogenic non-epileptic seizures (PNES). To explore this possibility, we applied a graph theoretical approach to functional networks based on resting state EEGs from 13 PNES patients and 13 age- and gender-matched controls. The networks were extracted from Laplacian-transformed time-series by a cross-correlation method. PNES patients showed close to normal local and global connectivity and small-world structure, estimated with clustering coefficient, modularity, global efficiency, and small-worldness (SW) metrics, respectively. Yet the number of PNES attacks per month correlated with a weakness of local connectedness and a skewed balance between local and global connectedness quantified with SW, all in EEG alpha band. In beta band, patients demonstrated above-normal resiliency, measured with assortativity coefficient, which also correlated with the frequency of PNES attacks. This interictal EEG phenotype may help improve differentiation between PNES and epilepsy. The results also suggest that local connectivity could be a target for therapeutic interventions in PNES. Selective modulation (strengthening) of local connectivity might improve the skewed balance between local and global connectivity and so prevent PNES events.

Structural and functional brain abnormalities in children with subclinical depression

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal.

Dyspnea-related cues engage the prefrontal cortex - evidence from functional brain imaging in COPD

Dyspnea is the major source of disability in chronic obstructive pulmonary disease (COPD). In COPD, environmental cues (e.g. the prospect of having to climb stairs) become associated with dyspnea, and may trigger dyspnea even before physical activity commences. We hypothesised that brain activation relating to such cues would be different between COPD patients and healthy controls, reflecting greater engagement of emotional mechanisms in patients. Methods: Using FMRI, we investigated brain responses to dyspnea-related word cues in 41 COPD patients and 40 healthy age-matched controls. We combined these findings with scores of self-report questionnaires thus linking the FMRI task with clinically relevant measures. This approach was adapted from studies in pain that enables identification of brain networks responsible for pain processing despite absence of a physical challenge. Results: COPD patients demonstrate activation in the medial prefrontal cortex (mPFC), and anterior cingulate cortex (ACC) which correlated with the visual analogue scale (VAS) response to word cues. This activity independently correlated with patient-reported questionnaires of depression, fatigue and dyspnea vigilance. Activation in the anterior insula, lateral prefrontal cortex (lPFC) and precuneus correlated with the VAS dyspnea scale but not the questionnaires. Conclusions: Our findings suggest that engagement of the brain's emotional circuitry is important for interpretation of dyspnea-related cues in COPD, and is influenced by depression, fatigue, and vigilance. A heightened response to salient cues is associated with increased symptom perception in chronic pain and asthma, and our findings suggest such mechanisms may be relevant in COPD.

Gross total resection rates in contemporary glioblastoma surgery: results of an institutional protocol combining 5-aminolevulinic acid intraoperative fluorescence imaging and brain mapping

Complete resection of contrast-enhancing tumor has been recognized as an important prognostic factor in patients with glioblastoma and is a primary goal of surgery. Various intraoperative technologies have recently been introduced to improve glioma surgery.

Social Cognition And Functional Brain Imaging: Extending The Broader Autism Phenotype

Evidence suggests that the social cognition deficits prevalent in autism spectrum disorders (ASDs) are widely distributed in first degree and extended relatives. This ¿broader autism phenotype¿ (BAP) can be extended into non-clinical populations and show wide distributions of social behaviors such as empathy and social responsiveness ¿ with ASDs exhibiting these behaviors on the lower ends of the distributions. Little evidence has previously shown relationships between self-report measures of social cognition and more objective tasks such as face perception in functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs). In this study, three specific hypotheses were addressed: a) increased social ability, as measured by an increased Empathy Quotient, decreased Social Responsiveness Scale (SRS-A) score, and increased Social Attribution Task score, will predict increased activation of the fusiform gyrus in response to faces as compared to houses; b) these same measures will predict N170 amplitude and latency showing decreased latency and increased amplitude for faces as compared to houses with increased social ability; c) increased amygdala volume will predict increased fusiform gyrus activation when viewing faces as compared to houses. Findings supported all of the hypotheses. Empathy scores significantly predicted both right FFG activation [F(1,20) = 4.811, p = .041, ß = .450, R2 = 0.20] and left FFG activation [F(1,20) = 7.70, p = .012, ß = .537, R2 = 0.29]. Based on ERP results increased right lateralization face-related N170 was significantly predicted by the EQ [F(1,54) = 6.94, p = .011, ß = .338, R2 = 0.11]. Finally, total amygdala volume significantly predicted right [F(1,20) = 7.217, p = .014, ß = .515, R2 = 0.27] and left [F(1,20) = 36.77, p < .001, ß = .805, R2 = 0.65] FFG activation. Consistent with the a priori hypotheses, traits attributed to the BAP can significantly predict neural responses to faces in a non-clinical population. This is consistent with the face processing deficits seen in ASDs. The findings presented here contribute to the extension of the BAP from unaffected relatives of individuals with ASDs to the general population. These findings also give continued evidence in support of a continuous distribution of traits found in psychiatric illnesses in place of a traditional, dichotomous ¿all-or-nothing¿ diagnostic framework of neurodevelopmental and neuropsychiatric disorders.