Static body equilibrium is an essential requisite for human daily life. It is known that visual and vestibular systems must work together to support equilibrium. However, the relationship between these two systems is not fully understood. In this work, we present the results of a study which identify the interaction of brain areas that are involved with concurrent visual and vestibular inputs. The visual and the vestibular systems were individually and simultaneously stimulated, using flickering checkerboard (without movement stimulus) and galvanic current, during experiments of functional magnetic resonance imaging. Twenty-four right-handed and non-symptomatic subjects participated in this study. Single visual stimulation shows positive blood-oxygen-level-dependent (BOLD) responses (PBR) in the primary and associative visual cortices. Single vestibular stimulation shows PBR in the parieto-insular vestibular cortex, inferior parietal lobe, superior temporal gyrus, precentral gyrus and lobules V and VI of the cerebellar hemisphere. Simultaneous stimulation shows PBR in the middle and inferior frontal gyri and in the precentral gyrus. Vestibular- and somatosensory-related areas show negative BOLD responses (NBR) during simultaneous stimulation. NBR areas were also observed in the calcarine gyrus, lingual gyrus, cuneus and precuneus during simultaneous and single visual stimulations. For static visual and galvanic vestibular simultaneous stimulation, the reciprocal inhibitory visual-vestibular interaction pattern is observed in our results. The experimental results revealed interactions in frontal areas during concurrent visual-vestibular stimuli, which are affected by intermodal association areas in occipital, parietal, and temporal lobes.
Patients with low-grade glioma (LGG) have been studied as a model of functional brain reorganization due to their slow-growing nature. However, there is no information regarding which brain areas are involved during verbal memory encoding after extensive left frontal LGG resection. In addition, it remains unknown whether these patients can improve their memory performance after instructions to apply efficient strategies. The neural correlates of verbal memory encoding were investigated in patients who had undergone extensive left frontal lobe (LFL) LGG resections and healthy controls using fMRI both before and after directed instructions were given for semantic organizational strategies. Participants were scanned during the encoding of word lists under three different conditions before and after a brief period of practice. The conditions included semantically unrelated (UR), related-non-structured (RNS), and related-structured words (RS), allowing for different levels of semantic organization. All participants improved on memory recall and semantic strategy application after the instructions for the RNS condition. Healthy subjects showed increased activation in the left inferior frontal gyrus (IFG) and middle frontal gyrus (MFG) during encoding for the RNS condition after the instructions. Patients with LFL excisions demonstrated increased activation in the right IFG for the RNS condition after instructions were given for the semantic strategies. Despite extensive damage in relevant areas that support verbal memory encoding and semantic strategy applications, patients that had undergone resections for LFL tumor could recruit the right-sided contralateral homologous areas after instructions were given and semantic strategies were practiced. These results provide insights into changes in brain activation areas typically implicated in verbal memory encoding and semantic processing.
The depression-executive dysfunction syndrome, a late-onset depression of vascular origin with executive dysfunction and psychomotor retardation, has also been described after stroke. We verified whether this syndrome also occurs in nonelderly stroke patients by investigating the association between domains of depressive symptoms with executive functions in 87 first-ever ischemic stroke patients. The retardation domain of the 31-item Hamilton Rating Scale for Depression was associated with decreased performance on verbal fluency (assessed with FAS). The association was maintained for younger patients (aged <60 years) after adjusting for confounders. This result supports the clinical presentation of depression-executive dysfunction syndrome in younger stroke patients. Confirmation of this finding, its neural correlates, and clinical implication deserve further investigation.
Investigations of brain maturation processes are a key step to understand the cognitive and emotional changes of adolescence. Although structural imaging findings have delineated clear brain developmental trajectories for typically developing individuals, less is known about the functional changes of this sensitive development period. Developmental changes, such as abstract thought, complex reasoning, and emotional and inhibitory control, have been associated with more prominent cortical control. The aim of this study is to assess brain networks connectivity changes in a large sample of 7- to 15-year-old subjects, testing the hypothesis that cortical regions will present an increasing relevance in commanding the global network. Functional magnetic resonance imaging (fMRI) data were collected in a sample of 447 typically developing children from a Brazilian community sample who were submitted to a resting state acquisition protocol. The fMRI data were used to build a functional weighted graph from which eigenvector centrality (EVC) was extracted. For each brain region (a node of the graph), the age-dependent effect on EVC was statistically tested and the developmental trajectories were estimated using polynomial functions. Our findings show that angular gyrus become more central during this maturation period, while the caudate; cerebellar tonsils, pyramis, thalamus; fusiform, parahippocampal and inferior semilunar lobe become less central. In conclusion, we report a novel finding of an increasing centrality of the angular gyrus during the transition to adolescence, with a decreasing centrality of many subcortical and cerebellar regions.
The investigation of neurodevelopment during late childhood and pre-adolescence has recently attracted a great deal of interest in the field of neuroimaging. One promising topic in this field is the formation of brain networks in healthy subjects. The integration between neural modules characterizes the ability of the network to process information globally. Although many fMRI-based neurodevelopment studies can be found in the literature, the analyses of very large samples (on the order of hundreds of subjects) that focus on the late childhood/pre-adolescence period and resting state fMRI are scarce, and most studies have focused solely on North American and European populations.
Histopathological studies in Alzheimer's disease (AD) suggest severe and region-specific neurodegeneration of the basal forebrain cholinergic system (BFCS). Here, we studied the between-center reliability and diagnostic accuracy of MRI-based BFCS volumetry in a large multicenter data set, including participants with prodromal (n = 41) or clinically manifest AD (n = 134) and 148 cognitively healthy controls. Atrophy was determined using voxel-based and region-of-interest based analyses of high-dimensionally normalized MRI scans using a newly created map of the BFCS based on postmortem in cranio MRI and histology. The AD group showed significant volume reductions of all subregions of the BFCS, which were most pronounced in the posterior nucleus basalis Meynert (NbM). The mild cognitive impairment-AD group showed pronounced volume reductions in the posterior NbM, but preserved volumes of anterior-medial regions. Diagnostic accuracy of posterior NbM volume was superior to hippocampus volume in both groups, despite higher multicenter variability of the BFCS measurements. The data of our study suggest that BFCS morphometry may provide an emerging biomarker in AD.
Primary progressive aphasia (PPA) is characterized by left hemispheric frontotemporal cortical atrophy. Evidence from anatomical studies suggests that the nucleus subputaminalis (NSP), a subnucleus of the cholinergic basal forebrain, may be involved in the pathological process of PPA. Therefore, we studied the pattern of cortical and basal forebrain atrophy in 10 patients with a clinical diagnosis of PPA and 18 healthy age-matched controls using high-resolution magnetic resonance imaging (MRI). We determined the cholinergic basal forebrain nuclei according to Mesulam's nomenclature and the NSP in MRI reference space based on histological sections and the MRI scan of a post-mortem brain in cranio. Using voxel-based analysis, we found left hemispheric cortical atrophy in PPA patients compared with controls, including prefrontal, lateral temporal and medial temporal lobe areas. We detected cholinergic basal forebrain atrophy in left predominant localizations of Ch4p, Ch4am, Ch4al, Ch3 and NSP. For the first time, we have described the pattern of basal forebrain atrophy in PPA and confirmed the involvement of NSP that had been predicted based on theoretical considerations. Our findings may enhance understanding of the role of cholinergic degeneration for the regional specificity of the cortical destruction leading to the syndrome of PPA.
Despite growing interest in developing cognitive training interventions to minimize the aging cognitive decline process, no studies have attempted to explore which brain regions support the application of semantic strategies during verbal memory encoding. Our aim was to investigate the behavioral performance and brain correlates of these strategies in elderly individuals using fMRI in healthy older subjects.
High-frequency repetitive transcranial magnetic stimulation of the left dorsolateral prefrontal cortex (rTMS-DLPFC) is an effective treatment for depression. Preliminary studies indicated beneficial effects of rTMS-DLPFC on pain relief in patients treated for depression, and in patients with chronic migraine.
We compared accuracy of hippocampus and basal forebrain cholinergic system (BFCS) atrophy to predict cortical amyloid burden in 179 cognitively normal subjects (CN), 269 subjects with early stages of mild cognitive impairment (MCI), 136 subjects with late stages of MCI, and 86 subjects with Alzheimers disease (AD) dementia retrieved from the Alzheimers Disease Neuroimaging Initiative database. Hippocampus and BFCS volumes were determined from structural magnetic resonance imaging scans at 3 Tesla, and cortical amyloid load from AV45 (florbetapir) positron emission tomography scans. In receiver operating characteristics analyses, BFCS volume provided significantly more accurate classification into amyloid-negative and -positive categories than hippocampus volume. In contrast, hippocampus volume more accurately identified the diagnostic categories of AD, late and early MCI, and CN compared with whole and anterior BFCS volume, whereas posterior BFCS and hippocampus volumes yielded similar diagnostic accuracy. In logistic regression analysis, hippocampus and posterior BFCS volumes contributed significantly to discriminate MCI and AD from CN, but only BFCS volume predicted amyloid status. Our findings suggest that BFCS atrophy is more closely associated with cortical amyloid burden than hippocampus atrophy in predementia AD.
We previously described - studying transcriptional signatures of hippocampal CA3 explants - that febrile (FS) and afebrile (NFS) forms of refractory mesial temporal lobe epilepsy constitute two distinct genomic phenotypes. That network analysis was based on a limited number (hundreds) of differentially expressed genes (DE networks) among a large set of valid transcripts (close to two tens of thousands). Here we developed a methodology for complex network visualization (3D) and analysis that allows the categorization of network nodes according to distinct hierarchical levels of gene-gene connections (node degree) and of interconnection between node neighbors (concentric node degree). Hubs are highly connected nodes, VIPs have low node degree but connect only with hubs, and high-hubs have VIP status and high overall number of connections. Studying the whole set of CA3 valid transcripts we: i) obtained complete transcriptional networks (CO) for FS and NFS phenotypic groups; ii) examined how CO and DE networks are related; iii) characterized genomic and molecular mechanisms underlying FS and NFS phenotypes, identifying potential novel targets for therapeutic interventions. We found that: i) DE hubs and VIPs are evenly distributed inside the CO networks; ii) most DE hubs and VIPs are related to synaptic transmission and neuronal excitability whereas most CO hubs, VIPs and high hubs are related to neuronal differentiation, homeostasis and neuroprotection, indicating compensatory mechanisms. Complex network visualization and analysis is a useful tool for systems biology approaches to multifactorial diseases. Network centrality observed for hubs, VIPs and high hubs of CO networks, is consistent with the network disease model, where a group of nodes whose perturbation leads to a disease phenotype occupies a central position in the network. Conceivably, the chance for exerting therapeutic effects through the modulation of particular genes will be higher if these genes are highly interconnected in transcriptional networks.
In medical practice, diagnostic hypotheses are often made by physicians in the first moments of contact with patients; sometimes even before they report their symptoms. We propose that generation of diagnostic hypotheses in this context is the result of cognitive processes subserved by brain mechanisms that are similar to those involved in naming objects or concepts in everyday life.
A large number of functional neuroimaging studies have investigated the brain circuitry which is engaged during performance of phonological verbal fluency tasks, and the vast majority of these have been carried out in English. Although there is evidence that this paradigm varies depending on the language spoken, it is unclear if this difference is associated with differences in brain activation patterns. Also, there is neuroimaging evidence that the patterns of regional cerebral activation during verbal fluency tasks may vary with the level of task demanded. In particular, the engagement of the anterior cingulate cortex seems to be relative to cognitive demand. We compared functional magnetic resonance imaging data in healthy Portuguese-speaking subjects during overt production of words beginning with letters classified as easy or hard for word production in Portuguese. Compared to the baseline condition, the two verbal fluency tasks (with either easy or hard letters) engaged a network including the left inferior and middle frontal cortices, anterior cingulate cortex, putamen, thalamus and cerebellum (p < .001). The direct comparison between the two verbal fluency conditions showed greater cerebellar activation in the easy condition relative to the hard condition. In the anterior cingulate cortex, there was a direct correlation between activity changes and verbal fluency performance during the hard condition only. Despite grammatical differences, the changes in patterns of brain activity during verbal fluency performance observed in our study are in accordance with findings of previous neuroimaging studies of verbal fluency carried out in English and other languages, with recruitment of a set of distributed cerebral areas during word production.
Rapid developments in medical neuroimaging have made it possible to reconstruct the trajectory of Alzheimers disease (AD) as it spreads through the living brain. The current review focuses on the progressive signature of brain changes throughout the different stages of AD. We integrate recent findings on changes in cortical gray matter volume, white matter fiber tracts, neuropathological alterations, and brain metabolism assessed with molecular positron emission tomography (PET). Neurofibrillary tangles accumulate first in transentorhinal and cholinergic brain areas, and 4-D maps of cortical volume changes show early progressive temporo-parietal cortical thinning. Findings from diffusion tensor imaging (DTI) for assessment fiber tract integrity show cortical disconnection in corresponding brain networks. Importantly, the developmental trajectory of brain changes is not uniform and may be modulated by several factors such as onset of disease mechanisms, risk-associated and protective genes, converging comorbidity, and individual brain reserve. There is a general agreement between in vivo brain maps of cortical atrophy and amyloid pathology assessed through PET, reminiscent of post mortem histopathology studies that paved the way in the staging of AD. The association between in vivo and post mortem findings will clarify the temporal dynamics of pathophysiological alterations in the development of preclinical AD. This will be important in designing effective treatments that target specific underlying disease AD mechanisms.
Prolonged febrile seizures constitute an initial precipitating injury (IPI) commonly associated with refractory mesial temporal lobe epilepsy (RMTLE). In order to investigate IPI influence on the transcriptional phenotype underlying RMTLE we comparatively analyzed the transcriptomic signatures of CA3 explants surgically obtained from RMTLE patients with (FS) or without (NFS) febrile seizure history. Texture analyses on MRI images of dentate gyrus were conducted in a subset of surgically removed sclerotic hippocampi for identifying IPI-associated histo-radiological alterations.
Psychopathy is a disorder of personality characterized by severe impairments of social conduct, emotional experience, and interpersonal behavior. Psychopaths consistently violate social norms and bring considerable financial, emotional, or physical harm to others and to society as a whole. Recent developments in analysis methods of magnetic resonance imaging (MRI), such as voxel-based-morphometry (VBM), have become major tools to understand the anatomical correlates of this disorder. Nevertheless, the identification of psychopathy by neuroimaging or other neurobiological tools (e.g., genetic testing) remains elusive.
Increased, decreased or normal excitability to transcranial magnetic stimulation (TMS) has been reported in the motor (M1) and visual cortices of patients with migraine. Light deprivation (LD) has been reported to modulate M1 excitability in control subjects (CS). Still, effects of LD on M1 excitability compared to exposure to environmental light exposure (EL) had not been previously described in patients with migraine (MP). To further our knowledge about differences between CS and MP, regarding M1 excitability and effects of LD on M1 excitability, we opted for a novel approach by extending measurement conditions. We measured motor thresholds (MTs) to TMS, short-interval intracortical inhibition, and ratios between motor-evoked potential amplitudes and supramaximal M responses in MP and CS on two different days, before and after LD or EL. Motor thresholds significantly increased in MP in LD and EL sessions, and remained stable in CS. There were no significant between-group differences in other measures of TMS. Short-term variation of MTs was greater in MP compared to CS. Fluctuation in excitability over hours or days in MP is an issue that, until now, has been relatively neglected. The results presented here will help to reconcile conflicting observations.
Little is known about the relevance of lesion in neural circuits reported to be associated with major depressive disorder. We investigated the association between lesion stroke size in the limbic-cortical-striatal-pallidal-thalamic (LCSPT) circuit and incidence of major depressive episode (MDE).
Gliomas are a group of heterogeneous primary central nervous system (CNS) tumors arising from the glial cells. Malignant gliomas account for a majority of malignant primary CNS tumors and are associated with high morbidity and mortality. Glioblastoma is the most frequent and malignant glioma, and despite the recent advances in diagnosis and new treatment options, its prognosis remains dismal. New opportunities for the development of effective therapies for malignant gliomas are urgently needed. Magnetic hyperthermia (MHT), which consists of heat generation in the region of the tumor through the application of magnetic nanoparticles subjected to an alternating magnetic field (AMF), has shown positive results in both preclinical and clinical assays. The aim of this review is to assess the relevance of hyperthermia induced by magnetic nanoparticles in the treatment of gliomas and to note the possible variations of the technique and its implication on the effectiveness of the treatment. We performed an electronic search in the literature from January 1990 to October 2010, in various databases, and after application of the inclusion criteria we obtained a total of 15 articles. In vitro studies and studies using animal models showed that MHT was effective in the promotion of tumor cell death and reduction of tumor mass or increase in survival. Two clinical studies showed that MHT could be applied safely and with few side effects. Some studies suggested that mechanisms of cell death, such as apoptosis, necrosis, and antitumor immune response were triggered by MHT. Based on these data, we could conclude that MHT proved to be efficient in most of the experiments, and that the improvement of the nanocomposites as well as the AMF equipment might contribute toward establishing MHT as a promising tool in the treatment of malignant gliomas.
Social Anxiety Disorder (SAD) is more common among PD patients than in the general population. This association may be explained by psychosocial mechanisms but it is also possible that neurobiological mechanism underlying PD can predispose to SAD. The aim of this study was to investigate a possible dopaminergic mechanism involved in PD patients with SAD, by correlating striatal dopamine transporter binding potential (DAT-BP) with intensity of social anxiety symptoms in PD patients using SPECT with TRODAT-1 as the radiopharmaceutical. Eleven PD patients with generalized SAD and 21 PD patients without SAD were included in this study; groups were matched for age, gender, disease duration and disease severity. SAD diagnosis was determined according to DSM IV criteria assessed with SCID-I and social anxiety symptom severity with the Brief Social Phobia Scale (BSPS). Demographic and clinical data were also collected. DAT-BP was significantly correlated to scores on BSPS for right putamen (r=0.37, p=0.04), left putamen (r=0.43, p=0.02) and left caudate (r=0.39, p=0.03). No significant correlation was found for the right caudate (r=0.23, p=0.21). This finding may reinforce the hypothesis that dopaminergic dysfunction might be implicated in the pathogenesis of social anxiety in PD.
The extraction of information about neural activity timing from BOLD signal is a challenging task as the shape of the BOLD curve does not directly reflect the temporal characteristics of electrical activity of neurons. In this work, we introduce the concept of neural processing time (NPT) as a parameter of the biophysical model of the hemodynamic response function (HRF). Through this new concept we aim to infer more accurately the duration of neuronal response from the highly nonlinear BOLD effect. The face validity and applicability of the concept of NPT are evaluated through simulations and analysis of experimental time series. The results of both simulation and application were compared with summary measures of HRF shape. The experiment that was analyzed consisted of a decision-making paradigm with simultaneous emotional distracters. We hypothesize that the NPT in primary sensory areas, like the fusiform gyrus, is approximately the stimulus presentation duration. On the other hand, in areas related to processing of an emotional distracter, the NPT should depend on the experimental condition. As predicted, the NPT in fusiform gyrus is close to the stimulus duration and the NPT in dorsal anterior cingulate gyrus depends on the presence of an emotional distracter. Interestingly, the NPT in right but not left dorsal lateral prefrontal cortex depends on the stimulus emotional content. The summary measures of HRF obtained by a standard approach did not detect the variations observed in the NPT.
Meditation is a mental training, which involves attention and the ability to maintain focus on a particular object. In this study we have applied a specific attentional task to simply measure the performance of the participants with different levels of meditation experience, rather than evaluating meditation practice per se or task performance during meditation. Our objective was to evaluate the performance of regular meditators and non-meditators during an fMRI adapted Stroop Word-Colour Task (SWCT), which requires attention and impulse control, using a block design paradigm. We selected 20 right-handed regular meditators and 19 non-meditators matched for age, years of education and gender. Participants had to choose the colour (red, blue or green) of single words presented visually in three conditions: congruent, neutral and incongruent. Non-meditators showed greater activity than meditators in the right medial frontal, middle temporal, precentral and postcentral gyri and the lentiform nucleus during the incongruent conditions. No regions were more activated in meditators relative to non-meditators in the same comparison. Non-meditators showed an increased pattern of brain activation relative to regular meditators under the same behavioural performance level. This suggests that meditation training improves efficiency, possibly via improved sustained attention and impulse control.
Adherent umbilical cord blood stromal cells (AUCBSCs) are multipotent cells with differentiation capacities. Therefore, these cells have been investigated for their potential in cell-based therapies. Quantum Dots (QDs) are an alternative to organic dyes and fluorescent proteins because of their long-term photostability. In this study we determined the effects of the cell passage on AUCBSCs morphology, phenotype, and differentiation potential. QDs labeled AUCBSCs in the fourth cell passage were differentiated in the three mesodermal lineages and were evaluated using cytochemical methods and transmission electron microscopy (TEM). Gene and protein expression of the AUCBSCs immunophenotypic markers were also evaluated in the labeled cells by real-time quantitative PCR and flow cytometry. In this study we were able to define the best cellular passage to work with AUCBSCs and we also demonstrated that the use of fluorescent QDs can be an efficient nano-biotechnological tool in differentiation studies because labeled cells do not have their characteristics compromised.
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.
Among nonmotor symptoms observed in Parkinsons disease (PD) dysfunction in the visual system, including hallucinations, has a significant impact in their quality of life. To further explore the visual system in PD patients we designed two fMRI experiments comparing 18 healthy volunteers with 16 PD patients without visual complaints in two visual fMRI paradigms: the flickering checkerboard task and a facial perception paradigm. PD patients displayed a decreased activity in the primary visual cortex (Broadmann area 17) bilaterally as compared to healthy volunteers during flickering checkerboard task and increased activity in fusiform gyrus (Broadmann area 37) during facial perception paradigm. Our findings confirm the notion that PD patients show significant changes in the visual cortex system even before the visual symptoms are clinically evident. Further studies are necessary to evaluate the contribution of these abnormalities to the development visual symptoms in PD.
Despite recent advances, patients with malignant brain tumors still have a poor prognosis. Glioblastoma (WHO grade 4 astrocytoma), the most malignant brain tumor, represents 50% of all astrocytomas, with a median survival rate of <1 year. It is, therefore, extremely important to search for new diagnostic and therapeutic approaches for patients with glioblastoma. This study describes the application of superparamagnetic nanoparticles of iron oxide, as well as monoclonal antibodies, of immunophenotypic significance, conjoined to quantum dots for the ultrastructural assessment of glioblastoma cells. For this proposal, an immunophenotypic study by flow cytometry was carried out, followed by transmission electron microscopy analysis. The process of tumor cell labeling using nanoparticles can successfully contribute to the identification of tumorigenic cells and consequently for better understanding of glioblastoma genesis and recurrence. In addition, this method may help further studies in tumor imaging, diagnosis, and prognostic markers detection.
The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single "representative" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI.
The present study aimed to investigate the presence of corpus callosum (CC) volume deficits in a population-based recent-onset psychosis (ROP) sample, and whether CC volume relates to interhemispheric communication deficits. For this purpose, we used voxel-based morphometry comparisons of magnetic resonance imaging data between ROP (n =122) and healthy control (n = 94) subjects. Subgroups (38 ROP and 39 controls) were investigated for correlations between CC volumes and performance on the Crossed Finger Localization Test (CFLT). Significant CC volume reductions in ROP subjects versus controls emerged after excluding substance misuse and non-right-handedness. CC reductions retained significance in the schizophrenia subgroup but not in affective psychoses subjects. There were significant positive correlations between CC volumes and CFLT scores in ROP subjects, specifically in subtasks involving interhemispheric communication. From these results, we can conclude that CC volume reductions are present in association with ROP. The relationship between such deficits and CFLT performance suggests that interhemispheric communication impairments are directly linked to CC abnormalities in ROP.
The aim of the present work is the presentation of a quantification methodology for the control of the amount of superparamagnetic iron oxide nanoparticles (SPIONs) administered in biological materials by means of the ferromagnetic resonance technique (FMR) applied to studies both in vivo and in vitro. The in vivo study consisted in the analysis of the elimination and biodistribution kinetics of SPIONs after intravenous administration in Wistar rats. The results were corroborated by X-ray fluorescence. For the in vitro study, a quantitative analysis of the concentration of SPIONs bound to the specific AC133 monoclonal antibodies was carried out in order to detect the expression of the antigenic epitopes (CD133) in stem cells from human umbilical cord blood. In both studies FMR has proven to be an efficient technique for the SPIONs quantification per volume unit (in vivo) or per labeled cell (in vitro).
Depression is a frequent non-motor symptom in Parkinsons disease (PD) with increasing rates with the progression of the disease. Molecular imaging studies have shown a reduction of dopamine transporter (DAT) density in depressed PD patients (dPD); however, DAT role in the pathophysiology of PD depression is not clear since clinical matching was inappropriate and DAT reduction could be attributed to PD severity.
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.
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 haemodynamics 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.
To report Magnetic Resonance Imaging (MRI) and/or Magnetic Resonance Spectroscopy (MRS) findings in subjects with hypoxic encephalopathy caused by drowning in recent literature and to compare them with non-specific hypoxic encephalopathy.
The application of functional magnetic resonance imaging (fMRI) in neuroscience studies has increased enormously in the last decade. Although primarily used to map brain regions activated by specific stimuli, many studies have shown that fMRI can also be useful in identifying interactions between brain regions (functional and effective connectivity). Despite the widespread use of fMRI as a research tool, clinical applications of brain connectivity as studied by fMRI are not well established. One possible explanation is the lack of normal patterns and intersubject variability-two variables that are still largely uncharacterized in most patient populations of interest. In the current study, we combine the identification of functional connectivity networks extracted by using Spearman partial correlation with the use of a one-class support vector machine in order construct a normative database. An application of this approach is illustrated using an fMRI dataset of 43 healthy subjects performing a visual working memory task. In addition, the relationships between the results obtained and behavioral data are explored.
Resting state functional magnetic resonance imaging (fMRI) reveals a distinct network of correlated brain function representing a default mode state of the human brain. The underlying structural basis of this functional connectivity pattern is still widely unexplored. We combined fractional anisotropy measures of fiber tract integrity derived from diffusion tensor imaging (DTI) and resting state fMRI data obtained at 3 Tesla from 20 healthy elderly subjects (56 to 83 years of age) to determine white matter microstructure underlying default mode connectivity. We hypothesized that the functional connectivity between the posterior cingulate and hippocampus from resting state fMRI data would be associated with the white matter microstructure in the cingulate bundle and fiber tracts connecting posterior cingulate gyrus with lateral temporal lobes, medial temporal lobes, and precuneus. This was demonstrated at the p<0.001 level using a voxel-based multivariate analysis of covariance (MANCOVA) approach. In addition, we used a data-driven technique of joint independent component analysis (ICA) that uncovers spatial pattern that are linked across modalities. It revealed a pattern of white matter tracts including cingulate bundle and associated fiber tracts resembling the findings from the hypothesis-driven analysis and was linked to the pattern of default mode network (DMN) connectivity in the resting state fMRI data. Our findings support the notion that the functional connectivity between the posterior cingulate and hippocampus and the functional connectivity across the entire DMN is based on distinct pattern of anatomical connectivity within the cerebral white matter.
Depression is the most frequent psychiatric disorder in Parkinsons 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 prefrontal 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.
The histopathological counterpart of white matter hyperintensities is a matter of debate. Methodological and ethical limitations have prevented this question to be elucidated. We want to introduce a protocol applying state-of-the-art methods in order to solve fundamental questions regarding the neuroimaging-neuropathological uncertainties comprising the most common white matter hyperintensities [WMHs] seen in aging. By this protocol, the correlation between signal features in in situ, post mortem MRI-derived methods, including DTI and MTR and quantitative and qualitative histopathology can be investigated. We are mainly interested in determining the precise neuroanatomical substrate of incipient WMHs. A major issue in this protocol is the exact co-registration of small lesion in a tridimensional coordinate system that compensates tissue deformations after histological processing. The protocol is based on four principles: post mortem MRI in situ performed in a short post mortem interval, minimal brain deformation during processing, thick serial histological sections and computer-assisted 3D reconstruction of the histological sections. This protocol will greatly facilitate a systematic study of the location, pathogenesis, clinical impact, prognosis and prevention of WMHs.
Pattern recognition methods have been successfully applied in several functional neuroimaging studies. These methods can be used to infer cognitive states, so-called brain decoding. Using such approaches, it is possible to predict the mental state of a subject or a stimulus class by analyzing the spatial distribution of neural responses. In addition it is possible to identify the regions of the brain containing the information that underlies the classification. The Support Vector Machine (SVM) is one of the most popular methods used to carry out this type of analysis. The aim of the current study is the evaluation of SVM and Maximum uncertainty Linear Discrimination Analysis (MLDA) in extracting the voxels containing discriminative information for the prediction of mental states. The comparison has been carried out using fMRI data from 41 healthy control subjects who participated in two experiments, one involving visual-auditory stimulation and the other based on bi-manual fingertapping sequences. The results suggest that MLDA uses significantly more voxels containing discriminative information (related to different experimental conditions) to classify the data. On the other hand, SVM is more parsimonious and uses less voxels to achieve similar classification accuracies. In conclusion, MLDA is mostly focused on extracting all discriminative information available, while SVM extracts the information which is sufficient for classification.
Previous magnetic resonance imaging (MRI) studies described consistent age-related gray matter (GM) reductions in the fronto-parietal neocortex, insula and cerebellum in elderly subjects, but not as frequently in limbic/paralimbic structures. However, it is unclear whether such features are already present during earlier stages of adulthood, and if age-related GM changes may follow non-linear patterns at such age range. This voxel-based morphometry study investigated the relationship between GM volumes and age specifically during non-elderly life (18-50 years) in 89 healthy individuals (48 males and 41 females). Voxelwise analyses showed significant (p<0.05, corrected) negative correlations in the right prefrontal cortex and left cerebellum, and positive correlations (indicating lack of GM loss) in the medial temporal region, cingulate gyrus, insula and temporal neocortex. Analyses using ROI masks showed that age-related dorsolateral prefrontal volume decrements followed non-linear patterns, and were less prominent in females compared to males at this age range. These findings further support for the notion of a heterogeneous and asynchronous pattern of age-related brain morphometric changes, with region-specific non-linear features.
To assess intracellular labeling and quantification by magnetic resonance imaging using iron oxide magnetic nanoparticles coated with biocompatible materials in rat C6 glioma cells in vitro. These methods will provide direction for future trials of tumor induction in vivo as well as possible magnetic hyperthermia applications.
To describe the Single Photon Emission Microscope (SPEM), a state-of-the-art instrument for small animal SPECT imaging, and characterize its performance presenting typical images of different animal organs.
The objective was to establish a pattern of tumor growth of the C6 model of glioblastoma multiform in Wistar rats via magnetic resonance imaging (MRI) for the subsequent verification of tumor volume reduction due to magnetic hyperthermia therapy.
Multivariate pattern recognition approaches have become a prominent tool in neuroimaging data analysis. These methods enable the classification of groups of participants (e.g. controls and patients) on the basis of subtly different patterns across the whole brain. This study demonstrates that these methods can be used, in combination with automated morphometric analysis of structural MRI, to determine with great accuracy whether a single subject has been engaged in regular mental training or not. The proposed approach allowed us to identify with 94.87% accuracy (p<0.001) if a given participant is a regular meditator (from a sample of 19 regular meditators and 20 non-meditators). Neuroimaging has been a relevant tool for diagnosing neurological and psychiatric impairments. This study may suggest a novel step forward: the emergence of a new field in brain imaging applications, in which participants could be identified based on their mental experience.
Memory deficit is a frequent cognitive disorder following acquired prefrontal cortex lesions. In the present study, we investigated the brain correlates of a short semantic strategy training and memory performance of patients with distinct prefrontal cortex lesions using fMRI and cognitive tests.
Nanoparticles in suspension are often utilized for intracellular labeling and evaluation of toxicity in experiments conducted in vitro. The purpose of this study was to undertake a computational modeling analysis of the deposition kinetics of a magnetite nanoparticle agglomerate in cell culture medium.
Fibromyalgia is a primary brain disorder or a result of peripheral dysfunctions inducing brain alterations, with underlying mechanisms that partially overlap with other painful conditions. Although there are methodologic variations, neuroimaging studies propose neural correlations to clinical findings of abnormal pain modulation in fibromyalgia. Growing evidences of specific differences of brain activations in resting states and pain-evoked conditions confirm clinical hyperalgesia and impaired inhibitory descending systems, and also demonstrate cognitive-affective influences on painful experiences, leading to augmented pain-processing. Functional data of neural activation abnormalities parallel structural findings of gray matter atrophy, alterations of intrinsic connectivity networks, and variations in metabolites levels along multiple pathways. Data from positron-emission tomography, single-photon-emission-computed tomography, blood-oxygen-level-dependent, voxel-based morphometry, diffusion tensor imaging, default mode network analysis, and spectroscopy enable the understanding of fibromyalgia pathophysiology, and favor the future establishment of more tailored treatments.
A computational pipeline combining texture analysis and pattern classification algorithms was developed for investigating associations between high-resolution MRI features and histological data. This methodology was tested in the study of dentate gyrus images of sclerotic hippocampi resected from refractory epilepsy patients. Images were acquired using a simple surface coil in a 3.0T MRI scanner. All specimens were subsequently submitted to histological semiquantitative evaluation. The computational pipeline was applied for classifying pixels according to: a) dentate gyrus histological parameters and b) patients febrile or afebrile initial precipitating insult history. The pipeline results for febrile and afebrile patients achieved 70% classification accuracy, with 78% sensitivity and 80% specificity [area under the reader observer characteristics (ROC) curve: 0.89]. The analysis of the histological data alone was not sufficient to achieve significant power to separate febrile and afebrile groups. Interesting enough, the results from our approach did not show significant correlation with histological parameters (which per se were not enough to classify patient groups). These results showed the potential of adding computational texture analysis together with classification methods for detecting subtle MRI signal differences, a method sufficient to provide good clinical classification. A wide range of applications of this pipeline can also be used in other areas of medical imaging.
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