Frequency Domain Connectivity Identification: An Application of Partial Directed Coherence in fMRI

Functional magnetic resonance imaging (fMRI) has become an important tool in Neuroscience due to its noninvasive and high spatial resolution properties compared to other methods like PET or EEG. Characterization of the neural connectivity has been the aim of several cognitive researches, as the interactions among cortical areas lie at the heart of many brain dysfunctions and mental disorders. Several methods like correlation analysis, structural equation modeling, and dynamic causal models have been proposed to quantify connectivity strength. An important concept related to connectivity modeling is Granger causality, which is one of the most popular definitions for the measure of directional dependence between time series. In this article, we propose the application of the partial directed coherence (PDC) for the connectivity analysis of multisubject fMRI data using multivariate bootstrap. PDC is a frequency domain counterpart of Granger causality and has become a very prominent tool in EEG studies. The achieved frequency decomposition of connectivity is useful in separating interactions from neural modules from those originating in scanner noise, breath, and heart beating. Real fMRI dataset of six subjects executing a language processing protocol was used for the analysis of connectivity. Hum Brain Mapp 30:452-461, 2009. (C) 2007 Wiley-Liss, Inc.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

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. (c) 2010 Elsevier Inc. All rights reserved.

Abnormal Visual Activation in Parkinson`s Disease Patients

Among nonmotor symptoms observed in Parkinson`s 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 gyms (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. (C) 2010 Movement Disorder Society

Abnormally increased effective connectivity between parahippocampal gyrus and ventromedial prefrontal regions during emotion labeling in bipolar disorder

Emotional liability and mood dysregulation characterize bipolar disorder (BID), yet no study has examined effective connectivity between parahippocampal gyrus and prefrontal cortical regions in ventromedial and dorsal/lateral neural systems subserving mood regulation in BD. Participants comprised 46 individuals (age range: 18-56 years): 21 with a DSM-IV diagnosis of BID, type I currently remitted; and 25 age- and gender-matched healthy controls (HC). Participants performed an event-related functional magnetic resonance imaging paradigm, viewing mild and intense happy and neutral faces. We employed dynamic causal modeling (I)CM) to identify significant alterations in effective connectivity between BD and HC. Bayes model selection was used to determine the best model. The right parahippocampal gyrus (PHG) and right subgenual cingulate gyrus (sgCG) were included as representative regions of the ventromedial neural system. The right dorsolateral prefrontal cortex (DLPFC) region was included as representative of the dorsal/lateral neural system. Right PHG-sgCG effective connectivity was significantly greater in BD than HC, reflecting more rapid, forward PHG-sgCG signaling in BD than HC. There was no between-group difference in sgCG-DLPFC effective connectivity. In BD, abnormally increased right PHG-sgCG effective connectivity and reduced right PHG activity to emotional stimuli suggest a dysfunctional ventromedial neural system implicated in early stimulus appraisal, encoding and automatic regulation of emotion that may represent a pathophysiological functional neural mechanism for mood dysregulation in BD. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

Prefrontal cortical and striatal activity to happy and fear faces in bipolar disorder is associated with comorbid substance abuse and eating disorder

Background: The spectrum approach was used to examine contributions of comorbid symptom dimensions of substance abuse and eating disorder to abnormal prefrontal-cortical and subcortical-striatal activity to happy and fear faces previously demonstrated in bipolar disorder (BD). Method: Fourteen remitted BD-type I and sixteen healthy individuals viewed neutral, mild and intense happy and fear faces in two event-related fMRI experiments. All individuals completed Substance-Use and Eating-Disorder Spectrum measures. Region-of-Interest analyses for bilateral prefrontal and subcortical-striatal regions were performed. Results: BD individuals scored significantly higher on these spectrum measures than healthy individuals (p<0.05), and were distinguished by activity in prefrontal and subcortical-striatal regions. BD relative to healthy individuals showed reduced dorsal prefrontal-cortical activity to all faces. Only BD individuals showed greater subcortical-striatal activity to happy and neutral faces. In BD individuals, negative correlations were shown between substance use severity and right PFC activity to intense happy faces (p<0.04), and between substance use severity and right caudate nucleus activity to neutral faces (p<0.03). Positive correlations were shown between eating disorder and right ventral putamen activity to intense happy (p<0.02) and neutral faces (p<0.03). Exploratory analyses revealed few significant relationships between illness variables and medication upon neural activity in BID individuals. Limitations: Small sample size of predominantly medicated BD individuals. Conclusion: This study is the first to report relationships between comorbid symptom dimensions of substance abuse and eating disorder and prefrontal-cortical and subcortical-striatal activity to facial expressions in BD. Our findings suggest that these comorbid features may contribute to observed patterns of functional abnormalities in neural systems underlying mood regulation in BD. (C) 2009 Elsevier B.V. All rights reserved.

Abnormal Amygdala-Prefrontal Effective Connectivity to Happy Faces Differentiates Bipolar from Major Depression

Background: Bipolar disorder is frequently misdiagnosed as major depressive disorder, delaying appropriate treatment and worsening outcome for many bipolar individuals. Emotion dysregulation is a core feature of bipolar disorder. Measures of dysfunction in neural systems supporting emotion regulation might therefore help discriminate bipolar from major depressive disorder. Methods: Thirty-one depressed individuals-15 bipolar depressed (BD) and 16 major depressed (MDD), DSM-IV diagnostic criteria, ages 18-55 years, matched for age, age of illness onset, illness duration, and depression severity-and 16 age- and gender-matched healthy control subjects performed two event-related paradigms: labeling the emotional intensity of happy and sad faces, respectively. We employed dynamic causal modeling to examine significant among-group alterations in effective connectivity (EC) between right- and left-sided neural regions supporting emotion regulation: amygdala and orbitomedial prefrontal cortex (OMPFC). Results: During classification of happy faces, we found profound and asymmetrical differences in EC between the OMPFC and amygdala. Left-sided differences involved top-down connections and discriminated between depressed and control subjects. Furthermore, greater medication load was associated with an amelioration of this abnormal top-down EC. Conversely, on the right side the abnormality was in bottom-up EC that was specific to bipolar disorder. These effects replicated when we considered only female subjects. Conclusions: Abnormal, left-sided, top-down OMPFC-amygdala and right-sided, bottom-up, amygdala-OMPFC EC during happy labeling distinguish BD and MDD, suggesting different pathophysiological mechanisms associated with the two types of depression.

Escitalopram prolonged fear induced by simulated public speaking and released hypothalamic-pituitary-adrenal axis activation

Simulated public speaking (SPS) test is sensitive to drugs that interfere with serotonin-mediated neurotransmission and is supposed to recruit neural systems involved in panic disorder. The study was aimed at evaluating the effects of escitalopram, the most selective serotonin-selective reuptake inhibitor available, in SPS. Healthy males received, in a double-blind, randomized design, placebo (n = 12), 10 (n = 17) or 20 (n = 14) mg of escitalopram 2 hours before the test. Behavioural, autonomic and neuroendocrine measures were assessed. Both doses of escitalopram did not produce any effect before or during the speech but prolonged the fear induced by SPS. The test itself did not significantly change cortisol and prolactin levels but under the higher dose of escitalopram, cortisol and prolactin increased immediately after SPS. This fear-enhancing effect of escitalopram agrees with previously reported results with less selective serotonin reuptake inhibitors and the receptor antagonist ritanserin, indicating that serotonin inhibits the fear of speaking in public.

Human cortical processing of colour and pattern

The present study investigates human visual processing of simple two-colour patterns using a delayed match to sample paradigm with positron emission tomography (PET). This study is unique in that we specifically designed the visual stimuli to be the same for both pattern and colour recognition with all patterns being abstract shapes not easily verbally coded composed of two-colour combinations. We did this to explore those brain regions required for both colour and pattern processing and to separate those areas of activation required for one or the other. We found that both tasks activated similar occipital regions, the major difference being more extensive activation in pattern recognition. A right-sided network that involved the inferior parietal lobule, the head of the caudate nucleus, and the pulvinar nucleus of the thalamus was common to both paradigms. Pattern recognition also activated the left temporal pole and right lateral orbital gyrus, whereas colour recognition activated the left fusiform gyrus and several right frontal regions. (C) 2001 Wiley-Liss, Inc.

Detection and description of non-linear interdependence in normal multichannel human EEG data

Objectives: This study examines human scalp electroencephalographic (EEG) data for evidence of non-linear interdependence between posterior channels. The spectral and phase properties of those epochs of EEG exhibiting non-linear interdependence are studied. Methods: Scalp EEG data was collected from 40 healthy subjects. A technique for the detection of non-linear interdependence was applied to 2.048 s segments of posterior bipolar electrode data. Amplitude-adjusted phase-randomized surrogate data was used to statistically determine which EEG epochs exhibited non-linear interdependence. Results: Statistically significant evidence of non-linear interactions were evident in 2.9% (eyes open) to 4.8% (eyes closed) of the epochs. In the eyes-open recordings, these epochs exhibited a peak in the spectral and cross-spectral density functions at about 10 Hz. Two types of EEG epochs are evident in the eyes-closed recordings; one type exhibits a peak in the spectral density and cross-spectrum at 8 Hz. The other type has increased spectral and cross-spectral power across faster frequencies. Epochs identified as exhibiting non-linear interdependence display a tendency towards phase interdependencies across and between a broad range of frequencies. Conclusions: Non-linear interdependence is detectable in a small number of multichannel EEG epochs, and makes a contribution to the alpha rhythm. Non-linear interdependence produces spatially distributed activity that exhibits phase synchronization between oscillations present at different frequencies. The possible physiological significance of these findings are discussed with reference to the dynamical properties of neural systems and the role of synchronous activity in the neocortex. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

A marcha: a influência do Gerador de Padrão Central

A marcha é influenciada por um conjunto de factores que resultam da interacção e organização própria de sistemas neurais e mecânicos, entre os quais, da dinâmica músculo-esquelética, da modulação pelos centros nervosos superiores, pela modulação aferente e é, também, assumida como sendo controlada pelo Gerador de Padrão Central (GPC), que se define como um programa central baseado num circuito espinal geneticamente determinado, capaz de produzir um ritmo associado a cada marcha. Apresenta-se como objectivo deste trabalho abordar quais os modelos explicativos para o funcionamento do GPC e qual a evidência científica, que continua a ter muitas divergências.

A marcha: a influência do Gerador de Padrão Central

A marcha é influenciada por um conjunto de factores que resultam da interacção e organização própria de sistemas neurais e mecânicos, entre os quais, da dinâmica músculo-esquelética, da modulação pelos centros nervosos superiores, pela modulação aferente e é, também, assumida como sendo controlada pelo Gerador de Padrão Central (GPC), que se define como um programa central baseado num circuito espinal geneticamente determinado, capaz de produzir um ritmo associado a cada marcha. Apresenta-se como objectivo deste trabalho abordar quais os modelos explicativos para o funcionamento do GPC e qual a evidência científica, que continua a ter muitas divergências.

Sistemas Modulares de Escoramento para Estruturas de Contenção Enterradas

No presente trabalho apresentam-se estudos desenvolvidos com o objetivo de análise, conceção e dimensionamento de sistemas de escoramentos metálicos modulares e reaproveitáveis a usar como alternativa técnica e económica em estruturas de contenção periférica. O sistema concebido aplicouse a um caso concreto de uma escavação urbana executada no centro de Luanda, Angola. O projeto começou a ser estudado tendo em conta os estudos geológicos e geotécnicos do terreno em causa, e posteriormente foi estudada a solução construtiva elaborada. Feito o estudo sobre a obra que se realizou com uma parede moldada e ancoragens pré-esforçadas, foi possível, a partir dai, elaborar estudos com outro tipo de sistemas de apoio. Assim, realizaram-se estudos para sistemas de apoio com escoramento linear; colunas metálicas e por uma treliça. Posteriormente, de forma a completar, complementar e poder comparar toda a pesquisa, foram efetuados mais quatro estudos, sendo os sistemas de apoio constituídos por colunas metálicas e/ou tubos circulares ou retangulares em forma elíptica no terreno do projeto e num terreno em forma de quadrado perfeito. Através dos vários estudos foi possível comparar os resultados e perceber qual será a melhor forma de otimização para futuras obras. Foi gerado um método de escoramento, que é possível ser utilizado tendo em conta as particularidades de cada obra, constituído por perfis metálicos com dimensões standard formando elipses ou círculos, conforme a forma do terreno. De maneira a finalizar este projeto foram estudados vários tipos de ligações, quer entre perfis, quer para os perfis e a parede, como também os perfis e os apoios verticais, caso sejam necessários. Como conclusão, e de forma expedita foi analisado o custo direto que apenas abrange a quantidade de aço utilizada para cada tipo de apoio dimensionado, comparando a escavação do projeto em causa com a escavação quadrada.

Morphological development of Corydoras aff. paleatus (Siluriformes, Callichthyidae) and correlation with the emergence of motor and social behaviors

Here we examine major anatomical characteristics of Corydoras aff. paleatus (Jenyns, 1842) post-hatching development, in parallel with its neurobehavioral evolution. Eleutheroembryonic phase, 4.3-8.8 days post-fertilization (dpf); 4.3-6.4 mm standard length (SL) encompasses from hatching to transition to exogenous feeding. Protopterygiolarval phase (8.9-10.9 dpf; 6.5-6.7 mm SL) goes from feeding transition to the commencement of unpaired fin differentiation, which marks the start of pterygiolarval phase (11-33 dpf; 6.8-10.7 mm SL) defined by appearance of lepidotrichia in the dorsal part of the median finfold. This phase ends with the full detachment and differentiation of unpaired fins, events signaling the commencement of the juvenile period (34-60 dpf; 10.8-18.0 mm SL). Eleutheroembryonic phase focuses on hiding and differentiation of mechanosensory, chemosensory and central neural systems, crucial for supplying the larval period with efficient escape and nutrient detection-capture neurocircuits. Protopterygiolarval priorities include visual development and respiratory, digestive and hydrodynamic efficiencies. Pterygiolarval priorities change towards higher swimming efficacy, including carangiform and vertical swimming, necessary for the high social interaction typical of this species. At the end of the protopterygiolarval phase, simple resting and foraging aggregations are seen. Resting and foraging shoals grow in complexity and participant number during pterygiolarval phase, but particularly during juvenile period.

Synchronization of EEG: bivariate and multivariate measures.

Synchronization behavior of electroencephalographic (EEG) signals is important for decoding information processing in the human brain. Modern multichannel EEG allows a transition from traditional measurements of synchronization in pairs of EEG signals to whole-brain synchronization maps. The latter can be based on bivariate measures (BM) via averaging over pair-wise values or, alternatively, on multivariate measures (MM), which directly ascribe a single value to the synchronization in a group. In order to compare BM versus MM, we applied nine different estimators to simulated multivariate time series with known parameters and to real EEGs.We found widespread correlations between BM and MM, which were almost frequency-independent for all the measures except coherence. The analysis of the behavior of synchronization measures in simulated settings with variable coupling strength, connection probability, and parameter mismatch showed that some of them, including S-estimator, S-Renyi, omega, and coherence, aremore sensitive to linear interdependences,while others, like mutual information and phase locking value, are more responsive to nonlinear effects. Onemust consider these properties together with the fact thatMM are computationally less expensive and, therefore, more efficient for the large-scale data sets than BM while choosing a synchronization measure for EEG analysis.

Controversies about the enhanced vulnerability of the adolescent brain to develop addiction.

Adolescence, defined as a transition phase toward autonomy and independence, is a natural time of learning and adjustment, particularly in the setting of long-term goals and personal aspirations. It also is a period of heightened sensation seeking, including risk taking and reckless behaviors, which is a major cause of morbidity and mortality among teenagers. Recent observations suggest that a relative immaturity in frontal cortical neural systems may underlie the adolescent propensity for uninhibited risk taking and hazardous behaviors. However, converging preclinical and clinical studies do not support a simple model of frontal cortical immaturity, and there is substantial evidence that adolescents engage in dangerous activities, including drug abuse, despite knowing and understanding the risks involved. Therefore, a current consensus considers that much brain development during adolescence occurs in brain regions and systems that are critically involved in the perception and evaluation of risk and reward, leading to important changes in social and affective processing. Hence, rather than naive, immature and vulnerable, the adolescent brain, particularly the prefrontal cortex, should be considered as prewired for expecting novel experiences. In this perspective, thrill seeking may not represent a danger but rather a window of opportunities permitting the development of cognitive control through multiple experiences. However, if the maturation of brain systems implicated in self-regulation is contextually dependent, it is important to understand which experiences matter most. In particular, it is essential to unveil the underpinning mechanisms by which recurrent adverse episodes of stress or unrestricted access to drugs can shape the adolescent brain and potentially trigger life-long maladaptive responses.