Partial directed coherence statistical performance characteristics in frequency domain.

In this work we show the asymptotic behavior of information partial directed coherence estimator via the Monte Carlo simulation of a particular toy model taken from the literature. We show that the control of false positive rate tends to the chosen significance level if detection decision is made at specific frequency values.

A comparative study of statistical methods used to identify dependencies between gene expression signals.

One major task in molecular biology is to understand the dependency among genes to model gene regulatory networks. Pearson's correlation is the most common method used to measure dependence between gene expression signals, but it works well only when data are linearly associated. For other types of association, such as non-linear or non-functional relationships, methods based on the concepts of rank correlation and information theory-based measures are more adequate than the Pearson's correlation, but are less used in applications, most probably because of a lack of clear guidelines for their use. This work seeks to summarize the main methods (Pearson's, Spearman's and Kendall's correlations; distance correlation; Hoeffding's D: measure; Heller-Heller-Gorfine measure; mutual information and maximal information coefficient) used to identify dependency between random variables, especially gene expression data, and also to evaluate the strengths and limitations of each method. Systematic Monte Carlo simulation analyses ranging from sample size, local dependence and linear/non-linear and also non-functional relationships are shown. Moreover, comparisons in actual gene expression data are carried out. Finally, we provide a suggestive list of methods that can be used for each type of data set.

Measuring network's entropy in ADHD: a new approach to investigate neuropsychiatric disorders.

The application of graph analysis methods to the topological organization of brain connectivity has been a useful tool in the characterization of brain related disorders. However, the availability of tools, which enable researchers to investigate functional brain networks, is still a major challenge. Most of the studies evaluating brain images are based on centrality and segregation measurements of complex networks. In this study, we applied the concept of graph spectral entropy (GSE) to quantify the complexity in the organization of brain networks. In addition, to enhance interpretability, we also combined graph spectral clustering to investigate the topological organization of sub-network's modules. We illustrate the usefulness of the proposed approach by comparing brain networks between attention deficit hyperactivity disorder (ADHD) patients and the brain networks of typical developing (TD) controls. The main findings highlighted that GSE involving sub-networks comprising the areas mostly bilateral pre and post central cortex, superior temporal gyrus, and inferior frontal gyri were statistically different (p-value=0.002) between ADHD patients and TD controls. In the same conditions, the other conventional graph descriptors (betweenness centrality, clustering coefficient, and shortest path length) commonly used to identify connectivity abnormalities did not show statistical significant difference. We conclude that analysis of topological organization of brain sub-networks based on GSE can identify networks between brain regions previously unobserved to be in association with ADHD.

Discriminating different classes of biological networks by analyzing the graphs spectra distribution.

The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology. Recent studies indicate that some pathologies present topological network alterations relative to norms seen in the general population. Therefore, methods to discriminate the processes that generate the different classes of networks (e.g., normal and disease) might be crucial for the diagnosis, prognosis, and treatment of the disease. It is known that several topological properties of a network (graph) can be described by the distribution of the spectrum of its adjacency matrix. Moreover, large networks generated by the same random process have the same spectrum distribution, allowing us to use it as a "fingerprint". Based on this relationship, we introduce and propose the entropy of a graph spectrum to measure the "uncertainty" of a random graph and the Kullback-Leibler and Jensen-Shannon divergences between graph spectra to compare networks. We also introduce general methods for model selection and network model parameter estimation, as well as a statistical procedure to test the nullity of divergence between two classes of complex networks. Finally, we demonstrate the usefulness of the proposed methods by applying them to (1) protein-protein interaction networks of different species and (2) on networks derived from children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) and typically developing children. We conclude that scale-free networks best describe all the protein-protein interactions. Also, we show that our proposed measures succeeded in the identification of topological changes in the network while other commonly used measures (number of edges, clustering coefficient, average path length) failed.

Alzheimer's disease qEEG: spectral analysis versus coherence. which is the best measurement? / EEGq na doença de Alzheimer: análise espectral versus coerência. O que é melhor?

There is evidence in electroencephalography that alpha, theta and delta band oscillations reflect cognitive and memory performances and that quantitative techniques can improve the electroencephalogram (EEG) sensitivity. This paper presents the results of comparative analysis of qEEG variables as reliable markers for Alzheimer's disease (AD). We compared the sensitivity and specificity between spectral analysis (spectA) and coherence (Coh) within the same group of AD patients. SpectA and Coh were calculated from EEGs of 40 patients with mild to moderate AD and 40 healthy elderly controls. The peak of spectA was smaller in the AD group than in controls. AD group showed predominance of slow spectA in theta and delta bands and a significant reduction of inter-hemispheric Coh for occipital alpha 2 and beta 1 and for frontal delta sub-band. ROC curve supported that alpha band spectA was more sensitive than coherence to differentiate controls from AD.

Há evidências de que as oscilações das bandas teta, alfa e delta no eletroencefalograma podem refletir diferenças na cognição e memória; a sensibilidade deste método diagnóstico pode ser melhorada por técnicas de quantificação. Comparamos a sensibilidade e especificidade entre a análise espectral (spectA) e coerência (Coh) dentro do mesmo grupo de pacientes com doença de Alzheimer (DA) e contra um grupo controle. SpectA e Coh foram calculadas a partir de EEGs de 40 pacientes com DA leve a moderada e 40 idosos saudáveis. O pico do espectro foi menor no grupo DA que nos controles. O grupo DA também apresentou um espectro mais lento nas bandas teta e delta e menor coerência inter-hemisférica para as sub-bandas alfa 2 e beta 1 posterior e delta frontal. A curva ROC suporta que a análise espectral da banda alfa foi mais sensível que a coerência para diferenciar controles de DA.

Alzheimer's disease qEEG: spectral analysis versus coherence. Which is the best measurement?

There is evidence in electroencephalography that alpha, theta and delta band oscillations reflect cognitive and memory performances and that quantitative techniques can improve the electroencephalogram (EEG) sensitivity. This paper presents the results of comparative analysis of qEEG variables as reliable markers for Alzheimer's disease (AD). We compared the sensitivity and specificity between spectral analysis (spectA) and coherence (Coh) within the same group of AD patients. SpectA and Coh were calculated from EEGs of 40 patients with mild to moderate AD and 40 healthy elderly controls. The peak of spectA was smaller in the AD group than in controls. AD group showed predominance of slow spectA in theta and delta bands and a significant reduction of inter-hemispheric Coh for occipital alpha 2 and beta 1 and for frontal delta sub-band. ROC curve supported that alpha band spectA was more sensitive than coherence to differentiate controls from AD.

Asymptotic behavior of generalized partial directed coherence.

This paper examines the asymptotic behavior of a newly defined general form of partial directed coherence. Both confidence interval and null hypothesis testing results are presented and illustrated.

Hyperdopaminergia and NMDA receptor hypofunction disrupt neural phase signaling.

Neural phase signaling has gained attention as a putative coding mechanism through which the brain binds the activity of neurons across distributed brain areas to generate thoughts, percepts, and behaviors. Neural phase signaling has been shown to play a role in various cognitive processes, and it has been suggested that altered phase signaling may play a role in mediating the cognitive deficits observed across neuropsychiatric illness. Here, we investigated neural phase signaling in two mouse models of cognitive dysfunction: mice with genetically induced hyperdopaminergia [dopamine transporter knock-out (DAT-KO) mice] and mice with genetically induced NMDA receptor hypofunction [NMDA receptor subunit-1 knockdown (NR1-KD) mice]. Cognitive function in these mice was assessed using a radial-arm maze task, and local field potentials were recorded from dorsal hippocampus and prefrontal cortex as DAT-KO mice, NR1-KD mice, and their littermate controls engaged in behavioral exploration. Our results demonstrate that both DAT-KO and NR1-KD mice display deficits in spatial cognitive performance. Moreover, we show that persistent hyperdopaminergia alters interstructural phase signaling, whereas NMDA receptor hypofunction alters interstructural and intrastructural phase signaling. These results demonstrate that dopamine and NMDA receptor dependent glutamate signaling play a critical role in coordinating neural phase signaling, and encourage further studies to investigate the role that deficits in phase signaling play in mediating cognitive dysfunction.

Disclosure of the diagnosis of Alzheimer's disease: caregivers' opinions in a Brazilian sample.

BACKGROUND: Disclosure of the diagnosis of Alzheimer's disease (AD) remains a contentious issue, and has been little studied in developing countries. OBJECTIVE: To investigate the influence of socio-demographic factors and the experience of being a caregiver on opinion about disclosing AD diagnosis to the patient in a Brazilian sample. METHOD: Caregivers of 50 AD patients together with 50 control participants that did not have the experience of being a caregiver of AD patient were interviewed using a structured questionnaire. RESULTS: Most of the participants (73.0%) endorsed disclosure of the diagnosis, while caregivers were less prone to disclose (58.0%) than controls (88.0%; p=0.0007). Logistic regression confirmed that only the experience of being a caregiver was associated with a lesser tendency for disclosure endorsement. CONCLUSION: The majority of participants was in favor of disclosing the diagnosis, but caregivers were less willing to disclose the diagnosis to the AD patient.

Disclosure of the diagnosis of Alzheimer's disease: caregivers' opinions in a Brazilian sample / A revelação do diagnóstico de doença de Alzheimer: opiniões de cuidadores em uma amostra brasileira

BACKGROUND: Disclosure of the diagnosis of Alzheimer's disease (AD) remains a contentious issue, and has been little studied in developing countries. OBJECTIVE: To investigate the influence of socio-demographic factors and the experience of being a caregiver on opinion about disclosing AD diagnosis to the patient in a Brazilian sample. METHOD: Caregivers of 50 AD patients together with 50 control participants that did not have the experience of being a caregiver of AD patient were interviewed using a structured questionnaire. RESULTS: Most of the participants (73.0 percent) endorsed disclosure of the diagnosis, while caregivers were less prone to disclose (58.0 percent) than controls (88.0 percent; p=0.0007). Logistic regression confirmed that only the experience of being a caregiver was associated with a lesser tendency for disclosure endorsement. CONCLUSION: The majority of participants was in favor of disclosing the diagnosis, but caregivers were less willing to disclose the diagnosis to the AD patient.

FUNDAMENTO: A revelação do diagnóstico de doença de Alzheimer (DA) tem sido tema polêmico e pouco estudado em países em desenvolvimento. OBJETIVO: Investigar a influência de fatores sócio-demográficos e a experiência de ter sido cuidador na opinião sobre a revelação do diagnóstico em uma amostra brasileira. MÉTODO: Cuidadores de 50 pacientes com DA e 50 indívíduos controle que não tinham tido experiência como cuidadores de pacientes com DA foram entrevistados com o uso de um questionário estruturado. RESULTADOS: A maioria dos participantes (73,0 por cento) manifestou-se a favor da revelação diagnóstico aos pacientes, mas cuidadores foram menos favoráveis (58,0 por cento) que controles (88,0 por cento; p=0,0007). Regressão logística demonstrou que apenas a experiência como cuidador foi associada com menor tendência a apoiar a revelação do diagnóstico. CONCLUSÃO: A maioria dos participantes foi a favor da revelação do diagnóstico ao paciente, mas aqueles com experiência como cuidadores de pacientes com DA foram menos favoráveis.

Comparison of virtual cystoscopy and transabdominal ultrasonography with conventional cystoscopy for bladder tumor detection.

PURPOSE: We compare virtual cystoscopy (VC) and transabdominal ultrasonography (US) with conventional cystoscopy (CC),the gold standard, for detection of bladder tumors. PATIENTS AND METHODS: Forty-five patients suspected to have bladder neoplasms were evaluated prospectively.They underwent transabdominal US, followed by VC and CC. We compared sensitivity and specificity of US and VC and their positive and negative likelihood ratios. US and VC detection rates for tumors

qEEG spectral peak in Alzheimer's disease: A possible tool for treatment follow-up.

qEEG spectral analysis has been considered highly sensitive to cortical functional changes and agrees strongly with the clinical diagnosis of AD. The sensitivity of spectral analysis has ranged from 71% to 81% in several studies.1-3. OBJECTIVE: The aim of this study was to retrospectively evaluate whether alpha qEEG spectral peak can supplement clinical examination by constituting an independent tool to monitor treatment and follow-up of dementia progression in Alzheimer's disease (AD). In addition, we examined the demographic data and alpha power spectra distribution of patients and elderly normal controls. METHODS: qEEGs were selected from 2 groups of patients: normal controls (n=30), and patients who fulfilled criteria for mild probable AD diagnosis (n=41). The alpha qEEG spectral analysis and MMSE were performed once or twice a year. RESULTS: In our groups, MMSE scores and qEEG alpha spectral peak were unchanged (no statistical differences) after anticholinesterase use where qEEG spectral peak was never lower than 8 Hz in the control group. CONCLUSION: This study supports two important concepts. First, 8 Hz alpha appears to be the lowest awake spectral peak compatible with normality. And finally, in a clinical context, qEEG is a valuable diagnostic tool that could prove useful for Dementia follow-up.

A análise espectral do EEG tem sido considerada muito sensível para mudanças da função cortical e compatível com o diagnóstico clínico da Doença de Alzheimer (DA). A sensibilidade da análise espectral varia de 71% a 81% em alguns estudos.1-3. OBJETIVO: A proposta deste estudo foi uma avaliação retrospectiva sobre a possibilidade do pico espectral do alfa no EEG quantitativo (EEGq) complementar o exame clínico fornecendo uma ferramenta independente para monitorizar o tratamento e para seguimento da progressão da demência na DA. Além disso, foram examinados dados demográficos e a distribuição do espectro da potência alfa de pacientes e controles da mesma idade. MÉTODOS: EEGq foram selecionados de dois grupos de pacientes: os controles sem alterações e queixas de memória (n=30) e os pacientes com critérios preenchidos para DA provável (n=41). A análise do pico espectral do alfa no EEGq e o Mini-Exame do Estado Mental foram realizados uma ou duas vezes no ano. RESULTADOS: Neste grupo estudado, o Mini-Exame do Estado Mental e o pico espectral do alfa no EEGq não foram estatisticamente diferentes depois do uso de anticolinesterásicos e o pico espectral do EEGq não foi menor do que 8 Hz em todos indivíduos do grupo controle. CONCLUSÃO: Este estudo sustenta dois conceitos importantes. Primeiro, 8 Hz de pico espectral de alfa, em vigília, aparenta ser o menor valor compatível com normalidade. E finalmente, em contexto clínico, EEGq é uma ferramenta que pode ser útil no seguimento da de Demência.

Alzheimer's disease diagnosis disclosure in Brazil: a survey of specialized physicians' current practice and attitudes.

BACKGROUND: There is little, though growing, interest in the research area of attitudes held among physicians towards disclosing the diagnosis of dementia and Alzheimer's disease (AD), or the current practice on AD disclosure. This study aimed to investigate the practice and attitudes of specialized physicians towards AD diagnosis disclosure in Brazil. METHODS: A questionnaire was devised to survey the current practice and attitudes regarding diagnosis disclosure of AD in Brazil and sent to specialized physicians (170 geriatricians, 300 neurologists and 500 psychiatrists) by electronic mail. RESULTS: From 970 potential respondents, 181 physicians who usually attend AD patients returned the questionnaire. There were no significant differences between the three specialties regarding the frequency with which they informed patients of their AD diagnosis (p = 0.17). The results revealed that only 44.8% of the physicians would regularly inform the patient of the diagnosis, although 85.6% of these use clear terminology. Despite their usual practice, 76.8% would want to know their diagnosis if they themselves were affected by AD. CONCLUSIONS: Disclosure of AD diagnosis is not common among specialized physicians in Brazil and different factors are involved. In the clinical context, discussion on advantages of diagnosis disclosure can be useful for improving the care of AD patients and their families.

A method to produce evolving functional connectivity maps during the course of an fMRI experiment using wavelet-based time-varying Granger causality.

Functional magnetic resonance imaging (fMRI) is widely used to identify neural correlates of cognitive tasks. However, the analysis of functional connectivity is crucial to understanding neural dynamics. Although many studies of cerebral circuitry have revealed adaptative behavior, which can change during the course of the experiment, most of contemporary connectivity studies are based on correlational analysis or structural equations analysis, assuming a time-invariant connectivity structure. In this paper, a novel method of continuous time-varying connectivity analysis is proposed, based on the wavelet expansion of functions and vector autoregressive model (wavelet dynamic vector autoregressive-DVAR). The model also allows identification of the direction of information flow between brain areas, extending the Granger causality concept to locally stationary processes. Simulation results show a good performance of this approach even using short time intervals. The application of this new approach is illustrated with fMRI data from a simple AB motor task experiment.

Intervention models in functional connectivity identification applied to FMRI.

Recent advances in neuroimaging techniques have provided precise spatial localization of brain activation applied in several neuroscience subareas. The development of functional magnetic resonance imaging (fMRI), based on the BOLD signal, is one of the most popular techniques related to the detection of neuronal activation. However, understanding the interactions between several neuronal modules is also an important task, providing a better comprehension about brain dynamics. Nevertheless, most connectivity studies in fMRI are based on a simple correlation analysis, which is only an association measure and does not provide the direction of information flow between brain areas. Other proposed methods like structural equation modeling (SEM) seem to be attractive alternatives. However, this approach assumes prior information about the causality direction and stationarity conditions, which may not be satisfied in fMRI experiments. Generally, the fMRI experiments are related to an activation task; hence, the stimulus conditions should also be included in the model. In this paper, we suggest an intervention analysis, which includes stimulus condition, allowing a nonstationary modeling. Furthermore, an illustrative application to real fMRI dataset from a simple motor task is presented.

Avaliação da complexidade da dinâmica cardiovascular por entropia amostral / Evaluating cardiovascular dynamic complexity using sample entropy

Até os anos 1990 acreditava-se que para manter uma homeostase adequada era preciso que o sistema cardiovascular obedecesse a um ritmo regular, ou seja, um "bom coração" seria aquele capaz de manter um ritmo regular de pouca variabilidade. Contudo, novas abordagens oriundas do estudo de sistemas dinâmicos não-lineares trouxeram evidências teóricas e experimentais mostrando exatamente o contrário: maior adaptabilidade homeostática relaciona-se com uma maior capacidade do sistema cardiovascular em gerar padrões de ritmicidade mais erráticos, de maior complexidade. Assim conjectura-se que um sistema cardiovascular avaliado em repouso, com um padrão dinâmico mais complexo e menos regular, disponha de uma faixa dinâmica mais ampla de adaptação permitindo melhor regulação homeostática. Neste trabalho, demonstra-se a utilidade de medida estatística simples para estimar o grau de complexidade do padrão temporal de ritmicidade cardíaca, denominada entro pia amostral, aplicada a dados do repositório PhysioBank, disponíveis na Internet. Mostra-se que ela declina com a idade e que é menor em pacientes com insuficiência cardíaca congestiva. Por ser facilmente acessível aos clínicos perante a disponibilidade universal de sistemas digitais de monitoração, sugere-se o uso de entropia amostral em protocolos clínicos de hipertensão arterial para, por exemplo, avaliar os efeitos de diversos medicamentos anti-hipertensivos ou de exercícios físicos sobre o padrão de complexidade da dinâmica cardiovascular, analisado em diversas escalas de tempo

Mortality from dementia in a community-dwelling Brazilian population.

BACKGROUND: The influence of dementia on mortality has not yet been reported for a Latin American country. OBJECTIVES: To evaluate the influence of dementia on mortality of a community-dwelling elderly population in Brazil, and to verify the extent to which the diagnosis of dementia is reported on death certificates. METHODS: A cohort of 1,656 individuals, aged 65 and over, was screened for dementia at their domiciles, in 1997. The same population was re-evaluated in 2000, and information on deaths was obtained from relatives and from the municipal obituary service. Kaplan-Meier curves were used for the survival analysis, and the mortality risk ratio (MMR) was calculated using Cox proportional hazards models. RESULTS: We obtained data from 1,393 subjects, corresponding to 84.1% of the target population. The number of deaths was 58 (51.3%) among the patients with dementia and 163 (12.7%) among those without dementia in 1997 (p <0.0001). Dementia and Alzheimer's disease (AD) decreased survival, with hazards ratios of 5.16 [95% Confidence Interval (CI): 3.74-7.12] for dementia and 4.76 (95% CI: 3.16-7.18) for AD. The Cox proportional hazards model identified dementia (MMR=3.92, 95% CI: 2.80-5.48) as the most significant predictor of death, followed by age, history of stroke, complaints of visual impairment and heart failure and by severe arterial hypertension in the baseline evaluation. Dementia and/or AD were mentioned in only 12.5% of the death certificates of individuals with dementia. CONCLUSIONS: Dementia causes a significant decrease in survival, and the diagnosis of dementia is rarely reported on death certificates in Brazil.