Brain dynamics of mild cognitive impairment during face encoding

Brain oscillations are closely correlated with human information processing and fundamental aspects of cognition. Previous literature shows that due to the relation between brain oscillations and memory processes, spectral dynamics during such tasks are good candidates to study and characterize memory related pathologies. Mild cognitive impairment (MCI), defined as a clinical condition characterized by memory impairment and/ or deterioration of additional cognitive domains, is considered a preliminary stage in the dementia process. In consequence, the study of its brain patterns could help to achieve an early diagnosis of Alzheimer Disease.

HERMES: A user-friendly connectivity analysis software

The analysis of the interdependence between time series has become an important field of research, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, and the introduction of concepts such as Generalized (GS) and Phase synchronization (PS). This increase in the number of approaches to tackle the existence of the so-called functional (FC) and effective connectivity (EC) (Friston 1994) between two, (or among many) neural networks, along with their mathematical complexity, makes it desirable to arrange them into a unified toolbox, thereby allowing neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of them.

Resting state functional connectivity patterns associated with ApoE genotype. A MEG study in Mild Cognitive Impairment (MCI)

Alteration of brain communication due to abnormal patterns of synchronization is nowadays one of the most suitable mechanisms for having a better understanding of brain pathologies. Very recently, it has been proved that abnormal changes in both local and long range functional interactions underlie the cognitive deficits associated with different brain disorders. Mild cognitive impairment (MCI) is a state characterized for cognitive dysfunction, such as the memory. The study of the spatial and dynamic alterations in MCI subjects' functional networks could provide important evidences of the brain mechanisms responsible for such impairment.

HERMES: Towards an Integrated Toolbox to Characterize Functional and Effective Brain Connectivity

The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ‘traditional’ set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified-easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis.

Mild cognitive impairment subtypes: An MEG study

Previous studies of the dementia continuum have characterized the early disruption of the brain oscillatory activity at the stage of Mild cognitive impairment (MCI). Reduction in power in posterior regions in the alpha band has been one of the landmarks of the Alzheimer Disease accompanied by the anteriorization of the theta band power. However, little is known about the neurophysiological differences between single and multidomain MCI patients.Our goal is to study the differences in oscillatory magnetic activity between amnestic single and multidomain MCI. This will allow us to test whether the effect of the impairment in a single cognitive domain or in a more widespread functional impairment can be reflected in specific neurophysiological profiles.

HERMES: towards an integrated toolbox to characterize functional and effective brain connectivity

The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ?traditional? set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified, easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis.

Functional hubs in mild cognitive impairment

We investigate how hubs of functional brain networks are modified as a result of mild cognitive impairment (MCI), a condition causing a slight but noticeable decline in cognitive abilities, which sometimes precedes the onset of Alzheimer's disease. We used magnetoencephalography (MEG) to investigate the functional brain networks of a group of patients suffering from MCI and a control group of healthy subjects, during the execution of a short-term memory task. Couplings between brain sites were evaluated using synchronization likelihood, from which a network of functional interdependencies was constructed and the centrality, i.e. importance, of their nodes was quantified. The results showed that, with respect to healthy controls, MCI patients were associated with decreases and increases in hub centrality respectively in occipital and central scalp regions, supporting the hypothesis that MCI modifies functional brain network topology, leading to more random structures.

Dynamics of brain networks in aesthetic appreciation

Neuroimage experiments have been essential for identifying active brain networks. During cognitive tasks as in, e.g., aesthetic appreciation, such networks include regions that belong to the default mode network (DMN). Theoretically, DMN activity should be interrupted during cognitive tasks demanding attention, as is the case for aesthetic appreciation. Analyzing the functional connectivity dynamics along three temporal windows and two conditions, beautiful and not beautiful stimuli, here we report experimental support for the hypothesis that aesthetic appreciation relies on the activation of two different networks, an initial aesthetic network and a delayed aesthetic network, engaged within distinct time frames. Activation of the DMN might correspond mainly to the delayed aesthetic network. We discuss adaptive and evolutionary explanations for the relationships existing between the DMN and aesthetic networks and offer unique inputs to debates on the mind/brain interaction.

Cognitive reserve benefits brain efficiency in healthy aging

The concept of cognitive reserve (CR) describes the mind’s resistance to the progressive damage of the brain and probably this can be reflected as the ability to recruit brain networks in an effective way. It is as- sociated with the abilityto copewith the deleterious effects of brain damage,brain degeneration, or age-related changes on cognitive performance.

MEG networks organization is related to white matter integrity

Many studies have assessed the characterization of anatomical or functional connectivity in mild cognitive impairment (MCI), however it is still unknown how they are related in the course of the pathology. Here we integrate the analysis of magnetoencephalographic (MEG) data with white matter (WM) integrity quantification from diffusion weighted imaging (DWI), to asses whether the damage in the WM tracts disrupt the organization of the functional networks.

Cognitive reserve is associated with the functional organization of brain networks in healthy aging: a MEG study

The proportion of elderly people in the population has increased rapidly in the last century and consequently "healthy aging" is expected to become a critical area of research in neuroscience. Evidence reveals how healthy aging depends on three main behavioral factors: social lifestyle, cognitive activity and physical activity. In this study, we focused on the role of cognitive activity, concentrating specifically on educational and occupational attainment factors, which were considered two of the main pillars of cognitive reserve. 21 subjects with similar rates of social lifestyle, physical and cognitive activity were selected from a sample of 55 healthy adults. These subjects were divided into two groups according to their level of cognitive reserve; one group comprised subjects with high cognitive reserve (9 members) and the other contained those with low cognitive reserve (12 members). To evaluate the cortical brain connectivity network, all participants were recorded by Magnetoencephalography (MEG) while they performed a memory task (modified version of the Sternberg¿s Task). We then applied two algorithms (Phase Locking Value & Phase-Lag Index) to study the dynamics of functional connectivity. In response to the same task, the subjects with lower cognitive reserve presented higher functional connectivity than those with higher cognitive reserve. These results may indicate that participants with low cognitive reserve needed a greater 'effort' than those with high cognitive reserve to achieve the same level of cognitive performance. Therefore, we conclude that cognitive reserve contributes to the modulation of the functional connectivity patterns of the aging brain.

TMS- EEG Signatures of GABAergic Neurotransmission in the Human Cortex

Combining transcranial magnetic stimulation (TMS) and electroencephalography (EEG) constitutes a powerful tool to directly assess human cortical excitability and connectivity. TMS of the primary motor cortex elicits a sequence of TMS-evoked EEG potentials (TEPs). It is thought that inhibitory neurotransmission through GABA-A receptors (GABAAR) modulates early TEPs (<50 ms after TMS), whereas GABA-B receptors (GABABR) play a role for later TEPs (at ∼100 ms after TMS). However, the physiological underpinnings of TEPs have not been clearly elucidated yet. Here, we studied the role of GABAA/B-ergic neurotransmission for TEPs in healthy subjects using a pharmaco-TMS-EEG approach. In Experiment 1, we tested the effects of a single oral dose of alprazolam (a classical benzodiazepine acting as allosteric-positive modulator at α1, α2, α3, and α5 subunit-containing GABAARs) and zolpidem (a positive modulator mainly at the α1 GABAAR) in a double-blind, placebo-controlled, crossover study. In Experiment 2, we tested the influence of baclofen (a GABABR agonist) and diazepam (a classical benzodiazepine) versus placebo on TEPs. Alprazolam and diazepam increased the amplitude of the negative potential at 45 ms after stimulation (N45) and decreased the negative component at 100 ms (N100), whereas zolpidem increased the N45 only. In contrast, baclofen specifically increased the N100 amplitude. These results provide strong evidence that the N45 represents activity of α1-subunit-containing GABAARs, whereas the N100 represents activity of GABABRs. Findings open a novel window of opportunity to study alteration of GABAA-/GABAB-related inhibition in disorders, such as epilepsy or schizophrenia.

Anomalous Consistency in Mild Cognitive Impairment: A Complex Networks Approach

Increased variability in performance has been associated with the emergence of several neurological and psychiatric pathologies. However, whether and how consistency of neuronal activity may also be indicative of an underlying pathology is still poorly understood. Here we propose a novel method for evaluating consistency from non-invasive brain recordings. We evaluate the consistency of the cortical activity recorded with magnetoencephalography in a group of subjects diagnosed with Mild Cognitive Impairment (MCI), a condition sometimes prodromal of dementia, during the execution of a memory task. We use metrics coming from nonlinear dynamics to evaluate the consistency of cortical regions. A representation known as parenclitic networks is constructed, where atypical features are endowed with a network structure, the topological properties of which can be studied at various scales. Pathological conditions correspond to strongly heterogeneous networks, whereas typical or normative conditions are characterized by sparsely connected networks with homogeneous nodes. The analysis of this kind of networks allows identifying the extent to which consistency is affected in the MCI group and the focal points where MCI is especially severe. To the best of our knowledge, these results represent the first attempt at evaluating the consistency of brain functional activity using complex networks theory.

AS INOVAÇÕES TECNOLÓGICAS E OS INTERMEDIÁRIOS DA PRODUÇÃO E DO ACESSO À INFORMAÇÃO JORNALÍSTICA

O jornalismo é um dos principais meios de oferta de temas para a discussão e formação da opinião pública, porém depende de um sistema técnico para ser transmitido. Durante mais de cem anos as informações produzidas pela imprensa foram emitidas, armazenadas, transmitidas e recebidas pelos chamados veículos de comunicação de massa que utilizam a rede centralizada cujas características estão na escassez material, produção em série e massificação. Esse sistema separa no tempo e no espaço emissores e receptores criando uma relação desigual de força em que as grandes empresas controlaram o fluxo informativo, definindo quais fatos seriam veiculados como notícia. Em 1995, a internet cuja informação circula sob a tecnologia da rede distribuída, foi apropriada pela sociedade, alterando a forma de produção, armazenamento e transmissão de informação. A tecnologia despertou a esperança de que esta ferramenta poderia proporcionar uma comunicação mais dialógica e democrática. Mas aos poucos pode-se perceber novas empresas se apropriando da tecnologia da rede distribuída sob a qual circula a internet, gerando um novo controle do fluxo informativo. Realizou-se nessa pesquisa um levantamento bibliográfico para estabelecer uma reflexão crítica dos diferentes intermediários entre fato e a notícia tanto da rede centralizada como na rede distribuída, objetivando despertar uma discussão que possa oferecer novas ideias para políticas, bem como alternativas para uma comunicação mais democrática e mais libertária.

O BOCA A BOCA ON-LINE: AS IMPLICAÇÕES DA VOZ DO CONSUMIDOR NA COMUNICAÇÃO DE MERCADO

O consumidor contemporâneo, inserido em um novo ambiente de comunicação, potencializa suas expressões, capaz de avaliar uma marca ou produto e transmitir sua opinião pelas redes sociais, ou seja, o consumidor expressa suas opiniões e desejos dialogando com seus pares de forma espontânea nas redes sociais on-line. É neste ambiente de participação e interação (ciberespaço) que está nosso objeto de estudo, o boca a boca on-line – a voz do consumidor contemporâneo, também conhecido como uma manifestação informativa pessoal ou uma conversa, a opinion sharing. Proporcionado pelos consumidores nas redes sociais on-line, o boca a boca se fortalece em função das possibilidades de interação, característica da sociedade em rede. Nesse cenário, oobjetivo desta pesquisa é caracterizar o boca a boca on-line como um novo fluxo comunicacional entre consumidores, hoje potencializado pelas novas tecnologias da comunicação, capazes de alterar a percepção da marca e demonstrar o uso, pelas marcas, das redes sociais on-line ainda como um ambiente de comunicação unidirecional. Mediante três casos selecionados por conveniência (dois casos nacionais e um internacional), o corpus de análise de nossa pesquisa se limitou aos 5.084 comentários disponibilizados após publicação de matérias jornalísticas no Portal G1 e nas fanpages (Facebook), ambos relativos aos casos selecionados. Com a Análise de Conteúdo dos posts, identificamos e categorizamos a fala do consumidor contemporâneo, sendo assim possível comprovar que as organizações/marcas se valem da cultura do massivo, não dialogando com seus consumidores, pois utilizam as redes sociais on-line ainda de forma unidirecional, além de não darem a devida atenção ao atual fluxo onde se evidencia a opinião compartilhada dos consumidores da sociedade em rede.