Daniel Yasumasa Takahashi

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.

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, 2009.

Connectivity Inference between Neural Structures via Partial Directed Coherence

Abstract This paper describes the rigorous asymptotic distributions of the recently introduced partial directed coherence (PDC) – a frequency domain description of Granger causality between multivariate time series represented by vector autoregressive models. We show that, when not zero, PDC is asymptotically normally distributed and therefore provides means of comparing different strengths of connection between observed time series. Zero PDC indicates an absence of a direct connection between time series, and its otherwise asymptotically normal behavior degenerates into that of a mixture of variables allowing the computation of rigorous thresholds for connectivity tests using either numerical integration or approximate numerical methods. A Monte Carlo study illustrates the power of the test under PDC nullity. An analysis of electroencephalographic data, before and during an epileptic seizure episode, is used to portray the usefulness of the test in a real application.

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.

Cineradiography of Monkey Lip-Smacking Reveals Putative Precursors of Speech Dynamics

A key feature of speech is its stereotypical 5 Hz rhythm. One theory posits that this rhythm evolved through the modification of rhythmic facial movements in ancestral primates. If the hypothesis has any validity, then a comparative approach may shed some light. We tested this idea by using cineradiography (X-ray movies) to characterize and quantify the internal dynamics of the macaque monkey vocal tract during lip-smacking (a rhythmic facial expression) versus chewing. Previous human studies showed that speech movements are faster than chewing movements, and the functional coordination between vocal tract structures is different between the two behaviors. If rhythmic speech evolved through a rhythmic ancestral facial movement, then one hypothesis is that monkey lip-smacking versus chewing should also exhibit these differences. We found that the lips, tongue, and hyoid move with a speech-like 5 Hz rhythm during lip-smacking, but not during chewing. Most importantly, the functional coordination between these structures was distinct for each behavior. These data provide empirical support for the idea that the human speech rhythm evolved from the rhythmic facial expressions of ancestral primates.

Information theoretic interpretation of frequency domain connectivity measures

In order to provide adequate multivariate measures of information flow between neural structures, modified expressions of partial directed coherence (PDC) and directed transfer function (DTF), two popular multivariate connectivity measures employed in neuroscience, are introduced and their formal relationship to mutual information rates are proved.

Avaliação cognitiva breve de pacientes atendidos em ambulatórios de neurologia geral

INTRODUCAO: O exame das funcoes cognitivas e habitual na avaliacao das demencias, porem nao e usualmente realizado em pacientes com outras doencas neurologicas. OBJETIVO: Investigar a relevância da semiologia cognitiva sistematica em pacientes com doencas neurologicas diversas. METODO: Foram avaliados 105 pacientes consecutivamente atendidos no periodo de um ano em ambulatorio de neurologia geral de hospital universitario publico, sem queixas de alteracoes cognitivas. Os pacientes foram submetidos aos seguintes testes cognitivos: mini-exame do estado mental (MEEM), extensao de digitos, testes de memoria de figuras, fluencia verbal e desenho do relogio. Sempre que possivel as notas de corte foram corrigidas em funcao da escolaridade. RESULTADOS: Cerca de 2/3 dos pacientes apresentaram alteracoes do desempenho em pelo menos um teste. O MEEM mostrou-se alterado em 20% dos pacientes, o teste da extensao de digitos apresentou alteracao em 50,4% (29,5% na ordem direta e 20,9% na indireta). A evocacao tardia esteve alterada em 14,2% dos casos, a fluencia verbal esteve abaixo da nota de corte em 27,6% dos pacientes e o desenho do relogio, em 40,0%. CONCLUSAO: Os dados obtidos comprovam a necessidade da inclusao da avaliacao cognitiva como parte obrigatoria do exame neurologico, mesmo em pacientes sem queixas relacionadas.

The evolution of speech: vision, rhythm, cooperation

A full account of human speech evolution must consider its multisensory, rhythmic, and cooperative characteristics. Humans, apes, and monkeys recognize the correspondence between vocalizations and their associated facial postures, and gain behavioral benefits from them. Some monkey vocalizations even have a speech-like acoustic rhythmicity but lack the concomitant rhythmic facial motion that speech exhibits. We review data showing that rhythmic facial expressions such as lip-smacking may have been linked to vocal output to produce an ancestral form of rhythmic audiovisual speech. Finally, we argue that human vocal cooperation (turn-taking) may have arisen through a combination of volubility and prosociality, and provide comparative evidence from one species to support this hypothesis.

Early development of turn-taking with parents shapes vocal acoustics in infant marmoset monkeys

In humans, vocal turn-taking is a ubiquitous form of social interaction. It is a communication system that exhibits the properties of a dynamical system: two individuals become coupled to each other via acoustic exchanges and mutually affect each other. Human turn-taking develops during the first year of life. We investigated the development of vocal turn-taking in infant marmoset monkeys, a New World species whose adult vocal behaviour exhibits the same universal features of human turn-taking. We find that marmoset infants undergo the same trajectory of change for vocal turn-taking as humans, and do so during the same life-history stage. Our data show that turn-taking by marmoset infants depends on the development of self-monitoring, and that contingent parental calls elicit more mature-sounding calls from infants. As in humans, there was no evidence that parental feedback affects the rate of turn-taking maturation. We conclude that vocal turn-taking by marmoset monkeys and humans is an instance of convergent evolution, possibly as a result of pressures on both species to adopt a cooperative breeding strategy and increase volubility.

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. Pearsons 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 Pearsons 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 (Pearsons, Spearmans and Kendalls correlations; distance correlation; Hoeffdings 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.