Effects of Age-Related Cognitive Deficits on EEG Phase Coherence

Body and brain undergo several changes with aging. One of these changes is the loss of neuroplasticity, which leads to the decrease of cognitive abilities. Hence the necessity of stopping or reversing these changes is of utmost importance to contemporary society. In the present work, electroencephalogram (EEG) markers of cognitive decline are sought whilst the subjects perform the Wisconsin Card Sorting Test (WCST). Considering the expected age-related cognitive deficits, WCST was applied to young and elder participants. The results suggest that coherence on theta and alpha EEG rhythms decrease with aging and increase with performance. Additionally, theta phase coherence seems more sensitive to performance, while alpha synchronization appears as a potential ageing marker.

Experimentally determined chaotic phase synchronization in a neuronal system

Mathematical analysis of the subthreshold oscillatory properties of inferior olivary neurons in vitro indicates that the oscillation is nonlinear and supports low dimensional chaotic dynamics. This property leads to the generation of complex functional states that can be attained rapidly via phase coherence that conform to the category of “generalized synchronization.” Functionally, this translates into neuronal ensemble properties that can support maximum functional permissiveness and that rapidly can transform into robustly determined multicellular coherence.

Brain dynamics sustaining rapid rule extraction from speech

Language acquisition is a complex process that requires the synergic involvement of different cognitive functions, which include extracting and storing the words of the language and their embedded rules for progressive acquisition of grammatical information. As has been shown in other fields that study learning processes, synchronization mechanisms between neuronal assemblies might have a key role during language learning. In particular, studying these dynamics may help uncover whether different oscillatory patterns sustain more item-based learning of words and rule-based learning from speech input. Therefore, we tracked the modulation of oscillatory neural activity during the initial exposure to an artificial language, which contained embedded rules. We analyzed both spectral power variations, as a measure of local neuronal ensemble synchronization, as well as phase coherence patterns, as an index of the long-range coordination of these local groups of neurons. Synchronized activity in the gamma band (2040 Hz), previously reported to be related to the engagement of selective attention, showed a clear dissociation of local power and phase coherence between distant regions. In this frequency range, local synchrony characterized the subjects who were focused on word identification and was accompanied by increased coherence in the theta band (48 Hz). Only those subjects who were able to learn the embedded rules showed increased gamma band phase coherence between frontal, temporal, and parietal regions.

Étude intracrânienne sur les mécanismes cérébraux permettant la reconnaissance d’objets

La reconnaissance d’objets est une tâche complexe au cours de laquelle le cerveau doit assembler de manière cohérente tous les éléments d’un objet accessible à l’œil afin de le reconnaître. La construction d’une représentation corticale de l’objet se fait selon un processus appelé « bottom-up », impliquant notamment les régions occipitales et temporales. Un mécanisme « top-down » au niveau des régions pariétales et frontales, facilite la reconnaissance en suggérant des identités potentielles de l’objet à reconnaître. Cependant, le mode de fonctionnement de ces mécanismes est peu connu. Plusieurs études ont démontré une activité gamma induite au moment de la perception cohérente de stimuli, lui conférant ainsi un rôle important dans la reconnaissance d’objets. Cependant, ces études ont utilisé des techniques d’enregistrement peu précises ainsi que des stimuli répétitifs. La première étude de cette thèse vise à décrire la dynamique spatio-temporelle de l’activité gamma induite à l’aide de l’électroencéphalographie intracrânienne, une technique qui possède des résolutions spatiales et temporelles des plus précises. Une tâche d’images fragmentées a été conçue dans le but de décrire l’activité gamma induite selon différents niveaux de reconnaissance, tout en évitant la répétition de stimuli déjà reconnus. Afin de mieux circonscrire les mécanismes « top-down », la tâche a été répétée après un délai de 24 heures. Les résultats démontrent une puissante activité gamma induite au moment de la reconnaissance dans les régions « bottom-up ». Quant aux mécanismes « top-down », l’activité était plus importante aux régions occipitopariétales. Après 24 heures, l’activité était davantage puissante aux régions frontales, suggérant une adaptation des procédés « top-down » selon les demandes de la tâche. Très peu d’études se sont intéressées au rythme alpha dans la reconnaissance d’objets, malgré qu’il soit bien reconnu pour son rôle dans l’attention, la mémoire et la communication des régions neuronales distantes. La seconde étude de cette thèse vise donc à décrire plus précisément l’implication du rythme alpha dans la reconnaissance d’objets en utilisant les techniques et tâches identiques à la première étude. Les analyses révèlent une puissante activité alpha se propageant des régions postérieures aux régions antérieures, non spécifique à la reconnaissance. Une synchronisation de la phase de l’alpha était, quant à elle, observable qu’au moment de la reconnaissance. Après 24 heures, un patron similaire était observable, mais l’amplitude de l’activité augmentait au niveau frontal et les synchronies de la phase étaient davantage distribuées. Le rythme alpha semble donc refléter des processus attentionnels et communicationnels dans la reconnaissance d’objets. En conclusion, cette thèse a permis de décrire avec précision la dynamique spatio-temporelle de l’activité gamma induite et du rythme alpha ainsi que d’en apprendre davantage sur les rôles potentiels que ces deux rythmes occupent dans la reconnaissance d’objets.

Curcumin protects organotypic hippocampal slice cultures 4 from Ab1–42 -induced synaptic toxicity

Increasing evidence demonstrates that beta-amyloid (Ab) is toxic to synapses, resulting in the progressive dismantling of neuronal circuits. Counteract the synaptotoxic effects of Ab could be particularly relevant for providing effective treatments for Alzheimer’s disease (AD). Curcumin was recently reported to improve learning and memory in animal models of AD. Little is currently known about the specific mechanisms by which Ab affects neuronal excitability and curcumin ameliorates synaptic transmission in the hippocampus. Organotypic hippocampal slice cultures exposed to Ab1–42 were used to study the neuroprotective effects of curcumin through a spectral analysis of multi-electrode array (MEA) recordings of spontaneous neuronal activity. Curcumin counteracted both deleterious effects of Ab; the initial synaptic dysfunction and the later neuronal death. The analysis of MEA recordings of spontaneous neuronal activity showed an attenuation of signal propagation induced by Ab before cell death and curcumin-induced alterations to local field potential (LFP) phase coherence. Curcumin-mediated attenuation of Ab-induced synaptic dysfunction involved regulation of synaptic proteins, namely phospho-CaMKII and phosphosynapsin I. Taken together, our results expand the neuroprotective role of curcumin to a synaptic level. The identification of these mechanisms underlying the effects of curcumin may lead to new targets for future therapies for AD.

Ketamine alters oscillatory coupling in the hoppocampus

Recent studies show that higher order oscillatory interactions such as cross-frequency coupling are important for brain functions that are impaired in schizophrenia, including perception, attention and memory. Here we investigated the dynamics of oscillatory coupling in the hippocampus of awake rats upon NMDA receptor blockade by ketamine, a pharmacological model of schizophrenia. Ketamine (25, 50 and 75 mg/kg i.p.) increased gamma and high-frequency oscillations (HFO) in all depths of the CA1-dentate axis, while theta power changes depended on anatomical location and were independent of a transient increase of delta oscillations. Phase coherence of gamma and HFO increased across hippocampal layers. Phase-amplitude coupling between theta and fast oscillations was markedly altered in a dose-dependent manner: ketamine increased hippocampal theta-HFO coupling at all doses, while theta-gamma coupling increased at the lowest dose and was disrupted at the highest dose. Our results demonstrate that ketamine alters network interactions that underlie cognitively relevant theta-gamma coupling.

Mean-field model for Josephson oscillation in a Bose-Einstein condensate on an one-dimensional optical trap

Using the axially-symmetric time-dependent Gross-Pitaevskii equation we study the phase coherence in a repulsive Bose-Einstein condensate (BEC) trapped by a harmonic and an one-dimensional optical lattice potential to describe the experiment by Cataliotti et al. on atomic Josephson oscillation [Science 293, 843 (2001)]. The phase coherence is maintained after the BEC is set into oscillation by a small displacement of the magnetic trap along the optical lattice. The phase coherence in the presence of oscillating neutral current across an array of Josephson junctions manifests in an interference pattern formed upon free expansion of the BEC. The numerical response of the system to a large displacement of the magnetic trap is a classical transition from a coherent superfluid to an insulator regime and a subsequent destruction of the interference pattern in agreement With the more recent experiment by Cataliotti et al. [New J. Phys. 5, 71 (2003)].

Dynamical classical superfluid-insulator transition in a Bose-Einstein condensate on an optical lattice

We predict a dynamical: classical superfluid-insulator transition in a Bose-Einstein condensate (BEC) trapped in combined optical and axially symmetrical harmonic potentials initiated by the periodic modulation of the radial trapping potential. The transition is marked by a loss of phase coherence in the BEC and a subsequent destruction of the interference pattern upon free:expansion. For a weak modulation of the radial potential the phase coherence is maintained. For a stronger modulation and a longer holding time in the modulated trap, the phase coherence is destroyed thus signalling a classical superfluid-insulator transition. The results are illustrated by a complete numerical solution of the axially symmetrical mean-field Gross-Pitaevskii equation for a repulsive BEC. Suggestions for future experimentation are-made.

Detecção de potenciais corticais antecipatórios em sinais de eletroencefalografia (EEG) durante a condução de carros

O reconhecimento da intenção do condutor a partir de sinais de eletroencefalografia (EEG) pode ser útil no desenvolvimento de interfaces cérebro computador (BCI) para serem usadas em sinergia com veículos inteligentes. Isso pode ser benéfico para melhorar a qualidade de interação entre o motorista e o carro, por exemplo, fornecendo uma resposta do carro inteligente alinhada com a intenção do motorista. Neste estudo, considera-se a antecipação como sendo o estado cognitivo que leva a ações especificas durante a condução de um automóvel. Portanto, propomos investigar a presença de padrões antecipatórios em sinais EEG durante a condução de veículos para determinar duas ações especifícas (1) virar à esquerda e (2) virar à direita, alguns milissegundos antes que tais ações aconteçam. Um protocolo experimental foi proposto para gravar sinais EEG de 5 indivíduos enquanto eles operam um simulador de realidade virtual não invasiva - que foi projetado para tal experimento - que simula a condução de um carro virtual. O protocolo experimental é uma variante do paradigma da variação negativa contingente (CNV) com condições Go e No-go no sistema de condução de realidade virtual. Os resultados apresentados neste estudo indicam a presença de padrões antecipatórios em potenciais corticais lentos observados no domínio do tempo (medias dos sinais EEG) e da frequência (Power Spectra e coerência de fase). Isso abre um leque de possibilidades no desenvolvimento de sistemas BCI - baseados em sinais antecipatórios - que conectem o motorista ao veiculo inteligente favorecendo uma tomada de decisão que analise as intenções dos condutores podendo eventualmente evitar acidentes durante a condução.

Study of the Influence of Localized Vibrational Modes in Charge Transport Properties at Nanoscale Systems.

In molecular and atomic devices the interaction between electrons and ionic vibrations has an important role in electronic transport. The electron-phonon coupling can cause the loss of the electron's phase coherence, the opening of new conductance channels and the suppression of purely elastic ones. From the technological viewpoint phonons might restrict the efficiency of electronic devices by energy dissipation, causing heating, power loss and instability. The state of the art in electron transport calculations consists in combining ab initio calculations via Density Functional Theory (DFT) with Non-Equilibrium Green's Function formalism (NEGF). In order to include electron-phonon interactions, one needs in principle to include a self-energy scattering term in the open system Hamiltonian which takes into account the effect of the phonons over the electrons and vice versa. Nevertheless this term could be obtained approximately by perturbative methods. In the First Born Approximation one considers only the first order terms of the electronic Green's function expansion. In the Self-Consistent Born Approximation, the interaction self-energy is calculated with the perturbed electronic Green's function in a self-consistent way. In this work we describe how to incorporate the electron-phonon interaction to the SMEAGOL program (Spin and Molecular Electronics in Atomically Generated Orbital Landscapes), an ab initio code for electronic transport based on the combination of DFT + NEGF. This provides a tool for calculating the transport properties of materials' specific system, particularly in molecular electronics. Preliminary results will be presented, showing the effects produced by considering the electron-phonon interaction in nanoscale devices.

What do brain network interactions tell about cognitive processes? How to seek causality?

Optimal adjustment of brain networks allows the biased processing of information in response to the demand of environments and is therefore prerequisite for adaptive behaviour. It is widely shown that a biased state of networks is associated with a particular cognitive process. However, those associations were identified by backward categorization of trials and cannot provide a causal association with cognitive processes. This problem still remains a big obstacle to advance the state of our field in particular human cognitive neuroscience. In my talk, I will present two approaches to address the causal relationships between brain network interactions and behaviour. Firstly, we combined connectivity analysis of fMRI data and a machine leaning method to predict inter-individual differences of behaviour and responsiveness to environmental demands. The connectivity-based classification approach outperforms local activation-based classification analysis, suggesting that interactions in brain networks carry information of instantaneous cognitive processes. Secondly, we have recently established a brand new method combining transcranial alternating current stimulation (tACS), transcranial magnetic stimulation (TMS), and EEG. We use the method to measure signal transmission between brain areas while introducing extrinsic oscillatory brain activity and to study causal association between oscillatory activity and behaviour. We show that phase-matched oscillatory activity creates the phase-dependent modulation of signal transmission between brain areas, while phase-shifted oscillatory activity blunts the phase-dependent modulation. The results suggest that phase coherence between brain areas plays a cardinal role in signal transmission in the brain networks. In sum, I argue that causal approaches will provide more concreate backbones to cognitive neuroscience.

Digital elevation model (DEM) of the ice sheet in western Dronning Maud Land, Antarctica

In this paper, a new digital elevation model (DEM) is derived for the ice sheet in western Dronning Maud Land, Antarctica. It is based on differential interferometric synthetic aperture radar (SAR) from the European Remote Sensing 1/2 (ERS-1/2) satellites, in combination with ICESat's Geoscience Laser Altimeter System (GLAS). A DEM mosaic is compiled out of 116 scenes from the ERS-1 ice phase in 1994 and the ERS-1/2 tandem mission between 1996 and 1997 with the GLAS data acquired in 2003 that served as ground control. Using three different SAR processors, uncertainties in phase stability and baseline model, resulting in height errors of up to 20 m, are exemplified. Atmospheric influences at the same order of magnitude are demonstrated, and corresponding scenes are excluded. For validation of the DEM mosaic, covering an area of about 130,000 km**2 on a 50-m grid, independent ICESat heights (2004-2007), ground-based kinematic GPS (2005), and airborne laser scanner data (ALS, 2007) are used. Excluding small areas with low phase coherence, the DEM differs in mean and standard deviation by 0.5 +/- 10.1, 1.1 +/- 6.4, and 3.1 +/- 4.0 m from ICESat, GPS, and ALS, respectively. The excluded data points may deviate by more than 50 m. In order to suppress the spatially variable noise below a 5-m threshold, 18% of the DEM area is selectively averaged to a final product at varying horizontal spatial resolution. Apart from mountainous areas, the new DEM outperforms other currently available DEMs and may serve as a benchmark for future elevation models such as from the TanDEM-X mission to spatially monitor ice sheet elevation.

Gaussian Process Kernels for Cross-Spectrum Analysis in Electrophysiological Time Series

Multi-output Gaussian processes provide a convenient framework for multi-task problems. An illustrative and motivating example of a multi-task problem is multi-region electrophysiological time-series data, where experimentalists are interested in both power and phase coherence between channels. Recently, the spectral mixture (SM) kernel was proposed to model the spectral density of a single task in a Gaussian process framework. This work develops a novel covariance kernel for multiple outputs, called the cross-spectral mixture (CSM) kernel. This new, flexible kernel represents both the power and phase relationship between multiple observation channels. The expressive capabilities of the CSM kernel are demonstrated through implementation of 1) a Bayesian hidden Markov model, where the emission distribution is a multi-output Gaussian process with a CSM covariance kernel, and 2) a Gaussian process factor analysis model, where factor scores represent the utilization of cross-spectral neural circuits. Results are presented for measured multi-region electrophysiological data.

Ketamine alters oscillatory coupling in the hoppocampus

Recent studies show that higher order oscillatory interactions such as cross-frequency coupling are important for brain functions that are impaired in schizophrenia, including perception, attention and memory. Here we investigated the dynamics of oscillatory coupling in the hippocampus of awake rats upon NMDA receptor blockade by ketamine, a pharmacological model of schizophrenia. Ketamine (25, 50 and 75 mg/kg i.p.) increased gamma and high-frequency oscillations (HFO) in all depths of the CA1-dentate axis, while theta power changes depended on anatomical location and were independent of a transient increase of delta oscillations. Phase coherence of gamma and HFO increased across hippocampal layers. Phase-amplitude coupling between theta and fast oscillations was markedly altered in a dose-dependent manner: ketamine increased hippocampal theta-HFO coupling at all doses, while theta-gamma coupling increased at the lowest dose and was disrupted at the highest dose. Our results demonstrate that ketamine alters network interactions that underlie cognitively relevant theta-gamma coupling.

Ketamine alters oscillatory coupling in the hoppocampus

Recent studies show that higher order oscillatory interactions such as cross-frequency coupling are important for brain functions that are impaired in schizophrenia, including perception, attention and memory. Here we investigated the dynamics of oscillatory coupling in the hippocampus of awake rats upon NMDA receptor blockade by ketamine, a pharmacological model of schizophrenia. Ketamine (25, 50 and 75 mg/kg i.p.) increased gamma and high-frequency oscillations (HFO) in all depths of the CA1-dentate axis, while theta power changes depended on anatomical location and were independent of a transient increase of delta oscillations. Phase coherence of gamma and HFO increased across hippocampal layers. Phase-amplitude coupling between theta and fast oscillations was markedly altered in a dose-dependent manner: ketamine increased hippocampal theta-HFO coupling at all doses, while theta-gamma coupling increased at the lowest dose and was disrupted at the highest dose. Our results demonstrate that ketamine alters network interactions that underlie cognitively relevant theta-gamma coupling.