Spatio-temporal dynamics of alpha brain electric fields, and cognitive modes

Brian electric activity is viewed as sequences of momentary maps of potential distribution. Frequency-domain source modeling, estimation of the complexity of the trajectory of the mapped brain field distributions in state space, and microstate parsing were used as analysis tools. Input-presentation as well as task-free (spontaneous thought) data collection paradigms were employed. We found: Alpha EEG field strength is more affected by visualizing mentation than by abstract mentation, both input-driven as well as self-generated. There are different neuronal populations and brain locations of the electric generators for different temporal frequencies of the brain field. Different alpha frequencies execute different brain functions as revealed by canonical correlations with mentation profiles. Different modes of mentation engage the same temporal frequencies at different brain locations. The basic structure of alpha electric fields implies inhomogeneity over time — alpha consists of concatenated global microstates in the sub-second range, characterized by quasi-stable field topographies, and rapid transitions between the microstates. In general, brain activity is strongly discontinuous, indicating that parsing into field landscape-defined microstates is appropriate. Different modes of spontaneous and induced mentation are associated with different brain electric microstates; these are proposed as candidates for psychophysiological ``atoms of thought''.

First valence, then arousal: the temporal dynamics of brain electric activity evoked by emotional stimuli

The temporal dynamics of the neural activity that implements the dimensions valence and arousal during processing of emotional stimuli were studied in two multi-channel ERP experiments that used visually presented emotional words (experiment 1) and emotional pictures (experiment 2) as stimulus material. Thirty-two healthy subjects participated (mean age 26.8 +/- 6.4 years, 24 women). The stimuli in both experiments were selected on the basis of verbal reports in such a way that we were able to map the temporal dynamics of one dimension while controlling for the other one. Words (pictures) were centrally presented for 450 (600) ms with interstimulus intervals of 1,550 (1,400) ms. ERP microstate analysis of the entire epochs of stimulus presentations parsed the data into sequential steps of information processing. The results revealed that in several microstates of both experiments, processing of pleasant and unpleasant valence (experiment 1, microstate #3: 118-162 ms, #6: 218-238 ms, #7: 238-266 ms, #8: 266-294 ms; experiment 2, microstate #5: 142-178 ms, #6: 178-226 ms, #7: 226-246 ms, #9: 262-302 ms, #10: 302-330 ms) as well as of low and high arousal (experiment 1, microstate #8: 266-294 ms, #9: 294-346 ms; experiment 2, microstate #10: 302-330 ms, #15: 562-600 ms) involved different neural assemblies. The results revealed also that in both experiments, information about valence was extracted before information about arousal. The last microstate of valence extraction was identical with the first microstate of arousal extraction.

DYPTOP: a cost-efficient TOPMODEL implementation to simulate sub-grid spatio-temporal dynamics of global wetlands and peatlands

Simulating the spatio-temporal dynamics of inundation is key to understanding the role of wetlands under past and future climate change. Earlier modelling studies have mostly relied on fixed prescribed peatland maps and inundation time series of limited temporal coverage. Here, we describe and assess the the Dynamical Peatland Model Based on TOPMODEL (DYPTOP), which predicts the extent of inundation based on a computationally efficient TOPMODEL implementation. This approach rests on an empirical, grid-cell-specific relationship between the mean soil water balance and the flooded area. DYPTOP combines the simulated inundation extent and its temporal persistency with criteria for the ecosystem water balance and the modelled peatland-specific soil carbon balance to predict the global distribution of peatlands. We apply DYPTOP in combination with the LPX-Bern DGVM and benchmark the global-scale distribution, extent, and seasonality of inundation against satellite data. DYPTOP successfully predicts the spatial distribution and extent of wetlands and major boreal and tropical peatland complexes and reveals the governing limitations to peatland occurrence across the globe. Peatlands covering large boreal lowlands are reproduced only when accounting for a positive feedback induced by the enhanced mean soil water holding capacity in peatland-dominated regions. DYPTOP is designed to minimize input data requirements, optimizes computational efficiency and allows for a modular adoption in Earth system models.

Self-organised transients in a neural mass model of epileptogenic tissue dynamics

Stimulation of human epileptic tissue can induce rhythmic, self-terminating responses on the EEG or ECoG. These responses play a potentially important role in localising tissue involved in the generation of seizure activity, yet the underlying mechanisms are unknown. However, in vitro evidence suggests that self-terminating oscillations in nervous tissue are underpinned by non-trivial spatio-temporal dynamics in an excitable medium. In this study, we investigate this hypothesis in spatial extensions to a neural mass model for epileptiform dynamics. We demonstrate that spatial extensions to this model in one and two dimensions display propagating travelling waves but also more complex transient dynamics in response to local perturbations. The neural mass formulation with local excitatory and inhibitory circuits, allows the direct incorporation of spatially distributed, functional heterogeneities into the model. We show that such heterogeneities can lead to prolonged reverberating responses to a single pulse perturbation, depending upon the location at which the stimulus is delivered. This leads to the hypothesis that prolonged rhythmic responses to local stimulation in epileptogenic tissue result from repeated self-excitation of regions of tissue with diminished inhibitory capabilities. Combined with previous models of the dynamics of focal seizures this macroscopic framework is a first step towards an explicit spatial formulation of the concept of the epileptogenic zone. Ultimately, an improved understanding of the pathophysiologic mechanisms of the epileptogenic zone will help to improve diagnostic and therapeutic measures for treating epilepsy.

Temporal sequence of hard and soft tissue healing around titanium dental implants.

The objective of the present review was to summarize the evidence available on the temporal sequence of hard and soft tissue healing around titanium dental implants in animal models and in humans. A search was undertaken to find animal and human studies reporting on the temporal dynamics of hard and soft tissue integration of titanium dental implants. Moreover, the influence of implant surface roughness and chemistry on the molecular mechanisms associated with osseointegration was also investigated. The findings indicated that the integration of titanium dental implants into hard and soft tissue represents the result of a complex cascade of biological events initiated by the surgical intervention. Implant placement into alveolar bone induces a cascade of healing events starting with clot formation and continuing with the maturation of bone in contact with the implant surface. From a genetic point of view, osseointegration is associated with a decrease in inflammation and an increase in osteogenesis-, angiogenesis- and neurogenesis-associated gene expression during the early stages of wound healing. The attachment and maturation of the soft tissue complex (i.e. epithelium and connective tissue) to implants becomes established 6-8 weeks following surgery. Based on the findings of the present review it can be concluded that improved understanding of the mechanisms associated with osseointegration will provide leads and targets for strategies aimed at enhancing the clinical performance of titanium dental implants.

Spatiotemporal dynamics of Puumala hantavirus associated with its rodent host, Myodes glareolus

Many viruses significantly impact human and animal health. Understanding the population dynamics of these viruses and their hosts can provide important insights for epidemiology and virus evolution. Puumala virus (PUUV) is a European hantavirus that may cause regional outbreaks of hemorrhagic fever with renal syndrome in humans. Here, we analyzed the spatiotemporal dynamics of PUUV circulating in local populations of its rodent reservoir host, the bank vole (Myodes glareolus) during eight years. Phylogenetic and population genetic analyses of all three genome segments of PUUV showed strong geographical structuring at a very local scale. There was a high temporal turnover of virus strains in the local bank vole populations, but several virus strains persisted through multiple years. Phylodynamic analyses showed no significant changes in the local effective population sizes of PUUV, although vole numbers and virus prevalence fluctuated widely. Microsatellite data demonstrated also a temporally persisting subdivision between local vole populations, but these groups did not correspond to the subdivision in the virus strains. We conclude that restricted transmission between vole populations and genetic drift play important roles in shaping the genetic structure and temporal dynamics of PUUV in its natural host which has several implications for zoonotic risks of the human population.

Rapid adaptation of visual search in simulated hemianopia

Patients with homonymous hemianopia have altered visual search patterns, but it is unclear how rapidly this develops and whether it reflects a strategic adaptation to altered perception or plastic changes to tissue damage. To study the temporal dynamics of adaptation alone, we used a gaze-contingent display to simulate left or right hemianopia in 10 healthy individuals as they performed 25 visual search trials. Visual search was slower and less accurate in hemianopic than in full-field viewing. With full-field viewing, there were improvements in search speed, fixation density, and number of fixations over the first 9 trials, then stable performance. With hemianopic viewing, there was a rapid shift of fixation into the blind field over the first 5-7 trials, followed by continuing gradual improvements in completion time, number of fixations, and fixation density over all 25 trials. We conclude that in the first minutes after onset of hemianopia, there is a biphasic pattern of adaptation to altered perception: an early rapid qualitative change that shifts visual search into the blind side, followed by more gradual gains in the efficiency of using this new strategy, a pattern that has parallels in other studies of motor learning.

Emotions, Arousal, and Frontal Alpha Rhythm Asymmetry During Beethoven's 5th Symphony

Music is capable of inducing emotional arousal. While previous studies used brief musical excerpts to induce one specific emotion, the current study aimed to identify the physiological correlates of continuous changes in subjective emotional states while listening to a complete music piece. A total of 19 participants listened to the first movement of Ludwig van Beethoven's 5th symphony (duration: ~7.4 min), during which a continuous 76-channel EEG was recorded. In a second session, the subjects evaluated their emotional arousal during the listening. A fast fourier transform was performed and covariance maps of spectral power were computed in association with the subjective arousal ratings. Subjective arousal ratings had good inter-individual correlations. Covariance maps showed a right-frontal suppression of lower alpha-band activity during high arousal. The results indicate that music is a powerful arousal-modulating stimulus. The temporal dynamics of the piece are well suited for sequential analysis, and could be necessary in helping unfold the full emotional power of music.

Early loss of arteriolar smooth muscle cells: more than just a pericyte loss in diabetic retinopathy

Incipient diabetic retinopathy is characterized by increased capillary permeability and progressive capillary occlusion. The earliest structural change is the loss of pericytes (PC) from the retinal capillaries. With the availability of the XLacZ mouse, which expresses the LacZ reporter in a PC/vascular smooth muscle cell (vSMC) specific fashion, we quantitatively assessed the temporal dynamics of smooth muscle cells in arterioles under hyperglycemic conditions. We induced stable hyperglycemia in XLacZ mice. After 4, 8, and 12 weeks of diabetes retinae were isolated and beta-galactosidase/lectin stained. The numbers of smooth muscle cells were counted in retinal whole mounts, and diameters of retinal radial and branching arterioles and venules were analyzed at different distances apart from the center of the retina. After eight weeks of diabetes, the numbers of vSMCs were significantly reduced in radial arterioles 1000 microm distant from the optic disc. At proximal sites of branching arterioles (400 microm distant from the center), and at distal sites (1000 microm), vSMC were significantly reduced already after 4 weeks (to a maximum of 31 %). These changes were not associated with any measurable variation in vessel diameters. These data indicate quantitatively that hyperglycemia not only causes pericyte loss, but also loss of vSMCs in the retinal vasculature. Our data suggest that arteriolar vSMC in the eye underlie similar regulations which induce early pericyte loss in the diabetic retina.

Visual vector inversion during memory antisaccades--a TMS study

In the memory antisaccade task, subjects are instructed to look at an imaginary point precisely at the opposite side of a peripheral visual stimulus presented short time previously. To perform this task accurately, the visual vector, i.e., the distance between a central fixation point and the peripheral stimulus, must be inverted from one visual hemifield to the other. Recent data in humans and monkeys suggest that the posterior parietal cortex (PPC) might be critically involved in the process of visual vector inversion. In the present study, we investigated the temporal dynamics of visual vector inversion in the human PPC by using transcranial magnetic stimulation (TMS). In six healthy subjects, single pulse TMS was applied over the right PPC during a memory antisaccade task at four different time intervals: 100 ms, 217 ms, 333 ms, or 450 ms after target onset. The results indicate that for rightward antisaccades, i.e., when the visual target was presented in the left screen-half, TMS had a significant effect on saccade gain when applied 100 ms after target onset, but not later. For leftward antisaccades, i.e., when the visual target was presented in the right screen-half, a significant TMS effect on gain was found for the 333 ms and 450 ms conditions, but not for the earlier ones. This double dissociation of saccade gain suggests that the initial process of vector inversion can be disrupted 100 ms after onset of the visual stimulus and that TMS interfered with motor saccade planning based on an inversed vector signal at 333 ms and 450 ms after stimulus onset.

Integration of electrical neuroimaging with other functional imaging methods

Integrating evidence from different imaging modalities is important to overcome specific limitations of any given imaging method, such as insensitivity of the EEG to unsynchronized neural events, or the lack of fMRI sensitivity to events of low metabolic demand. Processes that are visible in one modality may be related in a nontrivial way to other processes visible in another modality and insight may only be obtained by integrating both methods through a common analysis. For example, brain activity at rest seems to be at least partly determined by an interaction of cortical rhythms (visible to EEG but not to fMRI) with sub-cortical activity (visible to fMRI, but usually not to EEG without averaging). A combination of EEG and fMRI data during rest may thus be more informative than the sum of two separate analyses in both modalities. Integration is also an important source of converging evidence about specific aspects and general principles of neural functions and their dysfunctions in certain pathologies. This is because not only electrical, but also energetic, biochemical, hemodynamic and metabolic processes characterize neural states and functions, and because brain structure provides crucial constraints upon neural functions. Focusing on multimodal integration of functional data should not distract from the privileged status of the electric field as the primary direct, noninvasive real-time measure of neural transmission. The preceding chapters illustrate how electrical neuroimaging has turned scalp EEG into an imaging modality which directly captures the full temporal dynamics of neural activity in the brain.

Overview of analytical approaches

The general model The aim of this chapter is to introduce a structured overview of the different possibilities available to display and analyze brain electric scalp potentials. First, a general formal model of time-varying distributed EEG potentials is introduced. Based on this model, the most common analysis strategies used in EEG research are introduced and discussed as specific cases of this general model. Both the general model and particular methods are also expressed in mathematical terms. It is however not necessary to understand these terms to understand the chapter. The general model that we propose here is based on the statement made in Chapter 3, stating that the electric field produced by active neurons in the brain propagates in brain tissue without delay in time. Contrary to other imaging methods that are based on hemodynamic or metabolic processes, the EEG scalp potentials are thus “real-time,” not delayed and not a-priori frequency-filtered measurements. If only a single dipolar source in the brain were active, the temporal dynamics of the activity of that source would be exactly reproduced by the temporal dynamics observed in the scalp potentials produced by that source. This is illustrated in Figure 5.1, where the expected EEG signal of a single source with spindle-like dynamics in time has been computed. The dynamics of the scalp potentials exactly reproduce the dynamics of the source. The amplitude of the measured potentials depends on the relation between the location and orientation of the active source, its strength and the electrode position.

Cortical local and long-range synchronization interplay in human absence seizure initiation

Brain activity relies on transient, fluctuating interactions between segregated neuronal populations. Synchronization within a single and between distributed neuronal clusters reflects the dynamics of these cooperative patterns. Thus absence epilepsy can be used as a model for integrated, large-scale investigation of the emergence of pathological collective dynamics in the brain. Indeed, spike-wave discharges (SWD) of an absence seizure are thought to reflect abnormal cortical hypersynchronization. In this paper, we address two questions: how and where do SWD arise in the human brain? Therefore, we explored the spatio-temporal dynamics of interactions within and between widely distributed cortical sites using magneto-encephalographic recordings of spontaneous absence seizures. We then extracted, from their time-frequency analysis, local synchronization of cortical sources and long-range synchronization linking distant sites. Our analyses revealed a reproducible sequence of 1) long-range desynchronization, 2) increased local synchronization and 3) increased long-range synchronization. Although both local and long-range synchronization displayed different spatio-temporal profiles, their cortical projection within an initiation time window overlap and reveal a multifocal fronto-central network. These observations contradict the classical view of sudden generalized synchronous activities in absence epilepsy. Furthermore, they suggest that brain states transition may rely on multi-scale processes involving both local and distant interactions.

Landscape mosaics maps as a basis for spatial assessment and negotiation of ecosystem services and their trade-offs at the meso-scale: Examples from Laos, Madagascar and China

Mapping ecosystem services (ES) and their trade-offs is a key requirement for informed decision making for land use planning and management of natural resources that aim to move towards increasing the sustainability of landscapes. The negotiations of the purposes of landscapes and the services they should provide are difficult as there is an increasing number of stakeholders active at different levels with a variety of interests present on one particular landscape.Traditionally, land cover data is at the basis for mapping and spatial monitoring of ecosystem services. In light of complex landscapes it is however questionable whether land cover per se and as a spatial base unit is suitable for monitoring and management at the meso-scale. Often the characteristics of a landscape are defined by prevalence, composition and specific spatial and temporal patterns of different land cover types. The spatial delineation of shifting cultivation agriculture represents a prominent example of a land use system with its different land use intensities that requires alternative methodologies that go beyond the common remote sensing approaches of pixel-based land cover analysis due to the spatial and temporal dynamics of rotating cultivated and fallow fields.Against this background we advocate that adopting a landscape perspective to spatial planning and decision making offers new space for negotiation and collaboration, taking into account the needs of local resource users, and of the global community. For this purpose we introduce landscape mosaicsdefined as new spatial unit describing generalized land use types. Landscape mosaics have allowed us to chart different land use systems and land use intensities and permitted us to delineate changes in these land use systems based on changes of external claims on these landscapes. The underlying idea behindthe landscape mosaics is to use land cover data typically derived from remote sensing data and to analyse and classify spatial patterns of this land cover data using a moving window approach. We developed the landscape mosaics approach in tropical, forest dominated landscapesparticularly shifting cultivation areas and present examples ofour work from northern Laos, eastern Madagascarand Yunnan Province in China.