Hemodynamic and electrophysiological evidence of resting-state network activity in the primate

An expanding body of literature describes the existence of concerted brain activations in the absence of any external stimuli. Resting-state networks have been identified and demonstrated to be modulated during the performance of specific cognitive operations. However, despite mounting evidence the possibility still remains that those correlated signal fluctuations reflect non-neural phenomena. In order to isolate functionally relevant spontaneous coactivations, we utilized a multi-level sampling approach to obtain co-registered brain signals across a range of sampling resolution and sensitivity. Surface and local field potentials, hemodynamic signals (near-infrared spectroscopy, NIRS), and cell spiking were recorded from dorsolateral prefrontal and posterior parietal cortices in four monkeys trained to remain motionless in a primate chair. The use of an optical recording technique (NIRS) allows measurement of a signal that is physiologically equivalent to that obtained using BOLD fMRI, though with millisecond temporal resolution and minimal technical or environmental constraints. The different signal types exhibited correlations between the two regions of interest in both the frequency and time domains. This evidence suggests that the resting-state network activations detected by fMRI do in fact reflect functional coactivations of areas across multiple levels of network communication

Functional differentiation within the monkey cortex as revealed by near-infrared spectroscopy

The role of prefrontal cortex in working memory (WM) is well established. However, questions remain regarding the topography and “domain-specific differentiation” of different types of information processing in the cortex. While it has been theorized that dorsolateral (DPFC) and ventrolateral (VPFC) prefrontal cortex preferentially process spatial and object WM, respectively, both electrophysiological evidence in the monkey and neuroimaging in the human have largely failed to demonstrate such regional differentiation. In this study we use near-infrared spectroscopy (NIRS) to detect functional changes, across relatively large cortical cell populations, simultaneously from prefrontal and posterior parietal cortices. Imaging data were recorded from a Rhesus macaque performing two types of WM tasks: a spatial task in which the animal had to retain the spatial position of a visual stimulus, and a non-spatial task where he had to retain its color (red or green) during a 20s delay. During performance of the spatial WM task, cerebral activation trends were found in which DPFC exhibited stronger activation than did the VPFC, and posterior parietal cortex maintained higher delay activation than did frontal regions. These differences were less pronounced during performance of the non-spatial task. Additionally, incorrect trials generally elicited lower activations during the delay period than did trials ending with a correct response. Furthermore, NIRS data collected during the performance of a haptic WM task also appear to exhibit inter-regional differences in delay activation. The data thus suggest the presence of preferential cognitive processing between and within posterior and frontal cortical regions

Using A High-Temperature Flue Gases in the Technology of Combustion Neutralization of Wastewater

This paper provides an analysis of composition of typical polluting contaminants of industrial wastewater. The study suggest industry branches, wastewater of which contains the greatest amount of organic flammable substanses (petroleum и oil). The present study was conducted to analyze an opportunity to replace fuel torch by the high-temperature flow of flue gases in the realization thermal treatment method (combustion neutralization)

Zeitabhängige Stromdichterekonstruktion in einem standardisierten Finite-Elemente-Kopfmodell

The content of this work was the reconstruction of neuronal activity in a standardized headmodel under consideration of additional constraints on the time course of the solution. The thesis is divided into five chapters which describe the physiological basis of the neuronal generators of the electromagnetic fields and potentials, the finite element solution of the bioelectromagnetic forward solution, the solution of the inverse problem, the validation of the proposed algorithms and solutions and the implementation of a eeg-data analysis software package. The aim of the work was the extension and improvement of the existing sourcemodels by introducing an additional temporal modelterm and the simplification of the forward solution of realistic model by using a standardized head. The fMRI phantom created by Collins et al. was chosen as a generic model of the head. Based on voxel intensities of this MR image a cubic FE mesh with 2.5 mm sidelength was created. On the surface of this model, a larger number of equally spaced electrode positions was created and the a solution for all sensors was calculated for sourcelocations on a regular grid within the cortex. In order to verify the model, sources in individual head models were simulated and then reconstructed with the aid of the standard model. The localization error of the reconstructed sources was found to be less than one gridlength of the cortical reconstruction grid. In order to expand the source model such that a priori knowledge about the timecourse of the sources could be incorporated, a bayesian approach to inverse problem was used. Two basic temporal constraints were introduced, smoothness of first order and smoothness of second order and the properties of the temporal constrained source reconstruction were compared to spatial constrained reconstruction methods (e.g. minimum, LORETA). Two measures were used, the localization error of the sources and the correlation coefficient between the original and the reconstructed timecourses of the sources.Additonal physiological boundary conditions for the temporal constraints were introduced and a modified numerical efficient algorithm for the solution of the temporal constrained problem was proposed. The localization error and the correlation were analyzed for simulations on a planar model and also on a realistically shaped headmodel. Under assumption of biological noise, the temporal constrained methods yielded improved reconstruction results. The methods were also tested on experimental data. Three stimulation setups were used, i.e an acoustic, a visual and somatosensoric stimulus were presented and source reconstruction was done using spatially constrained and temporal constrained methods. All described methods and algorithms were implemented in an easi-to-use software package for efficient data processing