Modulation of intrinsic brain connectivity by implicit electroencephalographic neurofeedback
Despite the increasing popularity of neurofeedback, its mechanisms of action are still poorly understood. This study aims to describe the processes underlying implicit electroencephalographic neurofeedback. Fifty-two healthy volunteers were randomly assigned to a single session of infra-low frequency neurofeedback or sham neurofeedback, with electrodes over the right middle temporal gyrus and the right inferior parietal lobule. They observed a moving rocket, the speed of which was modulated by the waveform derived from a band-limited infra-low frequency filter. Immediately before and after the session, the participants underwent a resting-state fMRI. Network-based statistical analysis was applied, comparing post- vs. pre-session and real vs. sham neurofeedback conditions. As a result, two phenomena were observed. First, we described a brain circuit related to the implicit neurofeedback process itself, consisting of the lateral occipital cortex, right dorsolateral prefrontal cortex, left orbitofrontal cortex, right ventral striatum, and bilateral dorsal striatum. Second, we found increased connectivity between key regions of the salience, language, and visual networks, which is indicative of integration in sensory processing. Thus, it appears that a single session of implicit infra-low frequency electroencephalographic neurofeedback leads to significant changes in intrinsic brain connectivity.
Meditation is increasingly showing beneficial effects for psychiatric disorders. However, learning to meditate is not straightforward as there are no easily discernible outward signs of performance and thus no direct feedback is possible. As meditation has been found to correlate with posterior cingulate cortex (PCC) activity, we tested whether source-space EEG neurofeedback from the PCC followed the subjective experience of effortless awareness (a major component of meditation), and whether participants could volitionally control the signal.
Sixteen novice meditators and sixteen experienced meditators participated in the study. Novice meditators were briefly trained to perform a basic meditation practice to induce the subjective experience of effortless awareness in a progressively more challenging neurofeedback test-battery. Experienced meditators performed a self-selected meditation practice to induce this state in the same test-battery. Neurofeedback was provided based on gamma-band (40–57 Hz) PCC activity extracted using a beamformer algorithm. Associations between PCC activity and the subjective experience of effortless awareness were assessed by verbal probes.
Both groups reported that decreased PCC activity corresponded with effortless awareness (P < 0.0025 for each group), with high median confidence ratings (novices: 8 on a 0–10 Likert scale; experienced: 9). Both groups showed high moment-to-moment median correspondence ratings between PCC activity and subjective experience of effortless awareness (novices: 8, experienced: 9). Both groups were able to volitionally control the PCC signal in the direction associated with effortless awareness by practicing effortless awareness meditation (novices: median % of time = 77.97, P = 0.001; experienced: 89.83, P < 0.0005).
These findings support the feasibility of using EEG neurofeedback to link an objective measure of brain activity with the subjective experience of effortless awareness, and suggest potential utility of this paradigm as a tool for meditation training.
Using resting state fMRI for individual brain mapping in preneurosurgical planning is discussed. The purpose of our study was to compare the localization of eloquent cortex (motor, speech and executive areas) obtained from resting state fMRI (rsfMRI) and from task based fMRI (tbfMRI). The average percent of overlap of motor areas obtained by the two fMRI methods was appreciable (median 41 - 70), but the overlap revealed for speech and executive areas was very small (median 0 - 23). A significant correlation was revealed between the laterality indexes obtained from tbfMRI and seed-based analysis of rsfMRI. The substantial inter-individual variability in overlap for areas of eloquent cortex mapped by the two different fMRI methods appeals to the necessity of verification of rsfMRI data by direct cortical electrostimulation before using this method in routine clinical applications.
The retrieval of low frequency words is usually slower than that of high frequency words. Neuroimaging research on the role of word frequency in linguistic tasks suggests candidate brain areas for the neural substrates of this effect. The only previous fMRI study of word frequency in Russian (Malutina et al., 2012) used an action naming task and obtained data that were highly inconsistent with results for other languages, findings which were mainly obtained using noun-retrieval tasks. In order to verify whether the reasons for such inconsistency were methodological or cross-linguistic, we examined the fMRI correlates of word frequency in Russian using a covert object naming task. We found that the retrieval of low frequency and high frequency nouns activated the same general pattern of brain areas typical for object naming tasks in many languages. Several brain regions were more activated in the low frequency but not the high frequency condition, including the areas and structures usually associated with linguistic processing (the inferior frontal gyrus bilaterally, the left thalamus, the left insula), visual perception (the fusiform gyrus, the inferior occipital gyrus, the middle occipital gyrus bilaterally) and cognitive and motor control (the supplementary motor area and the right cingulate gyrus). The right cingulate gyrus was the only area that responded only to the low frequency stimuli but not the high frequency items, when compared to the baseline. At the same time, we found no brain areas that responded more to high versus low word frequency. These results are generally consistent with previous fMRI studies in English, German and Chinese and therefore suggest that the inconsistency between the previous research in Russian and other languages was due to the possible interaction of the part of speech (verb or noun) and word frequency in brain mechanisms for word retrieval, rather than cross-linguistic differences.
We present a publicly available dataset of 227 healthy participants comprising a young (N=153, 25.1±3.1 years, range 20–35 years, 45 female) and an elderly group (N=74, 67.6±4.7 years, range 59–77 years, 37 female) acquired cross-sectionally in Leipzig, Germany, between 2013 and 2015 to study mind-body-emotion interactions. During a two-day assessment, participants completed MRI at 3 Tesla (resting-state fMRI, quantitative T1 (MP2RAGE), T2-weighted, FLAIR, SWI/QSM, DWI) and a 62-channel EEG experiment at rest. During task-free resting-state fMRI, cardiovascular measures (blood pressure, heart rate, pulse, respiration) were continuously acquired. Anthropometrics, blood samples, and urine drug tests were obtained. Psychiatric symptoms were identified with Standardized Clinical Interview for DSM IV (SCID-I), Hamilton Depression Scale, and Borderline Symptoms List. Psychological assessment comprised 6 cognitive tests as well as 21 questionnaires related to emotional behavior, personality traits and tendencies, eating behavior, and addictive behavior. We provide information on study design, methods, and details of the data. This dataset is part of the larger MPI Leipzig Mind-Brain-Body database.
Neuroimaging studies are accumulating fast. A significant number of these studies use functional magnetic resonance imaging (fMRI) and report stereotactic brain coordinates. In the last 15 years meta-analytic software tools have been developed to identify over-arching data agreement across studies (e.g., http://www.brainmap.org/). Meta-analytic studies help establish statistical concordance and quantitatively summarize large amounts of evidence. To date there are 944 papers on fMRI meta-analyses, as indexed by Web of Science (WOS; 28/04/18). Before analyzing coordinates researchers have to compile, systematically review relevant literature and extract stereotaxic coordinates. One process of pooling information from the articles requires manual search of the articles and manual extraction the relevant data, such as coordinates (i.e., foci), contrasts (i.e., experiments) and types of analyses (whole-brain or region of interest). Another available approach is offered by software with pre-extracted information, such as Sleuth (http://brainmap.org/sleuth/), Neurosynth (http://neurosynth.org/) and other open-source programs. Critically, these methods do not have up to date datasets covering only a limited number of studies (e.g., 11406 papers in the Neurosynth and 3294 papers in the Sleuth 2.4 at the 28/04/2018), whereas, a WOS search for the keyword (“fMRI”) yields 61976 papers. To improve the quality of the manual search for area-based meta-analyses and increase the speed of the identification of the foci of interest, we developed CoordsFinder - standalone graphical interface software for addressing the challenge of processing multiple fMRI articles reporting data in coordinate space. The software is written using WPF (C# and XAML), based on .NET Framework 4.5.2, and it supports Microsoft Windows 7 operating system or higher. The CoordsFinder estimates the foci uploaded in the software manually and searches for it inside the specified folder, which contains the pdf files of the papers, as this is the most common file format for articles. Foci coordinates can be found both in tables and in a plain text of the articles. The foci file uploaded could contain MNI or TAL space coordinates, and the software can indicate each type. In the current version, CoordsFinder can explore only files stored at the user’s computer, and process 274 papers per minute for a typical computer. Practically this software provides a solution for automatically extracting coordinates from multiple articles for effectively organizing and further analyzing data already available in the literature.
This book presents the results of analysis of human capital in Murmansk and Archangelsk regions, republics of Komi and Karelia, and Nenets Autonomous Region. The authors considered migration processes and their trends; some of these were analyzed at municipal level. Having taken in account the importance of life expectancy as a complex indicator of sustainable development, the authors identified the periods of its growth and decline. Age-specific differences were also scrutinized. The relative contributions of major causes of mortality in life expectancy at birth were estimated. The authors described the dynamics of population of small indigenous peoples of the North (Vepsians, Nenets, Komi), the problems associated with their self-identification, census administration, migration, childbirth and life expectancy. The authors analyzed climate change as the new health risk factor, which affects safety of food and drinking water, accessibility of medical services and specific practices of deer-herding. A separate chapter of the book is devoted to current and future trends in working-age population until 2002. Each territory of Barents Sea Region displayed its own peculiar behavior of this indicator. The authors compared selected social, economic and demographic indicators in European part of Russian Arctic with those in foreign countries which belong to Barents Sea Region. This monograph was a product of collaborative efforts of the researchers from Economic Forecasting Institute and Institute of Demography of Higher School of Economics. B. A. Revich, Doctor of Medicine, and B. N. Porfiryev, Corresponding Member of Russian Academy of Sciences, edited this book.
In the internal medicine wide spectrum the gastroenterology is one of the chapters, less enlightened by the scientific evidence. It does not mean that the practice of the grasntroenterology may ot be improved by the systematic use of the approaches of the evidence based medicine
This prototype development explains the challenges encountered during the ISO/IEEE 11073 standard implementation process. The complexity of the standard and the consequent heavy requirements, which have not encouraged software engineers to adopt the standard. The developing complexity evaluation drives us to propose two possible implementation strategies that cover almost all possible use cases and eases handling the standard by non-expert users. The first one is focused on medical devices (MD) and proposes a low-memory and low-processor usage technique. It is based on message patterns that allow simple functions to generate ISO/IEEE 11073 messages and to process them easily. MD act as X73 agent. Second one is focused on more powerful device X73 manager, which do not have the MDs' memory and processor usage constraints. The protocol between Agent and Manager is point-to-point and we can distribute the functionality between devices.
Developed both implementation X73 Agent and Manager will cut developing time for applications based on ISO/EEE 11073.