Increased plasma levels of the mature and intermediate forms of adrenomedullin in obesity

Adrenomedullin (AM) is a cardiovascular protective peptide produced in various organs and tissues including adipose tissue. In the present study, we measured the plasma AM levels of subjects with or without obesity by two assay methods to separately evaluate the biologically active AM–NH₂ and the intermediate form of AM–glycine (AM–Gly). We measured the total AM and AM–NH₂ levels of plasma in 52 obese and 172 non-obese residents of a Japanese community, who received regular health check-ups and had no overt cardiovascular disease. AM–Gly values were obtained by subtracting AM–NH₂ levels from those of total AM. Both the AM–NH₂ and AM–Gly levels of the subjects with obesity were higher than those without obesity, and significant relationships were noted between body mass index (BMI) and the plasma levels of the two molecular forms of AM in a simple regression analysis. Moreover, the significant factors identified by multivariate analyses were BMI and serum triglyceride for AM–NH₂ and diastolic blood pressure, insulin, high-density lipoprotein-cholesterol, and plasma renin activity for AM–Gly. These results suggest active roles for the two molecular forms of AM in metabolic disorders associated with obesity in subjects without overt cardiovascular disease.     

A Computational Predictor of Human Episodic Memory Based on a Theta Phase Precession Network

In the rodent hippocampus, a phase precession phenomena of place cell firing with the local field potential (LFP) theta is called “theta phase precession” and is considered to contribute to memory formation with spike time dependent plasticity (STDP). On the other hand, in the primate hippocampus, the existence of theta phase precession is unclear. Our computational studies have demonstrated that theta phase precession dynamics could contribute to primate–hippocampal dependent memory formation, such as object–place association memory. In this paper, we evaluate human theta phase precession by using a theory–experiment combined analysis. Human memory recall of object–place associations was analyzed by an individual hippocampal network simulated by theta phase precession dynamics of human eye movement and EEG data during memory encoding. It was found that the computational recall of the resultant network is significantly correlated with human memory recall performance, while other computational predictors without theta phase precession are not significantly correlated with subsequent memory recall. Moreover the correlation is larger than the correlation between human recall and traditional experimental predictors. These results indicate that theta phase precession dynamics are necessary for the better prediction of human recall performance with eye movement and EEG data. In this analysis, theta phase precession dynamics appear useful for the extraction of memory-dependent components from the spatio–temporal pattern of eye movement and EEG data as an associative network. Theta phase precession may be a common neural dynamic between rodents and humans for the formation of environmental memories.     

Subbarrel Patterns in Somatosensory Cortical Barrels Can Emerge from Local Dynamic Instabilities

Complex spatial patterning, common in the brain as well as in other biological systems, can emerge as a result of dynamic interactions that occur locally within developing structures. In the rodent somatosensory cortex, groups of neurons called “barrels” correspond to individual whiskers on the contralateral face. Barrels themselves often contain subbarrels organized into one of a few characteristic patterns. Here we demonstrate that similar patterns can be simulated by means of local growth-promoting and growth-retarding interactions within the circular domains of single barrels. The model correctly predicts that larger barrels contain more spatially complex subbarrel patterns, suggesting that the development of barrels and of the patterns within them may be understood in terms of some relatively simple dynamic processes. We also simulate the full nonlinear equations to demonstrate the predictive value of our linear analysis. Finally, we show that the pattern formation is robust with respect to the geometry of the barrel by simulating patterns on a realistically shaped barrel domain. This work shows how simple pattern forming mechanisms can explain neural wiring both qualitatively and quantitatively even in complex and irregular domains.     

Rhythmicity of Biopotentials: Its Origin and Involvement in Information Processing

Experimental data and mathematical simulation of a neural network were used to develop ideas concerning the origin of the rhythmicity of biopotentials and its involvement in information processing. Baseline slow oscillations—the primate α rhythm, the α-like rhythms of lower animals, the Δ rhythm of humans and animals, secondary components of sensory evoked potentials or responses to direct brain stimulation, and pathological epileptiform potentials—develop as a result of interactions between excitatory and inhibitory postsynaptic potentials. The main inhibitory transmitter in the brain cortex is γ-aminobutyric acid (GABA). EEG activation in the form of a decrease in the amplitude of baseline oscillations and the appearance of the stress rhythm in the θ band upon exposure to new or biologically significant stimuli is associated with a relative decay of inhibitory hyperpolarization processes. The cholinergic and noradrenergic neurotransmitter systems are substantially involved in the rearrangement of the neural activity associated with EEG activation. An enhancement of high-amplitude baseline oscillations and phasic activity of neurons, i.e., alternation of activation and inhibition of firing, which reflects a relative enhancement of hyperpolarization processes, restricts excitation propagation over brain structures and impedes the fixation of new information. As a result of the decay of the inhibitory processes, EEG activation is accompanied by a higher regularity of neuronal firing and a decrease in entropy in the time distribution of firing in the form of tonic or grouped (in the stress rhythm) discharges. The resulting ordered streams of impulses transfer information, control its propagation, and ensure its fixation and reproduction.__________Translated from Fiziologiya Cheloveka, Vol. 31, No. 3, 2005, pp. 59–71.Original Russian Text Copyright © 2005 by Shul’gina.     

Neural signatures of syntactic variation in speech planning

Planning to speak is a challenge for the brain, and the challenge varies between and within languages. Yet, little is known about how neural processes react to these variable challenges beyond the planning of individual words. Here, we examine how fundamental differences in syntax shape the time course of sentence planning. Most languages treat alike (i.e., align with each other) the 2 uses of a word like “gardener” in “the gardener crouched” and in “the gardener planted trees.” A minority keeps these formally distinct by adding special marking in 1 case, and some languages display both aligned and nonaligned expressions. Exploiting such a contrast in Hindi, we used electroencephalography (EEG) and eye tracking to suggest that this difference is associated with distinct patterns of neural processing and gaze behavior during early planning stages, preceding phonological word form preparation. Planning sentences with aligned expressions induces larger synchronization in the theta frequency band, suggesting higher working memory engagement, and more visual attention to agents than planning nonaligned sentences, suggesting delayed commitment to the relational details of the event. Furthermore, plain, unmarked expressions are associated with larger desynchronization in the alpha band than expressions with special markers, suggesting more engagement in information processing to keep overlapping structures distinct during planning. Our findings contrast with the observation that the form of aligned expressions is simpler, and they suggest that the global preference for alignment is driven not by its neurophysiological effect on sentence planning but by other sources, possibly by aspects of production flexibility and fluency or by sentence comprehension. This challenges current theories on how production and comprehension may affect the evolution and distribution of syntactic variants in the world’s languages.

Little is known about the neural processes involved in planning to speak. This study uses eye-tracking and EEG to show that speakers prepare sentence structures in different ways and rely on alpha and theta oscillations differently when planning sentences with and without agent case marking, challenging theories on how production and comprehension affect language evolution.     

Study of the genesis of pathological EEG patterns in tumor and traumatic lesions of the human brain

Computer-assisted superimposition of the equivalent dipole sources (EDSs) of the main pathological EEG patterns with the results of computer tomography and magnetic resonance imaging of the brain was performed for patients with organic CNS lesions. The greatest degree of structural determination was revealed for local and lateralized (in a traumatic injury) slow waves, whose EDSs mapped to the perifocal zone of the injury focus. The EDSs of epileptiform patterns could be located in the zone of damaged brain substance or in the intact hemisphere (when the limbic structures were damaged), reflecting the formation of secondary functional foci in the latter case. Bilateral paroxysmal patterns were more frequently determined by the functional state of the medial brain structures. The EDSs of pathological (diencephalic, hippocampal) activity were closely associated with the corresponding anatomical brain structures, although without a strict dependence on the degree of their morphological intactness.Translated from Fiziologiya Cheloveka, Vol. 31, No. 1, 2005, pp. 24–32.Original Russian Text Copyright © 2005 by Boldyreva, Sharova, Koptelov, Shchepetkov, Nikitin, Kornienko, Fadeeva.     

The physical basis of alpha waves in the electroencephalogram and the origin of the “Berger effect”

Synchronised activity, differing in phase in different populations of neurons, plays an important role in existing theories on the function of brain oscillations (e.g., temporal correlation hypothesis). A prerequisite for this synchronisation is that stimuli are capable of affecting (resetting) the phase of brain oscillations. Such a change in the phase of brain waves is also assumed to underlie the Berger effect: when observers open their eyes, the amplitude of EEG oscillations in the alpha band (8–13 Hz) decreases significantly. This finding is usually thought to involve a desynchronisation of activity in different neurons. For functional interpretations of brain oscillations in the visual system, it therefore seems to be crucial to find out whether or not the phase of brain oscillations can be affected by visual stimuli. To answer this question, we investigated whether alpha waves are generated by a linear or a nonlinear mechanism. If the mechanism is linear – in contrast to nonlinear ones – phases cannot be reset by a stimulus. It is shown that alpha-wave activity in the EEG comprises both linear and nonlinear components. The generation of alpha waves basically is a linear process and flash-evoked potentials are superimposed on ongoing alpha waves without resetting their phase. One nonlinear component is due to light adaptation, which contributes to the Berger effect. The results call into question theories about brain-wave function based on temporal correlation or event-related desynchronisation.Electronic Supplementary Material: Supplementary material is available for this article at     

Two Distinct Dynamic Modes Subtend the Detection of Unexpected Sounds

The brain response to auditory novelty comprises two main EEG components: an early mismatch negativity and a late P300. Whereas the former has been proposed to reflect a prediction error, the latter is often associated with working memory updating. Interestingly, these two proposals predict fundamentally different dynamics: prediction errors are thought to propagate serially through several distinct brain areas, while working memory supposes that activity is sustained over time within a stable set of brain areas. Here we test this temporal dissociation by showing how the generalization of brain activity patterns across time can characterize the dynamics of the underlying neural processes. This method is applied to magnetoencephalography (MEG) recordings acquired from healthy participants who were presented with two types of auditory novelty. Following our predictions, the results show that the mismatch evoked by a local novelty leads to the sequential recruitment of distinct and short-lived patterns of brain activity. In sharp contrast, the global novelty evoked by an unexpected sequence of five sounds elicits a sustained state of brain activity that lasts for several hundreds of milliseconds. The present results highlight how MEG combined with multivariate pattern analyses can characterize the dynamics of human cortical processes.     

Mesoscopic neurodynamics: From neuron to brain

Intelligent behavior is characterized by flexible and creative pursuit of endogenously defined goals. Intentionality is a key concept by which to link neuron and brain to goal-directed behavior through brain dynamics. An archetypal form of intentional behavior is an act of observation in space-time, by which information is sought for the guidance of future action to explore unpredictable and ever-changing environments. These acts are based in the brain dynamics that creates spatiotemporal patterns of neural activity, serving as images of goals, of command sequences by which to act to reach goals, and of expected changes in sensory input resulting from intended actions. Prediction of the sensory consequences of intended action and evaluation of performance is by reafference. An intentional act is completed upon modification of the system by itself through learning. These principles are well known among psychologists and philosophers. What is new is the development of nonlinear mesoscopic brain dynamics, by which the theory of chaos can be used to understand and simulate the constructions of meaningful patterns of neural activity that implement the process of observation. The design of neurobiological experiments, analysis of the resulting data, and synthesis of explanatory models require an understanding of the hierarchical nature of brain organization, here conceived as single neurons and neural networks at the microscopic level; clinically defined cortical and subcortical systems studied by brain imaging (for example, fMRI) at the macroscopic level, and self-organizing neural populations at an intermediate mesoscopic level, at which synaptic interactions create novel activity patterns through nonlinear state transitions. The constructive neurodynamics of sensory cortices, when they are engaged in pattern recognition, is revealed by learning-dependent spatial patterns of amplitude modulation and by newly discovered radially symmetric spatial gradients of the phase of aperiodic carrier waves in multichannel subdural EEG recordings.     

Complexity of Multi-Dimensional Spontaneous EEG Decreases during Propofol Induced General Anaesthesia

Emerging neural theories of consciousness suggest a correlation between a specific type of neural dynamical complexity and the level of consciousness: When awake and aware, causal interactions between brain regions are both integrated (all regions are to a certain extent connected) and differentiated (there is inhomogeneity and variety in the interactions). In support of this, recent work by Casali et al (2013) has shown that Lempel-Ziv complexity correlates strongly with conscious level, when computed on the EEG response to transcranial magnetic stimulation. Here we investigated complexity of spontaneous high-density EEG data during propofol-induced general anaesthesia. We consider three distinct measures: (i) Lempel-Ziv complexity, which is derived from how compressible the data are; (ii) amplitude coalition entropy, which measures the variability in the constitution of the set of active channels; and (iii) the novel synchrony coalition entropy (SCE), which measures the variability in the constitution of the set of synchronous channels. After some simulations on Kuramoto oscillator models which demonstrate that these measures capture distinct ‘flavours’ of complexity, we show that there is a robustly measurable decrease in the complexity of spontaneous EEG during general anaesthesia.     

Localization of neural efficiency of the mathematically gifted brain through a feature subset selection method

Based on the neural efficiency hypothesis and task-induced EEG gamma-band response (GBR), this study investigated the brain regions where neural resource could be most efficiently recruited by the math-gifted adolescents in response to varying cognitive demands. In this experiment, various GBR-based mental states were generated with three factors (level of mathematical ability, task complexity, and short-term learning) modulating the level of neural activation. A feature subset selection method based on the sequential forward floating search algorithm was used to identify an “optimal” combination of EEG channel locations, where the corresponding GBR feature subset could obtain the highest accuracy in discriminating pairwise mental states influenced by each experiment factor. The integrative results from multi-factor selections suggest that the right-lateral fronto–parietal system is highly involved in neural efficiency of the math-gifted brain, primarily including the bilateral superior frontal, right inferior frontal, right-lateral central and right temporal regions. By means of the localization method based on single-trial classification of mental states, new GBR features and EEG channel-based brain regions related to mathematical giftedness were identified, which could be useful for the brain function improvement of children/adolescents in mathematical learning through brain–computer interface systems.     

Exploring Age-Related Changes in Dynamical Non-Stationarity in Electroencephalographic Signals during Early Adolescence

Dynamics of brain signals such as electroencephalogram (EEG) can be characterized as a sequence of quasi-stable patterns. Such patterns in the brain signals can be associated with coordinated neural oscillations, which can be modeled by non-linear systems. Further, these patterns can be quantified through dynamical non-stationarity based on detection of qualitative changes in the state of the systems underlying the observed brain signals. This study explored age-related changes in dynamical non-stationarity of the brain signals recorded at rest, longitudinally with 128-channel EEG during early adolescence (10 to 13 years of age, 56 participants). Dynamical non-stationarity was analyzed based on segmentation of the time series with subsequent grouping of the segments into clusters with similar dynamics. Age-related changes in dynamical non-stationarity were described in terms of the number of stationary states and the duration of the stationary segments. We found that the EEG signal became more non-stationary with age. Specifically, the number of states increased whereas the mean duration of the stationary segment decreased with age. These two effects had global and parieto-occipital distribution, respectively, with the later effect being most dominant in the alpha (around 10 Hz) frequency band.     

MEG responses to the perception of global structure within glass patterns

Background

The perception of global form requires integration of local visual cues across space and is the foundation for object recognition. Here we used magnetoencephalography (MEG) to study the location and time course of neuronal activity associated with the perception of global structure from local image features. To minimize neuronal activity to low-level stimulus properties, such as luminance and contrast, the local image features were held constant during all phases of the MEG recording. This allowed us to assess the relative importance of striate (V1) versus extrastriate cortex in global form perception.

Methodology/Principal Findings

Stimuli were horizontal, rotational and radial Glass patterns. Glass patterns without coherent structure were viewed during the baseline period to ensure neuronal responses reflected perception of structure and not changes in local image features. The spatial distribution of task-related changes in source power was mapped using Synthetic Aperture Magnetometry (SAM), and the time course of activity within areas of maximal power change was determined by calculating time-frequency plots using a Hilbert transform. For six out of eight observers, passive viewing of global structure was associated with a reduction in 10–20 Hz cortical oscillatory power within extrastriate occipital cortex. The location of greatest power change was the same for each pattern type, being close to or within visual area V3a. No peaks of activity were observed in area V1. Time-frequency analyses indicated that neural activity was least for horizontal patterns.

Conclusions

We conclude: (i) visual area V3a is involved in the analysis of global form; (ii) the neural signature for perception of structure, as assessed using MEG, is a reduction in 10–20 Hz oscillatory power; (iii) different neural processes may underlie the perception of horizontal as opposed to radial or rotational structure; and (iv) area V1 is not strongly activated by global form in Glass patterns.     

Sustained neural rhythms reveal endogenous oscillations supporting speech perception

Rhythmic sensory or electrical stimulation will produce rhythmic brain responses. These rhythmic responses are often interpreted as endogenous neural oscillations aligned (or “entrained”) to the stimulus rhythm. However, stimulus-aligned brain responses can also be explained as a sequence of evoked responses, which only appear regular due to the rhythmicity of the stimulus, without necessarily involving underlying neural oscillations. To distinguish evoked responses from true oscillatory activity, we tested whether rhythmic stimulation produces oscillatory responses which continue after the end of the stimulus. Such sustained effects provide evidence for true involvement of neural oscillations. In Experiment 1, we found that rhythmic intelligible, but not unintelligible speech produces oscillatory responses in magnetoencephalography (MEG) which outlast the stimulus at parietal sensors. In Experiment 2, we found that transcranial alternating current stimulation (tACS) leads to rhythmic fluctuations in speech perception outcomes after the end of electrical stimulation. We further report that the phase relation between electroencephalography (EEG) responses and rhythmic intelligible speech can predict the tACS phase that leads to most accurate speech perception. Together, we provide fundamental results for several lines of research—including neural entrainment and tACS—and reveal endogenous neural oscillations as a key underlying principle for speech perception.

Just as a child on a swing continues to move after the pushing stops, this study reveals similar entrained rhythmic echoes in brain activity after hearing speech and electrical brain stimulation; perturbation with tACS shows that these brain oscillations help listeners to understand speech.     

Definitions of state variables and state space for brain–computer interface

The hypothesis is proposed that the central dynamics of the action–perception cycle has five steps: emergence from an existing macroscopic brain state of a pattern that predicts a future goal state; selection of a mesoscopic frame for action control; execution of a limb trajectory by microscopic spike activity; modification of microscopic cortical spike activity by sensory inputs; construction of mesoscopic perceptual patterns; and integration of a new macroscopic brain state. The basis is the circular causality between microscopic entities (neurons) and the mesoscopic and macroscopic entities (populations) self-organized by axosynaptic interactions. Self-organization of neural activity is bidirectional in all cortices. Upwardly the organization of mesoscopic percepts from microscopic spike input predominates in primary sensory areas. Downwardly the organization of spike outputs that direct specific limb movements is by mesoscopic fields constituting plans to achieve predicted goals. The mesoscopic fields in sensory and motor cortices emerge as frames within macroscopic activity. Part 1 describes the action–perception cycle and its derivative reflex arc qualitatively. Part 2 describes the perceptual limb of the arc from microscopic MSA to mesoscopic wave packets, and from these to macroscopic EEG and global ECoG fields that express experience-dependent knowledge in successive states. These macroscopic states are conceived to embed and control mesoscopic frames in premotor and motor cortices that are observed in local ECoG and LFP of frontoparietal areas. The fields sampled by ECoG and LFP are conceived as local patterns of neural activity in which trajectories of multiple spike activities (MSA) emerge that control limb movements. Mesoscopic frames are located by use of the analytic signal from the Hilbert transform after band pass filtering. The state variables in frames are measured to construct feature vectors by which to describe and classify frame patterns. Evidence is cited to justify use of linear analysis. The aim of the review is to enable researchers to conceive and identify goal-oriented states in brain activity for use as commands, in order to relegate the details of execution to adaptive control devices outside the brain. http://sulcus.berkeley.edu     

EEG Spectral Characteristics in Junior Schoolchildren with Learning Problems

EEG spectral characteristics were studied in two age groups (7–8.5 and 8.5–10 years) of mentally healthy children and children with learning problems at rest and during performance of a Raven test. It was shown that slow frequencies are more pronounced in the EEG of 7- to 8.5-year-old children with learning problems than in EEG of healthy children of the same age group. An immature form of EEG activation, i.e., an increase not only in the but also in the frequencies during activity, was characteristic of these children. The reaction of the activation of the definitive type develops between the 8.5–10 years of age. This reaction is correlated with an increase in the efficiency of the sensory perceptive and sensorimotor activity. The distinctive feature of children with learning problems between 8.5–10 years of age is a greater expression of slow frequencies in the baseline EEG of the frontal (in particular, left frontal) areas of the cortex. The obtained results are considered as a reflection of a retardation of the functional maturation of the brain structures responsible for the deficit of involuntary and voluntary attention and the disorder of a systemic organization of perception and analytical–synthetic brain activity as compared to the normal age characteristics. Possible neurophysiological mechanisms responsible for learning problems in junior schoolchildren are discussed on the basis of the obtained results and evidence from the literature.     

A novel index of functional connectivity: phase lag based on Wilcoxon signed rank test

Phase synchronization has been an effective measurement of functional connectivity, detecting similar dynamics over time among distinct brain regions. However, traditional phase synchronization-based functional connectivity indices have been proved to have some drawbacks. For example, the phase locking value (PLV) index is sensitive to volume conduction, while the phase lag index (PLI) and the weighted phase lag index (wPLI) are easily affected by noise perturbations. In addition, thresholds need to be applied to these indices to obtain the binary adjacency matrix that determines the connections. However, the selection of the thresholds is generally arbitrary. To address these issues, in this paper we propose a novel index of functional connectivity, named the phase lag based on the Wilcoxon signed-rank test (PLWT). Specifically, it characterizes the functional connectivity based on the phase lag with a weighting procedure to reduce the influence of volume conduction and noise. Besides, it automatically identifies the important connections without relying on thresholds, by taking advantage of the framework of the Wilcoxon signed-rank test. The performance of the proposed PLWT index is evaluated on simulated electroencephalograph (EEG) datasets, as well as on two resting-state EEG datasets. The experimental results on the simulated EEG data show that the PLWT index is robust to volume conduction and noise. Furthermore, the brain functional networks derived by PLWT on the real EEG data exhibit a reasonable scale-free characteristic and high test–retest (TRT) reliability of graph measures. We believe that the proposed PLWT index provides a useful and reliable tool to identify the underlying neural interactions, while effectively diminishing the influence of volume conduction and noise.     

Associative Processing Is Inherent in Scene Perception

How are complex visual entities such as scenes represented in the human brain? More concretely, along what visual and semantic dimensions are scenes encoded in memory? One hypothesis is that global spatial properties provide a basis for categorizing the neural response patterns arising from scenes. In contrast, non-spatial properties, such as single objects, also account for variance in neural responses. The list of critical scene dimensions has continued to grow—sometimes in a contradictory manner—coming to encompass properties such as geometric layout, big/small, crowded/sparse, and three-dimensionality. We demonstrate that these dimensions may be better understood within the more general framework of associative properties. That is, across both the perceptual and semantic domains, features of scene representations are related to one another through learned associations. Critically, the components of such associations are consistent with the dimensions that are typically invoked to account for scene understanding and its neural bases. Using fMRI, we show that non-scene stimuli displaying novel associations across identities or locations recruit putatively scene-selective regions of the human brain (the parahippocampal/lingual region, the retrosplenial complex, and the transverse occipital sulcus/occipital place area). Moreover, we find that the voxel-wise neural patterns arising from these associations are significantly correlated with the neural patterns arising from everyday scenes providing critical evidence whether the same encoding principals underlie both types of processing. These neuroimaging results provide evidence for the hypothesis that the neural representation of scenes is better understood within the broader theoretical framework of associative processing. In addition, the results demonstrate a division of labor that arises across scene-selective regions when processing associations and scenes providing better understanding of the functional roles of each region within the cortical network that mediates scene processing.     

Role of the Right- and Left-Hemispheric Structures in Speech and Memory Formation in Children

The role of structures of the left and right cerebral hemispheres in formation of speech function and memory was studied on the basis of complex examination of children with developmental speech disorders. On the basis of EEG estimation of the functional state of the brain, children were classified in two groups depending on the side of localization of changes in electrical activity: those with local changes in electrical activity in the left hemisphere (group I) and those with changes in the right hemisphere (group II). The medical history suggested that the observed features of topography of local changes in electrical activity were linked with the character of prenatal and labor complications and their consequences leading to embryo- and ontogenetic disorders in development of different brain regions. Comparison of the results of neuropsychological examination of the two groups showed that different regions of the brain cortex of both the left and right hemispheres are involved in speech formation. However, a specific role of the right hemisphere in formation and actualization of automatic speech series was revealed. It was suggested that the integrity of gnostic functions of the right hemisphere and, primarily, the spatial organization of perception and movements is a necessary factor of development of auditory–speech and nominative memory.     

Interhemispheric EEG Coherence during Rehabilitation of Patients after Severe Craniocerebral Injury

Dynamic clinical and EEG examinations (78 observations) were carried out in 17 patients suffering from severe craniocerebral injury during the course of their rehabilitation. Successful recovery of functions to the point of social and family readaptation was reached in 61% of patients (group I), and in 39% of patients the results were poor (group II). The complex of EEG coherence parameters (six rhythmic bands, mean coherence levels for 26 intrahemispheric and 8 interhemispheric derivation pairs, and the asymmetry coefficient of the EEG coherence) was analyzed in patients in comparison with normal values (20 right-handers). The rehabilitation was most efficient in cases when a certain dynamic sequence of patterns of interhemispheric relations of the EEG coherence was observed. First, a stable formation of right-hemispheric dominance was observed (most expressed in the centrofrontal areas in the range). This asymmetry pattern was phenomenologically associated with the recovery of the emotional sphere and positive dynamics in the motor and autonomic spheres. Later on, formation of the left-hemispheric dominance of the EEG coherence was observed (in the frontotemporal areas in the – ranges. This pattern was associated with complication of the cognitive functions. In the most severe forms of brain damage, the rehabilitation process was accompanied by changes in the interhemispheric EEG coherence with the elements of stealing from one of the hemispheres, which was correlated with clinical dynamics. Different types of the dynamics of reactive changes in the EEG coherence were revealed in patients of the two groups: successive formation of a generalized and then local modally specific reaction to afferent stimuli was observed in group I, while the generalized type of reactivity persisted in group II until the end of rehabilitation. It is suggested that the different sequence of formation of the interhemispheric EEG coherence reflects the involvement of different brain regulation systems in different orders into the integrative activity, i.e., some specific features of the rehabilitation process.