Traumatic brain injury (TBI) usually resulting from a blow to the head is most common in people of working age, although it happens in the elderly too. TBI is a result of falls, road accidents, sports injuries, etc. Posttraumatic disorders are typically multi-component and involve the damage of pathways, cortical and subcortical structures     . Some injuries classified as moderate (mTBI) are not accompanied by hemiparesis and other neurological deficiencies. However, there is growing evidence that even years after mTBI, cognitive, affective, and behavioral functions may change, which leads to insolvency in work, school, or in social relations. Diffuse axonal injury is frequent in TBI (including mTBI) and disintegration is a significant pathogenic factor in this form of the brain pathology . Disintegrative processes including corpus callosum were described mostly in mTBI patients accompanied by disorders in different spheres  - .
Some investigations using brain imaging and other techniques have been devoted to links between brain disturbances with predominantly cognitive decline and attempts to return to former professional activity in mTBI patients  .
However, brain mechanisms of disorders during complex functional loads simulating real life after mTBI are not well understood. In context of professional human, dual-task algorithm modeling routine loads of real life is of considerable research interest in last time  - .
Different experimental situations were used for these purposes and the so-called dual-tasks are among them. Two tasks, including, as a rule, cognitive and motor components (walking and talking) have been suggested to solve  - . Walking as a motor component combined with cognitive tasks, such as talking, calculation, memorizing of text fragments or word lists, is often used in choice of dual-task components. Although walking is an automatic activity in healthy adults, it is also needs participation of cognitive functions. In the same way as other type of motor activity, voluntary postural control can be used for dual-tasking  - .
The ability to modulate attention may play an important role in the acquisition of dual-task coordination skill. The participation of cognitive component in the maintenance of dual-tasking (motor and cognitive) in healthy persons is confirmed by experimental studies  . Healthy individuals more often demonstrate lower quality of dual-tasking than quality of every task performed separately, while there are situations with more successful dual-task performance  . In extreme situations, certain individuals are also known to cope with exceptionally challenging tasks, which they are not able to carry out under the usual conditions. For example, professional athletes with their automated skills for performing motor loads are capable of higher-quality dual-task performance in compare with isolated ones . Our previous data demonstrated more successful performance of dual-task vs isolated ones by healthy persons with high levels of cognitive resource—volume of attention and memory, attention switching speed and others .
Although postural control of standing is highly automated, combining standing with cognitive task can interfere with the execution of one or both tasks in adult healthy subjects  . An impaired ability to maintain balance with simultaneously cognitive tasks has been associated with cognitive functional and physical decline in TBI patients  . On the other hand, a similar decrease in performance was observed in the elderly compared with young healthy people  .
These studies propose that the elderly require more processing resources for single-task performance, therefore increasing interference during dual-tasking . Results of some investigations demonstrated cognitive impairments, physical decline, etc., accompanying brain volume loss after trauma . These data allowed some authors to propose accelerated brain aging after TBI . They hypothesized that the discrepancy between chronological and predicted brain age would be reflected in cognitive changes and consistent with age-related cognitive impairment in older individuals and in patients after TBI .
There are different points of view on the brain mechanisms of dual-tasking performance in elderly healthy people and in TBI patients. The first one is: the same brain areas are used in both dual-task performance and separate performance of each ones. On the other hand there are data on involvement of additional brain areas and mobilization of additional brain resources in old persons or TBI patients     . It is specially noted mostly that the quality of performance of each component is worsened during dual-tasking in comparison with separate performance due to activity decrease of specific brain areas participating in both components of the dual-tasks in healthy persons, especially in the elderly and patients with brain damage  .
Advances in brain imaging have revealed important information regarding both structural   and functional    alteration in healthy adults, in old persons and in TBI patients. There is now overwhelming evidence that the elderly and TBI patients use explained brain networks and increased brain activation to perform a single motor or cognitive tasks or dual-tasks  - . The age- or traumatic-related increase in neural activation may lead to greater structural interference     . This hypothesis was tested in oddball task study with arithmetic and visual-motor task by looking at the increase in brain activation from single—to dual-task in shared brain regions . Less upregulation in the elderly or traumatic patients compared with young adults would indicate greater structural interference. Overlapping brain activation was observed in the elderly (or TBI patients) during performance of both single as well dual-tasks    . Another often debated aspect of dual-tasking is whether it requires additional brain activation of nonspecific motor or cognitive component of dual-tasking in aged persons or TBI patients . Usually balance-cognitive dual-tasking have been studied at behavioral level while in our study we would like to examine the neural correlates of balance-cognitive dual-tasking in mTBI patients compared in healthy adults using electroencephalogram (EEG).
EEG contains temporal component of the functional brain activation. EEG analysis gives the possibility to describe (both quantitatively and qualitatively) functional state of the human brain    . It is the important approach for estimation of reactive changes of the brain in mTBI patients while dual-tasking. The coherent analysis of EEG is widely used to estimate interregional relationship as systemic activity of the human brain. Coherent parameters of bioelectrical activity of the human brain were rather informative in analyzing of healthy brain connectivity and allow to estimate disconnection phenomenon in patients with organic lesions including mTBI  -    . The use of complex approach, which additionally includes a stabilographic study and quantitative clinical scales, expands the possibilities for assessing functional resources of a person in normal conditions or with various forms of cerebral pathology  - .
The aim of this investigation was to compare the efficiency of dual-task performance in mTBI patients in comparison with healthy people of the same age. We would like also to test the hypothesis of the brain aging in patients with mTBI and to estimate the effect of dual-task training as rehabilitation tool for improving the everyday life and social adaptation of patients after mTBI.
2. Materials and Methods
The study included 17 healthy subjects (11 male and 6 female aged 26.7 ± 5.1). The group of patients included 11 subjects with mTBI (7 male and 4 female aged 28.8 ± 8.4). The inclusion criteria to patient’s group were possibility to maintain a vertical posture without support, to understand and follow physician’s instructions. According to the Annett Hand Preference Questionnaire, all healthy subjects and patients were right-handed . Each subject signed an informed consent for the study approved by Ethics Committee at Institute of Higher Nervous Activity and Neurophysiology of Russian Academy of Sciences.
2.2. Data Acquisition and Processing
2.2.1. Clinical Assessment of Patients
Quantitative assessment of patient deficits in different spheres (motor, cognitive, emotional, etc.) was carried out using clinical scales (presented in Table 1): MPAI (Mayo-Portland Adaptability Inventory); FIM (Functional Independence Measure); MMSE (Mini Mental State Examination); Berg scale, assessing posture control .
Table 1. Summary of mTBI patients and parameters of clinical scales.
Note: SD—standard deviation. *—marked patients who have undergone rehabilitation course; in brackets, the values of the clinical scales after the rehabilitation course.
2.2.2. EEG Recording and Analysis
Monopolar EEG was recorded from 19 scalp locations, according to the international 10 - 20 system, using telemetric encephalograph (“Encephalan”, Russia) with a spectral band of 0.5 - 70 Hz and a sampling frequency of 250 Hz. As the reference, the combined ear electrode was used. EEG recording was performed throughout the experiment: at rest—maintaining a vertical posture on the stabiloplatform and during the performance of all tasks. Primary processing of EEG was carried out manually in the software of “Encephalan” in order to remove artifacts, including artifacts associated with the eye movements, and filter in the range of 0.5 - 40 Hz. The next step of processing was the spectral-coherent analysis which was calculated with a step 0.4 Hz for the following EEG frequency bands: delta, 1.2 - 3.9 Hz; theta, 4.3 - 7.8 Hz; alpha1, 8.2 - 10.2 Hz; alpha2, 10.5 - 12.9 Hz; beta, 13.3 - 30 and gamma, 30.4 - 40 Hz. No less than nine epochs with a 5.12-s overlap were analyzed. Last 50 - 55 s EEG’s were segmented in epochs of 5.12 s (a total no less 10 epochs were taken). Fast Fourier Transformation and magnitude-squared coherence function using the MatLab 6.0 software package (Math Works Inc.) .
Statistical analysis of EEG data was carried out in the program Brainstorm. Multivariate analysis with FDR (false discovery rate) correction with significance level p < 0.01 was used. To compare data within one group the nonparametric Wilcoxon test was used for related samples. To compare a group of patients with a group of healthy subjects, a non-parametric Mann-Whitney test with p < 0.01 with FDR correction was used. To compare individual data for healthy or patients between different conditions (tasks), the nonparametric Wilcoxon test was used for related samples with a significance level of p < 0.01 without FDR correction.
2.2.3. Stabilographic Study and Analysis
In order to perform the motor task, stabilographic platform (Stabilan 0.1, Russia) was used (Figure 1). When the subject performed the motor task, he was instructed, standing on the stabiloplatform, to keep balance maintaining the common center of pressure in the same position or to chage of perssure presented on the monitor screen (9Fi 1A and B). In this study we analyzed performance quality of motor tasks performed isolatly and while dual-tasks and speed of pessure fluctuation in these experimental situation. The quality of motor task performance was assessed automatically using the stabilographic equipment as a percentage of the subject’s center of pressure fixing time within the specified coordinates.
Statistical analysis of stabilographic data was carried out using the Shapiro-Wilk test for normal distribution in with a threshold p < 0.05. The distribution was abnormal, therefore, further comparison of groups of healthy subjects and patients by all indicators was carried out using the non-parametric Mann-Whitney test for independent samples in the R programming environment for statistical data processing (RStudio).The criterion of statistically significant differences between the two groups was p ≤ 0.05.
(a) (b) (c) (d)
Figure 1. The examples of experimental procedures. (а) motor static task М1, (b) motor dynamic task М2, (c) dual task C1M1, (d) dual task C2M1 (see explanation in the text).
2.2.4. Diffusion Tensor MRI Tractography Study
Diffusion tensor imaging (DTI) tractography is an imaging technique that quantifies water diffusivity along the axons, enabling in vivo study of neural pathways including of corpus callosum . MRI scan was performed using GE Signa HDxt 3.0T equipment (GE healthcare, Milwaukee, WI). Whole brain tractography was studied using ISA + BSM to reconstruct streamlines of white matter fibers using functional MRI. Along the tracts of each zone of corpus callosum, the FA was calculated, characterizing the integrity of axons. The correlation coefficient between the measurements by both experts was 0.92. Three patients from patient’s group and nine healthy volunteer were included in DTI tractography study.
2.3. Experimental Tasks
We used two cognitive and two motor tasks, which were presented initially separately and then simultaneously, using different variants. Participants performed motor tasks on the stabilographic platform with visual feedback. During the first “static” motor task (M1), the subject had to keep balance, holding the red circle, which reflects the position of his common center of pressure (CCP) on stabiloplatform, in the center of the target (Figure 1(a)). During the second “dynamic” motor task (M2), patient or a healthy volunteer had to change of CCP in accordance with the trajectory of movement presented on the screen. The green marker set the direction of movement (smoothly shifted to one of four sides), and the red marker displayed the participant’s position of center of pressure (Figure 1(b)). The task was to catch up green marker and hold the red on it.
As a cognitive task we used computing-logical C1 or C2 procedures. During the first cognitive task (C1) performance, the subject was asked to listen to series of high (800 Hz) and low tones (400 Hz) of 80 ms duration each, which were presented in a random order with varying intervals (Figure 1(c)). The percentage of low sounds was fewer than high tones and accounted for 40% of the total number presented. The subject needed to count mentally the number of the low-pitched presented tones. The second cognitive task (C2) was a listing of the names of objects in a random order, belonging to two categories (“clothing” or “food”, Figure 1(d)). Subject had to count number of objects belonging to one of two categories indicated by the experimenter, which also accounted for 40% of the total number of the all items. At the end of audio recording participant gave the answer. All tasks were presented for 60 s. The stimuli in two cognitive tasks were presented at a varying interval within 1.7 - 2.0 s. The quality of cognitive task performance was assessed by the number of computing operations performed per minute taking into account the number of errors.
2.4. The Experimental Setup
Telemetric equipment, including the electrode cap, was fixed on the head of the subject before the experiment. After, each participant was instructed about upcoming tasks and listened to the examples of cognitive tasks.
Firstly, the subject was standing on stabiloplatform with the eyes open without being instructed for 60 s while EEG was recorded. After he performed motor task M1 and then M2, also standing on the stabiloplatform. At the next stage of the study, the subject performed two cognitive tasks, standing on the floor with the eyes open (in front of the wall). After performing all isolated tasks, the participant standing again on the stabiloplatform started dual-tasking (С1M1, С2М1, С1М2, С2М2) in random order. Motor task also lasted 60 s.
2.5. Rehabilitation Procedure
Rehabilitation course with dual-tasks was carried out in four mTBI patients as a pilot study. It lasted 1.5 - 2 months with 2 sessions per week of 30 - 40 minutes duration for each session. Two tasks were used for simultaneous execution (cognitive and motor), differing from those used in the experiment described previously. It was done so that rehabilitation promotes learning to perform complex activities such as dual-tasks (motor and cognitive) with which patients can face in real life but not remembering of any tasks. The motor component included either walking along the corridor or performing stabilographic tasks with visual feedback. As a cognitive component, five variants of tasks were used, including a task for speech memory, attention, an understanding of the meaning of the text, spatial-visual and arithmetic tasks. Each rehabilitation session included new versions of cognitive tasks.
1) EEG data during dual-tasking
The results of the group-level EEG coherence analysis across single cognitive (C2), motor (M2) and dual-task (C2M2) performance are in Figure 2. It was shown an increase of EEG coherence (p < 0.01) for slow spectral bands (delta and theta) with some shift at the left hemisphere for performance of cognitive task. These data coincides with our and others previous data as marker of brain activation for cognitive task performance while dual-task procedure included other cognitive tasks (mental calculation)  . The single motor task performance (M2) was accompanied by an increase of EEG coherence (p < 0.01) for fast spectral bands (alpha-1, alpha-2 and beta) with some shift at the right hemisphere.
An increase of EEG coherence for cognitive and motor component was observed as specific brain activation while dual-tasks execution. This is consistent with our and others previous findings   . The decrease of EEG coherence for alpha 1 spectral band was observed predominantly at the frontal areas described us as a “conflict of interests” zone. These EEG coherence changes may be the reflection of “competition” for attention resources while each component of dual-task was performed.
Figure 3 shows the results of the group-level EEG coherence analysis across two-dual tasks performance: up row—while dual-task C1M1 was performed;
Figure 2. Averaged changes of EEG coherence while performing isolated C1 and M1 and also dual-tasks C1M1 in healthy subjects (n = 17) compared to baseline state (standing on the stabile platform with open eyes) (p < 0.01). Red lines demonstrate an increase of EEG coherence, while green lines—a decrease of EEG coherence.
Figure 3. Averaged changes of EEG coherence while performing dual-tasks C1M1 (A) and C2M2 (B) in healthy subjects (n = 17) were compared to baseline state (p < 0.01). Designations as in Figure 2.
lower row—while dual task C2M2 was performed by healthy persons. It was shown an increase of EEG coherence (p < 0.01) for slow spectral bands (delta and theta) with some shift at the left hemisphere for performance of both dual-tasks as a reflection of brain activation for cognitive component of dual-tasking with the most EEG coherence changes for the more difficult task (C2M2). These data coincides with our and other previous data while dual-task procedure included different cognitive task (mental calculation) and was performed by another group of healthy persons  .
Figure 4 demonstrates the results of individual EEG coherence analysis across two dual-tasks performance in p-t S and P-t F compared to baseline state. EEG coherence changes demonstrate the lower values for dual-tasking in both patients while in healthy persons (see Figure 2) The most decrease was observed for delta spectral bands (cognitive component) predominantly in frontal-temporal
Figure 4. Changes of EEG coherence compared to baseline state (p< 0.01) while performing dual-tasks C1M1 was performed in P-t S (18 y.o.; 5 months after TBI; MMSE—22; MPAI—25; FIM—110; Berg’s scale—56) and in B P-t F. (38 y.o., 1 month after TBI; MMSE—17; MPAI—35; FIM—83; Berg’s scale—53). Designations as in Figure 2.
areas of the left hemisphere for P-t F while dual-task C1M1 was performed. The decrease of EEG coherence for delta spectral bands was observed for long diagonal connections between frontal and parietal-occipital areas. EEG coherence for fast spectral bands had different reactive changes including signs of hypersynchronization for beta and gamma spectral band in patient F who had the most impairment of postural control (values of Berg’s scale at this patient was lower than in patient S).
According results of clinical scales examination (see Table 1) cognitive deficit in patients after trauma was more pronounced compared with ability to support vertical posture. The ability to maintain an upright posture has been practically intact in patients, but with greater efforts in comparison healthy persons (Figure 4(b) and Figure 6(c)). Cognitive data results at Figure 4 demonstrate the quality decline of cognitive component during dual-tasks performance in comparing with isolated performance, it declined even more when C2M2 dual-tasks executed.
Comparison of averaged EEG coherence values in healthy persons (n = 17) and patients with mTBI (n = 11) in state of rest (A) and while dual-task C1M1 are persented at Figure 5. EEG coherence decreased mostly only for slow spectral bands, whereas increase for fast spectral bands reflects more efforts for support the vertical pose in patients comparison healhy adults in state of wakefulness (open eyes). EEG coherence when performing dual tasks decreased for most slow frequencies in patients compared with healthy people (C2 + M2). These results demonstrate the possibility of using a persistent decrease in EEG coherence for slow frequencies as a marker of cognitive status.
2) Behavioral and stabilographic data during dual-tasking
Behavioral and stabilographic data estimated in single versus dual-task conditions are presented in Figure 6. They demonstrate the most decrease of the quality of cognitive tasks performance in dual-tasking versus single tasks, especially for C2. While the quality of motor tasks performance in isolation versus dual task conditions evaluated according to stabilographic data did not reveal significant differences from normative values.
Figure 5. Comparison of averaged EEG coherence changes in healthy persons (n = 17) and TBI (n = 11) in waking state (standing with open eyes) and during dual-task (p< 0.01). Designations as in Figure 2.
Figure 6. The quality of cognitive (C1, C2) and motor (M1) tasks performance, and single versus dual tasking conditions (in %) by healthy group (n = 17, blue bar) and by mTBI patients (n = 11, orange bar). *—significant changes p < 0.05.
3) Data of diffuse tensor MRI-Tractography study
Results of diffuse tensor MRI-tractography demonstrate decreased values of fraction anisotropy of patients with the greatest decline in anterior (frontal) areas (5 - 7) in comparison with healthy subjects (Figure 7). These low values of p-t’s fraction anisotropy correlated with cognitive decline (low values of MMSE scale) in patients in comparison normal values. The lowest values of fraction anisotropy were in p-t S, with the lowest values of MMSE scale of these patients.
Dual-Tasking as Rehabilitation Tool
As a pilot study, we included dual tasks in a special rehabilitation course for four TBI patients. Three patients underwent a rehabilitation course in the early period (2 - 5 months after TBI) (see Table 1), one in the delayed period (11 months after TBI). After early rehabilitation course positive dynamics were observed in all areas, mainly in the cognitive one (See Table 1).
There are EEG coherence changes of P-t S-v and P-t P-v after rehabilitation course at Figure 8. EEG coherence increased predominantly for delta band in different parts of spectrum mostly at delta and theta with shift to left hemisphere while dual-tasking after rehabilitation course. These EEG changes and an increase of cognitive functions were observed without loss of motor task performance quality.
(a) (b) (c)
Figure 7. (a) and (b) examples of diffuse tensor MRI tractography of corpus callosum in p-t S and P-t G and healthy adult Sh; (c) table with values of fraction anisotropy in zones 1 - 7 of corpus callosum (from posterior to anterior) and values of MMSE and Berg’s scales.
Figure 8. Features of EEG coherence changes in two TBI patients: p-t S (MMSE—22 (28); Berg’s scale—56 (56) and p-t P MMSE 26 (28); Berg’s scale—56 (55)—while a dual-task C1M1 was performed after the course of rehabilitation compared with the state before it (p < 0.01); In brackets—values of scales after rehabilitation. Designations as in Figure 2.
In contrast, patient P-v, performing a dual-task showed a less pronounced increase in EEG coherence, predominantly at delta range. Along with improving cognitive performance, quality of motor task decreased. The revealed differences in the effect of rehabilitation between patients can be explained by the fact that the patient S-v underwent a course earlier after injury (5 months), when recovery processes were more active. Whereas the patient P-v received his course later (11 - 13 months after injury), when recovery and compensation processes are not so actively, and cognitive deficits decrease, apparently, due to redistribution of brain resources, which affected the deterioration of the motor component.
Thus, the positive effect of rehabilitation course using dual-tasking was observed in mTBI patients. According clinical scales the most distinct positive effect was in the cognitive sphere. The EEG data demonstrate predominant increase of EEG coherence for slow spectral bands (marker of cognitive functions) with a tendency to normalization of spatial-frequency characteristics with the more changes at the frontal-temporal of the left hemisphere.
At the present study we found EEG data that provide support for a competition view to dual-task processing in healthy persons. They demonstrate combining of specific spatial and temporal resolution of the brain activation while motor (postural) and cognitive tasks that were performed at the same time—dual-tasking. Similar reactive changes of EEG were presented in our previous studies using other tasks. Specific EEG markers were obtained in the study while mental calculation and postural tasks were performed  - . In previous and present studies was shown, that EEG markers of the cognitive component of single and dual-tasks were expressed changes in lower spectral bands (delta and theta) of EEG. In contrast, the performance of motor (postural) component in both experimental conditions was accompanied by increasing of EEG for fast spectral bands (alpha2 and beta).
Taking into account published data on formation and functional importance of the EEG rhythms, one can assume that high-frequency components provide more quicker processes while low-frequency components. Similar data were described for motor component in dual-tasking for patients too. These processes manifest especially clearly in patients with various forms of cerebral pathology including mTBI      . Often patients perform the components of dual-tasking not simultaneously, but consistently, with identification of postural task performance as a priority   . These data suggest sequential performance of postural component as a more important one from the biological point of view. Our data and results of others support opinion that synchronization for fast spectral bands may provide the stronger sensorimotor integration needed for maintaining gait stability and spatial navigation . Additionally with respect of this function, some authors showed that vestibular and postural dominance has been presented within right hemisphere . Specific EEG markers obtained in our and other studies may to guarantee the preferential improvement and the priority of the postural component in healthy subjects too  - .
EEG markers of the cognitive component in dual-tasking were slow spectral bands (delta and theta) predominantly at the frontal-temporal areas of the left hemisphere. This phenomenon was expressed during all dual-tasks and was described at some investigations  -  . A widespread increase of cortical theta- or delta-rhythms synchronization during the encoding of items was recorded from scalp EEG recording in healthy adults . This publication focused on attention on the relationship between the brain theta-rhythms and memory. So, neural synchronization at low frequencies delta and theta (<8 Hz) and the predominantly at the left hemisphere might be viewed as general neurophysiological mechanism occurring when cognitive task increase at the healthy adults   .
At the present study we found greater dual task cost—increased brain activation while the most difficult cognitive component was included in dual-tasking in healthy adults. Some authors also have showed that increasing task demands from delta as well as theta frequency bands and this form of EEG activity was increased while difficult tasks were performed by healthy subjects  .
It was shown that the quality of cognitive component during dual-tasking in mTBI patients being lower than healthy persons. These behavioral data correlated with decrease values of EEG coherence namely for slow spectral bands—for delta as well as theta ones. In mTBI patients the decrease of EEG coherence for slow predominantly at the left hemisphere was observed as apposite healthy people’s data. According to Babilony neuronal synchronization of delta spectral bands can be interpreted as a general neurophysiological mechanism that sets in as cognitive task increasing. Consequently, information processing within distribution of functional neural networks had been enhanced   . These authors suggested that low spectral bands may govern a long-ranged coordination of distant brain regions.
Posttraumatic brain changes are thought to be progressive in nature, and potentially increase the risk for early cognitive decline. As a rule dementia was observed in mTBI patients similar to aged individuals    . Results of some investigations allowed the authors to propose accelerated brain aging after brain trauma . They hypothesized that the discrepancy between chronological and predicted brain age would be reflected predominantly in cognitive sphere and consistent with age-related cognitive impairment in older individuals.
Our fMRI and EEG data revealed the most expressed pathological reactive changes in the frontal temporal areas of the left hemisphere and the brain cortical structures in patients after mTBI . These results support the human brain aging HAROLD (hemispheric asymmetry reduction in elderly people) hypothesis of Cabeza, who explained the aging process mainly by a primary reduction of the left hemispheric functional activity . This opinion supports some studies that demonstrate significant greater left hemisphere and left frontal lobe volume atrophy in the aged subjects than the young participants  . From the other hand some authors support the right hemispheric aging model  . At last some investigations provide evidence of both, left frontal and right posterior parietal activations contribute to compensatory processes in normal aging .
It is important that not only after mTBI, but also after a concussion, a preferential decrease of coherence was revealed for distant, especially diagonal, connections between the frontal and parietal brain areas. Behavioral impairments were observed in patients predominantly for cognitive sphere   . It is interesting to note that in healthy people with high level of cognitive resources and the ability to successful dual-tasking, the coherence values for these diagonal connections were the highest . It can be assumed that the maximum decrease of EEG coherence for slow EEG rhythms at diagonal pairs between the frontal and parietal brain areas, as well as in the left fronto-temporal region, was found in patients after mTBI. May be these changes of EEG is marker of cognitive deficit in patients with this form of cerebral pathology. Thus, a multidisciplinary approach, on the one hand, and using of dual-tasks, on the other hand, may be effective tool for diagnostic estimation of cognitive deficit in population of mTBI patients.
Damaged distant, especially diagonal connections between frontal and parietal parts of the brain were also revealed in patients after mTBI, as well as after concussions, accompanied by a predominant cognitive impairment   . It should be noted that the coherence values of diagonal connections between the same areas were maximum in healthy people with high cognitive resources, able to more successfully perform dual tasks compared to single ones . It can be assumed that degradation of diagonal connections between frontal and parietal areas for slow EEG rhythms is also one of the important markers of cognitive deficit in patients after mTBI.
Thus, multidisciplinary research, coupled with dual-tasking, seems to be a promising diagnostic approach in ameliorating cognitive deficit in mTBI population. Rehabilitation programs with dual-tasking led to a decrease in cognitive deficit of brain-injured patients. According to the EEG data, this corresponded to an increase in the efficiency of functional connections for slow rhythms, mainly in left fronto-temporal areas with a trend to normalize intracortical connections. Thus, left hemisphere, on the one hand, is more sensitive to damaging effects, and on the other, and the more flexible in responding to rehabilitation procedures.
This stage of the study does not allow us to evaluate the effectiveness of the inclusion of dual tasking in the rehabilitation process due to the limited sample. Nevertheless, the results of a comprehensive EEG, stabilographic and clinical studies revealed a decrease in cognitive deficit after a rehabilitation course with dual-tasking at an early stage after mTBI. To obtain more convincing data in favor of this assumption, further studies are required, including an assessment of the rehabilitation effect at different times after mTBI. However, we do already argue that the dual-tasks are not only a diagnostic tool, but also a promising approach in creating individual rehabilitation programs for mTBI patients
Cognitive impairment was the most characteristic feature of patients after mTBI. According to EEG data, this corresponded to a predominant decrease of coherence for slow (delta, theta) spectral bands, most pronounced in the fronto-temporal areas of left hemisphere. The performance of cognitive tasks by healthy people was accompanied by increasing of EEG coherence for slow spectral bands, while for motor tasks the same was manifested at fast rhythms. The use of dual-tasking in rehabilitation course created a trend towards the restoration of impaired cognitive functions with the parallel normalization of the regional-frequency characteristics of the EEG. Thus, dual-tasking is a promising diagnostic and rehabilitation tool for traumatic brain damage. Results of our studies support hypothesis about predicted brain age with traumatic-related cognitive impairment in mTBI patients.
This study was supported by the RFBR Grant No 18-013-00355.
 Bigler, E.D. and Wilde, E.A. (2010) Quantitative Neuroimaging and the Prediction of Rehabilitation Outcome Following Traumatic Brain Injury. Frontiers in Human Neuroscience, 4, 228-238.
 Cherubini, A., Luccichenti, G., Peran, P., Hagberg, G.E., Barba, C., Formisano, R. and Sabatini, U. (2007) Multimodal fMRI Tractography in Normal Subjects and Clinically Recovered Traumatic Brain Injury Patients. Neuroimage, 34, 1331-1341.
 Levine, B., Fujiwara, E., O’Connor, C., et al. (2006) In Vivo Characterization of Traumatic Brain Injury Neuropathology with Structural and Functional Neuroimaging. Journal of Neurotrauma, 23, 1396-1403.
 Quinn, B. and Sullivan, S.J. (2000) The Identification by Physiotherapists of the Physical Problems Resulting from a Mild Traumatic Brain Injury. Brain Injury, 14, 1063-1076.
 Sharp, D.J., Beckmann, C.F., Greenwood, R., et al. (2011) Default Mode Network Functional and Structural Connectivity after Traumatic Brain Injury. Brain, 134, 2233-2247.
 Sidaros, A., Engberg, A.W., Sidaros, K., et al. (2008) Diffusion Tensor Imaging during Recovery from Severe Traumatic Brain Injury and Relation to Clinical Outcome: A Longitudinal Study. Brain, 131, 559-572.
 Sidaros, A., Skimminge, A., Liptrot, M.G., et al. (2008) Long-Term Global and Regional Brain Volume Changes Following Severe Traumatic Brain Injury: A Longitudinal Study with Clinical Correlates. NeuroImage, 44, 1-14.
 Bazarizan, J.J., Cernak, I. and Noble-Haeusslein, L. (2009) Long-Term Neurologic Outcomes after Traumatic Brain Injury. The Journal of Head Trauma Rehabilitation, 24, 439-451.
 Jaiswal, N., Ray, W. and Slobounov, S. (2010) Encoding of Visual-Spatial Information in Working Memory Requires More Cerebral Efforts than Retrieval: Evidence from an EEG and Virtual Reality Study. Brain Research, 1347, 80-89.
 Aftanas, L.I., Bazanova, O.M. and Novozhilova, N.V. (2018) Posture-Motor and Posture-Ideomotor Dual-Tasking: A Putative Marker of Psychomotor Retardation and Depressive Rumination in Patients with Major Depressive Disorder. Frontiers in Human Neuroscience, 12, 1-9.
 Erickson, K.I., Colcombe, S.J., Wadhwa, R., Bherer, L., Peterson, M.S., Scalf, P.E. and Kramer, A.F. (2005) Neural Correlates of Dual-Task Performance after Minimizing Task-Preparation. Neuroimage, 28, 967-979.
 Low, K.A., Leaver, E.E., Kramer, A.F., Fabiani, M. and Gratton, G. (2009) Share or Compete? Load-Dependent Recruitment of Prefrontal Cortex during Dual-Task Performance. Psychophysiology, 46, 1069-1079.
 Cocchi, L., Zalesky, A., Toepel, U., Whitford, T.J., De-Lucia, M.J., Murray, M.M. and Carter, O. (2011) Dynamic Changes in Brain Functional Connectivity during Concurrent Dual-Task Performance. PLoS One, 6, e28301.
 Hamilton, F., Rochester, L. and Paul, L. (2009) Walking and Talking: An Investigation of Cognitive-Motor Dual Tasking in Multiple Sclerosis. Multiple Sclerosis Journal, 15, 1215-1227.
 Salo, E., Rinne, T., Salonen, O. and Alho, K. (2015) Brain Activation during Bimodal Dual Tasks Depends on the Nature and Combination of Component Tasks. Frontiers in Human Neuroscience, 9, 1-10.
 Hiraga, C.Y., Garry, M.I., Carson, R.G. and Summers, J.J. (2009) Dual-Task Interference: Attentional and Neuropsychological Influences. Behavioural Brain Research, 205, 10-19.
 Zhavoronkova, L.A., Zharikova, A.V., Kushnir, E.M. and Mikhalkova, A.A. (2011) Characteristics of EEG Reactivity Changes during the Performance of Dual-Tasks in Healthy Subjects (Voluntary Postural Control and Calculation). Human Physiology, 37, 688-699.
 Zhavoronkova, L.A., Kushnir, E.M., Zharikova, A.V., Mikhalkova, A.A. and Kuptsova, S.V. (2015) Electroencephalographic Characteristics of Healthy People with Different Success in Performing Dual-Tasks (Posture Control and Counting). Zhurnal vysshei nervnoi deiatelnosti imeni I P Pavlova, 65, 1-10.
 Zhavoronkova, L.A., Shevtsova, T.P., Pozdneev, A.V., Kuptsova, S.V. and Maksakova, O.A. (2016) Dual-Task (Postural and Cognitive) Processing in Healthy Persons and Traumatic Brain Injury Patients. International Journal of Psychophysiology, 108, 26-27.
 Zhavoronkova, L., Zharikova, A. and Maksakova, O. (2013) Why Voluntary Postural Training Improves Recovery of Mental and Motor Functions in Patients with Traumatic Brain Injury? Journal of Behavioral and Brain Science, 3, 463-473.
 Zhavoronkova, L.A., Shevtsova, T.P., Moraresku, S.I., Pozdneev, A.V. and Kuptsova, S.V. (2019) Intracortical Connections in Dual-Tasks Including Motor and Computing-Logical or Spatial-Visual Components. Human Physiology, 45, 126-136.
 Papegaaij, S., Hortobagil, T., Godde, B., Kaan, W.A., Erhard, P. and Voelcker-Rehage, C. (2017) Neural Correlates of Motor-Cognitive Dual-Tasking in Young and Old Adults. PLoS One, 12, e0189025.
 Schaefer S. and Linderberger, U. (2013) Thinking while Walking: Experienced High-Heel Walkers Flexibly Adjust Their Gait. Frontiers in Psychology, 4, 1-6.
 Cole, J.H., Leech, R. and Sharp, D.J. (2015) Prediction of Brain Age Suggests Accelerated Atrophy after Traumatic Brain Injury. Annals of Neurology, 77, 571-581.
 Imeria, A., Suzuki, S., Rostowsky, K., Maher, A., Chowdhury, N. and Van Horn, J. (2018) Effects of Cerebrovascular Micropathology upon Cognitive Impairments and Brain Aging Trajectories Subsequent to Geriatric Brain Injury. International Journal of Psychophysiology, 131, S29.
 Slobounov, S., Sebastianellia, W. and Hallett, M. (2012) Residual Brain Dysfunction Observed One Year Post-Mild Traumatic Brain Injury: Combined EEG and Balance Study. Clinical Neurophysiology, 123, 1755-1761.
 Zhang, K., Johnson, B., Penelli, D., Ray, W., Sebastinelly, W. and Slobounov, S. (2010) Are Functional Deficits in Concussed Individuals Consistent with White Matter Structural Alterations: Combined fMRI and DTI Study. Experimental Brain Research, 204, 57-70.
 Johnson, B., Zhang, K., Gay, M., Horovitz, S., Hallett, M., Sebastianelli, W. and Slobounov, S. (2012) Alteration of Brain Default Network in Subacute Phase of Injury in Concussed Individuals: Resting-State fMRI Study. Neuroimage, 59, 511-518.
 Schumacher, E. and Schwarb, H. (2009) Parallel Response Selection Disrupts Sequence Learning under Dual-Task Conditions. Journal of Experimental Psychology: General, 138, 270-290.
 Little, C.E. and Woollacott, M. (2015) EEG Measures Reveal Dual-Task Interference in Postural Performance in Young Adults. Experimental Brain Research, 233, 27-37.
 Naschimbeni, A., Gaffuri, A., Penno, A. and Tavoni, M. (2010) Dual Task Interference during Gait in Patients with Unilateral Vestibular Disorders. Journal of NeuroEngineering and Rehabilitation, 7, Article No.: 47.
 Haggard, P., Cockburn, J. and Cock, J. (2000) Interference between Gait and Cognitive Tasks in a Rehabilitating Neurological Population. Journal of Neurology, Neurosurgery, and Psychiatry, 69, 479-485.
 Babiloni, F., Babiloni, C., Carducci, F., et al. (2003) Multimodal Integration of High-Resolution EEG and Functional Magnetic Resonance Imaging Data: A Simulation Study. NeuroImage, 19, 1-15.
 Babiloni, C., Infarinato, F., Marzano, N., Iacoboni, M., Dassù, F., Soricelli, A., Rossini, P.M., Limatola, C. and Del Percio, P. (2011) Intra-Hemispheric Functional Coupling of Alpha Rhythms Is Related to Golfer’s Performance: A Coherence EEG Study. International Journal of Psychophysiology, 121, 260-268.
 Babiloni, C., Del Percio, C., Arendt-Nelsen, L., Soricelli, A., Rossini, G.L. and Capotosto, P. (2014) Cortical EEG Alpha Rhythms Reflect Task-Specific Somatosensory and Motor Interactions in Human. Clinical Neurophysiology, 125, 1936-1945.
 Kirsch, V., Keeser, D., Hergenroeder, T., Erat, O., Erti-Wagner, B., Brandt, T. and Dieterich, M. (2016) Structural and Functional Connectivity Mapping of the Vestibular Circuitry from Human Brainstem to Cortex. Brain Structure and Function, 221, 1291-1308.
 Resch, J.E., May, B., Tomporowski, D. and Ferrara, M.S. (2011) Balance Performance with Cognitive Tasks: A Continuation of the Dual-Task Testing Paradigm. Journal of Athletic Training, 46, 170-175.
 Laufer, Y., Ashkenazi, T. and Josman, N. (2008) The Effects of a Concurrent Task Cognitive Task on the Postural Control of Young Children with and without Developmental Coordination. Gait & Posture, 27, 347-351.
 Doumas, M., Rapp, M. and Krampe, R. (2009) Working Memory and Postural Control: Adult Age Differences in Potential for Improvement, Task Priority, and Dual Tasking. The Journals of Gerontology, 64, 193-201.
 Schafer, S. and Lang, C. (2012) Using Dual Tasks to Test Immediate Transfer of Training Between Naturalistic Movements: A Proof-of-Principle Study. Journal of Motor Behavior, 44, 313-327.
 Schaefer, S., Krampe, R., Lindenberger, U. and Baltes, P. (2008) Age Differences between Children and Young Adults in the Dynamics of Dual-Task Prioritization: Body (Balance) versus Mind (Memory). Developmental Psychology, 44, 747-757.
 Annett, M. (2004) Hand Preference Observed in Large Healthy Samples: Classification, Norms and Interpretations of Increased Non-Right-Handedness by the Right Shift Theory. British Journal of Psychology, 95, 339-353.
 Malec, J.F. (2004) Comparability of Mayo-Portland Adaptability Inventory Ratings by Staff, Significant Others and People with Acquired Brain Injury. Brain Injury, 18, 563-575.
 Doumas, M., Rapp, M. and Krampe, R. (2009) Working Memory and Postural Control Adults Age Differences in Potential for Improvement Task Priority and Dual Tasking. The Journals of Gerontology: Series B, 64, 193-201.
 Blundon, E.B., Rumak, S.P. and Ward, L.M. (2017) Sequential Asymmetry: Behavioral and Psychophysiological Evidence from a Dual Oddball Task. PLoS One, 12, e0173237.
 Bohle, H., Rimpel, J., Schanenburg, G., Febel, A., Stelzel, C., Heinzel, S., Rapp, M. and Granacher, U. (2019) Behavioral and Neural Correlates of Cognitive-Motor Interference during Multitasking in Young and Old Adults. Hindawi Neural Plasticity, 2019, Article ID: 9478656.
 Jacob, E., Resch, J.E., May, B., Phillip, D., Tomporowski, P.D., Michael, S. and Ferrara, M.S. (2011) Balance Performance with a Cognitive Task: A Continuation of the Dual-Task Testing Paradigm. Journal of Athletic Training, 46, 170-175.
 Zhavoronkova, L., Moraresku, S., Boldyreva, G., Sharova, E., Kuptsova, S., Smirnov, A., Masherov, E., Maksakova, O. and Pronin, I. (2019) FMRI and EEG Reactions to Hand Motor Tasks in Patients with Mild Traumatic Brain Injury: Left-Hemispheric Sensitivity to Trauma. Journal of Behavioral and Brain Science, 9, 273-287.
 Shan, Z.Y., Liu, J.Z., Shahgal, V., Wang, B. and Yue, G.H. (2005) Selective Atrophy of Left Hemisphere and Frontal Lobe of the Brain in Old Men. The Journals of Gerontology: Series A, 60, 165-174.
 Kave, G., Gavrielli, R. and Mashal, N. (2014) Stronger Left Hemisphere Lateralization in Older versus Younger Adults While Processing Conventional Metaphors. Laterality, 19, 705-717.
 Meudell, P.R. and Greenhalgh, M. (1987) Age Related Differences in Left and Right Hand Skill and in Visuo-Spatial Performance: Their Possible Relationships to the Hypothesis That the Right Hemisphere Ages More Rapidly than the Left. Cortex, 23, 431-445.
 Dolcos, F., Rice, H.J. and Cabeza, R. (2002) Hemispheric Asymmetry and Aging: Right Hemisphere Decline or Asymmetry Reduction. Neuroscience & Biobehavioral Reviews, 26, 819-825.
 Huang, C.M., Polk, T.A., Goh, J.O. and Park, D.C. (2012) Both Left and Right Posterior Parietal Activations Contribute to Compensatory Processes in Normal Aging. Neuropsychologia, 50, 55-66.