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Changes in the theta band coherence during motor task after hand immobilization

Abstract

Many different factors can temporarily or permanently impair movement and impairs cortical organization, e.g. hand immobilization. Such changes have been widely studied using electroencephalography. Within this context, we have investigated the immobilization effects through the theta band coherence analysis, in order to find out whether the immobilization period causes any changes in the inter and intra-hemispheric coherence within the cerebral cortex, as well as to observe whether the theta band provides any information about the neural mechanisms involved during the motor act. We analyzed the cortical changes that occurred after 48 hours of hand immobilization. The theta band coherence was study through electroencephalography in 30 healthy subjects, divided into two groups (control and experimental). Within both groups, the subjects executed a task involving flexion and extension of the index finger, before and after 48 hours. The experimental group, however, was actually submitted to hand immobilization. We were able to observe an increase in the coupling within the experimental group in the frontal, parietal and temporal regions, and a decrease in the motor area. In order to execute manual tasks after some time of movement restriction, greater coherence is present in areas related to attention, movement preparation and sensorimotor integration processes. These results may contribute to a detailed assessment of involved neurophysiological mechanism in motor act execution.

Introduction

Sensorimotor integration mechanisms can be affected by many factors, among which are hand-immobilizing lesions that can temporarily or permanently impair movement and bring about changes to the cortical organization [1, 2] in addition to provoking a reduction of neuromuscular activity [3]. This has been observed in the study by Gondin [4] after submitting subjects to a two-week immobilization. Liepert [5] have also highlighted such phenomenon after submitting individuals to movement restriction. In addition to this, Seki [6] have found a reduction in motor neuron firing after a week of finger immobilization. In fact, Facchini [7] have observed that the cortical and neuromuscular excitability indexes are not influenced by a four-day period of finger immobilization. Within this context, body limbs immobilization has been used in many studies, not only to verify neuromuscular changes, but also to understand the influence of sensorimotor restriction on cortical behavior [6, 8–10].

Among the tools used to investigate the cortical changes after an immobilization period, quantitative electroencephalography (qEEG) has been widely employed [11, 12] and it has provided information about cortical activity with high temporal definition in motor, sensory and cognitive tasks [13, 14]. In particular, the qEEG theta band (4–8 Hz) has been associated to cognitive processing [15, 16] and to sensory stimuli identification and codification [17–19]. This way, theta band oscillations have been related to sensorimotor integration mechanisms [20]. In particular, the coherence analysis provides evidence of the coupling between cortical areas during task execution [21, 22]. Although researches have demonstrated the theta band involvement in studies about coherence in cognitive, sensory and motor tasks [17, 20], little is known about its activity when related to movement restriction.

This way, our study aimed at analyzing theta band coherence after 48 hours of hand immobilization. The electrode derivations were selected through qEEG in different brain regions: the frontal region, due to its relationship with the pre-motor and pre-frontal cortexes, which are functionally related to action creation and voluntary control [23] and to executive functions [24]; the central region, which represents motor act execution [25, 26]; the parietal region, because of its relationship with sensorimotor integration [23, 27] and the temporal region, since it represents the secondary motor areas [28]. Therefore, our study hypothesized that the hand immobilization period provokes changes in the inter and intra-hemispheric coherence in the frontal, central, parietal and temporal regions, as well as providing information about the neural mechanisms involved in the motor act execution. The objective of the present study is then to analyze the theta band coherence oscillations after 48 hours of hand immobilization.

Methods

Sample

The experimental group sample was composed of 15 healthy individuals (07 men and 08 women; mean age ± standard deviation [SD] = 24 ± 1.2 years; age range = 20–30 years); the control group sample was composed of 15 healthy individuals (07 men and 08 women; mean age ± SD 23 ± 1.4 years; age range = 20–30 years). The individuals were chosen randomly and the recruitment of the volunteers was accomplished thanks to the research announcements posted in different universities of Rio de Janeiro State. As inclusion criteria, the subjects needed to be right handed, have no mental or physical illness (previous anamnese) and not use any psychoactive or psychotropic substances during the whole time of the study. We applied a detailed questionnaire in order to exclude those individuals who could contaminate our results. Due to hand laterality, we utilized the Edinburgh inventory [29] to identify the predominance of the participants (right handed vs. left-handed). Consequently, the left-handed individuals were excluded from the experiment. We instructed the individuals to not use tobacco, coffee or alcoholic drinks 10 hours before the test. The participants received written information about the study procedures and we solicited their signature of the consent form. This study was approved by the ethics committee of Veiga de Almeida University with the number 149.817 in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki.

Tasks and procedures

We prepared a room with acoustic and electrical isolation. During the electroencephalography (EEG) signal acquisition, the lights were dimmed. The subjects sat in a chair with armrest, in order to minimize muscle artifact during EEG signal acquisition. A 15-inch monitor was placed on a table in front of the subjects. The monitor was turned on only when the subjects executed the task (i.e., flexion and extension of the index finger). Initially, the EEG signal acquisition lasted for 2 minutes (rest) with the monitor off, facing the subjects. Then, we coupled a sensor to measure acceleration (accelerometer) on the right index finger; during the visual feedback, the subjects executed the task (i.e., flexion and extension of the index finger). The accelerometer was connected to the EEG through an additional channel (i.e., channel 21). When the subjects performed the movement, the accelerometer provided a signal for the EEG. The subjects were instructed to perform the index finger flexion and extension when visual feedback was generated by a random image on the monitor. The subjects executed the task in 6 blocks of 15 trials. In order to avoid muscle fatigue, they rested for 3 minutes between each block. Thus, the task lasted 1 minute for each block with a 3 minute-interval between blocks, totaling 24 minutes for the whole task. After completing the task, the monitor was turned off and the subjects were submitted again to EEG during 2 minutes (rest). After EEG recording, a plaster cast was applied on the subjects’ right hand and they kept it on for 48 hours. The plaster cast was applied with the hand closed, in order to prevent any hand or finger movement. After this period, the experimental group subjects returned to the laboratory to remove the plaster cast and, after five minutes from cast removal, they were submitted again to the same task procedures executed before hand immobilization. The control group (non-plaster cast), after EEG recording, went back to the laboratory after 48 hours and executed the procedures again.

Data acquisition

Electroencephalography

The International 10/20 system for electrodes was used with a 20-channel Braintech-3000 EEG system (EMSA-Medical Instruments, Brazil). The 20 electrodes were arranged in a nylon cap (ElectroCap Inc., Fairfax, VA, USA), yielding mono-pole derivations to linked earlobes. In addition, two 9-mm diameter electrodes were attached above and on the external corner of the right eye, in a bipolar electrode montage, to monitor artifacts on eye-movements (EOG). Impedance of EEG and EOG electrodes was kept under 5–10 KΩ. The data acquired had total amplitude of less than 100 μV. The EEG signal was amplified with a gain of 22,000, analogically filtered between 0.01 Hz (high-pass) and 100 Hz (low-pass), and sampled at 240 Hz. The software Data Acquisition (Delphi 5.0) was employed to filter the raw data: notch (60 Hz), high-pass of 0.3 Hz and low-pass of 100Hz.

Accelerometer

In order to obtain signals from the accelerometer, the MMA7340 model of Freescale semiconductors was used. This system is a microelectronics mechanism, which explores the mechanic proprieties of silicone to create movable structures and to detect distinct movement directions [30]. The movement capture was conducted in actual time system, with the interaction of EEG software signal acquisition. As the movement was performed, the accelerometer showed a curve with acceleration variability providing information about velocity and time.

Data processing

In order to quantify reference-free data, a visual inspection and independent component analysis (ICA) was applied to identify and remove any remaining artifacts, i.e., eye blinks and ocular movements, produced by the task [31]. Data from individual electrodes exhibiting loss of contact with the scalp or high impedances (>10 kΩ) were discarded, and data from single-trial epochs exhibiting excessive movement artifacts (±100 μV) were also deleted. ICA was then applied to identify and remove any artifacts after the initial visual inspection. ICA is an information maximization algorithm to blind the EEG signals related to the artifacts [31]. Independent components resembling eye-blink or muscle artifacts were removed and the remaining components were then projected back onto the electrode data by multiplying it by the inverse matrix of the spatial filter coefficients derived from ICA, using established procedures. The ICA-filtered data were then reinspected for residual artifacts using the same rejection criteria described above. Then, a classic estimator was applied for the power spectral density, or directly from the square modulus of the Fourier Transform, performed by MATLAB (Matworks, Inc.). Quantitative EEG parameters were reduced to 4 s periods (the selected epoch started 2 s before and ended 2 s after the trigger). For this analysis, the channel 21 created for the accelerometer was excluded, in order to avoid any artifact (previously published by our group [11]).

Electrode spatial localization

Four regions of interest were selected: the pre-motor and pre-frontal cortex, represented by the F3/F4, F3/Fz and F7/Fz derivations, which are functionally responsible for action creation and voluntary control [24] and for executive functions [25]; the C3/Cz, C3/C4 and C4/Cz derivations for being representatives of primary motor areas related to the motor act execution [26]; the P3/Pz and P3/P4 derivations, due to their relationship with sensorimotor integration [2, 23, 32] and the secondary motor areas, represented by the T3/T4 derivations. For such analysis, theta band (4–7 Hz) was used, and it was chosen because of its association to cognitive functions, such as sensory information codification [33], attention mechanisms [34] and multi-sensory information transmission [13].

Statistical analysis

The coherence values were analyzed using a two-way ANOVA, with two factors: group (control and experimental) and visit (before and after 48 hours) for each derivation studied (F3/F4, F3/Fz, F7/Fz, C3/Cz, P3/Pz, P3/P4 and T3/T4). All possible interactions were examined by the one-way ANOVA. The significance level was established at p ≤ 0.007 (0.05/7 = 0.007).

Results

The data analysis was conducted using a two-way ANOVA with two factors: group (control and experimental) and visit (before and after 48 hours). A main effect was found for the F3/F4 [F (1.162) = 18.798; p = 0.001] derivations, with a coherence decrease in the control group, when compared to the experimental group (Figure 1a). A main effect with coherence decrease was also found for the F3/Fz [F (1.139) = 15.915; p = 0.001] derivations, showing a coherence reduction in the control group (Figure 1b). However, when analyzed within the groups, a main effect was found for the F7/Fz [F (1.80) = 5.992; p = 0.017] derivations (Figure 1c). Such finding shows that 48 hours of immobilization had an influence on the cortical activity between the pre (mean = -1.4448; SD = 0.744190) and post (mean = -1.6838; SD = 0.57597) moments. In addition to this, a main effect was also observed for the C3/Cz [F (1.153) = 5.335; p = 0.022] derivations, in the group condition with a coherence reduction for the experimental group, and a coherence reduction also occurred among the subjects of this group when examining the pre (mean = - 0.1883; SD = 0.64639) and post-immobilization (mean = -0.5445; SD = 0.40699) moments (Figure 2a). For the T3/T4 [F (1.79) = 5,08; p = 0.027] derivations, a main effect was found, but a significant difference was found only in the experimental group, highlighting a coherence reduction between before (mean = 0.1798; SD = 0.1442) and after (mean = 0.1308; SD = 0.0795) the immobilization period (Figure 2b). For the P3/P4 [F (1.155) = 8.651; p = 0.004] derivations, a main effect was observed in the experimental group, with a theta coherence reduction between the pre (mean = -1.9458; SD = 0.47145) and post-immobilization (mean = -1.9197; SD = 0.49664) moments (Figure 2c). In the parietal region, a main effect was found for the experimental group, with a decrease in coherence for the P3/Pz [F (1.114) = 39.903; p = 0.001] derivations, and an increase took place when analyzing the pre (mean = -0.6441; SD = 0.45417) and post (mean = -0.5445; SD = 0.35792) moments (Figure 2d).

Figure 1
figure 1

Cortical changes during motor tasks. a) Effects for factor group observed in the frontal inter-hemisphere (F3/F4) derivations by mean and SD (p < .001); b) Main effects for factor treatment observed in the left frontal cortex (F3/Fz) derivation by mean and SD (p < .001); c) Effects for factor treatment observed in the F7/Fz derivations by mean and SD (p = .017).

Figure 2
figure 2

Cortical changes occurring after hand immobilization. a) Effects for factor group observed in the left central cortex (C3/Cz) derivations by mean and SD (p = .022); b) Effects for factor treatment observed in the temporal inter-hemispheric (T3/T4) derivation by mean and SD (p = .004); c) Effects for factor treatment observed in the P3/P4 derivations by mean and SD (p = .004) and d) Main effects for factor treatment observed in the left parietal cortex (P3/Pz) derivation by mean and SD (p < .0001).

Discussion

The aim of the present study was to analyze the changes in theta band coherence after 48 hours of hand immobilization. In particular, we hypothesized that the theta band coherence oscillations provide information about the neural mechanisms involved in the motor act execution. In addition to this, changes were expected to occur in the inter- and intra-hemispheric coupling in the areas related to motor planning, sensorimotor integration, executive functions and motor act execution after 48 hours of hand immobilization. Our discussion is organized according to cortical regions (i.e., frontal, central, parietal and temporal), whose specific characteristics were related to theta band coherence.

Theta band coherence and its relationship with attention and movement preparation

Theta band coherence increased in the frontal region, especially for the F3/Fz derivations. Other studies have demonstrated that the pre-motor and pre-frontal cortexes are related to action creation and voluntary control and to executive functions [28, 31], and that theta activity occurs during that behavior which demands planning updating for the motor act, according to the received sensory information [5, 35]. This way, due to the fact of the coherence analysis presenting evidence of the coupling between cortical areas during motor task execution [21, 22], our findings demonstrate that, in order for the individual to execute the task, greater coupling between these areas was needed for the planning and motor response to the stimulus, which then demanded greater joint action of such cortical regions [36]. However, coherence reduction was detected for the F3/F4 derivations in the experimental group. This finding can be associated to the study by Hatfield [37], where they observed that learning is a skill-specific process and that those structures which are not directly responsible for task execution show a reduced activity when practicing the task, while the system directs its activity to areas that are more important for task execution. Therefore, we support the idea that our task does not provide any learning and, consequently, it would not promote changes such as those encountered for the F3/F4 derivations. However, due to the fact of such derivations being related to Broadmann area 8, we believe that their relationship with visuo-motor cortical activity and planning demonstrate greater efficiency for task execution [38]. This way, the immobilization period (i.e., 48 hours) demanded less coupling between the F3/F4 derivations, in order to meet the needs of other cortical regions involved in task execution; in other words, this area used all of its efficiency potential to execute the motor task [35, 39]. Such change in theta has also been observed in the study by Haufler [40] where the authors compared the cortical activity between beginner and professional shooters during a shooting competition. They found that theta band activity during the shooting task was lower in the professional shooters than in the beginners. Such finding complements our interpretation that immobilization caused greater efficiency for these derivations. In addition to this, the concentration and attention involved in motor task planning are lower when considering simple tasks [41–43]. In fact, when looking at the study by Haufler [40], theta band in experienced shooters was lower, due to the great amount of attention and concentration required of these professionals; on the other hand, our task did not promote an increase in attention nor concentration, since such task (i.e., flexion and extension of the index finger) involved simple daily movements. Despite the possible interpretation stating that the visual stimulus presented for task execution would be an indicator of attention increase, our analysis was carried out during the periods before and after the finger movement and, therefore, we cannot make such statement.

Theta band and motor act

A decrease in theta band coherence for the C3/Cz derivations in the experimental group can be associated with neurophysiologic findings, which relate such derivations to sensorial facilitation, movement [44, 45], motor act execution [25, 46], temporal organization, sequential movement coordination [47] and motor act organization [47, 48]. In addition to this, researches show that, after short periods of hand immobilization, cortical activity decreases in the motor region related to movement restriction [9, 49]. This way, the changes caused by hand immobilization are more significant when looking at the cortical activity decrease than at the changes themselves, which occurred after the motor act [50]. Within this context, our results indicate that the cortical representation of our task’s sequential actions (i.e., flexion and extension of the index finger) was influenced by the immobilization period [47, 51]. Therefore, our result for the control group demonstrates that such derivations acted as a whole during the motor act preparation; this way, the coherence increase indicates that, in order to execute the motor act, these derivations participated together to help the preparation, therefore working as a pre-stimulus and helping in the case of a future motor response [21, 52, 53].

Theta band oscillations in sensorimotor integration

Theta band coherence increased in the P3/Pz derivations in both the control and experimental groups. Such finding shows that movement control is distributed among the neuron populations which codify movement information; that is, the neural network modifies sensory information, turning it into an appropriate command for the motor system [54–56]. This way, sensorimotor activities occurred thanks to the integration of proprioceptive activities, in order to produce an appropriate motor response [57]. Additionally, we have observed that, apart from the functional relationship between the P3/Pz derivations with sensorimotor activity and motor act preparation [58–60], the fact of having greater coupling showed that these regions acted together, in order to facilitate the planning and organization of the sequence required to correctly execute the task [61], so that the motor act could be anticipated and selected [61] to be better executed [62].

When the theta band absolute power was investigated for the P3/P4 derivations, it could be observed that the sensory stimuli integration was modified by hand immobilization, therefore altering the relationship with the codification of the movements related to the task [63, 64]. Our results indicate greater coupling between the intra-hemispheric derivations, with less coupling for the P3-P4 derivations, meaning that the used intervention promoted inter-hemispheric coherence reduction in the parietal region. In addition to this, our findings can be related to the study by Catalan [65] and by Barany [66], who have defined the important role of the parietal cortex in the hand movement processing. The authors suggest that training promotes an involvement of these regions in motor program storing. Therefore, since our task did not involve complex movements nor previous training, theta coherence decreased for the P3/P4 derivations, showing that mechanisms of the sensorimotor integration associated with cognitive processing [15, 16, 20] and the sensory stimuli identification and codification [17] for the motor task planning underwent modifications [4, 31].

Theta band coherence also decreased in the T3/T4 derivations in the experimental group. Such alteration after the immobilization period (i.e. 48 hours) demonstrates that the temporal areas act as a multi-sensory integration center [67], that is, they are related to visual, auditory and somatosensory stimuli [68] and movement planning [69]. In their study, Balslev and colleagues asked the participants to reproduce the index finger movement of their left hand, imitating what was appearing on a screen [69]. They observed that the right temporal area was the most active during the task, therefore highlighting the importance of this region in sensory conflict situations. Despite our study not having directly examined sensory incongruence, theta coherence reduction was found between the hemispheres in the temporal region, therefore indicating that hand immobilization caused sensory conflict. In addition to this, the relationship between the temporal cortex and motor task was analyzed by Shannon and Bucker [70]. They have observed that, during the task-related memory, multi-sensory integration processes are solicited less, indicating that the temporal cortex is also participating less, in order for the neural network to transform sensory information into an appropriate command for the motor system. This way, the temporal region is associated more to memory management than to the motor act [71]. Therefore, we believe that, because of our task not demanding memory recovery, there was no need for greater coupling in the T3/T4 derivations.

Conclusion

Our study aimed at analyzing the cortical changes occurring after 48 hours of hand immobilization. Our hypothesis was that the hand immobilization period would promote changes in the inter and intra-hemispheric coherence, and that the theta band coherence oscillations would provide information about the neural mechanisms for motor act execution. Therefore, we conclude that greater inter-hemispheric coupling occurs, except for the motor cortex, which showed theta band coherence intra-hemispheric alteration. In addition to this, motor tasks can be observed through theta band coherence. Considering this, we expect that other studies will also point out theta band as a parameter to investigate tasks involving motor acts. Here, we have some limitations due to small sample; nevertheless these results may contribute to a detailed assessment of involved neurophysiological mechanism in motor act execution.

References

  1. Mano Y, Chuma T, Watanabe I: Cortical reorganization in training. J Electromyogr Kinesiol 2003,13(1):57–62. 10.1016/S1050-6411(02)00086-X

    Article  CAS  PubMed  Google Scholar 

  2. Huber R, Ghilardi MF, Massimini M, Ferrarelli F, Riedner BA, Peterson MJ, Tononi G: Arm immobilization causes cortical plastic changes and locally decreases sleep slow wave activity. Nat Neurosci 2006,9(9):1169–1176. 10.1038/nn1758

    Article  CAS  PubMed  Google Scholar 

  3. Lissek S, Diekamp B, Gunturkun O: Impaired learning of a color reversal task after NMDA receptor blockade in the pigeon (Columba livia) associative forebrain (neostriatum caudolaterale). Behav Neurosci 2002,116(4):523–529.

    Article  CAS  PubMed  Google Scholar 

  4. Gondin J, Guette M, Maffiuletti NA, Martin A: Neural activation of the triceps surae is impaired following 2 weeks of immobilization. Eur J Appl Physiol 2004,93(3):359–365. 10.1007/s00421-004-1225-z

    Article  CAS  PubMed  Google Scholar 

  5. Liepert J, Miltner WH, Bauder H, Sommer M, Dettmers C, Taub E, Weiller C: Motor cortex plasticity during constraint-induced movement therapy in stroke patients. Neurosci Lett 1998,250(1):5–8. 10.1016/S0304-3940(98)00386-3

    Article  CAS  PubMed  Google Scholar 

  6. Seki K, Kizuka T, Yamada H: Reduction in maximal firing rate of motoneurons after 1-week immobilization of finger muscle in human subjects. J Electromyogr Kinesiol 2007,17(2):113–120. 10.1016/j.jelekin.2005.10.008

    Article  PubMed  Google Scholar 

  7. Facchini S, Romani M, Tinazzi M, Aglioti SM: Time-related changes of excitability of the human motor system contingent upon immobilisation of the ring and little fingers. Clin Neurophysiol 2002,113(3):367–375. 10.1016/S1388-2457(02)00009-3

    Article  PubMed  Google Scholar 

  8. Taub E, Uswatte G, Mark VW, Morris DM: The learned nonuse phenomenon: implications for rehabilitation. Europa medicophysica 2006,42(3):241–256.

    CAS  PubMed  Google Scholar 

  9. Ngomo S, Leonard G, Mercier C: Influence of the amount of use on hand motor cortex representation: effects of immobilization and motor training. Neuroscience 2012, 220:208–214.

    Article  CAS  PubMed  Google Scholar 

  10. Zanette G, Manganotti P, Fiaschi A, Tamburin S: Modulation of motor cortex excitability after upper limb immobilization. Clin Neurophysiol 2004,115(6):1264–1275. 10.1016/j.clinph.2003.12.033

    Article  PubMed  Google Scholar 

  11. Fortuna M, Teixeira S, Machado S, Velasques B, Bittencourt J, Peressutti C, Budde H, Cagy M, Nardi AE, Piedade R, Ribeiro P, Arias-Carrión O: Cortical reorganization after hand immobilization: the beta qEEG spectral coherence evidences. PLoS One 2013,8(11):e79912. 10.1371/journal.pone.0079912

    Article  PubMed Central  PubMed  Google Scholar 

  12. Manaia F, Teixeira S, Velasques B, Bittencourt J, Salles JI, Arias-Carrion O, Basile LF, Peressutti C, de Carvalho MR, Cagy M, Piedade R, Ribeiro P, Machado S: Does immobilization of dependent hand promote adaptative changes in cerebral cortex? An analysis through qEEG asymmetry. Neurosci Lett 2013, 538:20–25.

    Article  CAS  PubMed  Google Scholar 

  13. Gevins A, Smith ME, McEvoy L, Yu D: High-resolution EEG mapping of cortical activation related to working memory: effects of task difficulty, type of processing, and practice. Cereb Cortex 1997,7(4):374–385. 10.1093/cercor/7.4.374

    Article  CAS  PubMed  Google Scholar 

  14. Machado D, Bastos VH, Cunha M, Velasques B, Machado S, Basile L, Cagy M, Piedade R, Ribeiro P: The effects of bromazepam on the performance of a sensory-motor activity: an electroencephalographic study. Rev Neurol 2009,49(6):295–299.

    CAS  PubMed  Google Scholar 

  15. Kerick SE, Hatfield BD, Allender LE: Event-related cortical dynamics of soldiers during shooting as a function of varied task demand. Aviat Space Environ Med 2007,78(5 Suppl):B153-B164.

    PubMed  Google Scholar 

  16. Luu P, Tucker DM, Makeig S: Frontal midline theta and the error-related negativity: neurophysiological mechanisms of action regulation. Clin Neurophysiol 2004,115(8):1821–1835. 10.1016/j.clinph.2004.03.031

    Article  PubMed  Google Scholar 

  17. Klimesch W, Doppelmayr M, Schwaiger J, Winkler T, Gruber W: Theta oscillations and the ERP old/new effect: independent phenomena? Clin Neurophysiol 2000,111(5):781–793. 10.1016/S1388-2457(00)00254-6

    Article  CAS  PubMed  Google Scholar 

  18. Basar E, Schurmann M, Sakowitz O: The selectively distributed theta system: functions. Int J Psychophysiol 2001,39(2–3):197–212.

    Article  CAS  PubMed  Google Scholar 

  19. Klimesch W, Hanslmayr S, Sauseng P, Gruber W, Brozinsky CJ, Kroll NE, Yonelinas AP, Doppelmayr M: Oscillatory EEG correlates of episodic trace decay. Cereb Cortex 2006,16(2):280–290.

    Article  CAS  PubMed  Google Scholar 

  20. Bland BH, Oddie SD: Theta band oscillation and synchrony in the hippocampal formation and associated structures: the case for its role in sensorimotor integration. Behav Brain Res 2001,127(1–2):119–136.

    Article  CAS  PubMed  Google Scholar 

  21. Babiloni C, Brancucci A, Vecchio F, Arendt-Nielsen L, Chen AC, Rossini PM: Anticipation of somatosensory and motor events increases centro-parietal functional coupling: an EEG coherence study. Clin Neurophysiol 2006,117(5):1000–1008. 10.1016/j.clinph.2005.12.028

    Article  PubMed  Google Scholar 

  22. Kay LM: Theta oscillations and sensorimotor performance. Proc Natl Acad Sci U S A 2005,102(10):3863–3868. 10.1073/pnas.0407920102

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  23. Smith ME, McEvoy LK, Gevins A: Neurophysiological indices of strategy development and skill acquisition. Brain Res Cogn Brain Res 1999,7(3):389–404. 10.1016/S0926-6410(98)00043-3

    Article  CAS  PubMed  Google Scholar 

  24. Moriguchi Y, Hiraki K: Prefrontal cortex and executive function in young children: a review of NIRS studies. Front Hum Neurosci 2013, 7:867.

    Article  PubMed Central  PubMed  Google Scholar 

  25. Szurhaj W, Derambure P, Labyt E, Cassim F, Bourriez JL, Isnard J, Guieu JD, Mauguiere F: Basic mechanisms of central rhythms reactivity to preparation and execution of a voluntary movement: a stereoelectroencephalographic study. Clin Neurophysiol 2003,114(1):107–119. 10.1016/S1388-2457(02)00333-4

    Article  PubMed  Google Scholar 

  26. Toni I, Shah NJ, Fink GR, Thoenissen D, Passingham RE, Zilles K: Multiple movement representations in the human brain: an event-related fMRI study. J Cogn Neurosci 2002,14(5):769–784. 10.1162/08989290260138663

    Article  PubMed  Google Scholar 

  27. Baker SN: Oscillatory interactions between sensorimotor cortex and the periphery. Curr Opin Neurobiol 2007,17(6):649–655. 10.1016/j.conb.2008.01.007

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  28. Cardoso de Oliveira S: The neuronal basis of bimanual coordination: recent neurophysiological evidence and functional models. Acta Psychol 2002,110(2–3):139–159.

    Article  Google Scholar 

  29. Oldfield RC: The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 1971,9(1):97–113. 10.1016/0028-3932(71)90067-4

    Article  CAS  PubMed  Google Scholar 

  30. Rowlands AV, Stiles VH: Accelerometer counts and raw acceleration output in relation to mechanical loading. J Biomech 2012,45(3):448–454. 10.1016/j.jbiomech.2011.12.006

    Article  CAS  PubMed  Google Scholar 

  31. Jung TP, Makeig S, Westerfield M, Townsend J, Courchesne E, Sejnowski TJ: Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects. Clin Neurophysiol 2000,111(10):1745–1758. 10.1016/S1388-2457(00)00386-2

    Article  CAS  PubMed  Google Scholar 

  32. Neuper C, Pfurtscheller G: Event-related dynamics of cortical rhythms: frequency-specific features and functional correlates. Int J Psychophysiol 2001,43(1):41–58. 10.1016/S0167-8760(01)00178-7

    Article  CAS  PubMed  Google Scholar 

  33. Bastiaansen MC, van Berkum JJ, Hagoort P: Syntactic processing modulates the theta rhythm of the human EEG. NeuroImage 2002,17(3):1479–1492. 10.1006/nimg.2002.1275

    Article  PubMed  Google Scholar 

  34. Velasques B, Machado S, Portella CE, Silva JG, Terra P, Ferreira C, Basile L, Cagy M, Piedade R, Ribeiro P: Cortical asymmetry: catching an object in free fall. Arq Neuropsiquiatr 2007,65(3A):623–627. 10.1590/S0004-282X2007000400015

    Article  PubMed  Google Scholar 

  35. Caplan JB, Madsen JR, Schulze-Bonhage A, Aschenbrenner-Scheibe R, Newman EL, Kahana MJ: Human theta oscillations related to sensorimotor integration and spatial learning. J Neurosci 2003,23(11):4726–4736.

    CAS  PubMed  Google Scholar 

  36. de Araujo DB, Baffa O, Wakai RT: Theta oscillations and human navigation: a magnetoencephalography study. J Cogn Neurosci 2002,14(1):70–78. 10.1162/089892902317205339

    Article  PubMed  Google Scholar 

  37. Hatfield BD, Haufler AJ, Hung TM, Spalding TW: Electroencephalographic studies of skilled psychomotor performance. J Clin Neurophysiol 2004,21(3):144–156. 10.1097/00004691-200405000-00003

    Article  PubMed  Google Scholar 

  38. Astafiev SV, Shulman GL, Stanley CM, Snyder AZ, Van Essen DC, Corbetta M: Functional organization of human intraparietal and frontal cortex for attending, looking, and pointing. J Neurosci 2003,23(11):4689–4699.

    CAS  PubMed  Google Scholar 

  39. Abe M, Hanakawa T: Functional coupling underlying motor and cognitive functions of the dorsal premotor cortex. Behav Brain Res 2009,198(1):13–23. 10.1016/j.bbr.2008.10.046

    Article  PubMed  Google Scholar 

  40. Haufler AJ, Spalding TW, Santa Maria DL, Hatfield BD: Neuro-cognitive activity during a self-paced visuospatial task: comparative EEG profiles in marksmen and novice shooters. Biol Psychol 2000,53(2–3):131–160.

    Article  CAS  PubMed  Google Scholar 

  41. Classen J, Gerloff C, Honda M, Hallett M: Integrative visuomotor behavior is associated with interregionally coherent oscillations in the human brain. J Neurophysiol 1998,79(3):1567–1573.

    CAS  PubMed  Google Scholar 

  42. von Stein A, Sarnthein J: Different frequencies for different scales of cortical integration: from local gamma to long range alpha/theta synchronization. Int J Psychophysiol 2000,38(3):301–313. 10.1016/S0167-8760(00)00172-0

    Article  CAS  PubMed  Google Scholar 

  43. Hummel F, Gerloff C: Larger interregional synchrony is associated with greater behavioral success in a complex sensory integration task in humans. Cereb Cortex 2005,15(5):670–678.

    Article  PubMed  Google Scholar 

  44. Machado S, Cunha M, Portella CE, Silva JG, Velasques B, Bastos VH, Budde H, Pompeu F, Basile L, Cagy M, Piedade R, Ribeiro P: Integration of cortical areas during performance of a catching ball task. Neurosci Lett 2008,446(1):7–10. 10.1016/j.neulet.2008.09.036

    Article  CAS  PubMed  Google Scholar 

  45. Machado S, Cunha M, Velasques B, Minc D, Teixeira S, Domingues CA, Silva JG, Bastos VH, Budde H, Cagy M, Basile L, Piedade R, Ribeiro P: Sensorimotor integration: basic concepts, abnormalities related to movement disorders and sensorimotor training-induced cortical reorganization. Rev Neurol 2010,51(7):427–436.

    PubMed  Google Scholar 

  46. Papenberg G, Hammerer D, Muller V, Lindenberger U, Li SC: Lower theta inter-trial phase coherence during performance monitoring is related to higher reaction time variability: a lifespan study. NeuroImage 2013, 83:912–920.

    Article  PubMed  Google Scholar 

  47. Minc D, Machado S, Bastos VH, Machado D, Cunha M, Cagy M, Budde H, Basile L, Piedade R, Ribeiro P: Gamma band oscillations under influence of bromazepam during a sensorimotor integration task: an EEG coherence study. Neurosci Lett 2010,469(1):145–149. 10.1016/j.neulet.2009.11.062

    Article  CAS  PubMed  Google Scholar 

  48. Coull JT, Frackowiak RS, Frith CD: Monitoring for target objects: activation of right frontal and parietal cortices with increasing time on task. Neuropsychologia 1998,36(12):1325–1334. 10.1016/S0028-3932(98)00035-9

    Article  CAS  PubMed  Google Scholar 

  49. Weibull A, Flondell M, Rosen B, Bjorkman A: Cerebral and clinical effects of short-term hand immobilisation. Eur J Neurosci 2011,33(4):699–704. 10.1111/j.1460-9568.2010.07551.x

    Article  PubMed  Google Scholar 

  50. Werhahn KJ, Mortensen J, Kaelin-Lang A, Boroojerdi B, Cohen LG: Cortical excitability changes induced by deafferentation of the contralateral hemisphere. Brain 2002,125(Pt 6):1402–1413.

    Article  PubMed  Google Scholar 

  51. Halsband U, Lange RK: Motor learning in man: a review of functional and clinical studies. J Physiol Paris 2006,99(4–6):414–424.

    Article  PubMed  Google Scholar 

  52. Kansaku K, Muraki S, Umeyama S, Nishimori Y, Kochiyama T, Yamane S, Kitazawa S: Cortical activity in multiple motor areas during sequential finger movements: an application of independent component analysis. NeuroImage 2005,28(3):669–681. 10.1016/j.neuroimage.2005.06.022

    Article  PubMed  Google Scholar 

  53. Zang Y, Jia F, Weng X, Li E, Cui S, Wang Y, Hazeltine E, Ivry R: Functional organization of the primary motor cortex characterized by event-related fMRI during movement preparation and execution. Neurosci Lett 2003,337(2):69–72. 10.1016/s0304-3940(02)01236-3

    Article  CAS  PubMed  Google Scholar 

  54. Ghafouri M, McIlroy WE, Maki BE: Initiation of rapid reach-and-grasp balance reactions: is a pre-formed visuospatial map used in controlling the initial arm trajectory? Exp Brain Res 2004,155(4):532–536. 10.1007/s00221-004-1855-8

    Article  PubMed  Google Scholar 

  55. Prablanc C, Desmurget M, Grea H: Neural control of on-line guidance of hand reaching movements. Prog Brain Res 2003, 142:155–170.

    Article  PubMed  Google Scholar 

  56. Desmurget M, Sirigu A: A parietal-premotor network for movement intention and motor awareness. Trends Cogn Sci 2009,13(10):411–419. 10.1016/j.tics.2009.08.001

    Article  PubMed  Google Scholar 

  57. Battaglia-Mayer A, Caminiti R, Lacquaniti F, Zago M: Multiple levels of representation of reaching in the parieto-frontal network. Cereb Cortex 2003,13(10):1009–1022. 10.1093/cercor/13.10.1009

    Article  PubMed  Google Scholar 

  58. Manginelli AA, Baumgartner F, Pollmann S: Dorsal and ventral working memory-related brain areas support distinct processes in contextual cueing. NeuroImage 2013, 67:363–374.

    Article  PubMed  Google Scholar 

  59. Andres M, Pelgrims B, Olivier E: Distinct contribution of the parietal and temporal cortex to hand configuration and contextual judgements about tools. Cortex 2013,49(8):2097–2105. 10.1016/j.cortex.2012.11.013

    Article  PubMed  Google Scholar 

  60. Wick G, Muller PU, Kuhn L, Lefkovits I: Molecular analysis of genetically determined target organ abnormalities in spontaneous autoimmune thyroiditis. Immunobiol 1990,181(4–5):414–429.

    Article  CAS  Google Scholar 

  61. Koeneke S, Lutz K, Wustenberg T, Jancke L: Bimanual versus unimanual coordination: what makes the difference? NeuroImage 2004,22(3):1336–1350. 10.1016/j.neuroimage.2004.03.012

    Article  PubMed  Google Scholar 

  62. Beudel M, Zijlstra S, Mulder T, Zijdewind I, de Jong BM: Secondary sensory area SII is crucially involved in the preparation of familiar movements compared to movements never made before. Hum Brain Mapp 2011,32(4):564–579. 10.1002/hbm.21044

    Article  CAS  PubMed  Google Scholar 

  63. Haaland KY, Harrington DL: Hemispheric control of the initial and corrective components of aiming movements. Neuropsychologia 1989,27(7):961–969. 10.1016/0028-3932(89)90071-7

    Article  CAS  PubMed  Google Scholar 

  64. van der Helden J, van Schie HT, Rombouts C: Observational learning of new movement sequences is reflected in fronto-parietal coherence. PLoS One 2010,5(12):e14482. 10.1371/journal.pone.0014482

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  65. Catalan MJ, Honda M, Weeks RA, Cohen LG, Hallett M: The functional neuroanatomy of simple and complex sequential finger movements: a PET study. Brain 1998,121(Pt 2):253–264.

    Article  PubMed  Google Scholar 

  66. Barany DA, Della-Maggiore V, Viswanathan S, Cieslak M, Grafton ST: Feature interactions enable decoding of sensorimotor transformations for goal-directed movement. J Neurosci 2014,34(20):6860–6873. 10.1523/JNEUROSCI.5173-13.2014

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  67. Beauchamp MS, Yasar NE, Frye RE, Ro T: Touch, sound and vision in human superior temporal sulcus. NeuroImage 2008,41(3):1011–1020. 10.1016/j.neuroimage.2008.03.015

    Article  PubMed Central  PubMed  Google Scholar 

  68. Bruce C, Desimone R, Gross CG: Visual properties of neurons in a polysensory area in superior temporal sulcus of the macaque. J Neurophysiol 1981,46(2):369–384.

    CAS  PubMed  Google Scholar 

  69. Balslev D, Nielsen FA, Paulson OB, Law I: Right temporoparietal cortex activation during visuo-proprioceptive conflict. Cereb Cortex 2005,15(2):166–169.

    Article  PubMed  Google Scholar 

  70. Shannon BJ, Buckner RL: Functional-anatomic correlates of memory retrieval that suggest nontraditional processing roles for multiple distinct regions within posterior parietal cortex. J Neurosci 2004,24(45):10084–10092. 10.1523/JNEUROSCI.2625-04.2004

    Article  CAS  PubMed  Google Scholar 

  71. Chapman H, Gavrilescu M, Wang H, Kean M, Egan G, Castiello U: Posterior parietal cortex control of reach-to-grasp movements in humans. Eur J Neurosci 2002,15(12):2037–2042. 10.1046/j.1460-9568.2002.02021.x

    Article  PubMed  Google Scholar 

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Correspondence to Oscar Arias-Carrión.

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None of the authors have actual or potential conflict of interest including any financial, personal or other relationships with other people or organizations that could inappropriately influence, or be perceived to influence, our work.

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IB, ST, BV, RP, PR and OAC designed, conducted the experiment and drafted most of the manuscript. JB, SM, MG, MG, VHB, DM, ASC and JSP performed the experiment, the literature review and the drafting of the manuscript. All authors read and approved the final manuscript.

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Brauns, I., Teixeira, S., Velasques, B. et al. Changes in the theta band coherence during motor task after hand immobilization. Int Arch Med 7, 51 (2014). https://doi.org/10.1186/1755-7682-7-51

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