Complete brachial plexus lesions lead to a total paresis of the affected arm resulting in a significant impairment in everyday life. Reinnervation of the affected musculocutaneous nerve via an intact C7 root or via the ipsilateral phrenic nerve can be performed to regain elbow flexion. In an fMRI study, Beisteiner et al. (2011) analyzed functional activation in three patients with complete brachial plexus lesions and in three healthy controls. Two patients underwent an end-to-side nerve reconstruction of the musculocutaneous nerve with the ipsilateral phrenic nerve and one patient received an end-to-end coaptation of the healthy contralateral C7 root with the musculocutaneous nerve. The advantage of the end-to-side technique is the preservation of the donor nerve function – that is, the control of the diaphragm persists via the modified phrenic nerve. However, after establishing an end-to-side connection, the phrenic nerve and its cortical projection area are required to perform a new double function: independent control of breathing and elbow flexion. In contrast, in the control patient (C7 – musculocutaneous connection) the phrenic nerve remained unchanged. FMRI tasks comprised elbow flexion of the healthy arm, elbow flexion of the diseased arm, forced abdominal inspiration, and foot flexion on the affected side. Clinical documentations such as electromyographic recording, chest radiography, and fluoroscopy of the thorax confirmed that end-to-side patients were able to control the diaphragm and the arm independently. In Fig. 2, functional imaging findings in patients and controls are summarized. Forced inspiration activated the diaphragm (phrenic nerve) area of the primary motor cortex bilaterally in all participants. In patients with end-to-side anastomoses, elbow flexion of the diseased arm resulted in unilateral activation of the arm area in the primary motor cortex and in an additional activation of the diaphragm area. This recruitment of the diaphragm area was absent when these patients performed movements of the healthy arm or the foot. As expected, neither the control patient nor the healthy control subjects showed activations in the phrenic nerve area during arm movement. These findings suggest that neuroplasticity may even transform a healthy monofunctional cortical area into a bifunctional area – here shown for the diaphragm area.

Eickhoff et al. (2008) investigated cortical plasticity in two patients that underwent a resection of parts of the forearm including the elbow joint due to a malignant soft tissue tumor and a subsequent reimplantation of the amputated distal forearm including the hand. Thereby, tendons of the finger flexors and extensors were attached to upper arm muscles, and distal forearm nerves were coaptated with the nerve trunks of the upper arm.

The 2 patients and 14 healthy control subjects performed a motor fMRI task comprising fist-closing movements with the right, left, or both hands simultaneously. Dynamic causal modeling (DCM) was applied to explore effective connectivity within an anatomically and functionally defined bilateral motor network consisting of the primary motor cortex (M1), the supplementary motor area (SMA), the ventral premotor cortex (PMC), and extrastriatal visual cortex (V5). The latter region was defined as the input region for the bilateral SMA and PMC as movements were visually paced in the fMRI task. All regions were defined for the affected hemisphere (hemisphere contralateral to the side of peripheral surgery) and the healthy hemisphere (hemisphere ipsilateral to the side of peripheral surgery). Effects of interest analysis revealed a significantly increased activation during tasks compared to the baseline in the motor ROIs. Intrinsic connectivity, that is, task-independent connectivity, was symmetrically organized in controls (Fig. 3, top panel) with a positive influence (green arrows) of the SMA and PMC on M1 and an inhibition (red arrows) between bilateral M1 and SMA. In contrast, both patients showed altered influence of the PMC of the affected hemisphere. However, the actual patterns of intrinsic connectivity differed between both patients as depicted in Fig. 3 (bottom panel). When moving the healthy hand, the PMC of the affected hemisphere was inhibited by the PMC and M1 of the healthy hemisphere in both patients. Eickhoff and colleagues interpreted this result as an enhanced suppression of the influence of the affected hemisphere on the control of the healthy hand. In both patients, movements of the replanted hand resulted in increased activation of the affected PMC that might reflect an increased effort required to perform the task. In addition, a pathological inhibition of the healthy M1 on the affected M1 was present in both patients when moving the replanted hand. The most prominent difference between the two patients was present in the affected PMC (Fig. 3, bottom panel). In patient J.H., the affected PMC had an increased positive influence (compared to controls) on the M1 of the same hemisphere at rest (intrinsic connectivity) as well as during movements of the replanted hand, while in patient G.M., the M1 was inhibited by the PMC. Correspondingly, motor performance of G.M. was worse than that of J.H. Eickhoff et al. concluded that different neuroplastic connectivity changes were related to clinical progress and behavioral performance stressing the importance of an early and intense rehabilitative exercise as it was the case for patient J.H.

Rath et al. (2008) reported a single-case fMRI study of a 27-year-old man who underwent a functional hemispherectomy at the age of 11. The patient suffered from an infarction of the right middle cerebral artery at 2 years of age. After the stroke he showed considerable improvements of motor functions of the left paretic hand; however, he developed intractable generalized epilepsy that required a resection of the affected right hemisphere. Although his hemiparesis worsened after hemispherectomy, hand function recovered again after physiotherapy and orthopedic surgeries. At the time of the MR investigation, the patient had spastic hemiparesis but voluntary control and sustained weak motor functions in the hemiparetic arm. Anatomical MRI revealed no pathological findings in the remaining left hemisphere. Functional imaging showed that movements of both hands induced significant activation in the remaining primary motor cortex. Movements of the healthy hand corresponded to activation in the typical hand motor area, whereas movements of the paretic hand produced two activation clusters in the periphery of the hand motor area (Fig. 4). This reorganization is likely to be induced by the hemispherectomy rather than by the initial stroke since hemiparesis showed an initial worsening after hemispherectomy and a secondary improvement after rehabilitation. This single case demonstrates that functional transition zones (i.e., the periphery of a functional cortical area) in the ipsilateral hemisphere can be used to restore functions when no contralateral functional tissue anymore exists.

Acute stroke often leads to impaired motor and cognitive functions that are sought to be improved by rehabilitation. Patients with only partial recovery suffering from residual impairments after rehabilitation are referred as chronic stroke patients.

Lazaridou et al. (2013b) investigated structural neuroplastic changes corresponding to a rehabilitative motor training by assessing cortical thickness with voxel-based morphometry (VBM) and white matter integrity with DTI in four patients with chronic stroke. The time interval between the onset of left-sided ischemic subcortical middle cerebral artery stroke and the participation in the study was more than 6 months. The patients underwent an 8-week-lasting motor training consisting of 1 h squeezing an exercise ball with the paretic hand for 3 days per week. MR scans were performed at baseline (before the training), after 4 weeks of training, at the end of the training period (after 8 weeks), and finally another 4 weeks later. For DTI fiber reconstruction, deterministic tractography was performed and visually inspected for directionality and location. The pons, the posterior limb of the internal capsule, and the motor cortex were selected as seed regions to reconstruct the corticospinal tract (CST).

Statistical analysis of CST fibers of the affected hemisphere revealed a significant increase in the number of fibers and average tract length as illustrated in Fig. 5 depicting CST fibers of a representative patient before, during, and after motor training. CST fibers (in blue) projected progressively closer to the motor cortex and showed increased density with ongoing training progress. In addition, VBM analysis showed a significantly increased cortical thickness of the ventral postcentral gyrus after training compared to the baseline. With this study, Lazaridou et al. could demonstrate that intensive motor training resulted in structural neuroplasticity in the sensorimotor system in chronic stroke patients and provided a new approach for the evaluation of the rehabilitation progress.

Traumatic brain injury (TBI) is often followed by persistent cognitive deficits affecting several cognitive domains like attention, working memory, speech, and executive functions such as planning, inhibition, and cognitive control.

Caeyenberghs et al. (2012b) addressed the latter issue using a functional imaging approach combined with a graph theoretical analysis. They examined 23 patients with mild to moderate TBI and 26 healthy control subjects applying an event-related fMRI paradigm previously used to investigate cognitive control in young and elderly adults (Coxon et al. 2010) and in TBI patients (Leunissen et al. 2013). Participants performed temporally coupled circular hand movements (either clockwise or counterclockwise) with each hand using a joystick. Visual cues indicated whether to switch the movement patterns from asymmetric to symmetric or vice versa or to continue the prior movement. The authors constructed a switching motor network consisting of 22 regions of interest that were defined as 10 mm spheres centered on peak activation coordinates reported by Coxon et al. (2010) and Leunissen et al. (2013). The network comprised regions of the medial frontal cortex, anterior cingulate cortex, bilateral dorsolateral prefrontal cortex, bilateral inferior frontal cortex (BA 44), basal ganglia, cerebellum, right precuneus, left premotor cortex, bilateral insula, and right superior and inferior parietal cortex. First, a contrast Switch > Continue was conducted to compute the average time series for each ROI of each subject which was then subjected to a partial correlation analysis. This method allowed a quantification of the unique correlation between two ROIs and the content filtering of the effects of all the other ROIs giving an appropriate measure for functional connections. For graph theoretical analysis, matrices with significant connections weighted by the correlation values between nodes (i.e., ROIs) were constructed. Weighted matrices were used to calculate the mean connection strength of the single nodes as well as of the overall network connection strength. The Brain Connectivity Toolbox (Rubinov and Sporns 2010) was employed to assess global network architecture and nodal properties.

TBI patients exhibited slower response times and more disruptions during the switching task than the controls that could not be explained by motor difficulties. Graph theoretical analysis revealed a significantly altered functional network in patients with higher connectivity degree and strength than in controls. Specifically, the patients exhibited a higher connectivity in the left ventral portion of M1 (compare yellow sphere in Fig. 6) possibly reflecting functional compensation as this area is involved in coordination and is strongly interconnected within the primary motor cortex. In addition, local efficiency was enhanced in patients with TBI which might indicate a compensatory increase of short-range connections between adjacent nodes. Besides, graph theoretical analysis provided information about hubs, that is, regions with a central role in a functional network. In both the patients and controls, the right insula with its critical role in the differentiation between internal and external stimuli presented as a hub, putatively due to the strong directive of a visual input to trigger movement switching. Interestingly, two regions mainly involved in movement planning (right dorsolateral prefrontal cortex and left dorsal premotor cortex) acted as hubs in the TBI group only. Caeyenberghs and colleagues (2012b) concluded that TBI patients might rely more on cognitive control and performance monitoring during the switching task. However, the higher mean connectivity degree in patients was related with poorer switching performance implying that increased connectivity not necessarily improves function. Moreover, higher connectivity degree was positively correlated with injury severity and might therefore be a result of a more severe brain damage reflecting a higher effort to manage cognitive control tasks.