CHAPTER 3 DISCUSSION AND CONCLUSIONS
3. Brain plasticity
Unilateral ischemic stroke and Alzheimer‟s disease have been associated with different types of plasticity. In stroke patients, we observed pathologically increased alpha band connectivity in the contralesional hemisphere. This increase was associated with poor behavioral performance. In contrast to stroke, in Alzheimer‟s disease patients we identified two types of adaptive network reorganization: 1) a frequency shift in a topographically unchanged network; 2) a substitution of a functional node by an increase of FC in the homologous contralateral hemisphere. The preliminary results of an ongoing study in the group of stroke patients also revealed adaptive network remodeling in ipsi- and contralesional functional nodes.
3.1. Interhemispheric Competition
In stroke patients we observed a hypo-connectivity of the stroke-affected hemisphere. At the same time, the contralesional hemisphere displayed a maladaptive increase of FC. The magnitude of coherence in this hemisphere correlated negatively with patients‟ performance in cognitive and motor tasks (Dubovik et al., 2012). Hence, levels of FC in the perilesional regions of the affected hemisphere and contralesional hemisphere played opposing roles in the maintenance of patients‟ cognitive and motor function. For example, patients with Broca‟s aphasia who displayed strongly increased right-hemispheric coherence performed worse than aphasic patients with a low magnitude of coherence in this hemisphere. Conversely, patients who had higher levels of FC in the lesioned hemisphere (specifically in the left IFG) performed better on the task. These findings not only illustrate the existence of reciprocal connectivity between homologous counterparts of two hemispheres, but also the competitive character of their relationship.
An altered interhemispheric balance of connectivity observed in our study demonstrates the well-known hyperexcitation of the healthy hemisphere resulting from disturbed transcallosal inhibition of the damaged hemisphere (Koch et al., 2008). According to the interhemispheric rivalry model, the equilibrium between the two hemispheres is maintained through mutual inhibition, but the unilateral lesion can reverse this (Cao et al., 1999; Corbetta et al., 2005). As a result of damage, the unbound activity of the healthy hemisphere suppresses its lesionary counterpart and could be a negative influence on the patient‟s recovery. Bi-hemispheric reorganization of activity was reported previously in task-based neuroimaging studies (Feydy et al., 2002; Saur et al., 2006). However, the findings concerning the role of contralesional hemisphere recruitment during task performance remained inconsistent. For instance, in aphasia, in some cases, the right hemisphere was found to play a beneficial role in language recovery (Warburton et al., 1999; Rosen et al., 2000), while other evidence suggested that activation of the right hemisphere during language tasks in patients with chronic
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aphasia is a reflection of inefficient mechanisms of language processing and may be deleterious to recovery (Martin et al., 2004; Naeser et al., 2005). A third group of studies have argued that activation of the right hemisphere areas neither facilitates nor hinders language recuperation (Thiel et al., 2001).Similarly to language improvement, the evidence for the involvement of the contralesional motor cortex‟s ability to reorganise itself successfully after strokes can be seen in some studies, but not in others, leading to inconsistent results. (Weiller et al., 1992; Feydy et al., 2002).
It has been suggested that the current inconsistent findings are due to the fact that studies were carried out amongst patients at different stages of recovery. Some authors have argued that plasticity is a dynamic process; it changes over time. The role of the hemispheric involvement in functional reorganization might therefore shift during the course of improvement (Hamilton et al., 2011). Indeed, longitudinal activation and connectivity studies reported changing influence of the contralesional hemisphere. For instance, it was observed that in patients with acute stroke and non-fluent aphasia, the right hemisphere exhibited stronger involvement during language tasks, whereas in the chronic phase the left hemisphere appeared to regain dominance (Saur et al., 2006). Further to this, increased FC in the ipsilesional cortex in combination with decreased contralesional FC was found to be associated with improved motor performance three weeks after stroke in patients with unilateral paresis (Westlake et al., 2012). Hence, it is likely that a range of changes take place in the recovery process. Neural activity may be initially lateralized to the contralesional cortex, but for functional improvement it needs to shift back to the ipsilesional cortex. Our findings demonstrate that in the subacute phase 3 months after a unilateral stroke, an increase in contralesional alpha-band FC is negatively related to behavior. It is possible however that at earlier times this lateralization could be useful for recovery.
We address this issue in our current analyses in a group of stroke patients. Two weeks after the stroke‟s onset, we observed an increase of FC in the perilesional region which is a positive marker of recovery, in agreement with previous studies. Contralateral FC was also larger in patients showing good language recovery, but was smaller in patients showing good motor recovery. Hence, our results suggest that contralesional recruitment in the acute phase after stroke can be beneficial for language recovery, but maladaptive for motor recovery. The combined FC changes in ipsi- and contralesional region have been found to have excellent positive predictive value (>95%) for good recovery after stroke for all functions.
The findings on activation and connectivity dynamics in stroke patients and the competitive character of interhemispheric relationships suggest that the treatments which rebalance activity and coherence between the hemispheres are likely to have positive effects in stroke patients. Non-invasive cortical stimulation like transcranial direct current stimulation (tDCS) or TMS are particularly appealing techniques to achieve this purpose. The main idea behind the application of tDCS or TMS in unilateral stroke is to facilitate excitability in lesioned or perilesional areas or to decrease excitability in inhibitory contralesional areas in order to improve the affected function (Ayache et al., 2012). To date, a range of trials have assessed the effects of stimulation on motor, language and attention deficits in stroke patients (Martin et al., 2004; Gerloff et al., 2006; Koch et al., 2008; Naeser et al., 2012). Nevertheless,
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after decades of research, concerns about the value of non-invasive stimulation techniques in promoting recovery still remain. For example, little is known about the mechanisms underlying individual responsiveness of the patients to the treatment. The optimal parameters of stimulation, in particular, the frequency of stimulation, site and side of the cortical targets also need more investigation (Ayache et al., 2012).3.2. Adaptive Mechanisms
A comparison of Alzheimer‟s disease patients to the healthy matched group revealed disease-related decrease of FC in alpha-band and an increase of FC in slow theta-band. The decrease of alpha-band FC observed in Alzheimer‟s disease patients seems to be a general consequence of brain lesion or neural loss since it has been noted in patients with different brain pathologies (Guggisberg et al., 2008; Martino et al., 2011; Dubovik et al., 2012). In contrast, the increase of theta-band connectivity in temporo-parietal regions could be specific only to Alzheimer‟s disease. Such an increase of slow band connectivity might represent a compensatory mechanism to optimize functional interactions of the remaining neuronal populations. Previous studies also reported a slowing of EEG frequencies in dementia (Fernandez et al., 2002; van der Hiele et al., 2007). It is important to note that the topography of the observed pathological connectivity in our study corresponded precisely to the areas characterized by early hypometabolism and atrophy (Stam et al., 2006; Alonso et al., 2011; Sankari et al., 2011). The fact that the same regions display simultaneous decreases of alpha- and increases of theta-band connectivity suggests that FC not simply retraces damaged brain tissue, but is also able to identify disease-specific network reorganization.
By correlating FC values with performance of the patients in language and episodic memory tasks, we could identify mechanisms of functional remodeling associated with relatively preserved cognitive function. Hence, not only dysfunctional but also adaptive restructuring of brain networks takes place in the early stages of Alzheimer‟s disease. In particular, we identified two mechanisms of adaptive plasticity that were not reported previously. In a network related to episodic verbal memory, we found a slowing of network interactions. Alpha-band FC magnitude between the left hippocampus and the ventro-medial prefrontal cortex (vmPFC) was significantly reduced and negatively correlated with the patient‟s performance. At the same time, increased connectivity between nodes of this network in the theta band was associated with better memory scores. As a result, Alzheimer‟s disease patients who had a shift of FC in the verbal memory network from alpha to theta frequencies displayed better performance in memory tasks. Both alpha and theta frequencies have been previously related to memory processes (Klimesch, 1996). One possible explanation for this finding might be to suggest a more effective adaptation of slower rhythms to the reduced number of available neurons in Alzheimer‟s disease patients.
In a language network, the usual alpha-band interactions between Broca‟s area and left hippocampal region observed in healthy subjects were suppressed. Instead, Alzheimer‟s disease patients included
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additional brain regions in their alpha-band network, namely the right homologue of Broca‟s area and the right hippocampal area. This recruitment was positively correlated with patients‟ performance in language tasks. The beneficial role of the additional contralateral recruitment might be surprising in view of our findings in stroke patients mentioned above (Dubovik et al., 2012) and in view of the well-known interhemispheric rivalry model. Language network changes observed in patients with Alzheimer‟s disease do not show interhemispheric rivalry, but constructive collaboration. It is currently unclear what triggers these mechanisms. One could speculate that it is related to the bilateral and relatively slow progression of the disease and neuronal loss which, unlike in unilateral stroke, might favor bilateral adaptive neural reorganization. Further studies are needed to answer this question.One potential limitation of this study is that some patients could not interrupt their drug treatment and were continuing with their recommended medication during our study. However, we controlled for possible confounding effects of the medication by including it as a co-factor in the statistical comparisons. This should have reduced major distortions of the results.