The pathophysiology of post-stroke aphasia: A network approach

1 Introduction

Post-stroke aphasia syndromes as a clinical entity arise from the disruption of brain networks specialized in language production and comprehension due to permanent focal ischemia. This approach to post-stroke aphasia is based on two pathophysiological concepts: 1) Understanding language processing in terms of distributed networks rather than language centers, a concept introduced by Wernicke and Lichtheim in the late 19th century and further developed into complex 21st century hierarchical networks derived from in vivo imaging and electrophysiological studies in healthy subjects and 2) understanding the molecular pathophysiology of ischemic brain injury as a dynamic process beyond the direct destruction of network centers and their connections, a concept that comprises mechanisms of secondary brain damage (such as inflammation and neurodegeneration) as well as recovery related molecular and cellular mechanisms usually referred to as “neuroplasticity”. While considerable progress has been made in the past 10 years to develop such models on a systems as well as a molecular level, the influence of these approaches on understanding and treating clinical aphasia syndromes has been limited. In this article, we will review current pathophysiological concepts of ischemic brain injury, their relationship to altered information processing in language networks after ischemic stroke and how these mechanisms may be influenced therapeutically to improve treatment of post-stroke aphasia.

2 Language networks in the normal brain

In the traditional view of the Wernicke-Lichtheim model from 1885, language function of the normal brain was thought to be supported by a perisylvian network of brain regions in the left hemisphere involving core nodes in the middle and superior temporal (Wernicke’s area) and inferior frontal gyrus (IFG, also known as Broca’s area) connected by a main fiber tract, the arcuate fascicle (Lichteim, 1885; Wernicke, 1874). This classical model was based on lesion studies and mainly used to explain aspects of single word processing. Newer cytoarchitectonic and myeloarchitectonic studies suggest however a Broca and Wernicke complex comprising several rather than a single area and subserving different linguistic functions (Amunts et al., 2004; Friederici & Gierhan, 2013; Poeppel, 2014). According to this view (see Fig. 1) the Broca complex consists of Brodmann areas (BA) 47,45,44 as well as the insular cortex and the premotor cortex (BA6) with BA47 and 45 being mainly involved in semantic (Amunts et al., 2004; Devlin, Matthews, & Rushworth, 2003) and syntactic processing (Friederici, Opitz, & von Cramon, 2000) while BA44 is supposed to be associated with phonetic encoding (Nixon, Lazarova, Hodinott-Hill et al., 2004) and BA6 as well as the anterior insular cortex with articulatory planning (Dronkers, 1996; Nestor et al., 2003). In a similar way the Wernicke complex comprises BA22, 41 and 42 in the superior temporal gyrus as well as BA37 and 21 in the middle temporal gyrus (Friederici & Gierhan, 2013). BA41 represents the primary auditory cortex (Heschl’s gyrus), while the secondary auditory cortex consists of BA42 (planum temporale) and BA22. Both areas appear to be associated with phonological decoding and pre-lexical processing while BA37 and 21 are thought to mediate lexical access (Hickok & Poeppel, 2007; Poeppel, 2014). Recent cytoarchitectonic studies (Amuntset al., 2010) seem to suggest that especially the Brodmann Areas in the Broca complex can be subdivided into even smaller subregions. This fine grain structure may explain why certain Brodmann areas appear to be activated by different linguistic tasks (e.g. BA45 in semantic as well as syntactic processing): Each task may actually activate specific subregions which cannot be distinguished because they are below the resolution of most functional imaging modalities.

In analogy to this more complex subdivision of Broca’s and Wernicke’s complex, imaging studies of fiber tracts suggest a similar organization of the connections between those complexes (Catani & Budisavljevic, 2013; Friederici, 2009; Turken & Dronkers, 2011). The dorsal language circuit connects BA44 with the posterior superior and middle temporal gyrus via the arcuate fascicle (AF) and the superior longitudinal fascicle (SFT) the middle and superior temporal gyrus to the pre-motor cortex (BA6) with the former being necessary for syntactic processing and the latter for word repetition (Friederici & Gierhan, 2013). The ventral circuit consists of at least two pathways, the uncinate fascicle connecting BA47 and 45 to the anterior temporal cortex (BA38 and 21) and the extreme capsule fiber system connecting those areas to the posterior temporal cortex (BA22 and 37). The ventral circuit is involved in syntactic processing (Friederici & Gierhan, 2013) as well as semantic judgment and categorization at the single word as well as sentence level. In general this dual circuit organization thus consists of a ventral stream which is responsible for mapping sound onto meaning and a dorsal stream involved in mapping sound onto articulation (Hickok & Poeppel, 2007). Although these circuits and specifically the ventral one are present in both hemispheres, the principal linguistic processing levels of verbal expression and comprehension (phonology, semantics, grammar, syntax) are mediated by this complex network mainly in the left hemisphere (Price, 2010). In addition to classical imaging and electrophysiological methods (like event related potentials), the virtual brain lesions approach, using transcranial magnetic stimulation (TMS), can be used in normal subjects to study the specific contribution of certain nodes in the dorsal or ventral pathways to language function. Such experiments have confirmed the left prefrontal and frontal contribution to language function. Verbal encoding for example was disrupted following a transient lesion of the left prefrontal cortex (PFC) whereas a right PFC lesion disrupted non-verbal encoding (Floel et al., 2004). Transient lesions applied to the left IFG (BA45) also interfere with semantic processing as measured by prolonged latencies in a verb generation task (Thiel, Habedank, Haupt et al., 2004).

It has to be mentioned, though, that the general interhemispheric distribution of the language network is subject to some individual variation and varies along a continuum. The left hemisphere is the dominant hemisphere for language processing in 95% of right-handed healthy subjects (Knecht et al., 2000; Pujol, Deus, Losilla, & Capdevila, 1999; Springeret al., 1999) and 78% of left-handed and ambidextrous subjects (Szaflarski et al., 2002). Females were found more likely to have a symmetrical pattern of connections though this remains controversial (Catani et al., 2007; Vikingstad, George, Johnson, & Cao, 2000).

Other left hemispheric cerebral regions which have been found to be active during semantic processing are not yet included into the traditional language networks reviewed above (Friederici & Gierhan, 2013; Poeppel, 2014). A meta-analysis focusing on the semantic processing of words showed that the left angular gyrus (BA39) was the most consistently activated region across 120 functional neuroimaging studies (Binder, Desai, Graves, & Conant, 2009). This region was described as a heteromodal association area in the sense that it receives input from multiple modalities without one being dominant over another. It is thought to play a role in complex information integration and knowledge retrieval, which is necessary not only for the semantic processing of words, sentences and discourse, but also for problem solving and planning in general. The work of Binderet al. also points to numerous other heteromodal regions with links to executive functions, episodic memory, emotion and motivation and can serve as an example to highlight the intricate nature of language networks and their interrelationship with other functional networks related to more general cognitive processing (e.g. executive function and problem solving). Furthermore, the combination of structural and functional connectivity analysis of main language areas of the left hemisphere continues revealing complex and widespread interactions with frontal, parietal, and temporal regions in the two hemispheres via numerous white matter pathways (Turken & Dronkers, 2011). In fact, regions of the right hemisphere have been found to support some aspects of language processing, such as the production of automated speech (Code, 1997), the capacity to understand figurative aspects of language (Bottini et al., 1994) as well as the prosodic aspects of speech (Kreitewolf, Friederici, & von Kriegstein, 2014).

Whether specifically targeting these more general cognitive networks will eventually improve language recovery in post-stroke aphasia remains however to be demonstrated.

3 Pathophysiology of cerebral ischemia and mechanisms of neuroplasticity

Focal ischemic brain lesions are caused by a disruption of the blood supply to the brain through occlusion of a cerebral artery. Once cerebral blood flow decreases below a critical threshold of about 20 ml/100 g/min neuronal tissue will cease functioning and neurological symptoms, such as aphasia, occur. In case the blood vessel occlusion persists and cerebral blood flow drops below 12 ml/100 g/min for a prolonged period of time the neuronal tissue will die and become necrotic (Powers, Grubb, Darriet, & Raichle, 1985). This area of necrosis constitutes the core of the infarct whereas brain areas where perfusion remains above the viability threshold may survive if normal blood flow is re-instated by therapeutic intervention. These potentially salvageable regions are called “penumbra” (Greek for “twilight”) (Astrup, Siesjö, & Symon, 1981).

It has been shown that the extent of the penumbra prior to treatment is correlated with very early recovery from aphasia (Reineck, Agarwal, & Hillis, 2005) and that restoring penumbral blood flow to specific cortical areas of the left hemisphere in aphasic patients can restore specific aspects of language function such as naming (Hillis et al., 2006) and writing (Hillis, Wityk, Barker, & Caramazza, 2003). While acute hypoperfusion and tissue necrosis first of all affect circumscribed brain regions and their fiber tract connections, secondary damage or deactivation due to apoptosis, inflammation, neurodegeneration or diaschisis however can also affect remote brain areas and may result in a more widespread perturbation of entire functional networks even in the non-ischemic hemisphere. Diaschisis, the direct modulation of electrical and metabolic brain activity in one or more brain regions caused by a distant brain lesion was first described in 1914 by v. Monakow. With the advent of advanced neuroimaging methods the diaschisis concept has recently been extended to functional and structural networks (Carrera & Tononi, 2014) and has been shown to account for context specific deficits in patients with post-stroke aphasia (Price, Warburton, Moore, Frackowiak, & Friston, 2001) or to cause aphasic symptoms in patients with thalamic infarcts. While the effects of diaschisis can be reversible, other mechanisms can cause irreversible remote effects. Delayed cell death by apoptosis can occur in structurally normal cortex and cause secondary damage to neurons in brain areas outside the necrotic area and as such affect larger scale networks and limit a patient’s potential for recovery (Carrera et al., 2013). Neuronal degeneration is another irreversible mechanism affecting structural and functional brain connectivity. While degeneration primarily occurs along those nerve fibers which are directly affected by the ischemic lesion (either through cortical ischemia resulting in the death of the cell bodies or by subcortical ischemia with direct damage of axons) transsynaptic effects can also be observed in fibers which were not directly affected by the ischemic lesion (Ginsberg & Martin, 2002; Radlinska et al., 2012). Neuroinflammation can also contribute to remote effects of focal ischemic lesions especially on fiber tracts and often co-occurs with neurodegenerative changes (Thiel et al.,2010).

While all these mechanisms are relevant to understand how language networks are disrupted, it is also important to understand the brain’s toolbox for compensating or repairing disrupted networks (Table 1). These mechanisms of neuroplasticity may become spontaneously active within seconds or minutes after the onset of ischemia or may take days or weeks to activate such as use-dependent axonal sprouting and rerouting of dendrites. In the context of aphasia the activation of pre-existing neuronal pathways, which are normally not used to perform specific language tasks is of special interest (Atwood & Wojtowicz, 1999). Network activity is re-routed through these pathways by unmasking of so called “silent synapses” through abolition of inhibitory activity by the infarct (Jacobs & Donoghue, 1991). Activity in these released (or disinhibited) circuits can be further modulated by processes such as long-term depression and long-term potentiation (Hess, Aizenman, & Donoghue, 1996; Hess & Donoghue, 1996) and may eventually form a persisting alternative compensatory pathway. The existence of some of these neuroplastic mechanisms in human language networks has been demonstrated with neuroimaging studies in patients with focal brain lesions (Heiss, Kessler, Thiel, & Ghaemi, 1999; Saur et al., 2006; Thiel et al., 2001), or by perturbation of language network activity in normal subjects with TMS (Thiel, Schumacher, et al., 2006).

4 Effects of ischemic stroke on language network activity

Ischemic lesions leading to aphasia result in complex network disruptions. Even the occlusion of a single branch of the middle cerebral artery (e.g. the prerolandic artery) causes a complex lesion affecting several areas of Broca’s complex as well as fibre tracts of the dorsal and ventral circuits. This results in a dramatic decrease of functional activity not only in the affected regions but also in the remaining intact language related cortex in the left hemisphere in the first week post stroke. Moreover, ischemic lesions in language areas may impact even on more distant brain areas. Structural and functional connectivity analyses recently revealed that main language areas in the left hemisphere are part of a richly interconnected network extending in the right hemisphere (Turken & Dronkers, 2011). The lesion may result in the disruption of interhemispheric inhibition, releasing activity in regions homologue to the lesioned area. This has been shown in normal subjects where activity in the right hemisphere homologue of Broca’s area is released within minutes after perturbation of left Broca’s area with TMS (Thiel, Schumacher, et al., 2006). It is not clear if this released activity has a determinant role in the symptomatology of aphasia in the acute post-stroke phase. Language performance (as measured by a sentence comprehension task) correlates with the residual activation of the left IFG in the first days after stroke (Saur et al., 2006). Acute lesions of the dorsal circuit or to the posterior temporoparietal region particularly affecting the periventricular white matter in projection of the dorsal superior longitudinal and arcuate fasciculus are associated with repetition impairments. In contrast more ventral-anterior lesions in the temporo-prefrontal region specifically between the insular cortex and the putamen in projection of the ventral extreme capsule are associated with comprehension deficits (Kümmerer et al., 2013).

Following the acute injury reorganization activity patterns in language networks can be observed. In a longitudinal study, Saur and collaborators (Saur et al., 2006) investigated the temporal dynamics of language related brain activation changes in 14 patients and found that the reorganization of network activity follows a specific pattern: After the acute phase (2– 5 days) where network wide activity is generally decreased, an increased recruitment of homologue language areas in the right hemisphere was observed over the following 2 weeks. This abnormal contralesional activation then normalized during the chronic phase (4 to 12 months post stroke) resulting on average in the restoration of a left dominant activity patterns. This shift of activity into homologous regions of the right hemisphere and its role for recovery of function is poorly understood. Based on similarities with motor learning mechanisms, it has been proposed that right hemispheric networks may be necessary to re-learn specific language skills but would then no longer be needed once the reacquisition of those skills has been completed (Raboyeauet al., 2008).

However, not all chronic patients eventually show a normalization of activation patterns. Right-lateralized brain activity can be observed beyond the sub-acute phase and can also co-exist with reactivation of perilesional areas in the left hemisphere (Turkeltaub, Messing, Norise, & Hamilton, 2011). The recruitment of perilesional areas may arise from the release of cortico-cortical inhibitory inputs (collateral disinhibition) emanating from the infarcted language centers (Shimizu et al., 2002) while the recruitment of homologue language zones in the right hemisphere is thought to occur through transcallosal disinhibition by the lesion in the left hemisphere (Thiel, Habedank, et al., 2006; Winhuisen et al., 2005).

The extent of the lesion seems to play a role as to which of these reorganization patterns persists up into the chronic phase. Anglade and collaborators did a meta-analysis of imaging studies examining right hemispheric language networks in patients with aphasia (Anglade, Thiel, & Ansaldo, 2014). They classified the lesion size based on functional or anatomic images and suggested that lesion extent determines right hemisphere involvement in the sense that larger left-hemisphere lesions lead to an increase in release of right hemisphere activity.

Infarct location may also affect cerebral activation patterns post stroke and may even be crucial for determining the plasticity patterns of the language networks since lesions in core areas for language processing may trigger right hemisphere recruitment (Thulborn, Carpenter, & Just, 1999).

5 Rational for modulation of network activity

It is of clinical interest to establish a relationship between the type of reorganization pattern and the extent of language recovery in order to possibly facilitate favourable patterns through individualized treatment. Studies using brain imaging techniques to examine patients who fully recovered give important insight into this relationship and generally report a normalization of the language network activity, or at least, a clear lateralization of activity back towards the left (Meinzer et al., 2008; Saur et al., 2006).

Reactivation of perilesional regions in cases of best recovery is not controversial (Anglade et al., 2014; Torres, Drebing, & Hamilton, 2013). Remaining activations surrounding the peri-infarct cortex have been related to therapy-induced language improvement (Meinzer et al., 2008). In particular, better outcome after naming therapy correlates with pre-treatment activation of the left premotor cortex (BA6) (Marcotte et al., 2012). Perilesional regions in the left hemisphere could therefore be considered as trigger circuits for possible language recovery.

In contrast, right hemispheric activations found in many patients in sub-acute and chronic phase post-stroke have been highly debated as to their role for language recovery because this pattern of plasticity can also come along with some functional improvements. As a result, several models have been proposed to account for the different functional neuroplastic changes accompanying language improvements after stroke. In the hierarchical model of brain compensation strategies after stroke (Heiss & Thiel, 2006), right hemisphere areas can support some language recovery only if essential language areas of the left hemisphere are destroyed. At the same time, Saur and collaborators pointed out that the transient activation of right hemisphere networks might be necessary to achieve good recovery and normalization of left-hemisphere network activity (Saur et al., 2006). It was also found that activated regions in the right hemisphere are not all exactly homologous to the infarcted left-hemisphere regions and it has been hypothesized that some of these may indeed be beneficial to language recovery while others would be detrimental (Torres et al., 2013; Turkeltaub et al., 2011). This could account for a recent case showing clinical recovery after receiving a treatment aimed at inhibiting the right IFG, but did worsen specifically on language outcomes after suffering a subsequent stroke of the right hemisphere (Turkeltaub et al., 2012). This model would also be compatible with the studies showing links between language improvements and a re-shift of the language network to perilesional areas, in particular in the left IFG(Marcotte et al., 2012; van Oers et al., 2010).

Given these data, the therapeutic modulation of the language network activity should theoretically favour a re-shift of activity to key left hemisphere regions for optimal recovery (i.e., when these regions are relatively spared by the lesion), and/or reduce the activity of those right hemisphere areas (or “noisy nodes”, Torres et al., 2013) which are not related to a full or near complete recovery.

The role of key left hemisphere regions has been identified by investigating factors influencing language recovery. In fact, lesion location has been shown to be crucial in multiple studies (Crinion & Leff, 2007; Fridriksson, Bonilha, Baker et al., 2010; Hamilton, Chrysikou, & Coslett, 2011; Karbe et al., 1998; Postman-Caucheteux et al., 2010). More specifically, the preservation of the right IFG correlates robustly with improvements following naming therapy in chronic patients (Abel, Weiller, Huber, Willmes, & Specht, 2015; Marcotte et al., 2012). Conversely, lesions in the superior temporal gyrus (STG) are associated with poor aphasia recovery (Demeurisse et al., 1980; Hanlon, Lux, & Dromerick, 1999; Kertesz, Lau, & Polk, 1993; Parkinson, Raymer, Chang et al., 2009; Selnes, Knopman, Niccum et al., 1983), especially the posterior part of the STG (Alexander, Naeser, & Palumbo, 1990; Naeser, Helm-Estabrooks, Haas et al., 1987). Presumably because large lesions are more likely to include these regions, lesion size was repeatedly pointed out as an important predictor of language outcome in most studies (Goldenberg & Spatt, 1994; Maas et al., 2012; Mazzoni et al., 1992; Naeser, Palumbo, & Helm-Estabrooks et al., 1989; Naeser & Palumbo, 1994), but see Lazar et al. for diverging results (Lazar, Speizer, Festa et al., 2008). (For a recent and comprehensive review of factors predicting post-stroke aphasia recovery, see Watila & Balarabe, 2015). It may thus be hypothesized that a relatively spared left IFG or STG is a necessary condition for successful modulation of language network activity towards a re-shift back to the left hemisphere and for best recovery outcomes.

In contrast, the exact locations of the beneficial and noisy nodes in the right hemisphere remain to be identified. It is likely that one right hemisphere region (e.g., the right IFG) can be considered as beneficial if its left counterpart (left IFG, a key region for recovery) is destroyed or as detrimental if the latter is spared and could actually be reactivated. Further research is warranted in this regard.

6 Implication for aphasia therapy

7 Conclusion

Understanding the pathophysiological mechanism of post-stroke aphasia on a neurophysiological systems level as well as on the molecular level becomes more and more important for aphasia treatment, as the field moves from standardized therapies towards more targeted individualized treatment strategies comprising behavioural therapies as well as non-invasive brain stimulation (NIBS). It appears that at present NIBS methods have so far been more successful to modulate the brain activity of recovering language networks in a targeted fashion than any other therapeutic strategy and thus improve aphasia outcome. However to apply these methods most efficiently in combination with appropriate behavioural therapy in the future, individualized diagnostics will gain in importance to better select individual patients for appropriate therapies.

Conflict of interest

The authors report no conflicts of interest.