Taking part in a conversation requires us to extract meaning from a complex series of sounds by recognising words and phrases. We then need to decide on a response, and plan and execute the lip and tongue movements necessary to generate that response. Each of these processes – from analysing the meaning of words to producing speech – requires a distinct set of brain regions to work together. However, we know relatively little about how these regions interact with one another during specific language processes, or about what happens when key regions are damaged.

Hartwigsen et al. have now used a technique called TMS in healthy volunteers to temporarily disrupt the activity of individual brain regions with a role in language. TMS involves applying small magnetic fields to the scalp over a target brain area. The magnetic fields induce electrical currents in the underlying brain tissue and temporarily scramble its activity. Hartwigsen et al. examined how this affected the volunteers’ performance on a language task, as well as the activity of other language areas.

Temporarily disrupting a single brain region involved in analysing the meaning of words reduced the activity of multiple other areas in the brain’s language networks. The greater this reduction in activity, the more poorly the volunteers performed on a language task. However, not all brain regions showed reduced activity. Areas adjacent to the disrupted region, which normally process the sounds of words, increased their activity. This increase may have partially compensated for the effects of the TMS to help limit the language impairments.

These findings offer insights into how the brain reacts and adapts when key language areas are damaged, for example as a result of stroke. The next step is to determine the extent to which healthy brain tissue can take over from damaged regions, and whether we can target this process to improve recovery after stroke.

The current knowledge of short- and long-term plasticity in the language network after stroke-induced aphasia is limited. For instance, it is still a matter of debate if the temporary recruitment of neighbouring, ipsilateral networks and / or homologous right-hemispheric regions after a lesion of one critical node in the left hemisphere is adaptive or maladaptive for stroke recovery (Chrysikou and Hamilton, 2011; Hamilton et al., 2011). To investigate the potential for rapid short-term reorganization and flexible redistribution of the functional weight in the language network, we combined controlled, focal virtual lesions in the healthy brain with effective connectivity analyses of neuroimaging data. We relied on an experimental task that required the rapid analysis of the meaning of sound patterns (i.e., semantic processing), which is crucial for efficient every-day communication in humans.

Previous studies associated semantic processing with increased neural activation of left-hemispheric temporal, inferior frontal and inferior parietal regions (Binder et al., 2009; Vigneau et al., 2006). In particular, left angular gyrus (AG) and anterior inferior frontal gyrus (aIFG) were identified as semantic key nodes by means of focal perturbations induced with transcranial magnetic stimulation (TMS) (Devlin et al., 2003; Sliwinska et al., 2015). Specifically, several TMS studies assigned the left aIFG a central role in semantic control processes (Hoffman et al., 2010; Whitney et al., 2011). Others demonstrated that a number of temporal regions are also crucial for different semantic aspects. These regions include the anterior temporal lobe (ATL) for core semantic representations and the posterior middle temporal gyrus (pMTG) as another key node for semantic control aspects (Binney and Ralph, 2015; Davey et al., 2015; Jung and Lambon Ralph, 2016; Whitney et al., 2012).

With respect to the interactions in the semantic network, it was shown that the contribution of the left aIFG to semantic decisions crucially depends on the functional integrity of the left AG (Hartwigsen et al., 2016). Hence, left AG was able to compensate for a focal perturbation of aIFG during semantic decisions unless it was additionally perturbed with TMS, indicating a strong interaction between both regions. In contrast, TMS over neighbouring supramarginal gyrus (SMG) selectively delayed phonological decisions (i.e., decisions on the sound of words) but not semantic decisions.

While the above-cited behavioural TMS studies clearly demonstrate, besides temporal regions, a critical contribution of AG and aIFG to semantic processing, they do not allow for any conclusions on the neural underpinnings of the observed flexible redistribution in the semantic network after a focal perturbation of the AG. Moreover, the precise role of the AG in semantic processing remains elusive. For instance, this region showed increased task-related activity for words as compared to non-words or concrete relative to abstract words (Binder et al., 2009; Seghier, 2013), but deactivation for other semantic tasks, with the amount of deactivation being correlated with increased task-difficulty (Humphreys et al., 2015). Besides, the AG also contributes to other functions outside the core language domain like episodic memory and social cognitive tasks (Bzdok et al., 2016). Hence, it is unclear whether the task-related upregulation of left AG during word processing is necessary for semantic computations or rather reflects more general processes related to the level of task difficulty (Graves et al., 2017; Ralph et al., 2017).

To elucidate the brain’s ability for adaptive short-term plasticity in response to a controlled virtual lesion and the contribution of left AG to semantic processing, we applied focal continuous theta-burst stimulation (cTBS) over AG or neighbouring SMG prior to neuroimaging (Figure 1). The inclusion of a phonological task allowed us to test for the task specificity of the perturbation effect. cTBS was applied in healthy subjects to investigate immediate and transient perturbation effects. The lasting cTBS-induced suppression of neuronal excitability should give rise to an acute adaptive reorganization within the non-affected functional nodes of the network to compensate for the cTBS-induced suppression of neuronal activity (Siebner and Rothwell, 2003).

Figure 1

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We expected to find a functional double dissociation of cTBS over AG vs. SMG on semantic vs. phonological decisions. Specifically, cTBS over AG should selectively inhibit task-related semantic activity at the targeted left AG, which might in turn lead to an upregulation of other important nodes in the semantic network (e.g. left aIFG, pMTG or ATL). Since our previous behavioural study (Hartwigsen et al., 2016) did not find a significant modulation of semantic response speed with a unifocal perturbation of AG, we did not expect any significant disruption of mean semantic response speed after cTBS of AG. However, in accordance with the previous study, cTBS of SMG should delay phonological decisions, which might be reflected in the suppression of task-related activity in the phonological network.

As an alternative hypothesis, cTBS might also affect neural activity on a larger network level. Indeed, combined TMS-fMRI studies often reveal widespread stimulation effects, involving neighbouring and distant interconnected brain regions (Bestmann et al., 2003). If this were the case, then we would expect that cTBS over AG should decrease neural activity not only at the stimulated site itself, but in a larger semantic network.

As cognitive processes are mediated by the dynamic interactions among relevant areas rather than by isolated regions, effective connectivity analyses that capture perturbation effects on the causal network level should be more closely related to the neurobiological mechanisms by which a (virtual) lesion changes a cognitive function (Hartwigsen et al., 2015). Such network effects might also mediate possible cTBS-induced changes on the behavioural level.

This study demonstrates functionally specific reorganization in the healthy semantic network after focal perturbation of a semantic key region. Our main novel finding was that cTBS over AG significantly decreased task-specific neural activity in a larger network of semantic regions, including the stimulated AG and left aIFG. Moreover, semantic suppression induced upregulation in neighbouring phonological regions that might have partially compensated for the disruptive effect on semantic decisions. In contrast, cTBS over SMG selectively affected phonological decisions, leading to decreased neural activity at the stimulated site and other phonological regions without any upregulation of the semantic network, as well as a significant delay in response speed. The observed functional-anatomical double dissociation during semantic vs. phonological decisions supports the notion that both processes are subserved by different networks (Hartwigsen et al., 2016) and suggests that these networks might differ in their potential to partially compensate for a focal disruption. The distinct contribution of AG and SMG to semantic and phonological decisions was further supported by their differential engagement in these processes after sham cTBS and by the respective differential task comparisons.

Notably, the task-specific perturbation effect in the semantic network was underpinned by a strong increase in the inhibitory influence from AG to aIFG, which predicted an individual delay in semantic performance after cTBS. In particular, individual response speed was prolonged as the inhibitory influence from left AG to aIFG increased. These findings suggest that a focal perturbation over a semantic key region can induce large-scale inhibitory effects on the network level. This provides new insight into the strong modulatory potential of cTBS. Probabilistic fiber tracking revealed that this effect was most probably mediated via anatomical long-distance connections that are part of the ventral association fibre system that was previously associated with semantic processing (Bajada et al., 2015).

We did not find a significant change in the mean semantic response speed after AG cTBS. However, a trend towards delayed semantic response speed with cTBS over AG indicated that this region contributes to semantic processing. We speculate that the relatively weak effect of AG cTBS on semantic decisions might be explained by the upregulation of the neighbouring phonological network that might have helped to maintain task processing. Indeed, the subject-specific degree of AG suppression after cTBS predicted the individual upregulation of neighbouring SMG. These results suggest that a topographically adjacent, yet functionally separate network may have the potential to partially support processing after disruption of a strategic key region in the language system. This interpretation is in line with our finding that the individual delay in semantic performance was correlated with the upregulation of the SMG after cTBS over AG. We conclude that a stronger individual disruption of the semantic network required a stronger contribution of the SMG to maintain task function. Together, our findings may show the inherent potential of the language system to flexibly recruit neighbouring regions, thus providing new insight in the dynamic regulation of intrahemispheric interactions in two functionally segregated processing streams. Specifically, the differential behavioural effects of cTBS over AG and SMG during semantic and phonological decisions suggest that lower-level resources like phonological working memory capacities (Nixon et al., 2004; Romero et al., 2006) might be recruited to partially contribute to higher-level semantic tasks to preserve task processing, but not the other way round. To the contrary, we observed a strong perturbation effect of SMG cTBS on task-related phonological activity and behaviour but no upregulation of semantic regions.

As an equally plausible alternative explanation, AG perturbation might have increased the overall task demands, thereby necessitating the contribution of more general executive control regions. Indeed, the upregulation of left SMG after cTBS of AG extended into the intraparietal sulcus (IPS) and superior parietal lobe (SPL) that were previously associated with executively demanding tasks (Humphreys et al., 2015) and are part of a multi-domain control system (Duncan, 2010; Whitney et al., 2012). Hence, AG perturbation might have increased the overall task demands, thereby requiring the contribution of these regions. In contrast, the strong perturbation effect on the phonological task after cTBS over SMG might be explained by the fact that (higher-level) semantic regions were not able to support task processing after disruption of the control network.

With respect to the role of the observed regions in semantic processing, both AG and aIFG were associated with executive control over semantic processing, although to a different degree (Noonan et al., 2013). Left AG corresponds to a high-level cross-modal convergence zone for concept retrieval and the integration of meaning and event representations and provides access to semantics (Binder et al., 2009). In particular, the ventral AG (overlapping with our stimulation site) was associated with automatic semantic retrieval, while a more dorsal subregion within the AG was assigned a role in controlled semantic retrieval (Noonan et al., 2013). aIFG, on the other hand, is an important node for top-down control during semantic processing and lexical retrieval (Whitney et al., 2012). Consequently, the observed network effect in our study might indicate that disruption of AG induced a functional disconnection by impairing the transfer of stimulus related activity from AG to aIFG, thereby necessitating the contribution of more domain-general resources under semantic conditions with increased task difficulty. However, the precise role of the AG in semantic processing remains a conundrum. A recent meta-analysis showed that most semantic tasks deactivate the core AG and rather activate neighbouring intraparietal sulcus (among other regions) (Humphreys et al., 2015). On the other hand, left AG is clearly engaged by non-semantic domains such as memory and social cognition (Bzdok et al., 2016; Humphreys et al., 2015). Its precise contribution in semantic processing thus remains elusive. In our study, the semantic task might have particularly engaged semantic working memory processes that contributed to the observed positive AG activation (Vigneau et al., 2006).

We believe that our results are noteworthy for several reasons. First, they implicate that the effects of a focal perturbation are not restricted to the stimulated area itself but might rather affect a larger network (see Bestmann et al., 2003). Specifically, our data indicate that remote effects may occur in distant cognitive network nodes. Notably, the strong modulation of task-specific activity patterns in the absence of a significant disruption of the mean semantic response speed after AG cTBS indicates that behavioural measures alone might not be sufficient to map a cTBS-induced perturbation effect. Rather, some modulatory effects induced by non-invasive brain stimulation might only be captured on the neural network level and most likely originate from a modulation of the effective connectivity in a network. These results provide new insight into the neural mechanisms of the perturbation effect. Indeed, our winning model revealed a positive intrinsic connection between AG and aIFG, indicating that without cTBS, there might be a (weak) facilitatory connectivity between both regions that turned into a strong inhibition after cTBS. The individual magnitude of the induced inhibitory drive between AG and aIFG was able to predict the individual delay in semantic response speed after AG cTBS, demonstrating the functional relevance of this effect.

Secondly, the observed upregulation of a neighbouring parieto-frontal network for phonological processing might indicate some degree of degeneracy (Price and Friston, 2002) in the language network that might have partly enabled cross-modal compensation even after inhibition of a large part of the semantic network. This is compatible with the notion that cTBS may give rise to an acute adaptive reorganization within the non-targeted functional loops of another network to compensate for the cTBS-induced suppression of task-specific neuronal activity (Hartwigsen and Siebner, 2012).

The observed greater resilience of the semantic relative to the phonological network against the behavioural lesion effect was underpinned by a difference in the flexible recruitment of neighbouring networks that was selectively observed for the semantic task. These findings are in line with previous behavioural results that a single perturbation of one semantic node did not affect semantic decisions, while phonological decisions were already impaired after perturbation of one key region (Hartwigsen et al., 2016). The difference in the flexible recruitment of neighbouring networks for semantic and phonological processes likely reflects the engagement of higher- vs. lower-level processes in both tasks. Indeed, our optimal DCM identified the SMG as the most likely source of the driving input among the selected regions. This indicates that left AG receives information from the neighbouring SMG, which is compatible with the above-discussed role of the AG as a heteromodal integration area (Seghier, 2013). This might explain the absence of any upregulation of the semantic system during phonological processing after cTBS over SMG, as processing was already disrupted at a lower level. Interestingly, disruption of this lower-level region was not sufficient to significantly affect semantic task processing.

We initially hypothesized that the virtual lesion of the AG might lead to an upregulation of other semantic key nodes. However, this is not consistent with the observed strong remote effects of cTBS. It is worth noting that few imaging studies have investigated short-term plasticity on the neural-network level in the healthy language network to date (Binney and Ralph, 2015; Hallam et al., 2016; Hartwigsen et al., 2013; Jung and Lambon Ralph, 2016). Some of these studies (Binney and Ralph, 2015; Hartwigsen et al., 2013; Jung and Lambon Ralph, 2016) reported increased task-related activity of the right-hemispheric homologue after perturbation of a left-hemispheric key region for speech or language that was interpreted as adaptive short-term compensation. Another study (Hallam et al., 2016) found that perturbation of left IFG increased the activation of left pMTG during the processing of weak semantic associations, demonstrating that compensation can also occur between different semantic nodes within the same left hemispheric network. Moreover, Jung and Lambon Ralph, 2016 showed that after cTBS over left ATL, the right ATL increased its intrinsic facilitatory influence on left ATL, indicating a flexible, bilateral organization of the semantic system with a strong degree of adaptive plasticity.

In contrast to the above cited studies, we did not observe an upregulation of other left-hemispheric semantic areas or homologous right-hemispheric regions. When lowering the threshold, neural activity in right AG was also decreased after cTBS of left AG, indicating a strong cTBS-induced inhibition in the semantic network. This suggests that left AG is a strategic core region for semantic processes, a notion that is compatible with the key role of the AG in all aspects of semantic processing that require concept retrieval (Binder et al., 2009; Seghier, 2013), including efficient retrieval of semantic information (Davey et al., 2015).

Together, the previous findings and our results demonstrate the potential for a flexible recruitment after disruption of a semantic key node that may include regions within the same left-hemispheric network, as well as contralateral homologous regions or neighbouring regions from a different network. The exact recruitment may depend on the degree of the disruption and the specific task demands.

Our findings have implications for the interpretation of reorganization effects in the lesioned language network. The upregulation of neighbouring regions outside the core semantic network shows that aside from the specific contributions of a specialized network, neighbouring networks might also be beneficially recruited. In this context, our finding of a positive intrinsic connection between AG and neighbouring SMG during semantic processing argues against the possible alternative explanation of the observed upregulation of SMG in terms of disinhibition. Our findings are more compatible with the notion of an adaptive contribution of ipsilateral regions after a lesion of a strategic left-hemispheric area (Heiss and Thiel, 2006), rather than supporting the concept of maladaptive plasticity after a release from the inhibition of neighbouring regions.

Indeed, previous studies on post-stroke aphasia suggest that the upregulation of ipsi- vs. contralateral regions after stroke might depend on the site, size and extent of the lesion (Chrysikou and Hamilton, 2011). Models of language recovery proposed that for smaller lesions of critical left-hemispheric language nodes, neighbouring perilesional regions might be adaptively recruited to subserve language function while more severe impairments might stronger draw on recruitment of homotopic regions (Hamilton et al., 2011). Our results show that even a relatively focal perturbation can already inhibit neural activity in a large network. In our case, the recruitment of neighbouring areas seems to be related to a high level of adaptation (i.e., the absence of a strong behavioural effect), indicating a general flexibility of brain networks in terms of distributed processing.

In summary, our results shed important new light on the dynamic regulation of intrahemispheric interactions in the healthy human brain that are highly relevant for a variety of cognitive processes. This is of potential relevance for understanding language recovery after left hemisphere stroke, indicating that neighbouring networks might bear the inherent potential to partially support task processing after a strategic lesion of one key region. Our results help to unravel neural mechanisms of perturbation effects, indicating that cTBS not only influences neural activity in the stimulated region but also in remote areas. Although the observed effects were transient, they were sufficient to influence task-related activity, connectivity, and behaviour, as evidenced by the significant correlation between individual connectivity strength and delay in response speed. This demonstrates the value of combining TMS with effective connectivity analyses of fMRI data to map the neural consequences of a focal perturbation and might further inform models of language reorganization in post-stroke aphasia.

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Author details

1. Gesa Hartwigsen

   1. Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Leipzig, Germany
   2. Language and Aphasia Laboratory, Department of Neurology, University of Leipzig, Leipzig, Germany

   Contribution

   GH, Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Investigation, Methodology, Writing—original draft, Project administration, Writing—review and editing

   For correspondence

   hartwigsen@cbs.mpg.de

   Competing interests

   The authors declare that no competing interests exist.

   "This ORCID iD identifies the author of this article:" 0000-0002-8084-1330

2. Danilo Bzdok

   1. Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen, Aachen, Germany
   2. JARA-BRAIN, Jülich-Aachen Research Alliance, Germany
   3. Parietal team, INRIA, Neurospin, bat 145, CEA Saclay, Gif-sur-Yvette, France

   Contribution

   DB, Data curation, Formal analysis, Methodology, Writing—review and editing

   Competing interests

   The authors declare that no competing interests exist.

   "This ORCID iD identifies the author of this article:" 0000-0003-3466-6620

3. Maren Klein

   Language and Aphasia Laboratory, Department of Neurology, University of Leipzig, Leipzig, Germany

   Contribution

   MK, Data curation, Formal analysis

   Competing interests

   The authors declare that no competing interests exist.

4. Max Wawrzyniak

   Language and Aphasia Laboratory, Department of Neurology, University of Leipzig, Leipzig, Germany

   Contribution

   MW, Data curation, Formal analysis

   Competing interests

   The authors declare that no competing interests exist.

5. Anika Stockert

   Language and Aphasia Laboratory, Department of Neurology, University of Leipzig, Leipzig, Germany

   Contribution

   AS, Data curation, Formal analysis, Visualization

   Competing interests

   The authors declare that no competing interests exist.

6. Katrin Wrede

   Language and Aphasia Laboratory, Department of Neurology, University of Leipzig, Leipzig, Germany

   Contribution

   KW, Data curation

   Competing interests

   The authors declare that no competing interests exist.

7. Joseph Classen

   Human Cortical Physiology and Motor Control Laboratory, Department of Neurology, University of Leipzig, Leipzig, Germany

   Contribution

   JC, Conceptualization, Writing—review and editing

   Competing interests

   The authors declare that no competing interests exist.

8. Dorothee Saur

   Language and Aphasia Laboratory, Department of Neurology, University of Leipzig, Leipzig, Germany

   Contribution

   DS, Conceptualization, Writing—review and editing

   Competing interests

   The authors declare that no competing interests exist.

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