Causal evidence for a coordinated temporal interplay within the language network.

Recent neurobiological models on language suggest that auditory sentence comprehension is supported by a coordinated temporal interplay within a left-dominant brain network, including the posterior inferior frontal gyrus (pIFG), posterior superior temporal gyrus and sulcus (pSTG/STS), and angular gyrus (AG). Here, we probed the timing and causal relevance of the interplay between these regions by means of concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG). Our TMS-EEG experiments reveal region- and time-specific causal evidence for a bidirectional information flow from left pSTG/STS to left pIFG and back during auditory sentence processing. Adapting a condition-and-perturb approach, our findings further suggest that the left pSTG/STS can be supported by the left AG in a state-dependent manner.

Differential contributions of inferior frontal gyrus subregions to sentence processing guided by intonation.

Auditory sentence comprehension involves processing content (semantics), grammar (syntax), and intonation (prosody). The left inferior frontal gyrus (IFG) is involved in sentence comprehension guided by these different cues, with neuroimaging studies preferentially locating syntactic and semantic processing in separate IFG subregions. However, this regional specialisation has not been confirmed with a neurostimulation method. Consequently, the causal role of such a specialisation remains unclear. This study probed the role of the posterior IFG (pIFG) for syntactic processing and the anterior IFG (aIFG) for semantic processing with repetitive transcranial magnetic stimulation (rTMS) in a task that required the interpretation of the sentence's prosodic realisation. Healthy participants performed a sentence completion task with syntactic and semantic decisions, while receiving 10 Hz rTMS over either left aIFG, pIFG, or vertex (control). Initial behavioural analyses showed an inhibitory effect on accuracy without task-specificity. However, electric field simulations revealed differential effects for both subregions. In the aIFG, stronger stimulation led to slower semantic processing, with no effect of pIFG stimulation. In contrast, we found a facilitatory effect on syntactic processing in both aIFG and pIFG, where higher stimulation strength was related to faster responses. Our results provide first evidence for the functional relevance of left aIFG in semantic processing guided by intonation. The stimulation effect on syntactic responses emphasises the importance of the IFG for syntax processing, without supporting the hypothesis of a pIFG-specific involvement. Together, the results support the notion of functionally specialised IFG subregions for diverse but fundamental cues for language processing.

Task-specific network interactions across key cognitive domains.

Human cognition is organized in distributed networks in the brain. Although distinct specialized networks have been identified for different cognitive functions, previous work also emphasizes the overlap of key cognitive domains in higher level association areas. The majority of previous studies focused on network overlap and dissociation during resting states whereas task-related network interactions across cognitive domains remain largely unexplored. A better understanding of network overlap and dissociation during different cognitive tasks may elucidate flexible (re-)distribution of resources during human cognition. The present study addresses this issue by providing a broad characterization of large-scale network dynamics in three key cognitive domains. Combining prototypical tasks of the larger domains of attention, language, and social cognition with whole-brain multivariate activity and connectivity approaches, we provide a spatiotemporal characterization of multiple large-scale, overlapping networks that differentially interact across cognitive domains. We show that network activity and interactions increase with increased cognitive complexity across domains. Interaction patterns reveal a common core structure across domains as well as dissociable domain-specific network activity. The observed patterns of activation and deactivation of overlapping and strongly coupled networks provide insight beyond region-specific activity within a particular cognitive domain toward a network perspective approach across diverse key cognitive functions.

Efficient high-resolution TMS mapping of the human motor cortex by nonlinear regression.

Transcranial magnetic stimulation (TMS) is a powerful tool to investigate causal structure-function relationships in the human brain. However, a precise delineation of the effectively stimulated neuronal populations is notoriously impeded by the widespread and complex distribution of the induced electric field. Here, we propose a method that allows rapid and feasible cortical localization at the individual subject level. The functional relationship between electric field and behavioral effect is quantified by combining experimental data with numerically modeled fields to identify the cortical origin of the modulated effect. Motor evoked potentials (MEPs) from three finger muscles were recorded for a set of random stimulations around the primary motor area. All induced electric fields were nonlinearly regressed against the elicited MEPs to identify their cortical origin. We could distinguish cortical muscle representation with high spatial resolution and localized them primarily on the crowns and rims of the precentral gyrus. A post-hoc analysis revealed exponential convergence of the method with the number of stimulations, yielding a minimum of about 180 random stimulations to obtain stable results. Establishing a functional link between the modulated effect and the underlying mode of action, the induced electric field, is a fundamental step to fully exploit the potential of TMS. In contrast to previous approaches, the presented protocol is particularly easy to implement, fast to apply, and very robust due to the random coil positioning and therefore is suitable for practical and clinical applications.

A novel approach to localize cortical TMS effects.

Despite the widespread use of transcranial magnetic stimulation (TMS), the precise cortical locations underlying the resulting physiological and behavioral effects are still only coarsely known. To date, mapping strategies have relied on projection approaches (often termed "center of gravity" approaches) or maximum electric field value evaluation, and therefore localize the stimulated cortical site only approximately and indirectly. Focusing on the motor cortex, we present and validate a novel method to reliably determine the effectively stimulated cortical site at the individual subject level. The approach combines measurements of motor evoked potentials (MEPs) at different coil positions and orientations with numerical modeling of induced electric fields. We identify sharply bounded cortical areas, around the gyral crowns and rims of the motor hand area, as the origin of MEPs and show that the magnitude of the tangential component and the overall magnitude of the electric field are most relevant for the observed effect. To validate our approach, we identified the coil location and orientation that produces the maximal electric field at the predicted stimulation site, and then experimentally show that this location produces MEPs more efficiently than other tested locations/orientations. Moreover, we used extensive uncertainty and sensitivity analyses to verify the robustness of the method and identify the most critical model parameters. Our generic approach improves the localization of the cortical area effectively stimulated by TMS and may be transferred to other modalities such as language mapping.

Revisiting the focality of non-invasive brain stimulation - Implications for studies of human cognition.

Non-invasive brain stimulation techniques are popular tools to investigate brain function in health and disease. Although transcranial magnetic stimulation (TMS) is widely used in cognitive neuroscience research to probe causal structure-function relationships, studies often yield inconclusive results. To improve the effectiveness of TMS studies, we argue that the cognitive neuroscience community needs to revise the stimulation focality principle - the spatial resolution with which TMS can differentially stimulate cortical regions. In the motor domain, TMS can differentiate between cortical muscle representations of adjacent fingers. However, this high degree of spatial specificity cannot be obtained in all cortical regions due to the influences of cortical folding patterns on the TMS-induced electric field. The region-dependent focality of TMS should be assessed a priori to estimate the experimental feasibility. Post-hoc simulations allow modeling of the relationship between cortical stimulation exposure and behavioral modulation by integrating data across stimulation sites or subjects.

No effects of 1 Hz offline TMS on performance in the stop-signal game.

Stopping an already initiated action is crucial for human everyday behavior and empirical evidence points toward the prefrontal cortex playing a key role in response inhibition. Two regions that have been consistently implicated in response inhibition are the right inferior frontal gyrus (IFG) and the more superior region of the dorsolateral prefrontal cortex (DLPFC). The present study investigated the effect of offline 1 Hz transcranial magnetic stimulation (TMS) over the right IFG and DLPFC on performance in a gamified stop-signal task (SSG). We hypothesized that perturbing each area would decrease performance in the SSG, albeit with a quantitative difference in the performance decrease after stimulation. After offline TMS, functional short-term reorganization is possible, and the domain-general area (i.e., the right DLPFC) might be able to compensate for the perturbation of the domain-specific area (i.e., the right IFG). Results showed that 1 Hz offline TMS over the right DLPFC and the right IFG at 110% intensity of the resting motor threshold had no effect on performance in the SSG. In fact, evidence in favor of the null hypothesis was found. One intriguing interpretation of this result is that within-network compensation was triggered, canceling out the potential TMS effects as has been suggested in recent theorizing on TMS effects, although the presented results do not unambiguously identify such compensatory mechanisms. Future studies may result in further support for this hypothesis, which is especially important when studying reactive response in complex environments.

Precise motor mapping with transcranial magnetic stimulation.

We describe a routine to precisely localize cortical muscle representations within the primary motor cortex with transcranial magnetic stimulation (TMS) based on the functional relation between induced electric fields at the cortical level and peripheral muscle activation (motor-evoked potentials; MEPs). Besides providing insights into structure-function relationships, this routine lays the foundation for TMS dosing metrics based on subject-specific cortical electric field thresholds. MEPs for different coil positions and orientations are combined with electric field modeling, exploiting the causal nature of neuronal activation to pinpoint the cortical origin of the MEPs. This involves constructing an individual head model using magnetic resonance imaging, recording MEPs via electromyography during TMS and computing the induced electric fields with numerical modeling. The cortical muscle representations are determined by relating the TMS-induced electric fields to the MEP amplitudes. Subsequently, the coil position to optimally stimulate the origin of the identified cortical MEP can be determined by numerical modeling. The protocol requires 2 h of manual preparation, 10 h for the automated head model construction, one TMS session lasting 2 h, 12 h of computational postprocessing and an optional second TMS session lasting 30 min. A basic level of computer science expertise and standard TMS neuronavigation equipment suffices to perform the protocol.

Modeling the effects of transcranial magnetic stimulation on spatial attention.

Objectives. Transcranial magnetic stimulation (TMS) has been widely used to modulate brain activity in healthy and diseased brains, but the underlying mechanisms are not fully understood. Previous research leveraged biophysical modeling of the induced electric field (E-field) to map causal structure-function relationships in the primary motor cortex. This study aims at transferring this localization approach to spatial attention, which helps to understand the TMS effects on cognitive functions, and may ultimately optimize stimulation schemes.Approach. Thirty right-handed healthy participants underwent a functional magnetic imaging (fMRI) experiment, and seventeen of them participated in a TMS experiment. The individual fMRI activation peak within the right inferior parietal lobule (rIPL) during a Posner-like attention task defined the center target for TMS. Thereafter, participants underwent 500 Posner task trials. During each trial, a 5-pulse burst of 10 Hz repetitive TMS (rTMS) was given over the rIPL to modulate attentional processing. The TMS-induced E-fields for every cortical target were correlated with the behavioral modulation to identify relevant cortical regions for attentional orientation and reorientation.Main results. We did not observe a robust correlation between E-field strength and behavioral outcomes, highlighting the challenges of transferring the localization method to cognitive functions with high neural response variability and complex network interactions. Nevertheless, TMS selectively inhibited attentional reorienting in five out of seventeen subjects, resulting in task-specific behavioral impairments. The BOLD-measured neuronal activity and TMS-evoked neuronal effects showed different patterns, which emphasizes the principal distinction between the neural activity being correlated with (or maybe even caused by) particular paradigms, and the activity of neural populations exerting a causal influence on the behavioral outcome.Significance. This study is the first to explore the mechanisms of TMS-induced attentional modulation through electrical field modeling. Our findings highlight the complexity of cognitive functions and provide a basis for optimizing attentional stimulation protocols.

Online neurostimulation of Broca's area does not interfere with syntactic predictions: A combined TMS-EEG approach to basic linguistic combination.

Categorical predictions have been proposed as the key mechanism supporting the fast pace of syntactic composition in language. Accordingly, grammar-based expectations are formed-e.g., the determiner "a" triggers the prediction for a noun-and facilitate the analysis of incoming syntactic information, which is then checked against a single or few other word categories. Previous functional neuroimaging studies point towards Broca's area in the left inferior frontal gyrus (IFG) as one fundamental cortical region involved in categorical prediction during incremental language processing. Causal evidence for this hypothesis is however still missing. In this study, we combined Electroencephalography (EEG) and Transcranial Magnetic Stimulation (TMS) to test whether Broca's area is functionally relevant in predictive mechanisms for language. We transiently perturbed Broca's area during the first word in a two-word construction, while simultaneously measuring the Event-Related Potential (ERP) correlates of syntactic composition. We reasoned that if Broca's area is involved in predictive mechanisms for syntax, disruptive TMS during the first word would mitigate the difference in the ERP responses for predicted and unpredicted categories in basic two-word constructions. Contrary to this hypothesis, perturbation of Broca's area at the predictive stage did not affect the ERP correlates of basic composition. The correlation strength between the electrical field induced by TMS and the ERP responses further confirmed this pattern. We discuss the present results considering an alternative account of the role of Broca's area in syntactic composition, namely the bottom-up integration of words into constituents, and of compensatory mechanisms within the language predictive network.

Functional specialization within the inferior parietal lobes across cognitive domains.

The inferior parietal lobe (IPL) is a key neural substrate underlying diverse mental processes, from basic attention to language and social cognition, that define human interactions. Its putative domain-global role appears to tie into poorly understood differences between cognitive domains in both hemispheres. Across attentional, semantic, and social cognitive tasks, our study explored functional specialization within the IPL. The task specificity of IPL subregion activity was substantiated by distinct predictive signatures identified by multivariate pattern-learning algorithms. Moreover, the left and right IPL exerted domain-specific modulation of effective connectivity among their subregions. Task-evoked functional interactions of the anterior and posterior IPL subregions involved recruitment of distributed cortical partners. While anterior IPL subregions were engaged in strongly lateralized coupling links, both posterior subregions showed more symmetric coupling patterns across hemispheres. Our collective results shed light on how under-appreciated hemispheric specialization in the IPL supports some of the most distinctive human mental capacities.