Task-Dependent Functional and Effective Connectivity during Conceptual Processing

Impact of data processing varieties on DCM estimates of effective connectivity from task-fMRI

Effective connectivity (EC) refers to directional or causal influences between interacting neuronal populations or brain regions and can be estimated from functional magnetic resonance imaging (fMRI) data via dynamic causal modeling (DCM). In contrast to functional connectivity, the impact of data processing varieties on DCM estimates of task-evoked EC has hardly ever been addressed. We therefore investigated how task-evoked EC is affected by choices made for data processing. In particular, we considered the impact of global signal regression (GSR), block/event-related design of the general linear model (GLM) used for the first-level task-evoked fMRI analysis, type of activation contrast, and significance thresholding approach. Using DCM, we estimated individual and group-averaged task-evoked EC within a brain network related to spatial conflict processing for all the parameters considered and compared the differences in task-evoked EC between any two data processing conditions via between-group parametric empirical Bayes (PEB) analysis and Bayesian data comparison (BDC). We observed strongly varying patterns of the group-averaged EC depending on the data processing choices. In particular, task-evoked EC and parameter certainty were strongly impacted by GLM design and type of activation contrast as revealed by PEB and BDC, respectively, whereas they were little affected by GSR and the type of significance thresholding. The event-related GLM design appears to be more sensitive to task-evoked modulations of EC, but provides model parameters with lower certainty than the block-based design, while the latter is more sensitive to the type of activation contrast than is the event-related design. Our results demonstrate that applying different reasonable data processing choices can substantially alter task-evoked EC as estimated by DCM. Such choices should be made with care and, whenever possible, varied across parallel analyses to evaluate their impact and identify potential convergence for robust outcomes.

Experiential grounding of abstract concepts: Processing of abstract mental state concepts engages brain regions involved in mentalizing, automatic speech, and lip movements

concepts like mental state concepts lack a physical referent, which can be directly perceived. Classical theories therefore claim that abstract concepts require amodal representations detached from experiential brain systems. However, grounded cognition approaches suggest an involvement of modal experiential brain regions in the processing of abstract concepts. In the present functional magnetic resonance imaging study, we investigated the relation of the processing of abstract mental state concepts to modal experiential brain systems in a fine-grained fashion. Participants performed lexical decisions on abstract mental state as well as on verbal association concepts as control category. Experiential brain systems related to the processing of mental states, generating verbal associations, automatic speech as well as hand and lip movements were determined by corresponding localizer tasks. Processing of abstract mental state concepts neuroanatomically overlapped with activity patterns associated with processing of mental states, generating verbal associations, automatic speech and lip movements. Hence, mental state concepts activate the mentalizing brain network, complemented by perceptual-motor brain regions involved in simulation of visual or action features associated with social interactions, linguistic brain regions as well as face-motor brain regions recruited for articulation. The present results provide compelling evidence for the rich grounding of abstract mental state concepts in experiential brain systems related to mentalizing, verbal communication and mouth action.

The influence of sentence focus on motor system activity in language comprehension and its temporal dynamics: Preliminary evidence from sEMG

Previous research has shown that individual experiences and experimental tasks can influence the occurrence of mental simulation during sentence comprehension. However, little research has focused on the effect of sentence focus on mental simulation and its temporal dynamics. Sentence focus refers to the hierarchical structure of information within a sentence, where focused information represents the most prominent and essential information. In contrast, nonfocused information provides a background for the focused information. The present study investigated whether sentence focus would affect the activity of the motor system in language comprehension and at which stage the effect of sentence focus occurred. We measured spontaneous arm muscle electrical activity by surface electromyography (sEMG) while participants read action-focused, nonaction-focused, and control sentences. We observed greater spontaneous muscle electrical activity in the flexor common muscle of the fingers when participants read action-focused sentences compared to nonaction-focused and control sentences. Additionally, there was an interactive trend between sentence type and time, spontaneous muscle electrical activity while reading action-focused sentences was observed in both early (1 ms to 300 ms after the presentation of the action phrase) and late time windows (901 ms to 1500 ms after the action phrase). The findings suggest that the motor system exhibits flexible engagement during language comprehension and the impact of sentence focus on motor system activity may be throughout both the lexical-semantic retrieval and sentence-meaning integration stages.

Disrupted network interactions serve as a neural marker of dyslexia

Dyslexia, a frequent learning disorder, is characterized by severe impairments in reading and writing and hypoactivation in reading regions in the left hemisphere. Despite decades of research, it remains unclear to date if observed behavioural deficits are caused by aberrant network interactions during reading and whether differences in functional activation and connectivity are directly related to reading performance. Here we provide a comprehensive characterization of reading-related brain connectivity in adults with and without dyslexia. We find disrupted functional coupling between hypoactive reading regions, especially between the left temporo-parietal and occipito-temporal cortices, and an extensive functional disruption of the right cerebellum in adults with dyslexia. Network analyses suggest that individuals with dyslexia process written stimuli via a dorsal decoding route and show stronger reading-related interaction with the right cerebellum. Moreover, increased connectivity within networks is linked to worse reading performance in dyslexia. Collectively, our results provide strong evidence for aberrant task-related connectivity as a neural marker for dyslexia that directly impacts behavioural performance. The observed differences in activation and connectivity suggest that one effective way to alleviate reading problems in dyslexia is through modulating interactions within the reading network with neurostimulation methods.

Adaptive short-term plasticity in the typical reading network

The left temporo-parietal cortex (TPC) is crucial for phonological decoding, i.e., for learning and retaining sound-letter mappings, and appears hypoactive in dyslexia. Here, we tested the causal contribution of this area for reading in typical readers with transcranial magnetic stimulation (TMS) and explored the reading network's response with fMRI. By investigating the underlying neural correlates of stimulation-induced modulations of the reading network, we can help improve targeted interventions for individuals with dyslexia. 28 typical adult readers overtly read simple and complex words and pseudowords during fMRI after effective and sham TMS over the left TPC. To explore differences in functional activation and effective connectivity within the reading network, we performed univariate and multivariate analyses, as well as dynamic causal modeling. While TMS-induced effects on reading performance and brain activation showed large individual variability, multivariate analyses revealed a shift in activation in the left inferior frontal cortex for pseudoword reading after effective TMS. Furthermore, TMS increased effective connectivity from the left ventral occipito-temporal cortex to the left TPC. In the absence of effects on reading performance, the observed changes in task-related activity and the increase in functional coupling between the two core reading nodes suggest successful short-term compensatory reorganization in the reading network following TMS-induced disruption. This study is the first to explore neurophysiological changes induced by TMS to a core reading node in typical readers while performing an overt reading task. We provide evidence for remote stimulation effects and emphasize the relevance of functional interactions in the reading network.

Cognitive inflexibility is linked to abnormal frontoparietal-related activation and connectivity in obsessive-compulsive disorder

Although it was acknowledged that patients with obsessive-compulsive disorder (OCD) would exhibit cognitive inflexibility, the underlying neural mechanism has not been fully clarified. Therefore, this study aimed to investigate the neural substrates involved in cognitive inflexibility among individuals with OCD. A total of 42 patients with OCD and 48 healthy controls (HCs) completed clinical assessment and functional magnetic resonance imaging (fMRI) data collection during cued task switching. Behavioral performances and fMRI activation were compared between the OCD group and the HC group. Psychophysiological interactions (PPIs) analyses were applied to explore functional connectivity related to task switching. Pearson correlation was used to investigate the relationships among behavioral performance, fMRI activity, and obsessive-compulsive symptoms in OCD. The OCD group had a greater switch cost than HCs (χ2  = 5.89, p < .05). A significant difference in reaction time was found during switch (χ2  = 17.72, p < .001) and repeat (χ2  = 16.60, p = .018) between the two groups, while there was no significant difference in group accuracy. Comparison of group differences showed that the OCD group had increased activation in the right superior parietal cortex (rSPL) during task switching, and exhibited increased connectivity of frontoparietal network/default mode network (FPN-DMN; i.e., middle frontal gyrus [MFG]/inferior parietal cortex-precuneus, MFG-middle/posterior cingulate gyrus) and within the FPN (inferior parietal cortex-postcentral gyrus). In the OCD group, the compulsion score was positively correlated with accuracy during switch (r = .405, p = .008, FDRq <.05), and negatively correlated with activation of rSPL (r = -.328, p = .034, FDRq >.05). Patients with OCD had impaired cognitive flexibility and cautious response strategy. The neural mechanism of cognitive inflexibility in OCD may involve increased activation in the rSPL, as well as hyperconnectivity within the FPN and between the FPN and DMN.

Grounded Cognition Entails Linguistic Relativity: A Neglected Implication of a Major Semantic Theory

According to the popular Grounded Cognition Model (GCM), the sensory and motor features of concepts, including word meanings, are stored directly within neural systems for perception and action. More precisely, the core claim is that these concrete conceptual features reuse some of the same modality-specific representations that serve to categorize experiences involving the relevant kinds of objects and events. Research in semantic typology, however, has shown that word meanings vary significantly across the roughly 6500 languages in the world. I argue that this crosslinguistic semantic diversity has significant yet previously unrecognized theoretical consequences for the GCM. In particular, to accommodate the typological data, the GCM must assume that the concrete features of word meanings are not merely stored within sensory/motor brain systems, but are represented there in ways that are, to a nontrivial degree, language-specific. Moreover, it must assume that these conceptual representations are also activated during the nonlinguistic processing of the relevant kinds of objects and events (e.g., during visual perception and action planning); otherwise, they would not really be grounded, which is to say, embedded inside sensory/motor systems. Crucially, however, such activations would constitute what is traditionally called linguistic relativity-that is, the influence of language-specific semantic structures on other forms of cognition. The overarching aim of this paper is to elaborate this argument more fully and explore its repercussions. To that end, I discuss in greater detail the key aspects of the GCM, the evidence for crosslinguistic semantic diversity, pertinent work on linguistic relativity, the central claim that the GCM entails linguistic relativity, some initial supporting results, and some important limitations and future directions.

Concepts require flexible grounding

Research on semantic memory has a problem. On the one hand, a robust body of evidence implicates sensorimotor regions in conceptual processing. On the other hand, a different body of evidence implicates a modality independent semantic system. The standard solution to this tension is to posit a hub-and-spoke system with modality independent hubs and modality specific spokes. In this paper, I argue in support of an alternative view of grounding which remains committed to neural reenactment but emphasizes the multimodal and multilevel nature of the semantic system. This view is built upon the recognition that abstraction is a design feature of concepts. Semantic memory employs hierarchically structured representations to capture different degrees of abstraction. Grounding does not work the way that many embodied approaches have assumed.

Increased interhemispheric functional connectivity during non-dominant hand movement in right-handed subjects

Hand preference is one of the behavioral expressions of lateralization in the brain. Previous fMRI studies showed the activation in several regions including the motor cortex and the cerebellum during single-hand movement. However, functional connectivity related to hand preference has not been investigated. Here, we used the generalized psychophysiological interaction (gPPI) approach to investigate the alteration of functional connectivity during single-hand movement from the resting state in right-hand subjects. The functional connectivity in interhemispheric motor-related regions including the supplementary motor area, the precentral gyrus, and the cerebellum was significantly increased during non-dominant hand movement, while functional connectivity was not increased during dominant hand movement. The general linear model (GLM) showed activation in contralateral supplementary motor area, contralateral precentral gyrus, and ipsilateral cerebellum during right- or left-hand movement. These results indicate that a combination of GLM and gPPI analysis can detect the lateralization of hand preference more clearly.

Conceptual representations in the default, control and attention networks are task-dependent and cross-modal

Conceptual knowledge is central to human cognition. Neuroimaging studies suggest that conceptual processing involves modality-specific and multimodal brain regions in a task-dependent fashion. However, it remains unclear (1) to what extent conceptual feature representations are also modulated by the task, (2) whether conceptual representations in multimodal regions are indeed cross-modal, and (3) how the conceptual system relates to the large-scale functional brain networks. To address these issues, we conducted multivariate pattern analyses on fMRI data. 40 participants performed three tasks-lexical decision, sound judgment, and action judgment-on written words. We found that (1) conceptual feature representations are strongly modulated by the task, (2) conceptual representations in several multimodal regions are cross-modal, and (3) conceptual feature retrieval involves the default, frontoparietal control, and dorsal attention networks. Conceptual representations in these large-scale networks are task-dependent and cross-modal. Our findings support theories that assume conceptual processing to rely on a flexible, multi-level architecture.

Effective connectivity analysis of brain networks of mathematically gifted adolescents using transfer entropy

Using functional neuroimaging, electrophysiological techniques and neural data processing techniques, neuroscientists have found that mathematically gifted adolescents exhibit unusual neurocognitive features in the activation of task-related brain regions. Hemispheric information interaction, functional reorganization of networks, and utilization of task-related brain regions are beneficial to rapid and efficient task processing. Based on Granger causality channel selection, the transfer entropy (TE) value between effective channels was computed, and the information flow patterns in the directed functional brain networks derived from electroencephalography (EEG) data during deductive reasoning tasks were explored. We evaluated the workspace configuration patterns of the brain network and the global integration characteristics of separated brain regions using node strength, motif, directed clustering coefficient and characteristic path length in the brain networks of mathematically gifted adolescents with effective connectivity. The empirical results demonstrated that a more integrated functional network at the global level and a more efficient clique at the local level support a pattern of workspace configuration in the mathematically gifted brain that is more conducive to task-related information processing.

Multiple functions of the angular gyrus at high temporal resolution

Here, the functions of the angular gyrus (AG) are evaluated in the light of current evidence from transcranial magnetic/electric stimulation (TMS/TES) and EEG/MEG studies. 65 TMS/TES and 52 EEG/MEG studies were examined in this review. TMS/TES literature points to a causal role in semantic processing, word and number processing, attention and visual search, self-guided movement, memory, and self-processing. EEG/MEG studies reported AG effects at latencies varying between 32 and 800 ms in a wide range of domains, with a high probability to detect an effect at 300-350 ms post-stimulus onset. A three-phase unifying model revolving around the process of sensemaking is then suggested: (1) early AG involvement in defining the current context, within the first 200 ms, with a bias toward the right hemisphere; (2) attention re-orientation and retrieval of relevant information within 200-500 ms; and (3) cross-modal integration at late latencies with a bias toward the left hemisphere. This sensemaking process can favour accuracy (e.g. for word and number processing) or plausibility (e.g. for comprehension and social cognition). Such functions of the AG depend on the status of other connected regions. The much-debated semantic role is also discussed as follows: (1) there is a strong TMS/TES evidence for a causal semantic role, (2) current EEG/MEG evidence is however weak, but (3) the existing arguments against a semantic role for the AG are not strong. Some outstanding questions for future research are proposed. This review recognizes that cracking the role(s) of the AG in cognition is possible only when its exact contributions within the default mode network are teased apart.

The role of the angular gyrus in semantic cognition: a synthesis of five functional neuroimaging studies

Semantic knowledge is central to human cognition. The angular gyrus (AG) is widely considered a key brain region for semantic cognition. However, the role of the AG in semantic processing is controversial. Key controversies concern response polarity (activation vs. deactivation) and its relation to task difficulty, lateralization (left vs. right AG), and functional-anatomical subdivision (PGa vs. PGp subregions). Here, we combined the fMRI data of five studies on semantic processing (n = 172) and analyzed the response profiles from the same anatomical regions-of-interest for left and right PGa and PGp. We found that the AG was consistently deactivated during non-semantic conditions, whereas response polarity during semantic conditions was inconsistent. However, the AG consistently showed relative response differences between semantic and non-semantic conditions, and between different semantic conditions. A combined analysis across all studies revealed that AG responses could be best explained by separable effects of task difficulty and semantic processing demand. Task difficulty effects were stronger in PGa than PGp, regardless of hemisphere. Semantic effects were stronger in left than right AG, regardless of subregion. These results suggest that the AG is engaged in both domain-general task-difficulty-related processes and domain-specific semantic processes. In semantic processing, we propose that left AG acts as a "multimodal convergence zone" that binds different semantic features associated with the same concept, enabling efficient access to task-relevant features.

Meta-analytic evidence for a novel hierarchical model of conceptual processing

Conceptual knowledge plays a pivotal role in human cognition. Grounded cognition theories propose that concepts consist of perceptual-motor features represented in modality-specific perceptual-motor cortices. However, it is unclear whether conceptual processing consistently engages modality-specific areas. Here, we performed an activation likelihood estimation (ALE) meta-analysis across 212 neuroimaging experiments on conceptual processing related to 7 perceptual-motor modalities (action, sound, visual shape, motion, color, olfaction-gustation, and emotion). We found that conceptual processing consistently engages brain regions also activated during real perceptual-motor experience of the same modalities. In addition, we identified multimodal convergence zones that are recruited for multiple modalities. In particular, the left inferior parietal lobe (IPL) and posterior middle temporal gyrus (pMTG) are engaged for three modalities: action, motion, and sound. These "trimodal" regions are surrounded by "bimodal" regions engaged for two modalities. Our findings support a novel model of the conceptual system, according to which conceptual processing relies on a hierarchical neural architecture from modality-specific to multimodal areas up to an amodal hub.

Dynamic Effective Connectivity using Physiologically informed Dynamic Causal Model with Recurrent Units: A functional Magnetic Resonance Imaging simulation study

Functional MRI (fMRI) is an indirect reflection of neuronal activity. Using generative biophysical model of fMRI data such as Dynamic Causal Model (DCM), the underlying neuronal activities of different brain areas and their causal interactions (i.e., effective connectivity) can be calculated. Most DCM studies typically consider the effective connectivity to be static for a cognitive task within an experimental run. However, changes in experimental conditions during complex tasks such as movie-watching might result in temporal variations in the connectivity strengths. In this fMRI simulation study, we leverage state-of-the-art Physiologically informed DCM (P-DCM) along with a recurrent window approach and discretization of the equations to infer the underlying neuronal dynamics and concurrently the dynamic (time-varying) effective connectivities between various brain regions for task-based fMRI. Results from simulation studies on 3- and 10-region models showed that functional magnetic resonance imaging (fMRI) blood oxygenation level-dependent (BOLD) responses and effective connectivity time-courses can be accurately predicted and distinguished from faulty graphical connectivity models representing cognitive hypotheses. In summary, we propose and validate a novel approach to determine dynamic effective connectivity between brain areas during complex cognitive tasks by combining P-DCM with recurrent units.

Function without feeling: neural reactivity and intercommunication during flexible motor adjustments evoked by emotional and neutral stimuli

Motor conflicts arise when we need to quickly overwrite prepotent behavior. It has been proposed that affective stimuli modulate the neural processing of motor conflicts. However, previous studies have come to inconsistent conclusions regarding the neural impact of affective information on conflict processing. We employed functional magnetic resonance imaging during a Go/Change-Go task, where motor conflicts were either evoked by neutral or emotionally negative stimuli. Dynamic causal modeling was used to investigate how motor conflicts modulate the intercommunication between the anterior cingulate cortex (ACC) and the anterior insula (AI) as 2 central regions for cognitive control. Conflicts compared to standard actions were associated with increased BOLD activation in several brain areas, including the dorsal ACC and anterior insula. There were no differences in neural activity between emotional and non-emotional conflict stimuli. Conflicts compared to standard actions lowered neural self-inhibition of the ACC and AI and led to increased effective connectivity from the ACC to AI contralateral to the acting hand. Thus, our study indicates that neural conflict processing is primarily driven by the functional relevance of action-related stimuli, not their inherent affective meaning. Furthermore, it sheds light on the role of interconnectivity between ACC and AI for the implementation of flexible behavioral change.

The expanding horizons of network neuroscience: From description to prediction and control

The field of network neuroscience has emerged as a natural framework for the study of the brain and has been increasingly applied across divergent problems in neuroscience. From a disciplinary perspective, network neuroscience originally emerged as a formal integration of graph theory (from mathematics) and neuroscience (from biology). This early integration afforded marked utility in describing the interconnected nature of neural units, both structurally and functionally, and underscored the relevance of that interconnection for cognition and behavior. But since its inception, the field has not remained static in its methodological composition. Instead, it has grown to use increasingly advanced graph-theoretic tools and to bring in several other disciplinary perspectives-including machine learning and systems engineering-that have proven complementary. In doing so, the problem space amenable to the discipline has expanded markedly. In this review, we discuss three distinct flavors of investigation in state-of-the-art network neuroscience: (i) descriptive network neuroscience, (ii) predictive network neuroscience, and (iii) a perturbative network neuroscience that draws on recent advances in network control theory. In considering each area, we provide a brief summary of the approaches, discuss the nature of the insights obtained, and highlight future directions.

Neural correlates of embodied action language processing: a systematic review and meta-analytic study

The neural correlates of action language processing are still debated within embodied cognition research and little is known about the flexible involvement of modality-specific pre-motor system and multimodal high-level temporo-parietal regions as a function of explicit and implicit tasks. A systematic review and the Activation likelihood estimation (ALE) meta-analyses on functional neuroimaging studies were performed to identify neural correlates of action language processing activated during explicit and implicit tasks. The contrast ALE meta-analysis revealed activation of modality-specific premotor area and inferior frontal areas during explicit action language tasks while a greater activation of posterior temporo-occipital areas emerged for implicit tasks. The conjunction analysis revealed overlap in the temporo-parietal multimodal high-level regions for both types of tasks. Functional specialization of the middle temporal gyrus was found where the more posterior-occipital part resulted activated during implicit action language tasks whereas the antero-lateral part was involved in explicit tasks. Our findings were discussed within a conceptual flexibility perspective about the involvement of both the modality-specific and multimodal brain system during action language processing depending on different types of tasks.

A generalised semantic cognition account of aesthetic experience

Given that aesthetic experiences typically involve extracting meaning from environment, we believe that semantic cognition research has much to offer the field of neuroaesthetics. In the current paper, we propose a generalised framework that is inspired by the semantic cognition literature and that treats aesthetic experience as just one example of how meaning accumulates. According to our framework, aesthetic experiences are underpinned by the same cognitive and brain systems that are involved in deriving meaning from the environment in general, such as modality-specific conceptual representations and controlled processes for retrieving the appropriate type of information. Our generalised semantic cognition view of aesthetic experience has substantial implications for theory development: it leads to novel, falsifiable predictions and it reconfigures foundational assumptions regarding the structure of the cognitive and brain systems that may be involved in aesthetic experiences.

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.

Differential temporo-spatial pattern of electrical brain activity during the processing of abstract concepts related to mental states and verbal associations

Refined grounded cognition accounts propose that abstract concepts might be grounded in brain circuits involved in mentalizing. In the present event-related potential (ERP) study, we compared the time course of neural processing in response to semantically predefined abstract mental states and verbal association concepts during a lexical decision task. In addition to scalp ERPs, source estimates of underlying volume brain activity were determined to reveal spatio-temporal clusters of greater electrical brain activity to abstract mental state vs. verbal association concepts, and vice versa. Source estimates suggested early (onset 194 ms), but short-lived enhanced activity (offset 210 ms) to verbal association concepts in left occipital regions. Increased occipital activity might reflect retrieval of visual word form or access to visual conceptual features of associated words. Increased estimated source activity to mental state concepts was obtained in visuo-motor (superior parietal, pre- and postcentral areas) and mentalizing networks (lateral and medial prefrontal areas, insula, precuneus, temporo-parietal junction) with an onset of 212 ms, which extended to later time windows. The time course data indicated two processing phases: An initial conceptual access phase, in which linguistic and modal brain circuits rapidly process features depending on their relevance, and a later conceptual elaboration phase, in which elaborative processing within feature-specific networks further refines the concept. This study confirms the proposal that abstract concepts are based on representations in distinct neural circuits depending on their semantic feature content. The present research also highlights the importance of investigating sets of abstract concepts with a defined semantic content.

Task modulation of spatiotemporal dynamics in semantic brain networks: An EEG/MEG study

How does brain activity in distributed semantic brain networks evolve over time, and how do these regions interact to retrieve the meaning of words? We compared spatiotemporal brain dynamics between visual lexical and semantic decision tasks (LD and SD), analysing whole-cortex evoked responses and spectral functional connectivity (coherence) in source-estimated electroencephalography and magnetoencephalography (EEG and MEG) recordings. Our evoked analysis revealed generally larger activation for SD compared to LD, starting in primary visual area (PVA) and angular gyrus (AG), followed by left posterior temporal cortex (PTC) and left anterior temporal lobe (ATL). The earliest activation effects in ATL were significantly left-lateralised. Our functional connectivity results showed significant connectivity between left and right ATL, PTC and right ATL in an early time window, as well as between left ATL and IFG in a later time window. The connectivity of AG was comparatively sparse. We quantified the limited spatial resolution of our source estimates via a leakage index for careful interpretation of our results. Our findings suggest that the different demands on semantic information retrieval in lexical and semantic decision tasks first modulate visual and attentional processes, then multimodal semantic information retrieval in the ATLs and finally control regions (PTC and IFG) in order to extract task-relevant semantic features for response selection. Whilst our evoked analysis suggests a dominance of left ATL for semantic processing, our functional connectivity analysis also revealed significant involvement of right ATL in the more demanding semantic task. Our findings demonstrate the complementarity of evoked and functional connectivity analysis, as well as the importance of dynamic information for both types of analyses.