Cortical dynamics of word recognition

On the ability of standard and brain-constrained deep neural networks to support cognitive superposition: a position paper

The ability to coactivate (or "superpose") multiple conceptual representations is a fundamental function that we constantly rely upon; this is crucial in complex cognitive tasks requiring multi-item working memory, such as mental arithmetic, abstract reasoning, and language comprehension. As such, an artificial system aspiring to implement any of these aspects of general intelligence should be able to support this operation. I argue here that standard, feed-forward deep neural networks (DNNs) are unable to implement this function, whereas an alternative, fully brain-constrained class of neural architectures spontaneously exhibits it. On the basis of novel simulations, this proof-of-concept article shows that deep, brain-like networks trained with biologically realistic Hebbian learning mechanisms display the spontaneous emergence of internal circuits (cell assemblies) having features that make them natural candidates for supporting superposition. Building on previous computational modelling results, I also argue that, and offer an explanation as to why, in contrast, modern DNNs trained with gradient descent are generally unable to co-activate their internal representations. While deep brain-constrained neural architectures spontaneously develop the ability to support superposition as a result of (1) neurophysiologically accurate learning and (2) cortically realistic between-area connections, backpropagation-trained DNNs appear to be unsuited to implement this basic cognitive operation, arguably necessary for abstract thinking and general intelligence. The implications of this observation are briefly discussed in the larger context of existing and future artificial intelligence systems and neuro-realistic computational models.

Automating the analysis of eye movement for different neurodegenerative disorders

The clinical observation and assessment of extra-ocular movements is common practice in assessing neurodegenerative disorders but remains observer-dependent. In the present study, we propose an algorithm that can automatically identify saccades, fixation, smooth pursuit, and blinks using a non-invasive eye tracker. Subsequently, response-to-stimuli-derived interpretable features were elicited that objectively and quantitatively assess patient behaviors. The cohort analysis encompasses persons with mild cognitive impairment (MCI), Alzheimer's disease (AD), Parkinson's disease (PD), Parkinson's disease mimics (PDM), and controls (CTRL). Overall, results suggested that the AD/MCI and PD groups had significantly different saccade and pursuit characteristics compared to CTRL when the target moved faster or covered a larger visual angle during smooth pursuit. These two groups also displayed more omitted antisaccades and longer average antisaccade latency than CTRL. When reading a text passage silently, people with AD/MCI had more fixations. During visual exploration, people with PD demonstrated a more variable saccade duration than other groups. In the prosaccade task, the PD group showed a significantly smaller average hypometria gain and accuracy, with the most statistical significance and highest AUC scores of features studied. The minimum saccade gain was a PD-specific feature different from CTRL and PDM. These features, as oculographic biomarkers, can be potentially leveraged in distinguishing different types of NDs, yielding more objective and precise protocols to diagnose and monitor disease progression.

Interhemispheric functional brain connectivity predicts new language learning success in adults

Investigating interhemispheric interactions between homologous cortical regions during language processing is of interest. Despite prevalent left hemisphere lateralization of language, the right hemisphere also plays an important role and interhemispheric connectivity is influenced by language experience and is implicated in second language (L2) acquisition. Regions involved in language processing have differential connectivity to other cortical regions and to each other, and play specific roles in language. We examined the interhemispheric interactions of subregions of the inferior frontal gyrus (areas 44 and 45), the adjacent area 9/46v in the middle frontal gyrus, the superior temporal gyrus (STG), and the posterior inferior parietal lobule (pIPL) in relation to distinct and specific aspects of L2 learning success. The results indicated that the connectivity between left and right areas 44 and 9/46v predicted improvement in sentence repetition, connectivity between left and right area 45 and mid-STG predicted improvement in auditory comprehension, and connectivity between left and right pIPL predicted improvement in reading speed. We show interhemispheric interactions in the specific context of facilitating performance in adult L2 acquisition that follow an anterior to posterior gradient in the brain, and are consistent with the respective roles of these regions in language processing.

Altered topological properties of white matter structural network in adults with autism spectrum disorder

BACKGROUND

Autism spectrum disorder (ASD) is a complex developmental disability and is currently viewed as a disorder of brain connectivity in which white matter abnormalities. However, the majority of the research to date has focused on children with ASD. Understanding the topological organization of the white matter structural network in adults may help uncover the nature of ASD pathology in adulthood.

METHOD

This study investigated the topological properties of white matter structural network using diffusion tensor imaging and graph theory analysis in a sample of 32 adults with ASD compared to 35 matched typically developing (TD) controls. Group differences in global and nodal topological metrics were compared. The relationships between the altered network metrics and the severity of clinical symptoms were calculated.

RESULTS

Compared to TD controls, ASD patients exhibited decreased small-worldness and increased global efficiency. In addition, the reduced nodal efficiency and increased nodal degree were found in the frontal (e.g., the inferior frontal gyrus) and parietal (e.g., postcentral gyrus) regions. Furthermore, the altered topological metrics (e.g., increased global efficiency and reduced nodal efficiency) were correlated with the severity of ASD symptoms.

CONCLUSION

These results indicated that the complicatedly topological organization of the white matter structural network was abnormal and may play an essential role in the underlying pathological mechanism of ASD in adults.

Significance of event related causality (ERC) in eloquent neural networks

Neural activity emerges and propagates swiftly between brain areas. Investigation of these transient large-scale flows requires sophisticated statistical models. We present a method for assessing the statistical confidence of event-related neural propagation. Furthermore, we propose a criterion for statistical model selection, based on both goodness of fit and width of confidence intervals. We show that event-related causality (ERC) with two-dimensional (2D) moving average, is an efficient estimator of task-related neural propagation and that it can be used to determine how different cognitive task demands affect the strength and directionality of neural propagation across human cortical networks. Using electrodes surgically implanted on the surface of the brain for clinical testing prior to epilepsy surgery, we recorded electrocorticographic (ECoG) signals as subjects performed three naming tasks: naming of ambiguous and unambiguous visual objects, and as a contrast, naming to auditory description. ERC revealed robust and statistically significant patterns of high gamma activity propagation, consistent with models of visually and auditorily cued word production. Interestingly, ambiguous visual stimuli elicited more robust propagation from visual to auditory cortices relative to unambiguous stimuli, whereas naming to auditory description elicited propagation in the opposite direction, consistent with recruitment of modalities other than those of the stimulus during object recognition and naming. The new method introduced here is uniquely suitable to both research and clinical applications and can be used to estimate the statistical significance of neural propagation for both cognitive neuroscientific studies and functional brain mapping prior to resective surgery for epilepsy and brain tumors.

A novel stroke lesion network mapping approach: improved accuracy yet still low deficit prediction

Lesion network mapping estimates functional network abnormalities caused by a focal brain lesion. The method requires embedding the volume of the lesion into a normative functional connectome and using the average functional magnetic resonance imaging signal from that volume to compute the temporal correlation with all other brain locations. Lesion network mapping yields a map of potentially functionally disconnected regions. Although promising, this approach does not predict behavioural deficits well. We modified lesion network mapping by using the first principal component of the functional magnetic resonance imaging signal computed from the voxels within the lesioned area for temporal correlation. We measured potential improvements in connectivity strength, anatomical specificity of the lesioned network and behavioural prediction in a large cohort of first-time stroke patients at 2-weeks post-injury (n = 123). This principal component functional disconnection approach localized mainly cortical voxels of high signal-to-noise; and it yielded networks with higher anatomical specificity, and stronger behavioural correlation than the standard method. However, when examined with a rigorous leave-one-out machine learning approach, principal component functional disconnection approach did not perform better than the standard lesion network mapping in predicting neurological deficits. In summary, even though our novel method improves the specificity of disconnected networks and correlates with behavioural deficits post-stroke, it does not improve clinical prediction. Further work is needed to capture the complex adjustment of functional networks produced by focal damage in relation to behaviour.

Simultaneously recorded subthalamic and cortical LFPs reveal different lexicality effects during reading aloud

Many language functions are traditionally assigned to cortical brain areas, leaving the contributions of subcortical structures to language processing largely unspecified. The present study examines a potential role of the subthalamic nucleus (STN) in lexical processing, specifically, reading aloud of words (e.g., 'fate') and pseudowords (e.g., 'fape'). We recorded local field potentials simultaneously from the STN and the cortex (precentral, postcentral, and superior temporal gyri) of 13 people with Parkinson's disease undergoing awake deep brain stimulation and compared STN's lexicality-related neural activity with that of the cortex. Both STN and cortical activity demonstrated significant task-related modulations, but the lexicality effects were different in the two brain structures. In the STN, an increase in gamma band activity (31-70 Hz) was present in pseudoword trials compared to word trials during subjects' spoken response. In the cortex, a greater decrease in beta band activity (12-30 Hz) was observed for pseudowords in the precentral gyrus. Additionally, 11 individual cortical sites showed lexicality effects with varying temporal and topographic characteristics in the alpha and beta frequency bands. These findings suggest that the STN and the sampled cortical regions are involved differently in the processing of lexical distinctions.

Abnormal Functional Connectivity of Posterior Cingulate Cortex Correlates With Phonemic Verbal Fluency Deficits in Major Depressive Disorder

Background: Major depressive disorder (MDD) patients face an increased risk of developing cognitive impairments. One of the prominent cognitive impairments in MDD patients is verbal fluency deficit. Nonetheless, it is not clear which vulnerable brain region in MDD is interactively linked to verbal fluency deficit. It is important to gain an improved understanding for verbal fluency deficit in MDD.

Methods: Thirty-four MDD patients and 34 normal controls (NCs) completed resting-state fMRI (rs-fMRI) scan and a set of verbal fluency tests (semantic VFT and phonemic VFT). Fourteen brain regions from five brain networks/systems (central executive network, default mode network, salience network, limbic system, cerebellum) based on their vital role in MDD neuropathology were selected as seeds for functional connectivity (FC) analyses with the voxels in the whole brain. Finally, correlations between the z-score of the FCs from clusters showing significant between-group difference and z-score of the VFTs were calculated using Pearson correlation analyses.

Results: Increased FCs in MDD patients vs. NCs were identified between the bilateral posterior cingulate cortex (PCC) and the right inferior frontal gyrus (triangular part), in which the increased FC between the right PCC and the right inferior frontal gyrus (triangular part) was positively correlated with the z score of phonemic VFT in the MDD patients. Moreover, decreased FCs were identified between the right hippocampal gyrus and PCC, as well as left cerebellum Crus II and right parahippocampal gyrus in MDD patients vs. NCs.

Conclusions: The MDD patients have altered FCs among key brain regions in the default mode network, the central executive network, the limbic system, and the cerebellum. The increased FC between the right PCC and the right inferior frontal gyrus (triangular part) may be useful to better characterize pathophysiology of MDD and functional correlates of the phonemic verbal fluency deficit in MDD.

Intracranial recording in patients with aphasia using nanomaterial-based flexible electronics: promises and challenges

In recent years, researchers have studied how nanotechnology could enhance neuroimaging techniques. The application of nanomaterial-based flexible electronics has the potential to advance conventional intracranial electroencephalography (iEEG) by utilising brain-compatible soft nanomaterials. The resultant technique has significantly high spatial and temporal resolution, both of which enhance the localisation of brain functions and the mapping of dynamic language processing. This review presents findings on aphasia, an impairment in language and communication, and discusses how different brain imaging techniques, including positron emission tomography, magnetic resonance imaging, and iEEG, have advanced our understanding of the neural networks underlying language and reading processing. We then outline the strengths and weaknesses of iEEG in studying human cognition and the development of intracranial recordings that use brain-compatible flexible electrodes. We close by discussing the potential advantages and challenges of future investigations adopting nanomaterial-based flexible electronics for intracranial recording in patients with aphasia.

Neural signatures of inhibitory control in intra-sentential code-switching: Evidence from fMRI

In this study we examined the neural control mechanisms that are at play when habitual code-switchers read code-switches embedded in a sentence context. The goal was also to understand if and to what extent the putative control network that is engaged during the comprehension of code-switched sentences is modulated by the linguistic regularity of those switches. Towards that goal, we tested two different types of code switches (switches at the noun-phrase boundary and switches at the verb-phrase boundary) that despite being both represented in naturalistic corpora of code switching, show different distributional properties. Results show that areas involved in general cognitive control (e.g., pre-SMA, anterior cingulate cortex) are recruited when processing code-switched sentences, relative to non-code-switched sentences. Additionally, significant activation in the cerebellum when processing sentences containing code-switches at the noun-phrase boundary suggests that habitual code-switchers might engage a wider control network to adapt inhibitory control processes according to task demands. Results are discussed in the context of the current literature on neural models of bilingual language control.

Contributions of electrophysiology for identifying cortical language systems in patients with epilepsy

A crucial element of the surgical treatment of medically refractory epilepsy is to delineate cortical areas that must be spared in order to avoid clinically relevant neurological and neuropsychological deficits postoperatively. For each patient, this typically necessitates determining the language lateralization between hemispheres and language localization within hemisphere. Understanding cortical language systems is complicated by two primary challenges: the extent of the neural tissue involved and the substantial variability across individuals, especially in pathological populations. We review the contributions made through the study of electrophysiological activity to address these challenges. These contributions are based on the techniques of magnetoencephalography (MEG), intracerebral recordings, electrical-cortical stimulation (ECS), and the electrovideo analyses of seizures and their semiology. We highlight why no single modality alone is adequate to identify cortical language systems and suggest avenues for improving current practice.

A shared neural substrate for action verbs and observed actions in human posterior parietal cortex

High-level sensory and motor cortical areas are activated when processing the meaning of language, but it is unknown whether, and how, words share a neural substrate with corresponding sensorimotor representations. We recorded from single neurons in human posterior parietal cortex (PPC) while participants viewed action verbs and corresponding action videos from multiple views. We find that PPC neurons exhibit a common neural substrate for action verbs and observed actions. Further, videos were encoded with mixtures of invariant and idiosyncratic responses across views. Action verbs elicited selective responses from a fraction of these invariant and idiosyncratic neurons, without preference, thus associating with a statistical sampling of the diverse sensory representations related to the corresponding action concept. Controls indicated that the results are not the product of visual imagery or arbitrary learned associations. Our results suggest that language may activate the consolidated visual experience of the reader.

Identifying task-relevant spectral signatures of perceptual categorization in the human cortex

Human brain has developed mechanisms to efficiently decode sensory information according to perceptual categories of high prevalence in the environment, such as faces, symbols, objects. Neural activity produced within localized brain networks has been associated with the process that integrates both sensory bottom-up and cognitive top-down information processing. Yet, how specifically the different types and components of neural responses reflect the local networks’ selectivity for categorical information processing is still unknown. In this work we train Random Forest classification models to decode eight perceptual categories from broad spectrum of human intracranial signals (4–150 Hz, 100 subjects) obtained during a visual perception task. We then analyze which of the spectral features the algorithm deemed relevant to the perceptual decoding and gain the insights into which parts of the recorded activity are actually characteristic of the visual categorization process in the human brain. We show that network selectivity for a single or multiple categories in sensory and non-sensory cortices is related to specific patterns of power increases and decreases in both low (4–50 Hz) and high (50–150 Hz) frequency bands. By focusing on task-relevant neural activity and separating it into dissociated anatomical and spectrotemporal groups we uncover spectral signatures that characterize neural mechanisms of visual category perception in human brain that have not yet been reported in the literature.

High gamma response tracks different syntactic structures in homophonous phrases

Syntax is a species-specific component of human language combining a finite set of words in a potentially infinite number of sentences. Since words are by definition expressed by sound, factoring out syntactic information is normally impossible. Here, we circumvented this problem in a novel way by designing phrases with exactly the same acoustic content but different syntactic structures depending on the other words they occur with. In particular, we used phrases merging an article with a noun yielding a Noun Phrase (NP) or a clitic with a verb yielding a Verb Phrase (VP). We performed stereo-electroencephalographic (SEEG) recordings in epileptic patients. We measured a different electrophysiological correlates of verb phrases vs. noun phrases in multiple cortical areas in both hemispheres, including language areas and their homologous in the non-dominant hemisphere. The high gamma band activity (150-300 Hz frequency), which plays a crucial role in inter-regional cortical communications, showed a significant difference during the presentation of the homophonous phrases, depending on whether the phrase was a verb phrase or a noun phrase. Our findings contribute to the ultimate goal of a complete neural decoding of linguistic structures from the brain.

Frequency-based Dissociation of Symbolic and Nonsymbolic Numerical Processing during Numerical Comparison

Recent evidence suggests that during numerical calculation, symbolic and nonsymbolic processing are functionally distinct operations. Nevertheless, both roughly recruit the same brain areas (spatially overlapping networks in the parietal cortex) and happen at the same time (roughly 250 msec poststimulus onset). We tested the hypothesis that symbolic and nonsymbolic processing are segregated by means of functionally relevant networks in different frequency ranges: high gamma (above 50 Hz) for symbolic processing and lower beta (12–17 Hz) for nonsymbolic processing. EEG signals were quantified as participants compared either symbolic numbers or nonsymbolic quantities. Larger EEG gamma-band power was observed for more difficult symbolic comparisons (ratio of 0.8 between the two numbers) than for easier comparisons (ratio of 0.2) over frontocentral regions. Similarly, beta-band power was larger for more difficult nonsymbolic comparisons than for easier ones over parietal areas. These results confirm the existence of a functional dissociation in EEG oscillatory dynamics during numerical processing that is compatible with the notion of distinct linguistic processing of symbolic numbers and approximation of nonsymbolic numerical information.

A neurocognitive model of perceptual decision-making on emotional signals

Humans make various kinds of decisions about which emotions they perceive from others. Although it might seem like a split-second phenomenon, deliberating over which emotions we perceive unfolds across several stages of decisional processing. Neurocognitive models of general perception postulate that our brain first extracts sensory information about the world then integrates these data into a percept and lastly interprets it. The aim of the present study was to build an evidence-based neurocognitive model of perceptual decision-making on others' emotions. We conducted a series of meta-analyses of neuroimaging data spanning 30 years on the explicit evaluations of others' emotional expressions. We find that emotion perception is rather an umbrella term for various perception paradigms, each with distinct neural structures that underline task-related cognitive demands. Furthermore, the left amygdala was responsive across all classes of decisional paradigms, regardless of task-related demands. Based on these observations, we propose a neurocognitive model that outlines the information flow in the brain needed for a successful evaluation of and decisions on other individuals' emotions. HIGHLIGHTS: Emotion classification involves heterogeneous perception and decision-making tasks Decision-making processes on emotions rarely covered by existing emotions theories We propose an evidence-based neuro-cognitive model of decision-making on emotions Bilateral brain processes for nonverbal decisions, left brain processes for verbal decisions Left amygdala involved in any kind of decision on emotions.

Cortical stimulation in aphasia following ischemic stroke: toward model-guided electrical neuromodulation

The aim of this paper is to integrate different bodies of research including brain traveling waves, brain neuromodulation, neural field modeling and post-stroke language disorders in order to explore the opportunity of implementing model-guided, cortical neuromodulation for the treatment of post-stroke aphasia. Worldwide according to WHO, strokes are the second leading cause of death and the third leading cause of disability. In ischemic stroke, there is not enough blood supply to provide enough oxygen and nutrients to parts of the brain, while in hemorrhagic stroke, there is bleeding within the enclosed cranial cavity. The present paper focuses on ischemic stroke. We first review accumulating observations of traveling waves occurring spontaneously or triggered by external stimuli in healthy subjects as well as in patients with brain disorders. We examine the putative functions of these waves and focus on post-stroke aphasia observed when brain language networks become fragmented and/or partly silent, thus perturbing the progression of traveling waves across perilesional areas. Secondly, we focus on a simplified model based on the current literature in the field and describe cortical traveling wave dynamics and their modulation. This model uses a biophysically realistic integro-differential equation describing spatially distributed and synaptically coupled neural networks producing traveling wave solutions. The model is used to calculate wave parameters (speed, amplitude and/or frequency) and to guide the reconstruction of the perturbed wave. A stimulation term is included in the model to restore wave propagation to a reasonably good level. Thirdly, we examine various issues related to the implementation model-guided neuromodulation in the treatment of post-stroke aphasia given that closed-loop invasive brain stimulation studies have recently produced encouraging results. Finally, we suggest that modulating traveling waves by acting selectively and dynamically across space and time to facilitate wave propagation is a promising therapeutic strategy especially at a time when a new generation of closed-loop cortical stimulation systems is about to arrive on the market.

Steady state visual evoked potentials in reading aloud: Effects of lexicality, frequency and orthographic familiarity

The present study explored the possibility to use Steady-State Visual Evoked Potentials (SSVEPs) as a tool to investigate the core mechanisms in visual word recognition. In particular, we investigated three benchmark effects of reading aloud: lexicality (words vs. pseudowords), frequency (high-frequency vs. low-frequency words), and orthographic familiarity ('familiar' versus 'unfamiliar' pseudowords). We found that words and pseudowords elicited robust SSVEPs. Words showed larger SSVEPs than pseudowords and high-frequency words showed larger SSVEPs than low-frequency words. SSVEPs were not sensitive to orthographic familiarity. We further localized the neural generators of the SSVEP effects. The lexicality effect was located in areas associated with early level of visual processing, i.e. in the right occipital lobe and in the right precuneus. Pseudowords produced more activation than words in left sensorimotor areas, rolandic operculum, insula, supramarginal gyrus and in the right temporal gyrus. These areas are devoted to speech processing and/or spelling-to-sound conversion. The frequency effect involved the left temporal pole and orbitofrontal cortex, areas previously implicated in semantic processing and stimulus-response associations respectively, and the right postcentral and parietal inferior gyri, possibly indicating the involvement of the right attentional network.

Consistent Gradient of Performance and Decoding of Stimulus Type and Valence From Local and Network Activity

The individual differences approach focuses on the variation of behavioral and neural signatures across subjects. In this context, we searched for intracranial neural markers of performance in three individuals with distinct behavioral patterns (efficient, borderline, and inefficient) in a dual-valence task assessing facial and lexical emotion recognition. First, we performed a preliminary study to replicate well-established evoked responses in relevant brain regions. Then, we examined time series data and network connectivity, combined with multivariate pattern analyses and machine learning, to explore electrophysiological differences in resting-state versus task-related activity across subjects. Next, using the same methodological approach, we assessed the neural decoding of performance for different dimensions of the task. The classification of time series data mirrored the behavioral gradient across subjects for stimulus type but not for valence. However, network-based measures reflected the subjects' hierarchical profiles for both stimulus types and valence. Therefore, this measure serves as a sensitive marker for capturing distributed processes such as emotional valence discrimination, which relies on an extended set of regions. Network measures combined with classification methods may offer useful insights to study single subjects and understand inter-individual performance variability. Promisingly, this approach could eventually be extrapolated to other neuroscientific techniques.

Neurolinguistics Research Advancing Development of a Direct-Speech Brain-Computer Interface

A direct-speech brain-computer interface (DS-BCI) acquires neural signals corresponding to imagined speech, then processes and decodes these signals to produce a linguistic output in the form of phonemes, words, or sentences. Recent research has shown the potential of neurolinguistics to enhance decoding approaches to imagined speech with the inclusion of semantics and phonology in experimental procedures. As neurolinguistics research findings are beginning to be incorporated within the scope of DS-BCI research, it is our view that a thorough understanding of imagined speech, and its relationship with overt speech, must be considered an integral feature of research in this field. With a focus on imagined speech, we provide a review of the most important neurolinguistics research informing the field of DS-BCI and suggest how this research may be utilized to improve current experimental protocols and decoding techniques. Our review of the literature supports a cross-disciplinary approach to DS-BCI research, in which neurolinguistics concepts and methods are utilized to aid development of a naturalistic mode of communication.

Task-induced gamma band effect in type II focal cortical dysplasia: An exploratory study

OBJECTIVE

Few data are available about the functionality of type II focal cortical dysplasia (FCD). Identification of high-frequency activities (HFAs) induced by cognitive tasks has been proposed as an additional way to map cognitive functions in patients undergoing presurgical evaluation using stereoelectroencephalography (SEEG). However, the repetitive subcontinuous spiking pattern which characterizes type II FCD might limit the reliability of this approach, and its feasibility in these patients remains to be evaluated.

METHODS

Seven patients whose magnetic resonance imaging (MRI) data, SEEG data, and/or pathological data were consistent with the diagnosis of type II FCD were included. All patients performed standardized cognitive tasks specifically designed to map task-induced increase of HFA (50 Hz to 150 Hz) at the recorded sites. Electrode contacts which showed an interictal SEEG pattern typical of type II FCD were considered to be localized within the FCD. A site was considered responsive if it was significantly different from baseline in at least one cognitive task.

RESULTS

Three of the seven patients (43%) had significant task-induced increase of HFA in the FCD for a total of 15 sites with an interictal SEEG pattern typical of type II FCD. These sites were always localized at the external border of the FCD whereas no HFA response was in the core of FCD. In three of the four other patients, a significant task-induced increase of HFA was observed in a cortical site immediately adjacent to the dysplastic cortex.

SIGNIFICANCE

Detection of task-induced HFA remains feasible despite the repetitive subcontinuous spiking pattern which characterizes type II FCD. Depending on the localization of the FCD, some sites of the dysplastic cortex were included in large-scale functional networks. However, these sites were always those closest to the nondysplastic cortex suggesting that persistence of cortical functions might be restricted to a limited part of the FCD.

Morphological representations are extrapolated from morpho-syntactic rules

The field of psycho- and neuro-linguistics has long-debated the decompositional model of visual word processing: Are written words processed via the visual forms of stem and affix morphemes, or as complex wholes? Although many have now settled upon a decompositional view, it is unclear what heuristic the brain uses to generate these visual morpheme-forms in the first place. Here we conduct a magneto-encephalography study to test two hypotheses for how this may be done: i) the brain encodes representations of the morphemes that follow the morpho-syntactic rules governing constituents: A stem morpheme will be represented if the word obeys the grammatical behaviour associated with its suffix; ii) the brain only encodes stem morphemes that occur with multiple suffixes or as words in isolation. Our results indicate that words with morpho-syntactic wellformedness as stem-suffix combinations are decomposed by the system, thus supporting the former hypothesis. This suggests that knowledge of morpho-syntactic rules can be used to form morphological representations of written words, in absence of independent experience with all of their constituent morphemes. Possible mechanisms supporting this computation are discussed.

Three- and four-dimensional mapping of speech and language in patients with epilepsy

We have provided 3-D and 4D mapping of speech and language function based upon the results of direct cortical stimulation and event-related modulation of electrocorticography signals. Patients estimated to have right-hemispheric language dominance were excluded. Thus, 100 patients who underwent two-stage epilepsy surgery with chronic electrocorticography recording were studied. An older group consisted of 84 patients at least 10 years of age (7367 artefact-free non-epileptic electrodes), whereas a younger group included 16 children younger than age 10 (1438 electrodes). The probability of symptoms transiently induced by electrical stimulation was delineated on a 3D average surface image. The electrocorticography amplitude changes of high-gamma (70-110 Hz) and beta (15-30 Hz) activities during an auditory-naming task were animated on the average surface image in a 4D manner. Thereby, high-gamma augmentation and beta attenuation were treated as summary measures of cortical activation. Stimulation data indicated the causal relationship between (i) superior-temporal gyrus of either hemisphere and auditory hallucination; (ii) left superior-/middle-temporal gyri and receptive aphasia; (iii) widespread temporal/frontal lobe regions of the left hemisphere and expressive aphasia; and (iv) bilateral precentral/left posterior superior-frontal regions and speech arrest. On electrocorticography analysis, high-gamma augmentation involved the bilateral superior-temporal and precentral gyri immediately following question onset; at the same time, high-gamma activity was attenuated in the left orbitofrontal gyrus. High-gamma activity was augmented in the left temporal/frontal lobe regions, as well as left inferior-parietal and cingulate regions, maximally around question offset, with high-gamma augmentation in the left pars orbitalis inferior-frontal, middle-frontal, and inferior-parietal regions preceded by high-gamma attenuation in the contralateral homotopic regions. Immediately before verbal response, high-gamma augmentation involved the posterior superior-frontal and pre/postcentral regions, bilaterally. Beta-attenuation was spatially and temporally correlated with high-gamma augmentation in general but with exceptions. The younger and older groups shared similar spatial-temporal profiles of high-gamma and beta modulation; except, the younger group failed to show left-dominant activation in the rostral middle-frontal and pars orbitalis inferior-frontal regions around stimulus offset. The human brain may rapidly and alternately activate and deactivate cortical areas advantageous or obtrusive to function directed toward speech and language at a given moment. Increased left-dominant activation in the anterior frontal structures in the older age group may reflect developmental consolidation of the language system. The results of our functional mapping may be useful in predicting, across not only space but also time and patient age, sites specific to language function for presurgical evaluation of focal epilepsy.

Key considerations in designing a speech brain-computer interface

Restoring communication in case of aphasia is a key challenge for neurotechnologies. To this end, brain-computer strategies can be envisioned to allow artificial speech synthesis from the continuous decoding of neural signals underlying speech imagination. Such speech brain-computer interfaces do not exist yet and their design should consider three key choices that need to be made: the choice of appropriate brain regions to record neural activity from, the choice of an appropriate recording technique, and the choice of a neural decoding scheme in association with an appropriate speech synthesis method. These key considerations are discussed here in light of (1) the current understanding of the functional neuroanatomy of cortical areas underlying overt and covert speech production, (2) the available literature making use of a variety of brain recording techniques to better characterize and address the challenge of decoding cortical speech signals, and (3) the different speech synthesis approaches that can be considered depending on the level of speech representation (phonetic, acoustic or articulatory) envisioned to be decoded at the core of a speech BCI paradigm.

Effective Connectivity between Ventral Occipito-Temporal and Ventral Inferior Frontal Cortex during Lexico-Semantic Processing. A Dynamic Causal Modeling Study

It has been suggested that dorsal and ventral pathways support distinct aspects of language processing. Yet, the full extent of their involvement and their inter-regional connectivity in visual word recognition is still unknown. Studies suggest that they might reflect the dual-route model of reading, with the dorsal pathway more involved in grapho-phonological conversion during phonological tasks, and the ventral pathway performing lexico-semantic access during semantic tasks. Furthermore, this subdivision is also suggested at the level of the inferior frontal cortex, involving ventral and dorsal parts for lexico-semantic and phonological processing, respectively. In the present study, we assessed inter-regional brain connectivity and task-induced modulations of brain activity during a phoneme detection and semantic categorization tasks, using fMRI in healthy subject. We used a dynamic causal modeling approach to assess inter-regional connectivity and task demand modulation within the dorsal and ventral pathways, including the following network components: the ventral occipito-temporal cortex (vOTC; dorsal and ventral), the superior temporal gyrus (STG; dorsal), the dorsal inferior frontal gyrus (dIFG; dorsal), and the ventral IFG (vIFG; ventral). We report three distinct inter-regional interactions supporting orthographic information transfer from vOTC to other language regions (vOTC -> STG, vOTC -> vIFG and vOTC -> dIFG) regardless of task demands. Moreover, we found that (a) during semantic processing (direct ventral pathway) the vOTC -> vIFG connection strength specifically increased and (b) a lack of modulation of the vOTC -> dIFG connection strength by the task that could suggest a more general involvement of the dorsal pathway during visual word recognition. Results are discussed in terms of anatomo-functional connectivity of visual word recognition network.

A Spiking Neurocomputational Model of High-Frequency Oscillatory Brain Responses to Words and Pseudowords

Experimental evidence indicates that neurophysiological responses to well-known meaningful sensory items and symbols (such as familiar objects, faces, or words) differ from those to matched but novel and senseless materials (unknown objects, scrambled faces, and pseudowords). Spectral responses in the high beta- and gamma-band have been observed to be generally stronger to familiar stimuli than to unfamiliar ones. These differences have been hypothesized to be caused by the activation of distributed neuronal circuits or cell assemblies, which act as long-term memory traces for learned familiar items only. Here, we simulated word learning using a biologically constrained neurocomputational model of the left-hemispheric cortical areas known to be relevant for language and conceptual processing. The 12-area spiking neural-network architecture implemented replicates physiological and connectivity features of primary, secondary, and higher-association cortices in the frontal, temporal, and occipital lobes of the human brain. We simulated elementary aspects of word learning in it, focussing specifically on semantic grounding in action and perception. As a result of spike-driven Hebbian synaptic plasticity mechanisms, distributed, stimulus-specific cell-assembly (CA) circuits spontaneously emerged in the network. After training, presentation of one of the learned "word" forms to the model correlate of primary auditory cortex induced periodic bursts of activity within the corresponding CA, leading to oscillatory phenomena in the entire network and spontaneous across-area neural synchronization. Crucially, Morlet wavelet analysis of the network's responses recorded during presentation of learned meaningful "word" and novel, senseless "pseudoword" patterns revealed stronger induced spectral power in the gamma-band for the former than the latter, closely mirroring differences found in neurophysiological data. Furthermore, coherence analysis of the simulated responses uncovered dissociated category specific patterns of synchronous oscillations in distant cortical areas, including indirectly connected primary sensorimotor areas. Bridging the gap between cellular-level mechanisms, neuronal-population behavior, and cognitive function, the present model constitutes the first spiking, neurobiologically, and anatomically realistic model able to explain high-frequency oscillatory phenomena indexing language processing on the basis of dynamics and competitive interactions of distributed cell-assembly circuits which emerge in the brain as a result of Hebbian learning and sensorimotor experience.

Clinical Impact and Implication of Real-Time Oscillation Analysis for Language Mapping

BACKGROUND

We developed a functional brain analysis system that enabled us to perform real-time task-related electrocorticography (ECoG) and evaluated its potential in clinical practice. We hypothesized that high gamma activity (HGA) mapping would provide better spatial and temporal resolution with high signal-to-noise ratios.

METHODS

Seven awake craniotomy patients were evaluated. ECoG was recorded during language tasks using subdural grids, and HGA (60-170 Hz) maps were obtained in real time. The patients also underwent electrocortical stimulation (ECS) mapping to validate the suspected functional locations on HGA mapping. The results were compared and calculated to assess the sensitivity and specificity of HGA mapping. For reference, bedside HGA-ECS mapping was performed in 5 epilepsy patients.

RESULTS

HGA mapping demonstrated functional brain areas in real time and was comparable with ECS mapping. Sensitivity and specificity for the language area were 90.1% ± 11.2% and 90.0% ± 4.2%, respectively. Most HGA-positive areas were consistent with ECS-positive regions in both groups, and there were no statistical between-group differences.

CONCLUSIONS

Although this study included a small number of subjects, it showed real-time HGA mapping with the same setting and tasks under different conditions. This study demonstrates the clinical feasibility of real-time HGA mapping. Real-time HGA mapping enabled simple and rapid detection of language functional areas in awake craniotomy. The mapping results were highly accurate, although the mapping environment was noisy. Further studies of HGA mapping may provide the potential to elaborate complex brain functions and networks.

Neural correlate of the construction of sentence meaning

The neural processes that underlie your ability to read and understand this sentence are unknown. Sentence comprehension occurs very rapidly, and can only be understood at a mechanistic level by discovering the precise sequence of underlying computational and neural events. However, we have no continuous and online neural measure of sentence processing with high spatial and temporal resolution. Here we report just such a measure: intracranial recordings from the surface of the human brain show that neural activity, indexed by γ-power, increases monotonically over the course of a sentence as people read it. This steady increase in activity is absent when people read and remember nonword-lists, despite the higher cognitive demand entailed, ruling out accounts in terms of generic attention, working memory, and cognitive load. Response increases are lower for sentence structure without meaning ("Jabberwocky" sentences) and word meaning without sentence structure (word-lists), showing that this effect is not explained by responses to syntax or word meaning alone. Instead, the full effect is found only for sentences, implicating compositional processes of sentence understanding, a striking and unique feature of human language not shared with animal communication systems. This work opens up new avenues for investigating the sequence of neural events that underlie the construction of linguistic meaning.

Neural Activity Elicited by a Cognitive Task can be Detected in Single-Trials with Simultaneous Intracerebral EEG-fMRI Recordings

Recent studies have shown that it is feasible to record simultaneously intracerebral EEG (icEEG) and functional magnetic resonance imaging (fMRI) in patients with epilepsy. While it has mainly been used to explore the hemodynamic changes associated with epileptic spikes, this approach could also provide new insight into human cognition. However, the first step is to ensure that cognitive EEG components, that have lower amplitudes than epileptic spikes, can be appropriately detected under fMRI. We compared the high frequency activities (HFA, 50-150[Formula: see text]Hz) elicited by a reading task in icEEG-only and subsequent icEEG-fMRI in the same patients ([Formula: see text]), implanted with depth electrodes. Comparable responses were obtained, with 71% of the recording sites that responded during the icEEG-only session also responding during the icEEG-fMRI session. For all the remaining sites, nearby clusters (distant of 7[Formula: see text]mm or less) also demonstrated significant HFA increase during the icEEG-fMRI session. Significant HFA increases were also observable at the single-trial level in icEEG-fMRI recordings. Our results show that low-amplitude icEEG signal components such as cognitive-induced HFAs can be reliably recorded with simultaneous fMRI. This paves the way for the use of icEEG-fMRI to address various fundamental and clinical issues, notably the identification of the neural correlates of the BOLD signal.

Modulation of Orthographic Decoding by Frontal Cortex

Opinions are divided on whether word reading processes occur in a hierarchical, feedforward fashion or within an interactive framework. To critically evaluate these competing theories, we recorded electrocorticographic (ECoG) data from 15 human patients with intractable epilepsy during a word completion task and evaluated brain network dynamics across individuals. We used a novel technique of analyzing multihuman ECoG recordings to identify cortical regions most relevant to processing lexical information. The mid fusiform gyrus showed the strongest, earliest response after stimulus onset, whereas activity was maximal in frontal, dorsal lateral prefrontal, and sensorimotor regions toward articulation onset. To evaluate interregional functional connectivity, ECoG data from electrodes situated over specific cortical regions of interest were fit into linear multivariate autoregressive (MVAR) models. Spectral characteristics of the MVAR models were used to precisely reveal the timing and the magnitude of information flow between localized brain regions. This is the first application of MVAR for developing a comprehensive account of interregional interactions from a word reading ECoG dataset. Our comprehensive findings revealed both top-down and bottom-up influences between higher-level language areas and the mid fusiform gyrus. Our findings thus challenge strictly hierarchical, feedforward views of word reading and suggest that orthographic processes are modulated by prefrontal and sensorimotor regions via an interactive framework.

SIGNIFICANCE STATEMENT

Word reading is a critical part of everyday life. When the ability to read is disrupted, it can lead to learning disorders, as well as emotional and academic difficulties. The neural mechanisms underlying word reading are not well understood due to limitations in the spatial and temporal specificity of prior word reading studies. Our research analyzed data recorded from sensors implanted directly from surface of human brains while these individuals performed a word reading task. Our research analyzed these recordings to infer how brain regions communicate during word reading. Our original results improve upon current models of word reading and can be used to develop treatment plans for individuals with reading disabilities.

Contribution of writing to reading: Dissociation between cognitive and motor process in the left dorsal premotor cortex

Functional brain imaging studies reported activation of the left dorsal premotor cortex (PMd), that is, a main area in the writing network, in reading tasks. However, it remains unclear whether this area is causally relevant for written stimulus recognition or its activation simply results from a passive coactivation of reading and writing networks. Here, we used chronometric paired-pulse transcranial magnetic stimulation (TMS) to address this issue by disrupting the activity of the PMd, the so-called Exner's area, while participants performed a lexical decision task. Both words and pseudowords were presented in printed and handwritten characters. The latter was assumed to be closely associated with motor representations of handwriting gestures. We found that TMS over the PMd in relatively early time-windows, i.e., between 60 and 160 ms after the stimulus onset, increased reaction times to pseudoword without affecting word recognition. Interestingly, this result pattern was found for both printed and handwritten characters, that is, regardless of whether the characters evoked motor representations of writing actions. Our result showed that under some circumstances the activation of the PMd does not simply result from passive association between reading and writing networks but has a functional role in the reading process. At least, at an early stage of written stimuli recognition, this role seems to depend on a common sublexical and serial process underlying writing and pseudoword reading rather than on an implicit evocation of writing actions during reading as typically assumed.

Brain Network Connectivity During Language Comprehension: Interacting Linguistic and Perceptual Subsystems

The dynamic neural processes underlying spoken language comprehension require the real-time integration of general perceptual and specialized linguistic information. We recorded combined electro- and magnetoencephalographic measurements of participants listening to spoken words varying in perceptual and linguistic complexity. Combinatorial linguistic complexity processing was consistently localized to left perisylvian cortices, whereas competition-based perceptual complexity triggered distributed activity over both hemispheres. Functional connectivity showed that linguistically complex words engaged a distributed network of oscillations in the gamma band (20-60 Hz), which only partially overlapped with the network supporting perceptual analysis. Both processes enhanced cross-talk between left temporal regions and bilateral pars orbitalis (BA47). The left-lateralized synchrony between temporal regions and pars opercularis (BA44) was specific to the linguistically complex words, suggesting a specific role of left frontotemporal cross-cortical interactions in morphosyntactic computations. Synchronizations in oscillatory dynamics reveal the transient coupling of functional networks that support specific computational processes in language comprehension.

The influence of lexical statistics on temporal lobe cortical dynamics during spoken word listening

Neural representations of words are thought to have a complex spatio-temporal cortical basis. It has been suggested that spoken word recognition is not a process of feed-forward computations from phonetic to lexical forms, but rather involves the online integration of bottom-up input with stored lexical knowledge. Using direct neural recordings from the temporal lobe, we examined cortical responses to words and pseudowords. We found that neural populations were not only sensitive to lexical status (real vs. pseudo), but also to cohort size (number of words matching the phonetic input at each time point) and cohort frequency (lexical frequency of those words). These lexical variables modulated neural activity from the posterior to anterior temporal lobe, and also dynamically as the stimuli unfolded on a millisecond time scale. Our findings indicate that word recognition is not purely modular, but relies on rapid and online integration of multiple sources of lexical knowledge.

Changes in Theta and Beta Oscillations as Signatures of Novel Word Consolidation

The complementary learning systems account of word learning states that novel words, like other types of memories, undergo an offline consolidation process during which they are gradually integrated into the neocortical memory network. A fundamental change in the neural representation of a novel word should therefore occur in the hours after learning. The present EEG study tested this hypothesis by investigating whether novel words learned before a 24-hr consolidation period elicited more word-like oscillatory responses than novel words learned immediately before testing. In line with previous studies indicating that theta synchronization reflects lexical access, unfamiliar novel words elicited lower power in the theta band (4–8 Hz) than existing words. Recently learned words still showed a marginally lower theta increase than existing words, but theta responses to novel words that had been acquired 24 hr earlier were indistinguishable from responses to existing words. Consistent with evidence that beta desynchronization (16–21 Hz) is related to lexical-semantic processing, we found that both unfamiliar and recently learned novel words elicited less beta desynchronization than existing words. In contrast, no difference was found between novel words learned 24 hr earlier and existing words. These data therefore suggest that an offline consolidation period enables novel words to acquire lexically integrated, word-like neural representations.

Selective Neural Synchrony Suppression as a Forward Gatekeeper to Piecemeal Conscious Perception

The emergence of conscious visual perception is assumed to ignite late (∼250 ms) gamma-band oscillations shortly after an initial (∼100 ms) forward sweep of neural sensory (nonconscious) information. However, this neural evidence is not utterly congruent with rich behavioral data which rather point to piecemeal (i.e., graded) perceptual processing. To address the unexplored neural mechanisms of piecemeal ignition of conscious perception, hierarchical script sensitivity of the putative visual word form area (VWFA) was exploited to signal null (i.e., sensory), partial (i.e., letter-level), and full (i.e., word-level) conscious perception. Two magnetoencephalography experiments were conducted in which healthy human participants viewed masked words (Experiment I: active task, Dutch words; Experiment II: passive task, Hebrew words) while high-frequency (broadband gamma) brain activity was measured. Findings revealed that piecemeal conscious perception did not ignite a linear piecemeal increase in oscillations. Instead, whereas late (∼250 ms) gamma-band oscillations signaled full conscious perception (i.e., word-level), partial conscious perception (i.e., letter-level) was signaled via the inhibition of the early (∼100 ms) forward sweep. This inhibition regulates the downstream broadcast to filter out irrelevant (i.e., masks) information. The findings thus highlight a local (VWFA) gatekeeping mechanism for conscious perception, operating by filtering out and in selective percepts.

Associations of endogenous 17-β-estradiol with theta amplitude and performance in semantic categorization in young women

In semantic categorization processes, individuals form a relation between perceived or imagined objects and knowledge about these objects. In the present semantic categorization study, we correlated endogenous 17-β-estradiol levels (E2) with performance as well as amplitude of theta oscillations in young women (age 23.1±3.4 years). The semantic categorization task consisted of nouns representing either living or non-living items. Each item was characterized either by many or by few features. We identified parameters associated or not associated with menstrual cycle phases. Irrespective of the menstrual cycle phase, women (1) responded faster to living items as well as to nouns characterized by many features compared to non-living items and items characterized by few features, (2) showed higher accuracy to non-living items and items having many features, and (3) showed negative correlation between response time (RT) and theta amplitude. RT, accuracy and post-stimulus theta amplitude were not statistically significantly different among early follicular, late follicular or luteal women. In early follicular but not in late follicular or luteal women, we observed (1) a positive correlation between E2 and latency in RT, (2) a negative correlation between E2 and accuracy, and (3) a negative correlation between E2 and post-stimulus theta amplitude. A mosaic of menstrual cycle phase-dependent and -independent associations may indicate that a similar performance in each menstrual cycle phase is related to different modulation of synaptic activity by hormones.

A neuronal gamma oscillatory signature during morphological unification in the left occipitotemporal junction

Morphology is the aspect of language concerned with the internal structure of words. In the past decades, a large body of masked priming (behavioral and neuroimaging) data has suggested that the visual word recognition system automatically decomposes any morphologically complex word into a stem and its constituent morphemes. Yet the reliance of morphology on other reading processes (e.g., orthography and semantics), as well as its underlying neuronal mechanisms are yet to be determined. In the current magnetoencephalography study, we addressed morphology from the perspective of the unification framework, that is, by applying the Hold/Release paradigm, morphological unification was simulated via the assembly of internal morphemic units into a whole word. Trials representing real words were divided into words with a transparent (true) or a nontransparent (pseudo) morphological relationship. Morphological unification of truly suffixed words was faster and more accurate and additionally enhanced induced oscillations in the narrow gamma band (60-85 Hz, 260-440 ms) in the left posterior occipitotemporal junction. This neural signature could not be explained by a mere automatic lexical processing (i.e., stem perception), but more likely it related to a semantic access step during the morphological unification process. By demonstrating the validity of unification at the morphological level, this study contributes to the vast empirical evidence on unification across other language processes. Furthermore, we point out that morphological unification relies on the retrieval of lexical semantic associations via induced gamma band oscillations in a cerebral hub region for visual word form processing.

High frequency gamma activity in the left hippocampus predicts visual object naming performance

Access to an object's name requires the retrieval of an arbitrary association between it's identity and a word-label. The hippocampus is essential in retrieving arbitrary associations, and thus could be involved in retrieving the link between an object and its name. To test this hypothesis we recorded the iEEG signal from epileptic patients, directly implanted in the hippocampus, while they performed a picture naming task. High-frequency broadband gamma (50-150 Hz) responses were computed as an index of population-level spiking activity. Our results show, for the first time, single-trial hippocampal dynamics between visual confrontation and naming. Remarkably, the latency of the hippocampal response predicts naming latency, while inefficient hippocampal activation is associated with "tip-of-the-tongue" states (a failure to retrieve the name of a recognized object) suggesting that the hippocampus is an active component of the naming network and that its dynamics are closely related to efficient word production.

Fast dynamics of cortical functional and effective connectivity during word reading

We describe for the first time the fast dynamics of functional and effective (causal) connectivity during word reading. Independent component analysis of high-density EEG recorded during a word reading task recovered multiple sources of electrical brain activity previously identified by fMRI and PET. Results confirmed the ventral occipito-temporal cortex (vOT) as a central hub for word reading, showing a progression of theta-band (3–7 Hz) and gamma-band (30–50 Hz) phase synchronization and directed theta-band and gamma-band information flow with both early visual areas and high-level language-processing areas. These results highlight the interplay between local and long-distance neural dynamics involved at each stage of the reading process. Moreover, these measures of functional and causal connectivity dynamics may be used as a benchmark for comparison with clinical populations (e.g. individuals with developmental dyslexia), such that disturbances in connectivity dynamics may provide insight as to underlying neurological problems with language processing, and their potential remediation.

Gamma- and theta-band synchronization during semantic priming reflect local and long-range lexical-semantic networks

Anterior and posterior brain areas are involved in the storage and retrieval of semantic representations, but it is not known how these areas dynamically interact during semantic processing. We hypothesized that long-range theta-band coherence would reflect coupling of these areas and examined the oscillatory dynamics of lexical-semantic processing using a semantic priming paradigm with a delayed letter-search task while recording subjects' EEG. Time-frequency analysis revealed facilitation of semantic processing for Related compared to Unrelated conditions, which resulted in a reduced N400 and reduced gamma power from 150 to 450ms. Moreover, we observed greater anterior-posterior theta coherence for Unrelated compared to Related conditions over the time windows 150-425ms and 600-900ms. We suggest that while gamma power reflects activation of local functional networks supporting semantic representations, theta coherence indicates dynamic coupling of anterior and posterior areas for retrieval and post-retrieval processing and possibly an interaction between semantic relatedness and working memory.

The non-stop road from concrete to abstract: high concreteness causes the activation of long-range networks

Current grounding theories propose that sensory-motor brain systems are not only modulated by the comprehension of concrete but also partly of abstract language. In order to investigate whether concrete or abstract language elicits similar or distinct brain activity, neuronal synchronization patterns were investigated by means of long-range EEG coherence analysis. Participants performed a semantic judgment task with concrete and abstract sentences. EEG coherence between distant electrodes was analyzed in various frequencies before and during sentence processing using a bivariate AR-model with time-varying parameters. The theta frequency band (3–7 Hz) reflected common and different synchronization networks related to working memory processes and memory-related lexico-semantic retrieval during processing of both sentence types. In contrast, the beta1 band (13–18 Hz) showed prominent differences between both sentence types, whereby concrete sentences were associated with higher coherence implicating a more widespread range and intensity of mental simulation processes. The gamma band (35–40 Hz) reflected the sentences' congruency and indicated the more difficult integration of incongruent final nouns into the sentence context. Most importantly, findings support the notion that different cognitive operations during sentence processing are associated with multiple brain oscillations.