Large-scale functional networks connect differently for processing words and symbol strings

Beta- and gamma-band cortico-cortical interactions support naturalistic reading of continuous text

Large-scale integration of information across cortical structures, building on neural connectivity, has been proposed to be a key element in supporting human cognitive processing. In electrophysiological neuroimaging studies of reading, quantification of neural interactions has been limited to the level of isolated words or sentences due to artefacts induced by eye movements. Here, we combined magnetoencephalography recording with advanced artefact rejection tools to investigate both cortico-cortical coherence and directed neural interactions during naturalistic reading of full-page texts. Our results show that reading versus visual scanning of text was associated with wide-spread increases of cortico-cortical coherence in the beta and gamma bands. We further show that the reading task was linked to increased directed neural interactions compared to the scanning task across a sparse set of connections within a wide range of frequencies. Together, the results demonstrate that neural connectivity flexibly builds on different frequency bands to support continuous natural reading.

Contribution and functional connectivity between cerebrum and cerebellum on sub-lexical and lexical-semantic processing of verbs

Language comprehension involves both sub-lexical (e.g., phonological) and lexical-semantic processing. We conducted a task using functional magnetic resonance imaging (fMRI) to compare the processing of verbs in these two domains. Additionally, we examined the representation of concrete-motor and abstract-non-motor concepts by including two semantic categories of verbs: motor and mental. The findings indicate that sub-lexical processing during the reading of pseudo-verbs primarily involves the left dorsal stream of the perisylvian network, while lexical-semantic representation during the reading of verbs predominantly engages the ventral stream. According to the embodied or grounded cognition approach, modality-specific mechanisms (such as sensory-motor systems) and the well-established multimodal left perisylvian network contribute to the semantic representation of both concrete and abstract verbs. Our study identified the visual system as a preferential modality-specific system for abstract-mental verbs, which exhibited functional connectivity with the right crus I/lobule VI of the cerebellum. Taken together, these results confirm the dissociation between sub-lexical and lexical-semantic processing and provide neurobiological evidence of functional coupling between specific visual modality regions and the right cerebellum, forming a network that supports the semantic representation of abstract concepts. Further, the results shed light on the underlying mechanisms of semantic processing and contribute to our understanding of how the brain processes abstract concepts.

Task-Modulated Corticocortical Synchrony in the Cognitive-Motor Network Supporting Handwriting

Both motor and cognitive aspects of behavior depend on dynamic, accurately timed neural processes in large-scale brain networks. Here, we studied synchronous interplay between cortical regions during production of cognitive-motor sequences in humans. Specifically, variants of handwriting that differed in motor variability, linguistic content, and memorization of movement cues were contrasted to unveil functional sensitivity of corticocortical connections. Data-driven magnetoencephalography mapping (n = 10) uncovered modulation of mostly left-hemispheric corticocortical interactions, as quantified by relative changes in phase synchronization. At low frequencies (~2–13 Hz), enhanced frontoparietal synchrony was related to regular handwriting, whereas premotor cortical regions synchronized for simple loop production and temporo-occipital areas for a writing task substituting normal script with loop patterns. At the beta-to-gamma band (~13–45 Hz), enhanced synchrony was observed for regular handwriting in the central and frontoparietal regions, including connections between the sensorimotor and supplementary motor cortices and between the parietal and dorsal premotor/precentral cortices. Interpreted within a modular framework, these modulations of synchrony mainly highlighted interactions of the putative pericentral subsystem of hand coordination and the frontoparietal subsystem mediating working memory operations. As part of cortical dynamics, interregional phase synchrony varies depending on task demands in production of cognitive-motor sequences.

Auditory cortex sensitivity to the loudness attribute of verbs

The auditory cortex was shown to be activated during the processing of words describing actions with acoustic features. The present study further examines whether processing visually presented action words characterized by different levels of loudness, i.e. "loud" (to shout) and "quiet" actions (to whisper), differentially engage the auditory cortex. Twenty healthy participants were measured with magnetoencephalography (MEG) while reading inflected verbs followed by a short tone and semantic tasks. Based on the results of a localizer task, loudness sensitive temporal Brodmann areas A22, A41/42, and pSTS were inspected in the word paradigm. "Loud" actions induced significantly stronger beta power suppression compared to "quiet" actions in the left hemisphere. Smaller N100m amplitude related to tones following "loud" compared to "quiet" actions confirmed that auditory cortex sensitivity was modulated by action words. Results point to possible selective auditory simulation mechanisms involved in verb processing and support embodiment theories.

Influence of reading skill and word length on fixation-related brain activity in school-aged children during natural reading

Word length is one of the main determinants of eye movements during reading and has been shown to influence slow readers more strongly than typical readers. The influence of word length on reading in individuals with different reading skill levels has been shown in separate eye-tracking and electroencephalography studies. However, the influence of reading difficulty on cortical correlates of word length effect during natural reading is unknown. To investigate how reading skill is related to brain activity during natural reading, we performed an exploratory analysis on our data set from a previous study, where slow reading (N = 27) and typically reading (N = 65) 12-to-13.5-year-old children read sentences while co-registered ET-EEG was recorded. We extracted fixation-related potentials (FRPs) from the sentences using the linear deconvolution approach. We examined standard eye-movement variables and deconvoluted FRP estimates: intercept of the response, categorical effect of first fixation versus additional fixation and continuous effect of word length. We replicated the pattern of stronger word length effect in eye movements for slow readers. We found a difference between typical readers and slow readers in the FRP intercept, which contains activity that is common to all fixations, within a fixation time-window of 50-300 ms. For both groups, the word length effect was present in brain activity during additional fixations; however, this effect was not different between groups. This suggests that stronger word length effect in the eye movements of slow readers might be mainly due re-fixations, which are more probable due to the lower efficiency of visual processing.

Analysis of Functional Connectivity and Oscillatory Power Using DICS: From Raw MEG Data to Group-Level Statistics in Python

Communication between brain regions is thought to be facilitated by the synchronization of oscillatory activity. Hence, large-scale functional networks within the brain may be estimated by measuring synchronicity between regions. Neurophysiological recordings, such as magnetoencephalography (MEG) and electroencephalography (EEG), provide a direct measure of oscillatory neural activity with millisecond temporal resolution. In this paper, we describe a full data analysis pipeline for functional connectivity analysis based on dynamic imaging of coherent sources (DICS) of MEG data. DICS is a beamforming technique in the frequency-domain that enables the study of the cortical sources of oscillatory activity and synchronization between brain regions. All the analysis steps, starting from the raw MEG data up to publication-ready group-level statistics and visualization, are discussed in depth, including methodological considerations, rules of thumb and tradeoffs. We start by computing cross-spectral density (CSD) matrices using a wavelet approach in several frequency bands (alpha, theta, beta, gamma). We then provide a way to create comparable source spaces across subjects and discuss the cortical mapping of spectral power. For connectivity analysis, we present a canonical computation of coherence that facilitates a stable estimation of all-to-all connectivity. Finally, we use group-level statistics to limit the network to cortical regions for which significant differences between experimental conditions are detected and produce vertex- and parcel-level visualizations of the different brain networks. Code examples using the MNE-Python package are provided at each step, guiding the reader through a complete analysis of the freely available openfMRI ds000117 “familiar vs. unfamiliar vs. scrambled faces” dataset. The goal is to educate both novice and experienced data analysts with the “tricks of the trade” necessary to successfully perform this type of analysis on their own data.