Neurobiology of Language最新文献

Speech motor learning depends on phonological working memory mechanisms in left posterior inferior frontal sulcus (LpIFS) and motor learning mechanisms in right cerebellum (RCbm). This study examines how transcranial direct current stimulation (tDCS), applied focally to these regions, affects speech production speed and accuracy when practicing novel syllables containing non-native consonant clusters. Healthy young adults (N = 105) practiced producing four pseudowords containing non-native clusters (e.g., "vzutp") with either anodal stimulation to LpIFS, anodal stimulation to RCbm, or no stimulation (i.e., sham; n = 35 participants per condition). Trained stimuli were produced more quickly and accurately than novel stimuli across all stimulation conditions. Overall accuracy (novel and trained combined) was higher after LpIFS stimulation compared to sham but not significantly different between LpIFS and RCbm stimulation, nor after RCbm stimulation compared to sham. The difference in accuracy between novel and trained stimuli (i.e., trained - novel accuracy) was higher after either LpIFS or RCbm stimulation compared to sham, indicating better learning of syllabic motor programs with excitation of these brain regions. No significant difference in trained - novel accuracy was found between LpIFS and RCbm stimulation. Our measure of speed (i.e., stimulus duration) was not differentially affected by stimulation condition. Taken together, these findings highlight the distinct contributions of phonological and motor learning mechanisms to non-native syllable acquisition and suggest that neural stimulation can enhance learning outcomes. Future research should explore the long-term retention of these effects and examine whether real-time feedback enhances learning outcomes.

Stroke affecting the basal ganglia and thalamus can lead to language deficits. In addition to the lesion's direct impact on language processing, connectional diaschisis involving cortical-subcortical interactions also plays a critical role. This study investigated connectional diaschisis using the dynamic meta-networking framework of language in patients with basal ganglia and thalamus stroke, analyzing longitudinal resting-state fMRI data collected at 2 weeks (n = 32), 3 months (n = 19), and 1 year post-stroke (n = 23). As expected, we observed dynamic cortico-subcortical interactions between cortical language regions and subcortical regions in healthy controls (HCs; n = 25). The cortical language network exhibited dynamic domain-segregation patterns in HCs, severely disrupted in the acute phase following stroke. The connectional diaschisis manifested as dual effects characterized by both hypo- and hyper-connectivity, which positively and negatively correlated with language deficits, respectively. State-specific changes in nodal and topological properties were also identified. Throughout language recovery, cortical language network dynamics gradually normalized toward suboptimal domain-segregation patterns, accompanied by the normalization of nodal and topological properties. These findings underscore the crucial role of cortico-subcortical interactions in language processing.

In hearing people visual word recognition relies on a hierarchical organization in left ventral occipitotemporal (vOT) cortex. While right hemisphere recruitment has been implicated in poor reading, this may not be the case for deaf readers as there is evidence that for skilled deaf readers the right vOT is also engaged during word recognition. However, the nature of representations along the vOT hierarchy and the degree of laterality in skilled deaf readers remain largely unknown. This study aimed to examine the hierarchical organization for written words in the vOT bilaterally for skill-matched deaf and hearing readers to determine whether deafness and phonological ability modulates the laterality of word-selectivity gradients. Using fMRI, we employed the same design as previous studies, presenting stimuli that represent a scale of orthographic regularity: consonant strings, pseudowords, and real words. For hearing readers, our results replicate previous findings showing a hierarchical structure solely in the left visual word form system (VWFS). For deaf readers, we find this same hierarchical structure in the left VWFS, but we also observe a similar hierarchical structure in the right VWFS. Unlike studies that show maladaptive right hemisphere activation in people with dyslexia, the bilateral tuning to written words seen in our study is not maladaptive since all participants were skilled readers. The bilateral hierarchical organization of the VWFS represents a unique neural signature for successful reading in deaf adults and suggests that the typical developmental shift from bilateral to predominantly left-lateralized processing is not necessary for successful reading.

Speaking is not only about retrieving words and structuring them into sentences; it also requires top-down control to plan and execute speech. In previous electrophysiological research with young adult speakers, mid-frontal theta oscillations have been observed using a picture-word interference paradigm. With this paradigm, participants name pictures while ignoring superimposed distractor words. In particular, mid-frontal theta power increases for categorically related distractors relative to other types of distractors, reflecting top-down interference control in resolving the competition between processing streams during word production. In the present study, we conceptually replicated the magnetoencephalography study by Piai, Roelofs, Jensen, et al. (2014) with an older group of healthy adults (mean age: 60 yr). Behaviorally, we replicated distractor semantic interference and Stroop-like interference effects typically observed in young adults. However, we did not find the corresponding theta modulation associated with these interference effects at the neural level. Instead, we found beta power decreases associated with interference control, mostly pronounced in the left posterior temporal and inferior parietal cortex. We further confirmed that these beta modulations were not present in the young adults' data. The distinct spectro-spatial-temporal profile of the oscillatory effects in the older population may reflect different underlying dynamics relative to the midline frontal effect previously found in young adult speakers. Our results indicate that the neural underpinnings of top-down interference control may be modified by aging and that the mid-frontal theta cannot be the exclusive oscillatory pattern enabling interference control during spoken word production.

Spoken language is central to human communication, influencing cognition, learning, and social interactions. Despite its spontaneous nature, characterized by disfluencies, fillers, self-corrections and irregular syntax, it effectively serves its communicative purpose. Understanding how the brain processes natural language offers valuable insights into the neurobiology of language. Recent neuroscience advancements allow us to study neural processes in response to ongoing speech, requiring detailed, time-locked descriptions of speech material to capture the nuances of spoken language. While there are many speech-to-text tools available, obtaining a time-locked true verbatim transcript, reflecting everything that was uttered, requires additional effort to achieve an accurate representation. We demonstrate the challenges involved in the process of obtaining time-resolved annotation of spontaneous speech, by presenting two semi-automatic pipelines, developed for German and Hebrew but adaptable to other languages. The outputs of these pipelines enable analyses of the neural representation and processing of key linguistic features. We discuss the methodological challenges and opportunities posed by current state-of-the-art pipelines, and advocate for new lines of natural language processing research aimed at advancing our understanding of how the brain processes everyday language.

This study investigates how selective auditory attention influences the lexical speech segmentation process to phonemes and words in a two competing speaker scenario. Using electroencephalography recordings from 20 participants, we applied temporal response function analysis to distinguish attention-driven neural activity to phoneme and word onsets for the attended and ignored speech stream separately. Our results reveal distinct attention effects for phoneme and word onsets. Phoneme onsets elicited significant selective attention effects at an early (18-94 ms, P1), middle (186-252 ms, P2), and late (302-382 ms, N2) time window. In contrast, word onsets showed attention effects only at a middle (192-280 ms, P2) and late (348-386 ms, N2) time window, occurring slightly later than phoneme-related effects. Prediction accuracy analyses demonstrated stronger model performance for the attended speech stream across all models, with notable improvements in prediction accuracy from a word model to a phoneme model to a combined word and phoneme model. These findings are in accordance with both hierarchical and parallel processing frameworks, where selective attention enhances lexical segmentation for attended speech, improving prediction accuracy. Early attention effects observed for phoneme onsets underscore their role in low-level speech processing, while late attention effects for word onsets may reflect higher level processing. This study highlights the importance of selective attention in neural speech tracking and provides insights into auditory processing mechanisms underlying speech comprehension in complex acoustic environments.

Left hemisphere stroke causes functional changes to the language network and may shift aspects of language processing to right hemisphere homotopes of perisylvian language regions. The result of right hemisphere recruitment is unclear. Studies suggest the right pars triangularis (rPTr) engagement in language processing corresponds to higher dysfunction. As a result, the region is a site for inhibitory neuromodulation, with evidence that inhibiting the region improves language function in persons with aphasia (PWA). However, studies have also found no relationship between rPTr functional activity and language performance in PWA. The mixed evidence regarding the rPTr suggests additional work is needed to understand the role of the region in PWA. We propose that the white matter connections that support communication between regions may be an important mediator. Thus, we sought to investigate if left hemisphere stroke leads to changes in the structural topological properties of the region. We used measures from network control theory (NCT) to compare the theoretical capacity of the rPTr to integrate communication across brain modules (i.e., boundary controllability [BC]) in the brain, in 60 PWA and 62 controls. We also examined whether BC corresponded to different aspects of language processing (i.e., semantic and phonological) in PWA. We found that PWA had a higher BC in the rPTr relative to controls. Higher BC was associated with fewer phonological errors in a picture naming task. These findings suggest that left hemisphere stroke causes shifts in the structural role of right hemisphere regions that relate to language processing in PWA.

Written language production is a fundamental aspect of daily communication, yet the neural pathways supporting it are far less studied than those for spoken language production. This study evaluated the contributions of speech-production pathways to written word production, specifically focusing on the central processes of word spelling rather than the motor production processes that support handwriting. Seventy-three English-speaking, neurotypical adults completed a spelling-to-dictation task and underwent diffusion MRI scans. The bilateral cerebello-thalamo-cortical pathways (CTC) and frontal aslant tract (FAT) were identified in individual participants using probabilistic tractography and automated segmentation tools. Fractional anisotropy (FA) values were computed along the trajectory of each tract and entered into correlation analyses with the spelling accuracy scores. A significant correlation was found between spelling accuracy scores and FA in the left CTC, which connects the left cerebellar hemisphere with the right cerebral hemisphere. This effect remained significant after controlling for spoken production measures. A similar trend was observed in the right homologous tract. In contrast, no significant correlations were identified between spelling accuracy scores and FA in the bilateral FAT. These findings demonstrate, for the first time, the involvement of cerebello-cerebral connections in spelling processes, aligning with the growing recognition regarding the role of the cerebellum in higher-order language functions. This effect did not generalize to the FAT, which may be relevant for more peripheral aspects of language production.

Individuals with post-stroke aphasia have long been observed to show relatively preserved musical and rhythm abilities in the presence of varied, and often profound, language impairments. Accordingly, speech-language pathologists frequently use rhythm-based strategies (e.g., tapping) to facilitate speech output in people with aphasia. However, there is little empirical work to support the clinical practice of using rhythm techniques. In this study, we investigated the neural bases of rhythm in aphasia by combining thorough behavioral rhythm assessments with structural brain imaging. Individuals with chronic, post-stroke aphasia (n = 33) and a matched neurotypical control group (n = 29) completed a rigorous battery of rhythm production and perception tasks. We found marked individual variability within the aphasia group, with about one third of individuals showing impaired rhythm processing, while the remaining two thirds performed within the control range. Using lesion-symptom mapping, we found that individual variability in tapping performance was associated with damage to a left temporoparietal area, extending into white matter specifically in the arcuate fasciculus. That is, individuals who struggled with tapping tended to have damage to this region. Tapping was also associated with language production scores, but not motor speech, in the aphasia group. These findings, which systematically link rhythm, language, and the brain, have the potential to be translated into clinical practice for understanding which patients may benefit the most from rhythm-based treatments. Our study in a population with focal brain injury complements evolutionary work highlighting the importance of the left temporoparietal region and underlying white matter for beat synchronization.

Prediction has become a key concept for understanding language comprehension, language production, and more recently reading. Recent studies suggest that predictive mechanisms in reading may be related to domain-general statistical learning (SL) abilities that support the extraction of regularities from sequential input. Both mechanisms have been discussed in relation to developmental dyslexia. Some suggest that SL is impaired in dyslexia with negative effects on the ability to make linguistic predictions. Others suggest that dyslexic readers rely to a greater extent on semantic and syntactic predictions to compensate for lower-level deficits. Here, we followed these two research questions in a single study. We therefore assessed the effects of semantic and syntactic prediction in reading and SL abilities in a population of university students with dyslexia and a group of typical readers using fMRI. The SL task was a serial reaction time (SRT) task that was performed inside and outside the scanner. The predictive reading task was performed in the scanner and used predictive versus nonpredictive semantic and syntactic contexts. Our results revealed distinct neural networks underlying semantic and syntactic predictions in reading, group differences in predictive processing in the left precentral gyrus and right anterior insula, and an association between predictive reading and SL, particularly in dyslexic readers. These findings contribute to our understanding of the interplay between SL, predictive processing, and compensation in dyslexia, providing new insights into the neural mechanisms that support reading.