Revealing the dual streams of speech processing

Effects of attentional instructions on the behavioral and neural mechanisms of speech auditory feedback control

The present study investigated how instructions for paying attention to auditory feedback may affect speech error detection and sensorimotor control. Electroencephalography (EEG) and speech signals were recorded from 21 neurologically intact adult subjects while they produced the speech vowel sound /a/ and received randomized ±100 cents pitch-shift alterations in their real-time auditory feedback. Subjects were instructed to pay attention to their auditory feedback and press a button to indicate whether they detected a pitch-shift stimulus during trials. Data for this group was compared with 22 matched subjects who completed the same speech task under altered auditory feedback condition without attentional instructions. Results revealed a significantly smaller magnitude of speech compensations in the attentional-instruction vs. no-instruction group and a positive linear association between the magnitude of compensations and P2 event-related potential (ERP) amplitudes. In addition, we found that the amplitude of P2 ERP component was significantly larger in the attentional-instruction vs. no-instruction group. Source localization analysis showed that this effect was accounted for by significantly stronger neural activities in the right hemisphere insula, precentral gyrus, postcentral gyrus, transverse temporal gyrus, and superior temporal gyrus in the attentional-instruction group. These findings suggest that attentional instructions may enhance speech auditory feedback error detection, and subsequently improve sensorimotor control via generating more stable speech outputs (i.e., smaller compensations) in response to pitch-shift alterations. Our data are informative for advancing theoretical models and motivating targeted interventions with a focus on the role of attentional instructions for improving treatment outcomes in patients with motor speech disorders.

Structure-function interrelationships and associated neurotransmitter profiles in drug-naïve benign childhood epilepsy with central-temporal spikes patients

OBJECTIVES

To explore the interrelationships between structural and functional changes as well as the potential neurotransmitter profile alterations in drug-naïve benign childhood epilepsy with central-temporal spikes (BECTS) patients.

METHODS

Structural magnetic resonance imaging (sMRI) and resting-state functional MRI data from 20 drug-naïve BECTS patients and 33 healthy controls (HCs) were acquired. Parallel independent component analysis (P-ICA) was used to identify covarying components among gray matter volume (GMV) maps and fractional amplitude of low-frequency fluctuations (fALFF) maps. Furthermore, we explored the spatial correlations between GMV/fALFF changes derived from P-ICA and neurotransmitter maps in JuSpace toolbox.

RESULTS

A significantly positive correlation (p < 0.001) was identified between one structural component (GMV_IC6) and one functional component (fALFF_IC4), which showed significant group differences between drug-naïve BECTS patients and HCs (GMV_IC6: p < 0.01; fALFF_IC4: p < 0.001). GMV_IC6 showed increased GMV in the frontal lobe, temporal lobe, thalamus, and precentral gyrus as well as fALFF_IC4 had enhanced fALFF in the cerebellum in drug-naïve BECTS patients compared to HCs. Moreover, significant correlations between GMV alterations in GMV_IC6 and the serotonin (5HT1a: p < 0.001; 5HT2a: p < 0.001), norepinephrine (NAT: p < 0.001) and glutamate systems (mGluR5: p < 0.001) as well as between fALFF alterations in fALFF_IC4 and the norepinephrine system (NAT: p < 0.001) were detected.

CONCLUSION

The current findings suggest co-altered structural/functional components that reflect the correlation of language and motor networks as well as associated with the serotonergic, noradrenergic, and glutamatergic neurotransmitter systems.

CLINICAL RELEVANCE STATEMENT

The relationship between anatomical brain structure and intrinsic neural activity was evaluated using a multimodal fusion analysis and neurotransmitters which might provide an important window into the multimodal neural and underlying molecular mechanisms of benign childhood epilepsy with central-temporal spikes.

KEY POINTS

Structure-function relationships in drug-naïve benign childhood epilepsy with central-temporal spikes (BECTS) patients were explored. The interrelated structure-function components were found and correlated with the serotonin, norepinephrine, and glutamate systems. Co-altered structural/functional components reflect the correlation of language and motor networks and correlate with the specific neurotransmitter systems.

Spectrotemporal cortical dynamics and semantic control during sentence completion

OBJECTIVE

To investigate cortical oscillations during a sentence completion task (SC) using magnetoencephalography (MEG), focusing on the semantic control network (SCN), its leftward asymmetry, and the effects of semantic control load.

METHODS

Twenty right-handed adults underwent MEG while performing SC, consisting of low cloze (LC: multiple responses) and high cloze (HC: single response) stimuli. Spectrotemporal power modulations as event-related synchronizations (ERS) and desynchronizations (ERD) were analyzed: first, at the whole-brain level; second, in key SCN regions, posterior middle/inferior temporal gyri (pMTG/ITG) and inferior frontal gyri (IFG), under different semantic control loads.

RESULTS

Three cortical response patterns emerged: early (0-200 ms) theta-band occipital ERS; intermediate (200-700 ms) semantic network alpha/beta-band ERD; late (700-3000 ms) dorsal language stream alpha/beta/gamma-band ERD. Under high semantic control load (LC), pMTG/ITG showed prolonged left-sided engagement (ERD) and right-sided inhibition (ERS). Left IFG exhibited heightened late (2500-2550 ms) beta-band ERD with increased semantic control load (LC vs. HC).

CONCLUSIONS

SC involves distinct cortical responses and depends on the left IFG and asymmetric engagement of the pMTG/ITG for semantic control.

SIGNIFICANCE

Future use of SC in neuromagnetic preoperative language mapping and for understanding the pathophysiology of language disorders in neurological conditions.

Functional and Effective Connectivity Underlying Semantic Verbal Fluency

Semantic verbal fluency (SVF) impairment is present in several neurological disorders. Although activation in SVF-related areas has been reported, how these regions are connected and their functional roles in the network remain divergent. We assessed SVF static and dynamic functional connectivity (FC) and effective connectivity in healthy participants using functional magnetic resonance imaging. We observed activation in the inferior frontal (IFG), middle temporal (pMTG) and angular gyri (AG), anterior cingulate (AC), insular cortex, and regions of the superior, middle, and medial frontal gyri (SFG, MFG, MidFG). Our static FC analysis showed a highly interconnected task and resting state network. Increased connectivity of AC with the pMTG and AG was observed for the task. The dynamic FC analysis provided circuits with connections similarly modulated across time and regions related to category identification, language comprehension, word selection and recovery, word generation, inhibition of speaking, speech planning, and articulatory planning of orofacial movements. Finally, the effective connectivity analysis provided a network that best explained our data, starting at the AG and going to the pMTG, from which there was a division between the ventral and dorsal streams. The SFG and MFG regions were connected and modulated by the MidFG, while the inferior regions formed the ventral stream. Therefore, we successfully assessed the SVF network, exploring regions associated with the entire processing, from category identification to word generation. The methodological approach can be helpful for further investigation of the SVF network in neurological disorders.

Pars Opercularis Underlies Efferent Predictions and Successful Auditory Feedback Processing in Speech: Evidence From Left-Hemisphere Stroke

Hearing one's own speech allows for acoustic self-monitoring in real time. Left-hemisphere motor planning regions are thought to give rise to efferent predictions that can be compared to true feedback in sensory cortices, resulting in neural suppression commensurate with the degree of overlap between predicted and actual sensations. Sensory prediction errors thus serve as a possible mechanism of detection of deviant speech sounds, which can then feed back into corrective action, allowing for online control of speech acoustics. The goal of this study was to assess the integrity of this detection-correction circuit in persons with aphasia (PWA) whose left-hemisphere lesions may limit their ability to control variability in speech output. We recorded magnetoencephalography (MEG) while 15 PWA and age-matched controls spoke monosyllabic words and listened to playback of their utterances. From this, we measured speaking-induced suppression of the M100 neural response and related it to lesion profiles and speech behavior. Both speaking-induced suppression and cortical sensitivity to deviance were preserved at the group level in PWA. PWA with more spared tissue in pars opercularis had greater left-hemisphere neural suppression and greater behavioral correction of acoustically deviant pronunciations, whereas sparing of superior temporal gyrus was not related to neural suppression or acoustic behavior. In turn, PWA who made greater corrections had fewer overt speech errors in the MEG task. Thus, the motor planning regions that generate the efferent prediction are integral to performing corrections when that prediction is violated.

Lateralization of dorsal fiber tract targeting Broca's area concurs with language skills during development

Language is bounded to the left hemisphere in the adult brain and the functional lateralization can already be observed early during development. Here we investigate whether this is paralleled by a lateralization of the white matter structural language network. We analyze the strength and microstructural properties of language-related fiber tracts connecting temporal and frontal cortices with a separation of two dorsal tracts, one targeting the posterior Broca's area (BA44) and one targeting the precentral gyrus (BA6). In a large sample of young children (3-6 years), we demonstrate that, in contrast to the BA6-targeting tract, the microstructural asymmetry of the BA44-targeting fiber tract significantly correlates locally with different aspects of development. While the asymmetry in its anterior segment reflects age, the asymmetry in its posterior segment is associated with the children's language skills. These findings demonstrate a fine-grained structure-to-function mapping in the lateralized network and go beyond our current view of language-related human brain maturation.

Why did humans surpass all other primates? Are our brains so different? Part 1

This review is based on a conference presented in June 2023. Its main objective is to explain the cognitive differences between humans and non-human primates (NHPs) focusing on characteristics of their brains. It is based on the opinion of a clinical neurologist and does not intend to go beyond an overview of this complex topic. As language is the main characteristic differentiating humans from NHPs, this review is targeted at their brain networks related to language. NHPs have rudimentary forms of language, including primitive lexical/semantic signs. Humans have a much broader lexical/semantic repertory, but syntax is the most important characteristic, which is probably unique to Homo sapiens. Angular gyrus, Broca's area, temporopolar areas, and arcuate fascicle, are much more developed in humans. These differences may explain why NHPs did not develop a similar language to ours. Language had a profound influence on all other higher nervous activities.

Discourse- and lesion-based aphasia quotient estimation using machine learning

Discourse is a fundamentally important aspect of communication, and discourse production provides a wealth of information about linguistic ability. Aphasia commonly affects, in multiple ways, the ability to produce discourse. Comprehensive aphasia assessments such as the Western Aphasia Battery-Revised (WAB-R) are time- and resource-intensive. We examined whether discourse measures can be used to estimate WAB-R Aphasia Quotient (AQ), and whether this can serve as an ecologically valid, less resource-intensive measure. We used features extracted from discourse tasks using three AphasiaBank prompts involving expositional (picture description), story narrative, and procedural discourse. These features were used to train a machine learning model to predict the WAB-R AQ. We also compared and supplemented the model with lesion location information from structural neuroimaging. We found that discourse-based models could estimate AQ well, and that they outperformed models based on lesion features. Addition of lesion features to the discourse features did not improve the performance of the discourse model substantially. Inspection of the most informative discourse features revealed that different prompt types taxed different aspects of language. These findings suggest that discourse can be used to estimate aphasia severity, and provide insight into the linguistic content elicited by different types of discourse prompts.

Structural connectome combining DTI features predicts postoperative language decline and its recovery in glioma patients

OBJECTIVES

A decline in language function is a common complication after glioma surgery, affecting patients' quality of life and survival. This study predicts the postoperative decline in language function and whether it can be recovered based on the preoperative white matter structural network.

MATERIALS AND METHODS

Eighty-one right-handed patients with glioma involving the left hemisphere were retrospectively included. Their language function was assessed using the Western Aphasia Battery before and 1 week and 3 months after surgery. Structural connectome combining DTI features was selected to predict postoperative language decline and recovery. Nested cross-validation was used to optimize the models, evaluate the prediction performance of the models, and identify the most predictive features.

RESULTS

Five, seven, and seven features were finally selected as the predictive features in each model and used to establish predictive models for postoperative language decline (1 week after surgery), long-term language decline (3 months after surgery), and language recovery, respectively. The overall accuracy of the three models in nested cross-validation and overall area under the receiver operating characteristic curve were 0.840, 0.790, and 0.867, and 0.841, 0.778, and 0.901, respectively.

CONCLUSION

We used machine learning algorithms to establish models to predict whether the language function of glioma patients will decline after surgery and whether postoperative language deficit can recover, which may help improve the development of treatment strategies. The difference in features in the non-language decline or the language recovery group may reflect the structural basis for the protection and compensation of language function in gliomas.

CLINICAL RELEVANCE STATEMENT

Models can predict the postoperative language decline and whether it can recover in glioma patients, possibly improving the development of treatment strategies. The difference in selected features may reflect the structural basis for the protection and compensation of language function.

KEY POINTS

• Structural connectome combining diffusion tensor imaging features predicted glioma patients' language decline after surgery. • Structural connectome combining diffusion tensor imaging features predicted language recovery of glioma patients with postoperative language disorder. • Diffusion tensor imaging and connectome features related to language function changes imply plastic brain regions and connections.

Phase-encoded fMRI tracks down brainstorms of natural language processing with subsecond precision

Natural language processing unfolds information overtime as spatially separated, multimodal, and interconnected neural processes. Existing noninvasive subtraction-based neuroimaging techniques cannot simultaneously achieve the spatial and temporal resolutions required to visualize ongoing information flows across the whole brain. Here we have developed rapid phase-encoded designs to fully exploit the temporal information latent in functional magnetic resonance imaging data, as well as overcoming scanner noise and head-motion challenges during overt language tasks. We captured real-time information flows as coherent hemodynamic waves traveling over the cortical surface during listening, reading aloud, reciting, and oral cross-language interpreting tasks. We were able to observe the timing, location, direction, and surge of traveling waves in all language tasks, which were visualized as "brainstorms" on brain "weather" maps. The paths of hemodynamic traveling waves provide direct evidence for dual-stream models of the visual and auditory systems as well as logistics models for crossmodal and cross-language processing. Specifically, we have tracked down the step-by-step processing of written or spoken sentences first being received and processed by the visual or auditory streams, carried across language and domain-general cognitive regions, and finally delivered as overt speeches monitored through the auditory cortex, which gives a complete picture of information flows across the brain during natural language functioning. PRACTITIONER POINTS: Phase-encoded fMRI enables simultaneous imaging of high spatial and temporal resolution, capturing continuous spatiotemporal dynamics of the entire brain during real-time overt natural language tasks. Spatiotemporal traveling wave patterns provide direct evidence for constructing comprehensive and explicit models of human information processing. This study unlocks the potential of applying rapid phase-encoded fMRI to indirectly track the underlying neural information flows of sequential sensory, motor, and high-order cognitive processes.

Features of the speech processing network in post- and prelingually deaf cochlear implant users

The onset of hearing loss can lead to altered brain structure and functions. However, hearing restoration may also result in distinct cortical reorganization. A differential pattern of functional remodeling was observed between post- and prelingual cochlear implant users, but it remains unclear how these speech processing networks are reorganized after cochlear implantation. To explore the impact of language acquisition and hearing restoration on speech perception in cochlear implant users, we conducted assessments of brain activation, functional connectivity, and graph theory-based analysis using functional near-infrared spectroscopy. We examined the effects of speech-in-noise stimuli on three groups: postlingual cochlear implant users (n = 12), prelingual cochlear implant users (n = 10), and age-matched individuals with hearing controls (HC) (n = 22). The activation of auditory-related areas in cochlear implant users showed a lower response compared with the HC group. Wernicke's area and Broca's area demonstrated differences network attributes in speech processing networks in post- and prelingual cochlear implant users. In addition, cochlear implant users maintain a high efficiency of the speech processing network to process speech information. Taken together, our results characterize the speech processing networks, in varying noise environments, in post- and prelingual cochlear implant users and provide new insights for theories of how implantation modes impact remodeling of the speech processing functional networks.

Aging effects on dual-route speech processing networks during speech perception in noise

Healthy aging leads to complex changes in the functional network of speech processing in a noisy environment. The dual-route neural architecture has been applied to the study of speech processing. Although evidence suggests that senescent increases activity in the brain regions across the dorsal and ventral stream regions to offset reduced periphery, the regulatory mechanism of dual-route functional networks underlying such compensation remains largely unknown. Here, by utilizing functional near-infrared spectroscopy (fNIRS), we investigated the compensatory mechanism of the dual-route functional connectivity, and its relationship with healthy aging by using a speech perception task at varying signal-to-noise ratios (SNR) in healthy individuals (young adults, middle-aged adults, and older adults). Results showed that the speech perception scores showed a significant age-related decrease with the reduction of the SNR. The analysis results of dual-route speech processing networks showed that the functional connection of Wernicke's area and homolog Wernicke's area were age-related increases. Further to clarify the age-related characteristics of the dual-route speech processing networks, graph-theoretical network analysis revealed an age-related increase in the efficiency of the networks, and the age-related differences in nodal characteristics were found both in Wernicke's area and homolog Wernicke's area under noise environment. Thus, Wernicke's area might be a key network hub to maintain efficient information transfer across the speech process network with healthy aging. Moreover, older adults would recruit more resources from the homologous Wernicke's area in a noisy environment. The recruitment of the homolog of Wernicke's area might provide a means of compensation for older adults for decoding speech in an adverse listening environment. Together, our results characterized dual-route speech processing networks at varying noise environments and provided new insight for the compensatory theories of how aging modulates the dual-route speech processing functional networks.

Network-based statistics distinguish anomic and Broca's aphasia

INTRODUCTION

Aphasia is a speech-language impairment commonly caused by damage to the left hemisphere. The neural mechanisms that underpin different types of aphasia and their symptoms are still not fully understood. This study aims to identify differences in resting-state functional connectivity between anomic and Broca's aphasia measured through resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS

We used the network-based statistic (NBS) method, as well as voxel- and connectome-based lesion symptom mapping (V-, CLSM), to identify distinct neural correlates of the anomic and Broca's groups. To control for lesion effect, we included lesion volume as a covariate in both the NBS method and LSM.

RESULTS

NBS identified a subnetwork located in the dorsal language stream bilaterally, including supramarginal gyrus, primary sensory, motor, and auditory cortices, and insula. The connections in the subnetwork were weaker in the Broca's group than the anomic group. The properties of the subnetwork were examined through complex network measures, which indicated that regions in right inferior frontal sulcus, right paracentral lobule, and bilateral superior temporal gyrus exhibit intensive interaction. Left superior temporal gyrus, right postcentral gyrus, and left supramarginal gyrus play an important role in information flow and overall communication efficiency. Disruption of this network underlies the constellation of symptoms associated with Broca's aphasia. Whole-brain CLSM did not detect any significant connections, suggesting an advantage of NBS when thousands of connections are considered. However, CLSM identified connections that differentiated Broca's from anomic aphasia when analysis was restricted to a hypothesized network of interest.

DISCUSSION

We identified novel signatures of resting-state brain network differences between groups of individuals with anomic and Broca's aphasia. We identified a subnetwork of connections that statistically differentiated the resting-state brain networks of the two groups, in comparison with standard CLSM results that yielded isolated connections. Network-level analyses are useful tools for the investigation of the neural correlates of language deficits post-stroke.

Longitudinal Progression of White Matter Hyperintensity Severity in Chronic Stroke Aphasia

Objective

To determine whether longitudinal progression of small vessel disease in chronic stroke survivors is associated with longitudinal worsening of chronic aphasia severity.

Design

A longitudinal retrospective study. Severity of white matter hyperintensities (WMHs) as a marker for small vessel disease was assessed on fluid-attenuated inversion recovery (FLAIR) scans using the Fazekas scale, with ratings for deep WMHs (DWMHs) and periventricular WMHs (PVHs).

Setting

University research laboratories.

Participants

This study includes data from 49 chronic stroke survivors with aphasia (N=49; 15 women, 34 men, age range=32-81 years, >6 months post-stroke, stroke type: [46 ischemic, 3 hemorrhagic], community dwelling). All participants completed the Western Aphasia Battery-Revised (WAB) and had FLAIR scans at 2 timepoints (average years between timepoints: 1.87 years, SD=3.21 years).

Interventions

Not applicable.

Main Outcome Measures

Change in white matter hyperintensity severity (calculated using the Fazekas scale) and change in aphasia severity (difference in Western Aphasia Battery scores) were calculated between timepoints. Separate stepwise regression models were used to identify predictors of WMH severity change, with lesion volume, age, time between timepoints, body mass index (BMI), and presence of diabetes as independent variables. Additional stepwise regression models investigated predictors of change in aphasia severity, with PVH change, DWMH change, lesion volume, time between timepoints, and age as independent predictors.

Results

22.5% of participants (11/49) had increased WMH severity. Increased BMI was associated with increases in PVH severity (P=.007), whereas the presence of diabetes was associated with increased DWMH severity (P=.002). Twenty-five percent of participants had increased aphasia severity which was significantly associated with increased severity of PVH (P<.001, 16.8% variance explained).

Conclusion

Increased small vessel disease burden is associated with contributing to chronic changes in aphasia severity. These findings support the idea that good cardiovascular risk factor control may play an important role in the prevention of long-term worsening of aphasic symptoms.

Degeneracy in the neurological model of auditory speech repetition

Both classic and contemporary models of auditory word repetition involve at least four left hemisphere regions: primary auditory cortex for processing sounds; pSTS (within Wernicke's area) for processing auditory images of speech; pOp (within Broca's area) for processing motor images of speech; and primary motor cortex for overt speech articulation. Previous functional-MRI (fMRI) studies confirm that auditory repetition activates these regions, in addition to many others. Crucially, however, contemporary models do not specify how regions interact and drive each other during auditory repetition. Here, we used dynamic causal modelling, to test the functional interplay among the four core brain regions during single auditory word and pseudoword repetition. Our analysis is grounded in the principle of degeneracy-i.e., many-to-one structure-function relationships-where multiple neural pathways can execute the same function. Contrary to expectation, we found that, for both word and pseudoword repetition, (i) the effective connectivity between pSTS and pOp was predominantly bidirectional and inhibitory; (ii) activity in the motor cortex could be driven by either pSTS or pOp; and (iii) the latter varied both within and between individuals. These results suggest that different neural pathways can support auditory speech repetition. This degeneracy may explain resilience to functional loss after brain damage.

A prospective 5-year longitudinal study detects neurocognitive and imaging correlates of seizure remission in self-limiting Rolandic epilepsy

OBJECTIVE

Self-limiting Rolandic epilepsy (RE) is the most common epilepsy in school-age children. Seizures are generally infrequent, but cognitive, language, and motor coordination problems can significantly impact the child's life. To better understand brain structure and function changes in RE, we longitudinally assessed neurocognition, cortical thickness, and subcortical volumes.

METHODS

At baseline, we recruited 30 participants diagnosed with RE and 24-healthy controls and followed up for 4.94 ± 0.8 years when the participants with RE were in seizure remission. Measures included were as follows: T1-weighted magnetic resonance brain imaging (MRI) with FreeSurfer analysis and detailed neuropsychological assessments. MRI and neuropsychological data were compared between baseline and follow-up in seizure remission.

RESULTS

Longitudinal MRI revealed excess cortical thinning in the left-orbitofrontal (p = 0.0001) and pre-central gyrus (p = 0.044). There is a significant association (p = 0.003) between a reduction in cortical thickness in the left-orbitofrontal cluster and improved processing of filtered words. Longitudinal neuropsychology revealed significant improvements in the symptoms of developmental coordination disorder (DCD, p = 0.005) in seizure remission.

CONCLUSIONS

There is evidence for altered development of neocortical regions between active seizure state and seizure remission in RE within two clusters maximal in the left-orbitofrontal and pre-central gyrus. There is significant evidence for improvement in motor coordination between active seizures and seizure remission and suggestive evidence for a decline in fluid intelligence and gains in auditory processing.

Effects of Damage to the Integrity of the Left Dual-Stream Frontotemporal Network Mediated by the Arcuate Fasciculus and Uncinate Fasciculus on Acute/Subacute Post-Stroke Aphasia

(1) Background: To investigate the correlation between the integrity of the left dual-stream frontotemporal network mediated by the arcuate fasciculus (AF) and uncinate fasciculus (UF), and acute/subacute post-stroke aphasia (PSA). (2) Methods: Thirty-six patients were recruited and received both a language assessment and a diffusion tensor imaging (DTI) scan. Correlations between diffusion indices in the bilateral LSAF/UF and language performance assessment were analyzed with correlation analyses. Multiple linear regression analysis was also implemented to investigate the effects of the integrity of the left LSAF/UF on language performance. (3) Results: Correlation analyses showed that the diffusion indices, including mean fractional anisotropy (FA) values and the fiber number of the left LSAF rather than the left UF was significantly positively associated with language domain scores (p < 0.05). Multiple linear regression analysis revealed an independent and positive association between the mean FA value of the left LSAF and the percentage score of language subsets. In addition, no interaction effect of the integrity of the left LSAF and UF on language performance was found (p > 0.05). (4) Conclusions: The integrity of the left LSAF, but not the UF, might play important roles in supporting residual language ability in individuals with acute/subacute PSA; simultaneous disruption of the dual-stream frontotemporal network mediated by the left LSAF and UF would not result in more severe aphasia than damage to either pathway alone.

Neural oscillations reveal disrupted functional connectivity associated with impaired speech auditory feedback control in post-stroke aphasia

The oscillatory brain activities reflect neuro-computational processes that are critical for speech production and sensorimotor control. In the present study, we used neural oscillations in left-hemisphere stroke survivors with aphasia as a model to investigate network-level functional connectivity deficits associated with disrupted speech auditory feedback control. Electroencephalography signals were recorded from 40 post-stroke aphasia and 39 neurologically intact control participants while they performed speech vowel production and listening tasks under pitch-shifted altered auditory feedback (AAF) conditions. Using weighted phase-lag index, we calculated broadband (1-70 Hz) functional neural connectivity between electrode pairs covering the frontal, pre- and post-central, and parietal regions. Results revealed reduced fronto-central delta and theta band and centro-parietal low-beta band connectivity in left-hemisphere electrodes associated with diminished speech AAF compensation responses in post-stroke aphasia compared with controls. Lesion-mapping analysis demonstrated that stroke-induced damage to multi-modal brain networks within the inferior frontal gyrus, Rolandic operculum, inferior parietal lobule, angular gyrus, and supramarginal gyrus predicted the reduced functional neural connectivity within the delta and low-beta bands during both tasks in aphasia. These results provide evidence that disrupted neural connectivity due to left-hemisphere brain damage can result in network-wide dysfunctions associated with impaired sensorimotor integration mechanisms for speech auditory feedback control.

Hodological organization of spoken language production and singing in the human brain

Theories expounding the neural relationship between speech and singing range from sharing neural circuitry, to relying on opposite hemispheres. Yet, hodological studies exploring their shared and distinct neural networks remain scarce. In this study, we combine a white matter connectometry approach together with comprehensive and naturalistic appraisal of verbal expression during spoken language production and singing in a sample of individuals with post-stroke aphasia. Our results reveal that both spoken language production and singing are mainly supported by the left hemisphere language network and projection pathways. However, while spoken language production mostly engaged dorsal and ventral streams of speech processing, singing was associated primarily with the left ventral stream. These findings provide evidence that speech and singing share core neuronal circuitry within the left hemisphere, while distinct ventral stream contributions explain frequently observed dissociations in aphasia. Moreover, the results suggest prerequisite biomarkers for successful singing-based therapeutic interventions.

The low dimensionality of post-stroke cognitive deficits: it's the lesion anatomy!

For years, dissociation studies on neurological single-case patients with brain lesions were the dominant method to infer fundamental cognitive functions in neuropsychology. In contrast, the association between deficits was considered to be of less epistemological value. Still, associational computational methods for dimensionality reduction-such as principal component analysis or factor analysis-became popular for the identification of fundamental cognitive functions and to understand human cognitive brain architecture from post-stroke neuropsychological profiles. In the present in silico study with lesion imaging of 300 stroke patients, we investigated the dimensionality of artificial simulated neuropsychological profiles that exclusively contained independent fundamental cognitive functions without any underlying low-dimensional cognitive architecture. Still, the anatomy of stroke lesions alone was sufficient to create a dependence between variables that allowed a low-dimensional description of the data with principal component analysis. All criteria that we used to estimate the dimensionality of data, including the Kaiser criterion, were strongly affected by lesion anatomy, while the Joliffe criterion provided the least affected estimates. The dimensionality of profiles was reduced by 62-70% for the Kaiser criterion, up to the degree that is commonly found in neuropsychological studies on actual cognitive measures. The interpretability of such low-dimensional factors as deficits of fundamental cognitive functions and their provided insights into human cognitive architecture thus seem to be severely limited, and the heavy focus of current cognitive neuroscience on group studies and associations calls for improvements. We suggest that qualitative criteria and dissociation patterns could be used to refine estimates for the dimensionality of the cognitive architecture behind post-stroke deficits. Further, given the strong impact of lesion anatomy on the associational structure of data, we see the need for further optimization of interpretation strategies of computational factors in post-stroke lesion studies of cognitive deficits.

Phase-encoded fMRI tracks down brainstorms of natural language processing with sub-second precision

The human language system interacts with cognitive and sensorimotor regions during natural language processing. However, where, when, and how these processes occur remain unclear. Existing noninvasive subtraction-based neuroimaging techniques cannot simultaneously achieve the spatial and temporal resolutions required to visualize ongoing information flows across the whole brain. Here we have developed phase-encoded designs to fully exploit the temporal information latent in functional magnetic resonance imaging (fMRI) data, as well as overcoming scanner noise and head-motion challenges during overt language tasks. We captured neural information flows as coherent waves traveling over the cortical surface during listening, reciting, and oral cross-language interpreting. The timing, location, direction, and surge of traveling waves, visualized as 'brainstorms' on brain 'weather' maps, reveal the functional and effective connectivity of the brain in action. These maps uncover the functional neuroanatomy of language perception and production and motivate the construction of finer-grained models of human information processing.

Aberrant modulation of broadband neural oscillations reflects vocal sensorimotor deficits in post-stroke aphasia

OBJECTIVE

The present study investigated the neural oscillatory correlates of impaired vocal sensorimotor control in left-hemisphere stroke.

METHODS

Electroencephalography (EEG) signals were recorded from 34 stroke and 46 control subjects during speech vowel vocalization and listening tasks under normal and pitch-shifted auditory feedback.

RESULTS

Time-frequency analyses revealed aberrantly decreased theta (4-8 Hz) and increased gamma band (30-80 Hz) power in frontal and posterior parieto-occipital regions as well as reduced alpha (8-13 Hz) and beta (13-30 Hz) desynchronization over sensorimotor areas before speech vowel vocalization in left-hemisphere stroke compared with controls. Subjects with the stroke also presented with aberrant modulation of broadband (4-80 Hz) neural oscillations over sensorimotor regions after speech vowel onset during vocalization and listening under normal and altered auditory feedback. We found that the atypical pattern of broadband neural oscillatory modulation was correlated with diminished vocal feedback error compensation behavior and the severity of co-existing language-related aphasia symptoms associated with left-hemisphere stroke.

CONCLUSIONS

These findings indicate complex interplays between the underlying mechanisms of speech and language and their deficits in post-stroke aphasia.

SIGNIFICANCE

Our data motivate the notion of studying neural oscillatory dynamics as a critical component for the examination of speech and language disorders in post-stroke aphasia.

The domain-separation language network dynamics in resting state support its flexible functional segregation and integration during language and speech processing

Modern linguistic theories and network science propose that language and speech processing are organized into hierarchical, segregated large-scale subnetworks, with a core of dorsal (phonological) stream and ventral (semantic) stream. The two streams are asymmetrically recruited in receptive and expressive language or speech tasks, which showed flexible functional segregation and integration. We hypothesized that the functional segregation of the two streams was supported by the underlying network segregation. A dynamic conditional correlation approach was employed to construct framewise time-varying language networks and k-means clustering was employed to investigate the temporal-reoccurring patterns. We found that the framewise language network dynamics in resting state were robustly clustered into four states, which dynamically reconfigured following a domain-separation manner. Spatially, the hub distributions of the first three states highly resembled the neurobiology of speech perception and lexical-phonological processing, speech production, and semantic processing, respectively. The fourth state was characterized by the weakest functional connectivity and was regarded as a baseline state. Temporally, the first three states appeared exclusively in limited time bins (∼15%), and most of the time (> 55%), state 4 was dominant. Machine learning-based dFC-linguistics prediction analyses showed that dFCs of the four states significantly predicted individual linguistic performance. These findings suggest a domain-separation manner of language network dynamics in resting state, which forms a dynamic "meta-network" framework to support flexible functional segregation and integration during language and speech processing.

Brain Areas Critical for Picture Naming: A Systematic Review and Meta-Analysis of Lesion-Symptom Mapping Studies

Lesion-symptom mapping (LSM) studies have revealed brain areas critical for naming, typically finding significant associations between damage to left temporal, inferior parietal, and inferior fontal regions and impoverished naming performance. However, specific subregions found in the available literature vary. Hence, the aim of this study was to perform a systematic review and meta-analysis of published lesion-based findings, obtained from studies with unique cohorts investigating brain areas critical for accuracy in naming in stroke patients at least 1 month post-onset. An anatomic likelihood estimation (ALE) meta-analysis of these LSM studies was performed. Ten papers entered the ALE meta-analysis, with similar lesion coverage over left temporal and left inferior frontal areas. This small number is a major limitation of the present study. Clusters were found in left anterior temporal lobe, posterior temporal lobe extending into inferior parietal areas, in line with the arcuate fasciculus, and in pre- and postcentral gyri and middle frontal gyrus. No clusters were found in left inferior frontal gyrus. These results were further substantiated by examining five naming studies that investigated performance beyond global accuracy, corroborating the ALE meta-analysis results. The present review and meta-analysis highlight the involvement of left temporal and inferior parietal cortices in naming, and of mid to posterior portions of the temporal lobe in particular in conceptual-lexical retrieval for speaking.

Precision fMRI reveals that the language-selective network supports both phrase-structure building and lexical access during language production

A fronto-temporal brain network has long been implicated in language comprehension. However, this network's role in language production remains debated. In particular, it remains unclear whether all or only some language regions contribute to production, and which aspects of production these regions support. Across 3 functional magnetic resonance imaging experiments that rely on robust individual-subject analyses, we characterize the language network's response to high-level production demands. We report 3 novel results. First, sentence production, spoken or typed, elicits a strong response throughout the language network. Second, the language network responds to both phrase-structure building and lexical access demands, although the response to phrase-structure building is stronger and more spatially extensive, present in every language region. Finally, contra some proposals, we find no evidence of brain regions-within or outside the language network-that selectively support phrase-structure building in production relative to comprehension. Instead, all language regions respond more strongly during production than comprehension, suggesting that production incurs a greater cost for the language network. Together, these results align with the idea that language comprehension and production draw on the same knowledge representations, which are stored in a distributed manner within the language-selective network and are used to both interpret and generate linguistic utterances.

Bayesian stroke modeling details sex biases in the white matter substrates of aphasia

Ischemic cerebrovascular events often lead to aphasia. Previous work provided hints that such strokes may affect women and men in distinct ways. Women tend to suffer strokes with more disabling language impairment, even if the lesion size is comparable to men. In 1401 patients, we isolate data-led representations of anatomical lesion patterns and hand-tailor a Bayesian analytical solution to carefully model the degree of sex divergence in predicting language outcomes ~3 months after stroke. We locate lesion-outcome effects in the left-dominant language network that highlight the ventral pathway as a core lesion focus across different tests of language performance. We provide detailed evidence for sex-specific brain-behavior associations in the domain-general networks associated with cortico-subcortical pathways, with unique contributions of the fornix in women and cingular fiber bundles in men. Our collective findings suggest diverging white matter substrates in how stroke causes language deficits in women and men. Clinically acknowledging such sex disparities has the potential to improve personalized treatment for stroke patients worldwide.

Comparing the brain-behaviour relationship in acute and chronic stroke aphasia

In stroke aphasia, lesion volume is typically associated with aphasia severity. Although this relationship is likely present throughout recovery, different factors may affect lesion volume and behaviour early into recovery (acute) and in the later stages of recovery (chronic). Therefore, studies typically separate patients into two groups (acute/chronic), and this is often accompanied with arguments for and against using data from acute stroke patients over chronic. However, no comprehensive studies have provided strong evidence of whether the lesion-behaviour relationship early in recovery is comparable to later in the recovery trajectory. To that end, we investigated two aims: (i) whether lesion data from acute and chronic patients yield similar results in region-based lesion-symptom mapping analyses and (ii) if models based on one timepoint accurately predict the other. Lesions and aphasia severity scores from acute (N = 63) and chronic (N = 109) stroke survivors with aphasia were entered into separate univariate region-based lesion-symptom mapping analyses. A support vector regression model was trained on lesion data from either the acute or chronic data set to give an estimate of aphasia severity. Four model-based analyses were conducted: trained on acute/chronic using leave-one-out, tested on left-out behaviour or trained on acute/chronic to predict the other timepoint. Region-based lesion-symptom mapping analyses identified similar but not identical regions in both timepoints. All four models revealed positive correlations between actual and predicted Western Aphasia Battery-Revised aphasia-quotient scores. Lesion-to-behaviour predictions were almost equivalent when comparing within versus across stroke stage, despite differing lesion size/locations and distributions of aphasia severity between stroke timepoints. This suggests that research investigating the brain-behaviour relationship including subsets of patients from only one timepoint may also be applicable at other timepoints, although it is important to note that these comparable findings may only be seen using broad measures such as aphasia severity, rather than those aimed at identifying more specific deficits. Subtle differences found between timepoints may also be useful in understanding the nature of lesion volume and aphasia severity over time. Stronger correlations found when predicting acute behaviour (e.g. predicting acute: r = 0.6888, P < 0.001, predicting chronic r = 0.5014, P < 0.001) suggest that the acute lesion/perfusion patterns more accurately capture the critical changes in underlying vascular territories. Differences in critical brain regions between timepoints may shed light on recovery patterns. Future studies could focus on a longitudinal design to compare acute and chronic patients in a more controlled manner.

Language Network Dysfunction and Formal Thought Disorder in Schizophrenia

BACKGROUND

Pathophysiological inquiries into schizophrenia require a consideration of one of its most defining features: disorganization and impoverishment in verbal behavior. This feature, often captured using the term Formal Thought Disorder (FTD), still remains to be one of the most poorly understood and understudied dimensions of schizophrenia. In particular, the large-scale network level dysfunction that contributes to FTD remains obscure to date.

STUDY DESIGN

In this narrative review, we consider the various challenges that need to be addressed for us to move towards mapping FTD (construct) to a brain network level account (circuit).

STUDY RESULTS

The construct-to-circuit mapping goal is now becoming more plausible than it ever was, given the parallel advent of brain stimulation and the tools providing objective readouts of human speech. Notwithstanding this, several challenges remain to be overcome before we can decisively map the neural basis of FTD. We highlight the need for phenotype refinement, robust experimental designs, informed analytical choices, and present plausible targets in and beyond the Language Network for brain stimulation studies in FTD.

CONCLUSIONS

Developing a therapeutically beneficial pathophysiological model of FTD is a challenging endeavor, but holds the promise of improving interpersonal communication and reducing social disability in schizophrenia. Addressing the issues raised in this review will be a decisive step in this direction.

Advanced Brain Age and Chronic Poststroke Aphasia Severity

BACKGROUND AND OBJECTIVES

Chronic poststroke language impairment is typically worse in older individuals or those with large stroke lesions. However, there is unexplained variance that likely depends on intact tissue beyond the lesion. Brain age is an emerging concept, which is partially independent from chronologic age. Advanced brain age is associated with cognitive decline in healthy older adults; therefore, we aimed to investigate the relationship with stroke aphasia. We hypothesized that advanced brain age is a significant factor associated with chronic poststroke language impairments, above and beyond chronologic age, and lesion characteristics.

METHODS

This cohort study retrospectively evaluated participants from the Predicting Outcomes of Language Rehabilitation in Aphasia clinical trial (NCT03416738), recruited through local advertisement in South Carolina (US). Primary inclusion criteria were left hemisphere stroke and chronic aphasia (≥12 months after stroke). Participants completed baseline behavioral testing including the Western Aphasia Battery-Revised (WAB-R), Philadelphia Naming Test (PNT), Pyramids and Palm Trees Test (PPTT), and Wechsler Adult Intelligence Scale Matrices subtest, before completing 6 weeks of language therapy. The PNT was repeated 1 month after therapy. We leveraged modern neuroimaging techniques to estimate brain age and computed a proportional difference between chronologic age and estimated brain age. Multiple linear regression models were used to evaluate the relationship between proportional brain age difference (PBAD) and behavior.

RESULTS

Participants (N = 93, 58 males and 35 females, average age = 61 years) had estimated brain ages ranging from 14 years younger to 23 years older than chronologic age. Advanced brain age predicted performance on semantic tasks (PPTT) and language tasks (WAB-R). For participants with advanced brain aging (n = 47), treatment gains (improvement on the PNT) were independently predicted by PBAD (T = -2.0474, p = 0.0468, 9% of variance explained).

DISCUSSION

Through the application of modern neuroimaging techniques, advanced brain aging was associated with aphasia severity and performance on semantic tasks. Notably, therapy outcome scores were also associated with PBAD, albeit only among participants with advanced brain aging. These findings corroborate the importance of brain age as a determinant of poststroke recovery and underscore the importance of personalized health factors in determining recovery trajectories, which should be considered during the planning or implementation of therapeutic interventions.

Network-based statistics distinguish anomic and Broca aphasia

Aphasia is a speech-language impairment commonly caused by damage to the left hemisphere. Due to the complexity of speech-language processing, the neural mechanisms that underpin various symptoms between different types of aphasia are still not fully understood. We used the network-based statistic method to identify distinct subnetwork(s) of connections differentiating the resting-state functional networks of the anomic and Broca groups. We identified one such subnetwork that mainly involved the brain regions in the premotor, primary motor, primary auditory, and primary sensory cortices in both hemispheres. The majority of connections in the subnetwork were weaker in the Broca group than the anomic group. The network properties of the subnetwork were examined through complex network measures, which indicated that the regions in the superior temporal gyrus and auditory cortex bilaterally exhibit intensive interaction, and primary motor, premotor and primary sensory cortices in the left hemisphere play an important role in information flow and overall communication efficiency. These findings underlied articulatory difficulties and reduced repetition performance in Broca aphasia, which are rarely observed in anomic aphasia. This research provides novel findings into the resting-state brain network differences between groups of individuals with anomic and Broca aphasia. We identified a subnetwork of, rather than isolated, connections that statistically differentiate the resting-state brain networks of the two groups, in comparison with standard lesion symptom mapping results that yield isolated connections.

Possible Effects of Acupuncture in Poststroke Aphasia

Neural plasticity promotes the reorganization of language networks and is an essential recovery mechanism for poststroke aphasia (PSA). Neuroplasticity may be a pivotal bridge to elucidate the potential recovery mechanisms of acupuncture for aphasia. Therefore, understanding the neuroplasticity mechanism of acupuncture in PSA is crucial. However, the underlying therapeutic mechanism of neuroplasticity in PSA after acupuncture needs to be explored. Excitotoxicity after brain injury affects the activity of neurotransmitters and disrupts the transmission of normal neuron information. Thus, a helpful strategy of acupuncture might be to improve PSA by affecting the availability of these neurotransmitters and glutamate receptors at synapses. In addition, the regulation of neuroplasticity by acupuncture may also be related to the regulation of astrocytes. Considering the guiding significance of acupuncture for clinical treatment, it is necessary to carry out further study about the influence of acupuncture on the recovery of aphasia after stroke. This study summarizes the current research on the neural mechanism of acupuncture in treating PSA. It seeks to elucidate the potential effect of acupuncture on the recovery of PSA from the perspective of synaptic plasticity and integrity of gray and white matter.

Early white matter connectivity and plasticity in post stroke aphasia recovery

A disruption of white matter connectivity is negatively associated with language (recovery) in patients with aphasia after stroke, and behavioral gains have been shown to coincide with white matter neuroplasticity. However, most brain-behavior studies have been carried out in the chronic phase after stroke, with limited generalizability to earlier phases. Furthermore, few studies have investigated neuroplasticity patterns during spontaneous recovery (i.e., not related to a specific treatment) in the first months after stroke, hindering the investigation of potential early compensatory mechanisms. Finally, the majority of previous research has focused on damaged left hemisphere pathways, while neglecting the potential protective value of their right hemisphere counterparts for language recovery. To address these outstanding issues, we present a longitudinal study of thirty-two patients with aphasia (21 males and 11 females, M = 69.47 years, SD = 10.60 years) who were followed up for a period of 1 year with test moments in the acute (1-2 weeks), subacute (3-6 months) and chronic phase (9-12 months) after stroke. Constrained Spherical Deconvolution-based tractography was performed in the acute and subacute phase to measure Fiber Bundle Capacity (FBC), a quantitative connectivity measure that is valid in crossing fiber regions, in the bilateral dorsal arcuate fasciculus (AF) and the bilateral ventral inferior fronto-occipital fasciculus (IFOF). First, concurrent analyses revealed positive associations between the left AF and phonology, and between the bilateral IFOF and semantics in the acute - but not subacute - phase, supporting the dual-stream language model. Second, neuroplasticity analyses revealed a decrease in connection density of the bilateral AF - but not the IFOF - from the acute to the subacute phase, possibly reflecting post stroke white matter degeneration in areas adjacent to the lesion. Third, predictive analyses revealed no contribution of acute FBC measures to the prediction of later language outcomes over and above the initial language scores, suggesting no added value ofthe diffusion measures for languageprediction. Our study provides new insights on (changes in) connectivity of damaged and undamaged language pathways in patients with aphasia in the first months after stroke, as well as if/how such measures are related to language outcomes at different stages of recovery. Individual results are discussed in the light of current frameworks of language processing and aphasia recovery.

Effects of a new speech support application on intensive speech therapy and changes in functional brain connectivity in patients with post-stroke aphasia

Aphasia is a language disorder that occurs after a stroke and impairs listening, speaking, reading, writing, and calculation skills. Patients with post-stroke aphasia in Japan are increasing due to population aging and the advancement of medical treatment. Opportunities for adequate speech therapy in chronic stroke are limited due to time constraints. Recent studies have reported that intensive speech therapy for a short period of time or continuous speech therapy using high-tech equipment, including speech applications (apps, can improve aphasia even in the chronic stage. However, its underlying mechanism for improving language function and its effect on other cognitive functions remains unclear. In the present study, we investigated whether intensive speech therapy using a newly developed speech support app could improve aphasia and other cognitive functions in patients with chronic stroke. Furthermore, we examined whether it can alter the brain network related to language and other cortical areas. Thus, we conducted a prospective, single-comparison study to examine the effects of a new speech support app on language and cognitive functions and used resting state functional MRI (rs-fMRI) regions of interest (ROI) to ROI analysis to determine changes in the related brain network. Two patients with chronic stroke participated in this study. They used the independent speech therapy system to perform eight sets of 20 randomly presented words/time (taking approximately 20 min), for 8 consecutive weeks. Their language, higher cognitive functions including attention function, and rs-fMRI, were evaluated before and after the rehabilitation intervention using the speech support app. Both patients had improved pronunciation, daily conversational situations, and attention. The rs-fMRI analysis showed increased functional connectivity of brain regions associated with language and attention related areas. Our results show that intensive speech therapy using this speech support app can improve language and attention functions even in the chronic stage of stroke, and may be a useful tool for patients with aphasia. In the future, we will conduct longitudinal studies with larger numbers of patients, which we hope will continue the trends seen in the current study, and provide even stronger evidence for the usefulness of this new speech support app.

Language Development in Preschool Duchenne Muscular Dystrophy Boys

BACKGROUND

the present study aims to assess language in preschool-aged Duchenne muscular dystrophy (DMD) boys with normal cognitive quotients, and to establish whether language difficulties are related to attentional aspects or to the involvement of brain dystrophin isoforms.

METHODS

20 children aged between 48 and 72 months were assessed with language and attention assessments for preschool children. Nine had a mutation upstream of exon 44, five between 44 and 51, four between 51 and 63, and two after exon 63. A control group comprising 20 age-matched boys with a speech language disorder and normal IQ were also used.

RESULTS

lexical and syntactic comprehension and denomination were normal in 90% of the boys with Duchenne, while the articulation and repetition of long words, and sentence repetition frequently showed abnormal results (80%). Abnormal results were also found in tests assessing selective and sustained auditory attention. Language difficulties were less frequent in patients with mutations not involving isoforms Dp140 and Dp71. The profile in Duchenne boys was different form the one observed in SLI with no cognitive impairment.

CONCLUSION

The results of our observational cross-sectional study suggest that early language abilities are frequently abnormal in preschool Duchenne boys and should be assessed regardless of their global neurodevelopmental quotient.

Population-based tract-to-region connectome of the human brain and its hierarchical topology

Connectome maps region-to-region connectivities but does not inform which white matter pathways form the connections. Here we constructed a population-based tract-to-region connectome to fill this information gap. The constructed connectome quantifies the population probability of a white matter tract innervating a cortical region. The results show that ~85% of the tract-to-region connectome entries are consistent across individuals, whereas the remaining (~15%) have substantial individual differences requiring individualized mapping. Further hierarchical clustering on cortical regions revealed dorsal, ventral, and limbic networks based on the tract-to-region connective patterns. The clustering results on white matter bundles revealed the categorization of fiber bundle systems in the association pathways. This tract-to-region connectome provides insights into the connective topology between cortical regions and white matter bundles. The derived hierarchical relation further offers a categorization of gray and white matter structures.

The brain connectome maps region-to-region connections but often ignores the role of the connecting pathways. Here, the authors mapped the tract-to-region relations to reveal the hierarchical relation of fiber bundles and dorsal, ventral, and limbic networks.

Research trends of the neuroimaging in aphasia: A bibliometric analysis and visualization analysis from 2004 to 2021

Objectives

To review the current research status of the neuroimaging of aphasia, and reveal the hotspots and frontiers of research in this field.

Methods

We searched articles related to the neuroimaging research on aphasia since Web of Science (WOS) database construction and extracted the data. CiteSpace and VOSviewer were used for the country/institution analysis, journal analysis, discipline analysis, burst keyword analysis and cited-reference cluster analysis.

Results

Of the studies retrieved from WOS, 2922 studies that related to the neuroimaging of aphasia were screened and finally included 2799 articles for research. The United States of America and University of California San Francisco were the main countries and institutions in this field. Brain had the highest impact factor in both published and cited journals. Through the discipline and topic analysis of this field, the most common category was Neurosciences and Neurology. The keyword with the strongest citation strength was “functional connectivity,” and the recent burst keywords were “functional connectivity” and “network.” The co-citation network showed seven clusters greater than 100. Among the top 5 clusters, the most recently formed cluster, Cluster #2 (progressive supranuclear palsy), had an average year of 2017. The literature in the top 5 clusters mainly focused on 3 aspects, specifically, the discovery of language processing models, injury and recovery mechanisms of post-stroke aphasia (PSA), and diagnosis of primary progressive aphasia (PPA) variants.

Conclusion

The results of this bibliometric study revealed the following three research hotspots in the neuroimaging of aphasia: clarifying the connotation of the most recognized language processing model, the dual-stream model, exploring the injury mechanism based on the dual-stream model and the recovery mechanism involving the left and right hemispheres of PSA, and determining the diagnostic criteria for PPA variants. A major research trend is to combine new neuroimaging technology, such as PET tracer technology, to realize the visual presentation of disease-specific proteins to improve the pathological diagnostic criteria of PPA variants. Accordingly, a visualized analysis of literature that uses CiteSpace provides a more rapid, repeatable and flexible method, which is more conducive to capturing research hotspots and emerging trends.

Effect of Rehabilitation on Brain Functional Connectivity in a Stroke Patient Affected by Conduction Aphasia

Stroke is a medical condition that affects the brain and represents a leading cause of death and disability. Associated with drug therapy, rehabilitative treatment is essential for promoting recovery. In the present work, we report an EEG-based study concerning a left ischemic stroke patient affected by conduction aphasia. Specifically, the objective is to compare the brain functional connectivity before and after an intensive rehabilitative treatment. The analysis was performed by means of local and global efficiency measures related to the execution of three tasks: naming, repetition and reading. As expected, the results showed that the treatment led to a balancing of the values of both parameters between the two hemispheres since the rehabilitation contributed to the creation of new neural patterns to compensate for the disrupted ones. Moreover, we observed that for both name and repetition tasks, shortly after the stroke, the global and local connectivity are lower in the affected lobe (left hemisphere) than in the unaffected one (right hemisphere). Conversely, for the reading task, global and local connectivity are higher in the impaired lobe. This apparently contrasting trend can be due to the effects of stroke, which affect not only the site of structural damage but also brain regions belonging to a functional network. Moreover, changes in network connectivity can be task-dependent. This work can be considered a first step for future EEG-based studies to establish the most suitable connectivity measures for supporting the treatment of stroke and monitoring the recovery process.

Language systems from lesion-symptom mapping in aphasia: A meta-analysis of voxel-based lesion mapping studies

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Meta-analysis of 2,007 individuals with aphasia from 25 voxel-based lesion mapping studies.

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Distinctive patterns of lesions in aphasia are associated with different language functions.

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The patterns of lesion in aphasia support the dual pathway model of language processing.

Background

Aphasia is one of the most common causes of post-stroke disabilities. As the symptoms and impact of post-stroke aphasia are heterogeneous, it is important to understand how topographical lesion heterogeneity in patients with aphasia is associated with different domains of language impairments. Here, we aim to provide a comprehensive overview of neuroanatomical basis in post-stroke aphasia through coordinate based meta-analysis of voxel-based lesion-symptom mapping studies.

Methods

We performed a meta-analysis of lesion-symptom mapping studies in post-stroke aphasia. We obtained coordinate-based structural neuroimaging data for 2,007 individuals with aphasia from 25 studies that met predefined inclusion criteria.

Results

Overall, our results revealed that the distinctive patterns of lesions in aphasia are associated with different language functions and tasks. Damage to the insular-motor areas impaired speech with preserved comprehension and a similar pattern was observed when the lesion covered the insular-motor and inferior parietal lobule. Lesions in the frontal area severely impaired speaking with relatively good comprehension. The repetition-selective deficits only arise from lesions involving the posterior superior temporal gyrus. Damage in the anterior-to-posterior temporal cortex was associated with semantic deficits.

Conclusion

The association patterns of lesion topography and specific language deficits provide key insights into the specific underlying language pathways. Our meta-analysis results strongly support the dual pathway model of language processing, capturing the link between the different symptom complexes of aphasias and the different underlying location of damage.

Revealing the Neuroimaging Mechanism of Acupuncture for Poststroke Aphasia: A Systematic Review

Background

Aphasia is a common symptom in stroke patients, presenting with the impairment of spontaneous speech, repetition, naming, auditory comprehension, reading, and writing function. Multiple rehabilitation methods have been suggested for the recovery of poststroke aphasia, including medication treatment, behavioral therapy, and stimulation approach. Acupuncture has been proven to have a beneficial effect on improving speech functions in repetition, oral speech, reading, comprehension, and writing ability. Neuroimaging technology provides a visualized way to explore cerebral neural activity, which helps reveal the therapeutic effect of acupuncture therapy. In this systematic review, we aim to reveal and summarize the neuroimaging mechanism of acupuncture therapy on poststroke aphasia to provide the foundation for further study.

Methods

Seven electronic databases were searched including PubMed, Web of Science, Embase, Cochrane Central Register of Controlled Trials, China National Knowledge Infrastructure, the Wanfang databases, and the Chinese Scientific Journal Database. After screening the studies according to the inclusion and exclusion criteria, we summarized the neuroimaging mechanism of acupuncture on poststroke aphasia, as well as the utilization of acupuncture therapy and the methodological characteristics.

Result

After searching, 885 articles were retrieved. After removing the literature studies, animal studies, and case reports, 16 studies were included in the final analysis. For the acupuncture type, 10 studies used manual acupuncture and 5 studies used electroacupuncture, while body acupuncture (10 studies), scalp acupuncture (7 studies), and tongue acupuncture (8 studies) were applied for poststroke aphasia patients. Based on blood oxygen level-dependent (BOLD) and diffusion tensor imaging (DTI) technologies, 4 neuroimaging analysis methods were used including amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), seed-based analysis, and independent component analysis (ICA). Two studies reported the instant acupuncture effect, and 14 studies reported the constant acupuncture's effect on poststroke aphasia patients. 5 studies analyzed the correlation between the neuroimaging outcomes and the clinical language scales.

Conclusion

In this systematic review, we found that the mechanism of acupuncture's effect might be associated with the activation and functional connectivity of language-related brain areas, such as brain areas around Broca's area and Wernicke's area in the left inferior temporal gyrus, supramarginal gyrus, middle frontal gyrus, and inferior frontal gyrus. However, these studies were still in the preliminary stage. Multicenter randomized controlled trials (RCT) with large sample sizes were needed to verify current evidence, as well as to explore deeply the neuroimaging mechanisms of acupuncture's effects.

Neural correlates of impaired vocal feedback control in post-stroke aphasia

We used left-hemisphere stroke as a model to examine how damage to sensorimotor brain networks impairs vocal auditory feedback processing and control. Individuals with post-stroke aphasia and matched neurotypical control subjects vocalized speech vowel sounds and listened to the playback of their self-produced vocalizations under normal (NAF) and pitch-shifted altered auditory feedback (AAF) while their brain activity was recorded using electroencephalography (EEG) signals. Event-related potentials (ERPs) were utilized as a neural index to probe the effect of vocal production on auditory feedback processing with high temporal resolution, while lesion data in the stroke group was used to determine how brain abnormality accounted for the impairment of such mechanisms. Results revealed that ERP activity was aberrantly modulated during vocalization vs. listening in aphasia, and this effect was accompanied by the reduced magnitude of compensatory vocal responses to pitch-shift alterations in the auditory feedback compared with control subjects. Lesion-mapping revealed that the aberrant pattern of ERP modulation in response to NAF was accounted for by damage to sensorimotor networks within the left-hemisphere inferior frontal, precentral, inferior parietal, and superior temporal cortices. For responses to AAF, neural deficits were predicted by damage to a distinguishable network within the inferior frontal and parietal cortices. These findings define the left-hemisphere sensorimotor networks implicated in auditory feedback processing, error detection, and vocal motor control. Our results provide translational synergy to inform the theoretical models of sensorimotor integration while having clinical applications for diagnosis and treatment of communication disabilities in individuals with stroke and other neurological conditions.

Effects of Mild Traumatic Brain Injury on Resting State Brain Network Connectivity in Older Adults

Older age is associated with worsened outcome after mild traumatic brain injury (mTBI) and a higher risk of developing persistent post-traumatic complaints. However, the effects of mTBI sequelae on brain connectivity at older age and their association with post-traumatic complaints remain understudied.We analyzed multi-echo resting-state functional magnetic resonance imaging data from 25 older adults with mTBI (mean age: 68 years, SD: 5 years) in the subacute phase (mean injury to scan interval: 38 days, SD: 9 days) and 20 age-matched controls. Severity of complaints (e.g. fatigue, dizziness) was assessed using self-reported questionnaires. Group independent component analysis was used to identify intrinsic connectivity networks (ICNs). The effects of group and severity of complaints on ICNs were assessed using spatial maps intensity (SMI) as a measure of within-network connectivity, and (static) functional network connectivity (FNC) as a measure of between-network connectivity.Patients indicated a higher total severity of complaints than controls. Regarding SMI measures, we observed hyperconnectivity in left-mid temporal gyrus (cognitive-language network) and hypoconnectivity in the right-fusiform gyrus (visual-cerebellar network) that were associated with group. Additionally, we found interaction effects for SMI between severity of complaints and group in the visual(-cerebellar) domain. Regarding FNC measures, no significant effects were found.In older adults, changes in cognitive-language and visual(-cerebellar) networks are related to mTBI. Additionally, group-dependent associations between connectivity within visual(-cerebellar) networks and severity of complaints might indicate post-injury (mal)adaptive mechanisms, which could partly explain post-traumatic complaints (such as dizziness and balance disorders) that are common in older adults during the subacute phase.

Grey and white matter atrophy one year after stroke aphasia

Dynamic whole-brain changes occur following stroke, and not just in association with recovery. We tested the hypothesis that the presence of a specific behavioural deficit after stroke would be associated with structural decline (atrophy) in the brain regions supporting the affected function, by examining language deficits post-stroke. We quantified whole-brain structural volume changes longitudinally (3–12 months) in stroke participants with (N = 32) and without aphasia (N = 59) as assessed by the Token Test at 3 months post-stroke, compared with a healthy control group (N = 29). While no significant difference in language decline rates (change in Token Test scores from 3 to 12 months) was observed between groups and some participants in the aphasic group improved their scores, stroke participants with aphasia symptoms at 3 months showed significant atrophy (>2%, P = 0.0001) of the left inferior frontal gyrus not observed in either healthy control or non-aphasic groups over the 3–12 months period. We found significant group differences in the inferior frontal gyrus volume, accounting for age, sex, stroke severity at baseline, education and total intracranial volume (Bonferroni-corrected P = 0.0003). In a subset of participants (aphasic N = 14, non-aphasic N = 36, and healthy control N = 25) with available diffusion-weighted imaging data, we found significant atrophy in the corpus callosum and the left superior longitudinal fasciculus in the aphasic compared with the healthy control group. Language deficits at 3 months post-stroke are associated with accelerated structural decline specific to the left inferior frontal gyrus, highlighting that known functional brain reorganization underlying behavioural improvement may occur in parallel with atrophy of brain regions supporting the language function.

Understanding Language Reorganization With Neuroimaging: How Language Adapts to Different Focal Lesions and Insights Into Clinical Applications

When the language-dominant hemisphere is damaged by a focal lesion, the brain may reorganize the language network through functional and structural changes known as adaptive plasticity. Adaptive plasticity is documented for triggers including ischemic, tumoral, and epileptic focal lesions, with effects in clinical practice. Many questions remain regarding language plasticity. Different lesions may induce different patterns of reorganization depending on pathologic features, location in the brain, and timing of onset. Neuroimaging provides insights into language plasticity due to its non-invasiveness, ability to image the whole brain, and large-scale implementation. This review provides an overview of language plasticity on MRI with insights for patient care. First, we describe the structural and functional language network as depicted by neuroimaging. Second, we explore language reorganization triggered by stroke, brain tumors, and epileptic lesions and analyze applications in clinical diagnosis and treatment planning. By comparing different focal lesions, we investigate determinants of language plasticity including lesion location and timing of onset, longitudinal evolution of reorganization, and the relationship between structural and functional changes.

The dual stream model of speech and language processing

The Wernicke-Lichtheim-Geschwind model of the neurology of language has served the field well despite its limited scope. More recent work has updated the basic architecture of the classical model and expanded its scope. This chapter briefly reviews the Wernicke-Lichtheim-Geschwind model and points out its shortcomings, then describes and motivates the dual stream model and how it solves several empirical shortcomings of the classical model. The chapter also (i) underscores how the dual stream model relates to the organization of nonlinguistic cortical networks, integrating language systems with the broader functional-anatomical landscape, (ii) describes recent work that further specifies the computational architecture and neural correlates of the dorsal speech production system, and (iii) summarizes recent extensions of the architectural framework to include syntax.

Language Recovery after Brain Injury: A Structural Network Control Theory Study

Aphasia recovery after stroke depends on the condition of the remaining, extralesional brain network. Network control theory (NCT) provides a unique, quantitative approach to assess the interaction between brain networks. In this longitudinal, large-scale, whole-brain connectome study, we evaluated whether controllability measures of language-related regions are associated with treated aphasia recovery. Using probabilistic tractography and controlling for the effects of structural lesions, we reconstructed whole-brain diffusion tensor imaging (DTI) connectomes from 68 individuals (20 female, 48 male) with chronic poststroke aphasia who completed a three-week language therapy. Applying principles of NCT, we computed regional (1) average and (2) modal controllability, which decode the ability of a region to (1) spread control input through the brain network and (2) to facilitate brain state transitions. We tested the relationship between pretreatment controllability measures of 20 language-related left hemisphere regions and improvements in naming six months after language therapy using multiple linear regressions and a parsimonious elastic net regression model with cross-validation. Regional controllability of the inferior frontal gyrus (IFG) pars opercularis, pars orbitalis, and the anterior insula were associated with treatment outcomes independently of baseline aphasia severity, lesion volume, age, education, and network size. Modal controllability of the IFG pars opercularis was the strongest predictor of treated aphasia recovery with cross-validation and outperformed traditional graph theory, lesion load, and demographic measures. Regional NCT measures can reflect the status of the residual language network and its interaction with the remaining brain network, being able to predict language recovery after aphasia treatment.SIGNIFICANCE STATEMENT Predicting and understanding language recovery after brain injury remains a challenging, albeit a fundamental aspect of human neurology and neuroscience. In this study, we applied network control theory (NCT) to fully harness the concept of brain networks as dynamic systems and to evaluate their interaction. We studied 68 stroke survivors with aphasia who underwent imaging and longitudinal behavioral assessments coupled with language therapy. We found that the controllability of the inferior frontal regional network significantly predicted recovery in language production six months after treatment. Importantly, controllability outperformed traditional demographic, lesion, and graph-theoretical measures. Our findings shed light on the neurobiological basis of human language and can be translated into personalized rehabilitation approaches.

Task-dependent cortical activations during selective attention to audiovisual speech

Selective listening to speech depends on widespread networks of the brain, but how the involvement of different neural systems in speech processing is affected by factors such as the task performed by a listener and speech intelligibility remains poorly understood. We used functional magnetic resonance imaging to systematically examine the effects that performing different tasks has on neural activations during selective attention to continuous audiovisual speech in the presence of task-irrelevant speech. Participants viewed audiovisual dialogues and attended either to the semantic or the phonological content of speech, or ignored speech altogether and performed a visual control task. The tasks were factorially combined with good and poor auditory and visual speech qualities. Selective attention to speech engaged superior temporal regions and the left inferior frontal gyrus regardless of the task. Frontoparietal regions implicated in selective auditory attention to simple sounds (e.g., tones, syllables) were not engaged by the semantic task, suggesting that this network may not be not as crucial when attending to continuous speech. The medial orbitofrontal cortex, implicated in social cognition, was most activated by the semantic task. Activity levels during the phonological task in the left prefrontal, premotor, and secondary somatosensory regions had a distinct temporal profile as well as the highest overall activity, possibly relating to the role of the dorsal speech processing stream in sub-lexical processing. Our results demonstrate that the task type influences neural activations during selective attention to speech, and emphasize the importance of ecologically valid experimental designs.