Language and action in Broca's area: Computational differentiation and cortical segregation

Distinct neural mechanisms for action access and execution in the human brain: insights from an fMRI study

Goal-directed actions are fundamental to human behavior, whereby inner goals are achieved through mapping action representations to motor outputs. The left premotor cortex (BA6) and the posterior portion of Broca's area (BA44) are two modulatory poles of the action system. However, how these regions support the representation-output mapping within the system is not yet understood. To address this, we conducted a finger-tapping functional magnetic resonance imaging experiment using action categories ranging from specific to general. Our study found distinct neural behaviors in BA44 and BA6 during action category processing and motor execution. During access of action categories, activity in a posterior portion of BA44 (pBA44) decreased linearly as action categories became less specific. Conversely, during motor execution, activity in BA6 increased linearly with less specific categories. These findings highlight the differential roles of pBA44 and BA6 in action processing. We suggest that pBA44 facilitates access to action categories by utilizing motor information from the behavioral context while the premotor cortex integrates motor information to execute the selected action. This finding enhances our understanding of the interplay between prefrontal cortical regions and premotor cortex in mapping action representation to motor execution and, more in general, of the cortical mechanisms underlying human behavior.

Rhythmic modulation of prediction errors: A top-down gating role for the beta-range in speech processing

Natural speech perception requires processing the ongoing acoustic input while keeping in mind the preceding one and predicting the next. This complex computational problem could be handled by a dynamic multi-timescale hierarchical inferential process that coordinates the information flow up and down the language network hierarchy. Using a predictive coding computational model (Precoss-β) that identifies online individual syllables from continuous speech, we address the advantage of a rhythmic modulation of up and down information flows, and whether beta oscillations could be optimal for this. In the model, and consistent with experimental data, theta and low-gamma neural frequency scales ensure syllable-tracking and phoneme-level speech encoding, respectively, while the beta rhythm is associated with inferential processes. We show that a rhythmic alternation of bottom-up and top-down processing regimes improves syllable recognition, and that optimal efficacy is reached when the alternation of bottom-up and top-down regimes, via oscillating prediction error precisions, is in the beta range (around 20-30 Hz). These results not only demonstrate the advantage of a rhythmic alternation of up- and down-going information, but also that the low-beta range is optimal given sensory analysis at theta and low-gamma scales. While specific to speech processing, the notion of alternating bottom-up and top-down processes with frequency multiplexing might generalize to other cognitive architectures.

Evolutionary neuroanatomical expansion of Broca's region serving a human-specific function

The question concerning the evolution of language is directly linked to the debate on whether language and action are dependent or not and to what extent Broca's region serves as a common neural basis. The debate resulted in two opposing views, one arguing for and one against the dependence of language and action mainly based on neuroscientific data. This article presents an evolutionary neuroanatomical framework which may offer a solution to this dispute. It is proposed that in humans, Broca's region houses language and action independently in spatially separated subregions. This became possible due to an evolutionary expansion of Broca's region in the human brain, which was not paralleled by a similar expansion in the chimpanzee's brain, providing additional space needed for the neural representation of language in humans.

Assistive Completion of Agrammatic Aphasic Sentences: Amalgamation of NLP and Neurolinguistics-based Synthetic Dataset

Damage to the inferior frontal gyrus (Broca's area) can cause agrammatic aphasia wherein patients, although able to comprehend, lack the ability to form complete sentences. This inability leads to communication gaps which cause difficulties in their daily lives. The usage of assistive devices can help in mitigating these issues and enable the patients to communicate effectively. However, due to lack of large scale studies of linguistic deficits in aphasia, research on such assistive technology is relatively limited. In this work, we present two contributions that aim to re-initiate research and development in this field. Firstly, we propose a model that uses linguistic features from small scale studies on aphasia patients and generates large scale datasets of synthetic aphasic utterances from grammatically correct datasets. We show that the mean length of utterance, the noun/verb ratio, and the simple/complex sentence ratio of our synthetic datasets correspond to the reported features of aphasic speech. Further, we demonstrate how the synthetic datasets may be utilized to develop assistive devices for aphasia patients. The pre-trained T5 transformer is fine-tuned using the generated dataset to suggest 5 corrected sentences given an aphasic utterance as input. We evaluate the efficacy of the T5 model using the BLEU and cosine semantic similarity scores. Affirming results with BLEU score of 0.827/1.00 and semantic similarity of 0.904/1.00 were obtained. These results provide a strong foundation for the concept that a synthetic dataset based on small scale studies on aphasia can be used to develop effective assistive technology.Clinical relevance- We demonstrate the utilization of Natural Language Processing (NLP) for developing assistive technology for Aphasia patients. While disorders like Broca's aphasia offer a small sample size of patients and data, synthetic linguistic models like ours offer extensive scope for developing assistive technology and rehabilitation monitoring.

Cortical mapping in multilinguals undergoing awake brain surgery for brain tumors: Illustrative cases and systematic review

BACKGROUND

Awake brain mapping in multilingual patients with brain tumors presents unique challenges to the neurosurgeon. Knowledge of potential eloquent sites is vital to preserve language function.

METHODS

We present two cases of pars opercularis glioma and perform a systematic review in accordance with PRISMA guidelines.

RESULTS

Our review yielded 7 studies, with a total of 25 multilingual brain tumor patients who underwent awake brain mapping. The age ranged from 25 to 62 years. Majority were female (56.5%). Most (52%) were trilingual, while 20% were quadrilingual and 28% were pentalingual. All tumors were left-sided, mostly in the frontal lobe. These were predominantly gliomas. Extent of resection was gross total in 61%. The brain mapping findings were heterogeneous. Some authors reported a greater number of cortical sites for the first language compared to others. Others found that the first and second languages shared cortical sites whereas the third and subsequent languages were located in distant sites. The peri-Sylvian area was also found to be involved in language that was learned at an earlier age. Subsequent languages thus involved more distant sites. A larger number of cortical areas were also activated for languages that were learned later in life. In terms of language disturbance and recovery, there were mixed results.

CONCLUSION

Cortical mapping in multilingual brain tumor patients showed heterogeneity in terms of the location and number of language areas in the face of pathology. These findings may influence neurosurgical and oncological management of tumors in the speech area but emphasize the need to tailor surgical approaches and intraoperative testing to the patient.

Online neurostimulation of Broca's area does not interfere with syntactic predictions: A combined TMS-EEG approach to basic linguistic combination

Categorical predictions have been proposed as the key mechanism supporting the fast pace of syntactic composition in language. Accordingly, grammar-based expectations are formed-e.g., the determiner "a" triggers the prediction for a noun-and facilitate the analysis of incoming syntactic information, which is then checked against a single or few other word categories. Previous functional neuroimaging studies point towards Broca's area in the left inferior frontal gyrus (IFG) as one fundamental cortical region involved in categorical prediction during incremental language processing. Causal evidence for this hypothesis is however still missing. In this study, we combined Electroencephalography (EEG) and Transcranial Magnetic Stimulation (TMS) to test whether Broca's area is functionally relevant in predictive mechanisms for language. We transiently perturbed Broca's area during the first word in a two-word construction, while simultaneously measuring the Event-Related Potential (ERP) correlates of syntactic composition. We reasoned that if Broca's area is involved in predictive mechanisms for syntax, disruptive TMS during the first word would mitigate the difference in the ERP responses for predicted and unpredicted categories in basic two-word constructions. Contrary to this hypothesis, perturbation of Broca's area at the predictive stage did not affect the ERP correlates of basic composition. The correlation strength between the electrical field induced by TMS and the ERP responses further confirmed this pattern. We discuss the present results considering an alternative account of the role of Broca's area in syntactic composition, namely the bottom-up integration of words into constituents, and of compensatory mechanisms within the language predictive network.

Broca area homologue's asymmetry reflects gestural communication lateralisation in monkeys (Papio anubis)

Manual gestures and speech recruit a common neural network, involving Broca’s area in the left hemisphere. Such speech-gesture integration gave rise to theories on the critical role of manual gesturing in the origin of language. Within this evolutionary framework, research on gestural communication in our closer primate relatives has received renewed attention for investigating its potential language-like features. Here, using in vivo anatomical MRI in 50 baboons, we found that communicative gesturing is related to Broca homologue’s marker in monkeys, namely the ventral portion of the Inferior Arcuate sulcus (IA sulcus). In fact, both direction and degree of gestural communication’s handedness – but not handedness for object manipulation are associated and correlated with contralateral depth asymmetry at this exact IA sulcus portion. In other words, baboons that prefer to communicate with their right hand have a deeper left-than-right IA sulcus, than those preferring to communicate with their left hand and vice versa. Interestingly, in contrast to handedness for object manipulation, gestural communication’s lateralisation is not associated to the Central sulcus depth asymmetry, suggesting a double dissociation of handedness’ types between manipulative action and gestural communication. It is thus not excluded that this specific gestural lateralisation signature within the baboons’ frontal cortex might reflect a phylogenetical continuity with language-related Broca lateralisation in humans.