Broca Area Research Articles

Music in noise recognition: An EEG study of listening effort in cochlear implant users and normal hearing controls.

Despite the plethora of studies investigating listening effort and the amount of research concerning music perception by cochlear implant (CI) users, the investigation of the influence of background noise on music processing has never been performed. Given the typical speech in noise recognition task for the listening effort assessment, the aim of the present study was to investigate the listening effort during an emotional categorization task on musical pieces with different levels of background noise. The listening effort was investigated, in addition to participants' ratings and performances, using EEG features known to be involved in such phenomenon, that is alpha activity in parietal areas and in the left inferior frontal gyrus (IFG), that includes the Broca's area. Results showed that CI users performed worse than normal hearing (NH) controls in the recognition of the emotional content of the stimuli. Furthermore, when considering the alpha activity corresponding to the listening to signal to noise ratio (SNR) 5 and SNR10 conditions subtracted of the activity while listening to the Quiet condition-ideally removing the emotional content of the music and isolating the difficulty level due to the SNRs- CI users reported higher levels of activity in the parietal alpha and in the homologous of the left IFG in the right hemisphere (F8 EEG channel), in comparison to NH. Finally, a novel suggestion of a particular sensitivity of F8 for SNR-related listening effort in music was provided.

Neural basis of sound-symbolic pseudoword-shape correspondences

Non-arbitrary mapping between the sound of a word and its meaning, termed sound symbolism, is commonly studied through crossmodal correspondences between sounds and visual shapes, e.g., auditory pseudowords, like ‘mohloh’ and ‘kehteh’, are matched to rounded and pointed visual shapes, respectively. Here, we used functional magnetic resonance imaging (fMRI) during a crossmodal matching task to investigate the hypotheses that sound symbolism (1) involves language processing; (2) depends on multisensory integration; (3) reflects embodiment of speech in hand movements. These hypotheses lead to corresponding neuroanatomical predictions of crossmodal congruency effects in (1) the language network; (2) areas mediating multisensory processing, including visual and auditory cortex; (3) regions responsible for sensorimotor control of the hand and mouth. Right-handed participants (n = 22) encountered audiovisual stimuli comprising a simultaneously presented visual shape (rounded or pointed) and an auditory pseudoword (‘mohloh’ or ‘kehteh’) and indicated via a right-hand keypress whether the stimuli matched or not. Reaction times were faster for congruent than incongruent stimuli. Univariate analysis showed that activity was greater for the congruent compared to the incongruent condition in the left primary and association auditory cortex, and left anterior fusiform/parahippocampal gyri. Multivoxel pattern analysis revealed higher classification accuracy for the audiovisual stimuli when congruent than when incongruent, in the pars opercularis of the left inferior frontal (Broca's area), the left supramarginal, and the right mid-occipital gyri. These findings, considered in relation to the neuroanatomical predictions, support the first two hypotheses and suggest that sound symbolism involves both language processing and multisensory integration.

A case of pure apraxia of speech after left hemisphere stroke: behavioral findings and neural correlates.

Apraxia of speech (AOS) is a motor speech disorder impairing the coordination of complex articulatory movements needed to produce speech. AOS typically co-occurs with a non-fluent aphasia, or language disorder, making it challenging to determine the specific brain structures that cause AOS. Cases of pure AOS without aphasia are rare but offer the best window into the neural correlates that support articulatory planning. The goal of the current study was to explore patterns of apraxic speech errors and their underlying neural correlates in a case of pure AOS. A 67-year-old right-handed man presented with severe AOS resulting from a fronto-insular lesion caused by an ischemic stroke. The participant's speech and language were evaluated at 1-, 3- and 12-months post-onset. High resolution structural MRI, including diffusion weighted imaging, was acquired at 12 months post-onset. At the first assessment, the participant made minor errors on the Comprehensive Aphasia Test, demonstrating mild deficits in writing, auditory comprehension, and repetition. By the second assessment, he no longer had aphasia. On the Motor Speech Evaluation, the severity of his AOS was initially rated as 5 (out of 7) and improved to a score of 4 by the second visit, likely due to training by his SLP at the time to slow his speech. Structural MRI data showed a fronto-insular lesion encompassing the superior precentral gyrus of the insula and portions of the inferior and middle frontal gyri and precentral gyrus. Tractography derived from diffusion MRI showed partial damage to the frontal aslant tract and arcuate fasciculus along the white matter projections to the insula. This pure case of severe AOS without aphasia affords a unique window into the behavioral and neural mechanisms of this motor speech disorder. The current findings support previous observations that AOS and aphasia are dissociable and confirm a role for the precentral gyrus of the insula and BA44, as well as underlying white matter in supporting the coordination of complex articulatory movements. Additionally, other regions including the precentral gyrus, Broca's area, and Area 55b are discussed regarding their potential role in successful speech production.

The Effects of Different Brain Regions on fNIRS-based Task-state Detection in Speech Imagery.

Brain-computer interface (BCI) based on speech imagery can decode users' verbal intent and help people with motor disabilities communicate naturally. Functional near-infrared spectroscopy (fNIRS) is a commonly used brain signal acquisition method. Asynchronous BCI can response to control commands at any time, which provides great convenience for users. Task state detection, defined as identifying whether user starts or continues covertly articulating, plays an important role in speech imagery BCIs. To better distinguish task state from idle state during speech imagery, this work used fNIRS signals from different brain regions to study the effects of different brain regions on task state detection accuracy. The imagined tonal syllables included four lexical tones and four vowels in Mandarin Chinese. The brain regions that were measured included Broca's area, Wernicke's area, Superior temporal cortex and Motor cortex. Task state detection accuracies of imagining tonal monosyllables with four different tones were analyzed. The average accuracy of four speech imagery tasks based on the whole brain was 0.67 and it was close to 0.69, which was the average accuracy based on Broca's area. The accuracies of Broca's area and the whole brain were significantly higher than those of other brain regions. The findings of this work demonstrated that using a few channels of Broca's area could result in a similar task state detection accuracy to that using all the channels of the brain. Moreover, it was discovered that speech imagery with tone 2/3 tasks yielded higher task state detection accuracy than speech imagery with other tones.

An ensemble-based Machine learning technique for dyslexia detection during a visual continuous performance task

BackgroundDyslexia is a neurological disorder which affects the learning of individuals suffering from it, especially children. It causes reading and writing difficulties, leading to anger, frustration, poor self-esteem, and other negative emotions. Early diagnosis of dyslexia can be extremely useful for dyslexic children since their learning requirements can be correctly handled. MethodThis study aimed to propose an efficient method for dyslexia detection via evoked-related potentials (ERPs) during a Visual Continuous Performance Task (VCPT). To this end, after extracting the latency and amplitude of the event-related potential components and a statistical analysis between the two groups, the number of data dimensions is reduced by the KS-test and principal component analysis (PCA). This method used the ensemble learning classification technique to classify the normal and dyslexic groups, including five classifiers, namely a Support Vector Machine (SVM), Decision Tree, Linear Discriminant Analysis (LDA), K-nearest Neighbors (KNN), and Naive Bayesian. Moreover, we have used an 8-fold cross-validation method to assess how generalized the process is and, more importantly, to have a well-performed control on overfitting. ResultsAccording to this approach, the overall average classification accuracy is 87.5%, and the sensitivity and specificity are 81.2% and 93.7%, respectively. ConclusionThe suggested technique can improve children's education before they start school and have any skills in writing and reading. The most discriminative electrodes were found in the left hemisphere, which can be related to the Wernicke and Broca areas that have an essential role in the brain's reading, writing, and language-related functions.

Changes in functional brain activity patterns associated with computer programming learning in novices.

Computer programming, the process of designing, writing, and testing executable computer code, is an essential skill in numerous fields. A description of the neural structures engaged and modified during programming skill acquisition could help improve training programs and provide clues to the neural substrates underlying the acquisition of related skills. Fourteen female university students without prior computer programing experience were examined by functional magnetic resonance imaging (fMRI) during the early and late stages of a 5-month 'Computer Processing' course. Brain regions involved in task performance and learning were identified by comparing responses to programming and control tasks during the early and late stages. The accuracy of performing a programming task was significantly improved during the late stage. Various regions of the frontal, temporal, parietal, and occipital cortex as well as several subcortical structures (caudate nuclei and cerebellum) were activated during programming tasks. Brain activity in the right inferior frontal gyrus was greater during the late stage and significantly correlated with improved task performance. Although the left inferior frontal gyrus was also highly active during the programming task, there were no learning-induced changes in activity or a significant correlation between activity and improved task performances. Computer programming learning among novices induces functional neuroplasticity within the right inferior frontal gyrus but not the left inferior gyrus (Broca's area).

Simultaneous fMRI and tDCS for Enhancing Training of Flight Tasks.

There is a gap in our understanding of how best to apply transcranial direct-current stimulation (tDCS) to enhance learning in complex, realistic, and multifocus tasks such as aviation. Our goal is to assess the effects of tDCS and feedback training on task performance, brain activity, and connectivity using functional magnetic resonance imaging (fMRI). Experienced glider pilots were recruited to perform a one-day, three-run flight-simulator task involving varying difficulty conditions and a secondary auditory task, mimicking real flight requirements. The stimulation group (versus sham) received 1.5 mA high-definition HD-tDCS to the right dorsolateral prefrontal cortex (DLPFC) for 30 min during the training. Whole-brain fMRI was collected before, during, and after stimulation. Active stimulation improved piloting performance both during and post-training, particularly in novice pilots. The fMRI revealed a number of tDCS-induced effects on brain activation, including an increase in the left cerebellum and bilateral basal ganglia for the most difficult conditions, an increase in DLPFC activation and connectivity to the cerebellum during stimulation, and an inhibition in the secondary task-related auditory cortex and Broca's area. Here, we show that stimulation increases activity and connectivity in flight-related brain areas, particularly in novices, and increases the brain's ability to focus on flying and ignore distractors. These findings can guide applied neurostimulation in real pilot training to enhance skill acquisition and can be applied widely in other complex perceptual-motor real-world tasks.

Use of longitudinal functional MRI to demonstrate translocation of language function in patients with brain tumors.

The ability of functional MRI (fMRI) to localize patient-specific eloquent areas has proved worthwhile in efforts to maximize resection while minimizing risk of iatrogenic damage in patients with brain tumors. Although cortical reorganization has been described, the frequency of its occurrence and the factors that influence incidence are not well understood. The authors investigated changes in language laterality between 2 fMRI studies in patients with brain tumors to elucidate factors contributing to cortical reorganization. The authors analyzed 33 patients with brain tumors involving eloquent language areas who underwent 2 separate presurgical, language task-based fMRI examinations (fMRI1 and fMRI2). Pathology consisted of low-grade glioma (LGG) in 15, and high-grade glioma (HGG) in 18. The mean time interval between scans was 35 ± 38 months (mean ± SD). Regions of interest were drawn for Broca's area (BA) and the contralateral BA homolog. The laterality index (LI) was calculated and categorized as follows: > 0.2, left dominance; 0.2 to -0.2, codominance; and < -0.2, right dominance. Translocation of language function was defined as a shift across one of these thresholds between the 2 scans. Comparisons between the 2 groups, translocation of language function (reorganized group) versus no translocation (constant group), were performed using the Mann-Whitney U-test. Nine (27%) of 33 patients demonstrated translocation of language function. Eight of 9 patients with translocation had tumor involvement of BA, compared to 5/24 patients without translocation (p < 0.0001). There was no difference in LI between the 2 groups at fMRI1. However, the reorganized group showed a decreased LI at fMRI2 compared to the constant group (-0.1 vs 0.53, p < 0.01). The reorganized cohort showed a significant difference between LI1 and LI2 (0.50 vs -0.1, p < 0.0001) whereas the constant cohort did not. A longer time interval was found in the reorganized group between fMRI1 and fMRI2 for patients with LGG (34 vs 107 months, p < 0.002). Additionally, the reorganized cohort had a greater proportion of local tumor invasion into eloquent areas at fMRI2 than the constant group. Aphasia was present following fMRI2 in 13/24 (54%) patients who did not exhibit translocation, compared to 2/9 (22%) patients who showed translocation. Translocation of language function in patients with brain tumor is associated with tumor involvement of BA, longer time intervals between scans, and is seen in both LGG and HGG. The reduced incidence of aphasia in the reorganized group raises the possibility that reorganization supports the conservation of language function. Therefore, longitudinal fMRI is useful because it may point to reorganization and could affect therapeutic planning for patients.

The importance of the dorsal branch of the arcuate fasciculus in phonological working memory.

Phonological working memory (PWM) is important for language learning and processing. The most studied language brain regions are the classical Broca's area on the inferior frontal gyrus and Wernicke's area on the posterior temporal region and their anatomical connection via the classic arcuate fasciculus (AF) referred to here as the ventral AF (AFv). However, areas on the middle frontal gyrus (MFG) are essential for PWM processes. There is also a dorsal branch of the AF (AFd) that specifically links the posterior temporal region with the MFG. Furthermore, there is the temporo-frontal extreme capsule fasciculus (TFexcF) that courses ventrally and links intermediate temporal areas with the lateral prefrontal cortex. The AFv, AFd and TFexcF were dissected virtually in the same participants who performed a PWM task in a functional magnetic resonance imaging study. The results showed that good performance on the PWM task was exclusively related to the properties of the left AFd, which specifically links area 8A (known to be involved in attentional aspects of executive control) with the posterior temporal region. The TFexcF, consistent with its known anatomical connection, was related to brain activation in area 9/46v of the MFG that is critical for monitoring the information in memory.

Beyond Broca's and Wernicke's: Functional Mapping of Ancillary Language Centers Prior to Brain Tumor Surgery.

Functional MRI is a well-established tool used for pre-surgical planning to help the neurosurgeon have a roadmap of critical functional areas that should be avoided, if possible, during surgery to minimize morbidity for patients with brain tumors (though this also has applications for surgical resection of epileptogenic tissue and vascular lesions). This article reviews the locations of secondary language centers within the brain along with imaging findings to help improve our confidence in our knowledge on language lateralization. Brief overviews of these language centers and their contributions to the language networks will be discussed. These language centers include primary language centers of "Broca's Area" and "Wernicke's Area". However, there are multiple secondary language centers such as the dorsal lateral prefrontal cortex (DLPFC), frontal eye fields, pre- supplemental motor area (pre-SMA), Basal Temporal Language Area (BTLA), along with other areas of activation. Knowing these foci helps to increase self-assurance when discussing the nature of laterality with the neurosurgeon. By knowing secondary language centers for language lateralization, via fMRI, one can feel confident on providing neurosurgeon colleagues with appropriate information on the laterality of language in preparation for surgery.

Diffuse Large B cell Lymphoma of the Broca Area presented as a Rare Cause of Progressive Cognitive Impairment in a Middle Aged Woman uncovered with DTI Fiber tracking and Spectroscopy

We present the case of a female patient in her 50s who presented with progressive language and cognitive impairments. The patient had a history of ocular vitreoretinal lymphoma, diagnosed three years prior to admission. Radiological investigations, including diffusion tensor imaging, fibertracking, dynamic contrast-enhanced MRI and spectroscopy were performed to establish a differential diagnosis for a relapsing lymphoma

Cerebellar mutism is linked to midbrain volatility and desynchronization from speech cortices.

Cerebellar mutism syndrome is a disorder of speech, movement and affect that can occur after tumour removal from the posterior fossa. Projections from the fastigial nuclei to the periaqueductal grey area were recently implicated in its pathogenesis, but the functional consequences of damaging these projections remain poorly understood. Here, we examine functional MRI data from patients treated for medulloblastoma to identify functional changes in key brain areas that comprise the motor system for speech, which occur along the timeline of acute speech impairment in cerebellar mutism syndrome. One hundred and twenty-four participants, all with medulloblastoma, contributed to the study: 45 with cerebellar mutism syndrome, 11 patients with severe postoperative deficits other than mutism, and 68 without either (asymptomatic). We first performed a data-driven parcellation to spatially define functional nodes relevant to the cohort that align with brain regions critical for the motor control of speech. We then estimated functional connectivity between these nodes during the initial postoperative imaging sessions to identify functional deficits associated with the acute phase of the disorder. We further analysed how functional connectivity changed over time within a subset of participants that had suitable imaging acquired over the course of recovery. Signal dispersion was also measured in the periaqueductal grey area and red nuclei to estimate activity in midbrain regions considered key targets of the cerebellum with suspected involvement in cerebellar mutism pathogenesis. We found evidence of periaqueductal grey dysfunction in the acute phase of the disorder, with abnormal volatility and desynchronization with neocortical language nodes. Functional connectivity with periaqueductal grey was restored in imaging sessions that occurred after speech recovery and was further shown to be increased with left dorsolateral prefrontal cortex. The amygdalae were also broadly hyperconnected with neocortical nodes in the acute phase. Stable connectivity differences between groups were broadly present throughout the cerebrum, and one of the most substantial differences-between Broca's area and the supplementary motor area-was found to be inversely related to cerebellar outflow pathway damage in the mutism group. These results reveal systemic changes in the speech motor system of patients with mutism, centred on limbic areas tasked with the control of phonation. These findings provide further support for the hypothesis that periaqueductal grey dysfunction (following cerebellar surgical injury) contributes to the transient postoperative non-verbal episode commonly observed in cerebellar mutism syndrome but highlights a potential role of intact cerebellocortical projections in chronic features of the disorder.

Acute effects of different exercise forms on executive function and the mechanism of cerebral hemodynamics in hospitalized T2DM patients: a within-subject study.

This study aimed to investigate the acute effects of aerobic exercise (AE), resistance exercise (RE), and integrated concurrent exercise (ICE; i.e., AE plus RE) on executive function among hospitalized type 2 diabetes mellitus (T2DM) inpatients, and the mechanism of cerebral hemodynamics. A within-subject design was applied in 30 hospitalized patients with T2DM aged between 45 and 70 years in the Jiangsu Geriatric Hospital, China. The participants were asked to take AE, RE, and ICE for 3 days at 48-h intervals. Three executive function (EF) tests, namely, Stroop, More-odd shifting, and 2-back tests, were applied at baseline and after each exercise. The functional near-infrared spectroscopy brain function imaging system was used to collect cerebral hemodynamic data. The one-way repeated measurement ANOVA was used to explore training effects on each test indicator. Compared with the baseline data, the EF indicators have been improved after both ICE and RE (p < 0.05). Compared with the AE group, the ICE and RE groups have demonstrated significant improvements in inhibition (ICE: MD = - 162.92 ms; RE: MD = -106.86 ms) and conversion functions (ICE: MD = -111.79 ms; RE: MD = -86.95 ms). Based on the cerebral hemodynamic data, the beta values of brain activation in executive function related brain regions increased after three kinds of exercise, the EF improvements after the ICE showed synchronous activation of blood flow in the dorsolateral prefrontal cortex (DLPFC), the frontal polar (FPA) and orbitofrontal cortex (OFC), the improvement of inhibitory function after RE displayed synchronous activation of DLPFC and FPA, and AE mainly activates DLPFC. The HbO2 concentration in the pars triangularis Broca's area increased significantly after AE, but the EF did not improve significantly. The ICE is preferred for the improvements of executive function in T2DM patients, while AE is more conducive to the improvements of refresh function. Moreover, a synergistic mechanism exists between cognitive function and blood flow activation in specific brain regions.

Exploring the neurobiology of Merge at a basic level: insights from a novel artificial grammar paradigm.

Human language allows us to generate an infinite number of linguistic expressions. It's proposed that this competence is based on a binary syntactic operation, Merge, combining two elements to form a new constituent. An increasing number of recent studies have shifted from complex syntactic structures to two-word constructions to investigate the neural representation of this operation at the most basic level. This fMRI study aimed to develop a highly flexible artificial grammar paradigm for testing the neurobiology of human syntax at a basic level. During scanning, participants had to apply abstract syntactic rules to assess whether a given two-word artificial phrase could be further merged with a third word. To control for lower-level template-matching and working memory strategies, an additional non-mergeable word-list task was set up. Behavioral data indicated that participants complied with the experiment. Whole brain and region of interest (ROI) analyses were performed under the contrast of "structure > word-list." Whole brain analysis confirmed significant involvement of the posterior inferior frontal gyrus [pIFG, corresponding to Brodmann area (BA) 44]. Furthermore, both the signal intensity in Broca's area and the behavioral performance showed significant correlations with natural language performance in the same participants. ROI analysis within the language atlas and anatomically defined Broca's area revealed that only the pIFG was reliably activated. Taken together, these results support the notion that Broca's area, particularly BA 44, works as a combinatorial engine where words are merged together according to syntactic information. Furthermore, this study suggests that the present artificial grammar may serve as promising material for investigating the neurobiological basis of syntax, fostering future cross-species studies.

Linguistic representation of vowels in speech imagery EEG.

Speech imagery recognition from electroencephalograms (EEGs) could potentially become a strong contender among non-invasive brain-computer interfaces (BCIs). In this report, first we extract language representations as the difference of line-spectra of phones by statistically analyzing many EEG signals from the Broca area. Then we extract vowels by using iterative search from hand-labeled short-syllable data. The iterative search process consists of principal component analysis (PCA) that visualizes linguistic representation of vowels through eigen-vectors φ(m), and subspace method (SM) that searches an optimum line-spectrum for redesigning φ(m). The extracted linguistic representation of Japanese vowels /i/ /e/ /a/ /o/ /u/ shows 2 distinguished spectral peaks (P1, P2) in the upper frequency range. The 5 vowels are aligned on the P1-P2 chart. A 5-vowel recognition experiment using a data set of 5 subjects and a convolutional neural network (CNN) classifier gave a mean accuracy rate of 72.6%.

Domain-general and domain-specific functional networks of Broca's area underlying language processing.

Despite abundant research on the role of Broca's area in language processing, there is still no consensus on language specificity of this region and its connectivity network. The present study employed the meta-analytic connectivity modeling procedure to identify and compare domain-specific (language-specific) and domain-general (shared between language and other domains) functional connectivity patterns of three subdivisions within the broadly defined Broca's area: pars opercularis (IFGop), pars triangularis (IFGtri), and pars orbitalis (IFGorb) of the left inferior frontal gyrus. The findings revealed a left-lateralized frontotemporal network for all regions of interest underlying domain-specific linguistic functions. The domain-general network, however, spanned frontoparietal regions that overlap with the multiple-demand network and subcortical regions spanning the thalamus and the basal ganglia. The findings suggest that language specificity of Broca's area emerges within a left-lateralized frontotemporal network, and that domain-general resources are garnered from frontoparietal and subcortical networks when required by task demands.

Broca’s Aphasia Caused by Hemorrhagic Stroke in a Young Patient: A Case Report

Broca aphasia is a non-fluent aphasia in which the output of spontaneous speech is markedly diminished and there is a loss of normal grammatical structure. We report a case of aphasia presenting different features of aphasia following cerebral hemorrhage in the left frontoparietal lobe, which includes Broca's area. A 25-year-old man presented to our emergency department with a headache, Broca aphasia, and difficulty in vision that started two days ago. Bilateral hemorrhagic areas were seen in dilated fundus examination. A CT scan was performed and showed multiple intracranial hemorrhages. Although stroke is considered a disease of the elderly, it can also be present among young people. An underlying malignancy may be the trigger for hemorrhagic ischemia. Injury to the frontal regions of the left hemisphere impacts how words are strung together to form complete sentences. This can lead to Broca's Aphasia.

Effect of tumor genetics, pathology, and location on fMRI of language reorganization in brain tumor patients

ObjectivesLanguage reorganization may follow tumor invasion of the dominant hemisphere. Tumor location, grade, and genetics influence the communication between eloquent areas and tumor growth dynamics, which are drivers of language plasticity. We evaluated tumor-induced language reorganization studying the relationship of fMRI language laterality to tumor-related variables (grade, genetics, location), and patient-related variables (age, sex, handedness).MethodsThe study was retrospective cross-sectional. We included patients with left-hemispheric tumors (study group) and right-hemispheric tumors (controls). We calculated five fMRI laterality indexes (LI): hemispheric, temporal lobe, frontal lobe, Broca’s area (BA), Wernicke’s area (WA). We defined LI ≥ 0.2 as left-lateralized (LL) and LI < 0.2 as atypical lateralized (AL). Chi-square test (p < 0.05) was employed to identify the relationship between LI and tumor/patient variables in the study group. For those variables having significant results, confounding factors were evaluated in a multinomial logistic regression model.ResultsWe included 405 patients (235 M, mean age: 51 years old) and 49 controls (36 M, mean age: 51 years old). Contralateral language reorganization was more common in patients than controls. The statistical analysis demonstrated significant association between BA LI and patient sex (p = 0.005); frontal LI, BA LI, and tumor location in BA (p < 0.001); hemispheric LI and fibroblast growth factor receptor (FGFR) mutation (p = 0.019); WA LI and O6-methylguanine-DNA methyltransferase promoter (MGMT) methylation in high-grade gliomas (p = 0.016).ConclusionsTumor genetics, pathology, and location influence language laterality, possibly due to cortical plasticity. Increased fMRI activation in the right hemisphere was seen in patients with tumors in the frontal lobe, BA and WA, FGFR mutation, and MGMT promoter methylation.Key Points• Patients harboring left-hemispheric tumors present with contralateral translocation of language function. Influential variables for this phenomenon included frontal tumor location, BA location, WA location, sex, MGMT promoter methylation, and FGFR mutation.• Tumor location, grade, and genetics may influence language plasticity, thereby affecting both communication between eloquent areas and tumor growth dynamics.• In this retrospective cross-sectional study, we evaluated language reorganization in 405 brain tumor patients by studying the relationship of fMRI language laterality to tumor-related variables (grade, genetics, location), and patient-related variables (age, sex, handedness).

Pterion topography in dry human skulls: A comprehensive institutional analysis from Kashmir valley, Northern India

The pterion is an important boane marker due to its frequent proximity to Broca's Area and the anterior branch of the middle meningeal artery. The aim of the study was to examine the different types of pterions and gauge the distance between bony landmarks on the skull and the midpoint of the pterion. The study used 30 adult dried human skulls of undetermined age and sex. Bilateral observation of pterion types and locations was made. The fronto-zygomatic suture, the center of the zygomatic arch, the tip of the mastoid process, the glabella, the anterosuperior edge of the external auditory meatus, and the asterion were all measured using a digital Vernier caliper. A total of five varieties of pterions were observed; Spheno-parietal, frontotemporal, stellate, epipteric, and atypical pterion. Bilaterally Sphenoparietal was the most prevalent form of skull among those examined. The mean distances from the midpoint of the pterion to the fronto-zygomatic suture were 30.99±5.48 mm and 30.21±5.72 mm, respectively. The average distances to the middle of the zygomatic arch were 37.77± 3.61 mm and 37.94±3.89 mm, respectively. The average distances to the asterion were 82.54±7.18 mm and 84.43±6.78 mm. The mean distances to the external acoustic meatus were 50.70±3.18 mm and 51.35±3.37 mm; to the glabella, it was 78.01±6.15 mm and 75.66±6.73mm; to the tip of the mastoid process, it was 80.27±6.20 mm on the right side and 78.98±5.45 mm on the left side. The pterion is the most popular surface landmark. Neurosurgeons, radiologists, anthropologists, and forensic pathologists will benefit from the study's findings about the classification of pterion.

Power spectral analysis can determine language laterality from resting-state functional MRI data in healthy controls.

Resting-state functional magnetic resonance imaging (rsfMRI) has been proposed as an alternative to task-based fMRI including clinical situations such as preoperative brain tumor planning, due to advantages including ease of performance and time savings. However, one of its drawbacks is the limited ability to accurately lateralize language function. Using the rsfMRI data of healthy controls, we carried out a power spectra analysis on three regions of interest (ROIs): Broca's area (BA) in the frontal cortex for language, hand motor (HM) area in the primary motor cortex, and the primary visual cortex (V1). Spike removal, motion correction, linear trend removal, and spatial smoothing were applied. Spontaneous low-frequency fluctuations (0.01-0.1Hz) were filtered to enable functional integration. BA showed greater power on the left hemisphere relative to the right (p=.0055), while HM (p=.1563) and V1 (p=.4681) were not statistically significant. A novel index, termed the power laterality index (PLI), computed to estimate the degree of power lateralization for each brain region, revealed a statistically significant difference between BA and V1 (p<.00001), where V1 was used as a control since the primary visual cortex does not lateralize. Validation studies used to compare PLI to a laterality index computed using phonemic fluency, a task-based, language fMRI paradigm, demonstrated good correlation. The power spectra for BA revealed left language lateralization, which was not replicated in HM or V1. This work demonstrates the feasibility and validity of an ROI-based power spectra analysis on rsfMRI data for language lateralization.