A Heteromodal Word-Meaning Binding Site in the Visual Word Form Area under Top-Down Frontoparietal Control.

The integral capacity of human language together with semantic memory drives the linkage of words and their meaning, which theoretically is subject to cognitive control. However, it remains unknown whether, across different language modalities and input/output formats, there is a shared system in the human brain for word-meaning binding and how this system interacts with cognitive control. Here, we conducted a functional magnetic resonance imaging experiment based on a large cohort of subjects (50 females, 50 males) to comprehensively measure the brain responses evoked by semantic processing in spoken and written word comprehension and production tasks (listening, speaking, reading, and writing). We found that heteromodal word input and output tasks involved distributed brain regions within a frontal-parietal-temporal network and focally coactivated the anterior lateral visual word form area (VWFA), which is located in the basal occipitotemporal area. Directed connectivity analysis revealed that the VWFA was invariably under significant top-down modulation of the frontoparietal control network and interacts with regions related to attention and semantic representation. This study reveals that the VWFA is a key site subserving general semantic processes linking words and meaning, challenging the predominant emphasis on this area's specific role in reading or more general visual processes. Our findings also suggest that the dynamics between semantic memory and cognitive control mechanisms during word processing are largely independent of the modalities of input or output.SIGNIFICANCE STATEMENT Binding words and their meaning into a coherent whole during retrieval requires accessing semantic memory and cognitive control, allowing our thoughts to be expressed and comprehended through mind-external tokens in multiple modalities, such as written or spoken forms. However, it is still unknown whether multimodal language comprehension and production share a common word-meaning binding system in human brains and how this system is connected to a cognitive control mechanism. By systematically measuring brain activity evoked by spoken and written verbal input and output tasks tagging word-meaning binding processes, we demonstrate a general word-meaning binding site within the visual word form area (VWFA) and how this site is modulated by the frontal-parietal control network.

Cortical electrophysiological evidence for individual-specific temporal organization of brain functional networks.

The human brain has been demonstrated to rapidly and continuously form and dissolve networks on a subsecond timescale, offering effective and essential substrates for cognitive processes. Understanding how the dynamic organization of brain functional networks on a subsecond level varies across individuals is, therefore, of great interest for personalized neuroscience. However, it remains unclear whether features of such rapid network organization are reliably unique and stable in single subjects and, therefore, can be used in characterizing individual networks. Here, we used two sets of 5-min magnetoencephalography (MEG) resting data from 39 healthy subjects over two consecutive days and modeled the spontaneous brain activity as recurring networks fast shifting between each other in a coordinated manner. MEG cortical maps were obtained through source reconstruction using the beamformer method and subjects' temporal structure of recurring networks was obtained via the Hidden Markov Model. Individual organization of dynamic brain activity was quantified with the features of the network-switching pattern (i.e., transition probability and mean interval time) and the time-allocation mode (i.e., fractional occupancy and mean lifetime). Using these features, we were able to identify subjects from the group with significant accuracies (~40% on average in 0.5-48 Hz). Notably, the default mode network displayed a distinguishable pattern, being the least frequently visited network with the longest duration for each visit. Together, we provide initial evidence suggesting that the rapid dynamic temporal organization of brain networks achieved in electrophysiology is intrinsic and subject specific.

Detecting resting-state brain activity using OEF-weighted imaging.

Traditional resting-state functional magnetic resonance imaging (fMRI) is mainly based on the blood oxygenation level-dependent (BOLD) contrast. The oxygen extraction fraction (OEF) represents an important parameter of brain metabolism and is a key biomarker of tissue viability, detecting the ratio of oxygen utilization to oxygen delivery. Investigating spontaneous fluctuations in the OEF-weighted signal is crucial for understanding the underlying mechanism of brain activity because of the immense energy budget during the resting state. However, due to the poor temporal resolution of OEF mapping, no studies have reported using OEF contrast to assess resting-state brain activity. In this fMRI study, we recorded brain OEF-weighted fluctuations for 10 min in healthy volunteers across two scanning visits, using our recently developed pulse sequence that can acquire whole-brain voxel-wise OEF-weighted signals with a temporal resolution of 3 s. Using both group-independent component analysis and seed-based functional connectivity analysis, we robustly identified intrinsic brain networks, including the medial visual, lateral visual, auditory, default mode and bilateral executive control networks, using OEF contrast. Furthermore, we investigated the resting-state local characteristics of brain activity based on OEF-weighted signals using regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFF). We demonstrated that the gray matter regions of the brain, especially those in the default mode network, showed higher ReHo and fALFF values with the OEF contrast. Moreover, voxel-wise test-retest reliability comparisons across the whole brain demonstrated that the reliability of resting-state brain activity based on the OEF contrast was moderate for the network indices and high for the local activity indices, especially for ReHo. Although the reliabilities of the OEF-based indices were generally lower than those based on BOLD, the reliability of OEF-ReHo was slightly higher than that of BOLD-ReHo, with a small effect size, which indicated that OEF-ReHo could be used as a reliable index for characterizing resting-state local brain activity as a complement to BOLD. In conclusion, OEF can be used as an effective contrast to study resting-state brain activity with a medium to high test-retest reliability.

Impact of brain segmentation methods on regional metabolism quantification in 18F-FDG PET/MR analysis.

BACKGROUND: Accurate analysis of quantitative PET data plays a crucial role in studying small, specific brain structures. The integration of PET and MRI through an integrated PET/MR system presents an opportunity to leverage the benefits of precisely aligned structural MRI and molecular PET images in both spatial and temporal dimensions. However, in many clinical workflows, PET studies are often performed without the aid of individually matched structural MRI scans, primarily for the sake of convenience in the data collection and brain segmentation possesses. Currently, two commonly employed segmentation strategies for brain PET analysis are distinguished: methods with or without MRI registration and methods employing either atlas-based or individual-based algorithms. Moreover, the development of artificial intelligence (AI)-assisted methods for predicting brain segmentation holds promise but requires further validation of their efficiency and accuracy for clinical applications. This study aims to compare and evaluate the correlations, consistencies, and differences among the above-mentioned brain segmentation strategies in quantification of brain metabolism in 18F-FDG PET/MR analysis. RESULTS: Strong correlations were observed among all methods (r = 0.932 to 0.999, P < 0.001). The variances attributable to subject and brain region were higher than those caused by segmentation methods (P < 0.001). However, intraclass correlation coefficient (ICC)s between methods with or without MRI registration ranged from 0.924 to 0.975, while ICCs between methods with atlas- or individual-based algorithms ranged from 0.741 to 0.879. Brain regions exhibiting significant standardized uptake values (SUV) differences due to segmentation methods were the basal ganglia nuclei (maximum to 11.50 ± 4.67%), and various cerebral cortexes in temporal and occipital regions (maximum to 18.03 ± 5.52%). The AI-based method demonstrated high correlation (r = 0.998 and 0.999, P < 0.001) and ICC (0.998 and 0.997) with FreeSurfer, substantially reducing the time from 8.13 h to 57 s on per subject. CONCLUSIONS: Different segmentation methods may have impact on the calculation of brain metabolism in basal ganglia nuclei and specific cerebral cortexes. The AI-based approach offers improved efficiency and is recommended for its enhanced performance.

Effects of mild hypoxia on oxygen extraction fraction responses to brain stimulation.

Characterizing the effect of limited oxygen availability on brain metabolism during brain activation is an essential step towards a better understanding of brain homeostasis and has obvious clinical implications. However, how the cerebral oxygen extraction fraction (OEF) depends on oxygen availability during brain activation remains unclear, which is mostly attributable to the scarcity and safety of measurement techniques. Recently, a magnetic resonance imaging (MRI) method that enables noninvasive and dynamic measurement of the OEF has been developed and confirmed to be applicable to functional MRI studies. Using this novel method, the present study investigated the motor-evoked OEF response in both normoxia (21% O2) and hypoxia (12% O2). Our results showed that OEF activation decreased in the brain areas involved in motor task execution. Decreases in the motor-evoked OEF response were greater under hypoxia (-21.7% ± 5.5%) than under normoxia (-11.8% ± 3.7%) and showed a substantial decrease as a function of arterial oxygen saturation. These findings suggest a different relationship between oxygen delivery and consumption during hypoxia compared to normoxia. This methodology may provide a new perspective on the effects of mild hypoxia on brain function.

Impaired cerebral vascular and metabolic responses to parametric N-back tasks in subjective cognitive decline.

Previous studies reported abnormally increased and/or decreased blood oxygen level-dependent (BOLD) activations during functional tasks in subjective cognitive decline (SCD). The neurophysiological basis underlying these functional aberrations remains debated. This study aims to investigate vascular and metabolic responses and their dependence on cognitive processing loads during functional tasks in SCD. Twenty-one SCD and 18 control subjects performed parametric N-back working-memory tasks during MRI scans. Task-evoked percentage changes (denoted as δ) in cerebral blood volume (δCBV), cerebral blood flow (δCBF), BOLD signal (δBOLD) and cerebral metabolic rate of oxygen (δCMRO2) were evaluated. In the frontal lobe, trends of decreased δCBV, δCBF and δCMRO2 and increased δBOLD were observed in SCD compared with control subjects under lower loads, and these trends increased to significant differences under the 3-back load. δCBF was significantly correlated with δCMRO2 in controls, but not in SCD subjects. As N-back loads increased, the differences between SCD and control subjects in δCBF and δCMRO2 tended to enlarge. In the parietal lobe, no significant between-group difference was observed. Our findings suggested that impaired vascular and metabolic responses to functional tasks occurred in the frontal lobe of SCD, which contributed to unusual BOLD hyperactivation and was modulated by cognitive processing loads.

Measurement of CMRO2 and its relationship with CBF in hypoxia with an extended calibrated BOLD method.

Cerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO2) are physiological parameters that not only reflect brain health and disease but also jointly contribute to blood oxygen level-dependent (BOLD) signals. Nevertheless, unsolved issues remain concerning the CBF-CMRO2 relationship in the working brain under various oxygen conditions. In particular, the CMRO2 responses to functional tasks in hypoxia are less studied. We extended the calibrated BOLD model to incorporate CMRO2 measurements in hypoxia. The extended model, which was cross-validated with a multicompartment BOLD model, considers the influences of the reduced arterial saturation level and increased baseline cerebral blood volume (CBV) and deoxyhemoglobin concentration on the changes of BOLD signals in hypoxia. By implementing a pulse sequence to simultaneously acquire the CBV-, CBF- and BOLD-weighted signals, we investigated the effects of mild hypoxia on the CBF and CMRO2 responses to graded visual stimuli. Compared with normoxia, mild hypoxia caused significant alterations in both the amplitude and the trend of the CMRO2 responses but did not impact the corresponding CBF responses. Our observations suggested that the flow-metabolism coupling strategies in the brain during mild hypoxia were different from those during normoxia.

Dynamic Neural Network Changes Revealed by Voxel-Based Functional Connectivity Strength in Left Basal Ganglia Ischemic Stroke.

OBJECTIVE: This study intends to track whole-brain functional connectivity strength (FCS) changes and the lateralization index (LI) in left basal ganglia (BG) ischemic stroke patients. METHODS: Twenty-five patients (N = 25; aged 52.73 ± 10.51 years) with five visits at <7, 14, 30, 90, and 180 days and 26 healthy controls (HCs; N = 26; 51.84 ± 8.06 years) were examined with resting-state functional magnetic resonance imaging (rs-fMRI) and motor function testing. FCS and LI were calculated through constructing the voxel-based brain functional network. One-way analysis of covariance (ANOVA) was first performed to obtain longitudinal FCS and LI changes in patients among the five visits (Bonferroni corrected, P < 0.05). Then, pairwise comparisons of FCS and LI were obtained during the five visits, and the two-sample t test was used to examine between-group differences in FCS [family-wise error (FWE) corrected, P < 0.05] and LI. Correlations between connectivity metrics (FCS and LI) and motor function were further assessed. RESULTS: Compared to HCs, decreased FCS in the patients localized in the calcarine and inferior occipital gyrus (IOG), while increased FCS gathered in the middle prefrontal cortex (MPFC), middle frontal gyrus, and insula (P < 0.05). The LI and FCS of patients first decreased and then increased, which showed significant differences compared with HCs (P < 0.05) and demonstrated a transition at the 30-day visit. Additionally, LI at the third visit was significantly different from those at the other visits (P < 0.05). No significant longitudinal correlations were observed between motor function and FCS or LI (P > 0.05). CONCLUSION: Focal ischemic stroke in the left BG leads to extensive alterations in the FCS. Strong plasticity in the functional networks could be reorganized in different temporal dynamics to facilitate motor recovery after BG stroke, contribute to diagnosing the disease course, and estimate the intervention treatment.

Projections of Brodmann Area 6 to the Pyramidal Tract in Humans: Quantifications Using High Angular Resolution Data.

Primate studies indicate that the pyramidal tract (PyT) could originate from Brodmann area (BA) 6. However, in humans, the accurate origin of PyT from BA 6 is still uncertain owing to difficulties in visualizing anatomical features such as the fanning shape at the corona radiata and multiple crossings at the semioval centrum. High angular-resolution diffusion imaging (HARDI) could reliably replicate these anatomical features. We explored the origin of the human PyT from BA 6 using HARDI. With HARDI data of 30 adults from the Massachusetts General Hospital-Human Connectome Project (MGH-HCP) database and the HCP 1021 template (average of 1021 HCP diffusion data), we visualized the PyT at the 30-averaged group level and the 1021 large-sample level and validated the observations in each of the individuals. Endpoints of the fibers within each subregion were quantified. PyT fibers originating from the BA 6 were consistently visualized in all images. Specifically, the bilateral supplementary motor area (SMA) and dorsal premotor area (dPMA) were consistently found to contribute to the PyT. PyT fibers from BA 6 and those from BA 4 exhibited a twisting topology. The PyT contains fibers originating from the SMA and dPMA in BA 6. Infarction of these regions or aging would result in incomplete provision of information to the PyT and concomitant decreases in motor planning and coordination abilities.