Intersubject Dynamic Conditional Correlation: A Novel Method to Track the Framewise Network Implication during Naturalistic Stimuli.

Naturalistic stimuli have become increasingly popular in modern cognitive neuroscience. These stimuli have high ecological validity due to their rich and multilayered features. However, their complexity also presents methodological challenges for uncovering neural network reconfiguration.

Reading anxiety modulates the functional connectivity of the reading-related network during adult reading.

Researchers have studied cognitive and linguistic skills in predicting reading abilities, but the impact of affective factors such as anxiety on reading at the neurobiological level is not well understood. Here, we used functional magnetic resonance imaging to investigate the neural correlates of reading anxiety in adult readers performing a semantic judgment task. The results showed that reading anxiety was significantly correlated with response time but not with accuracy.

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.

Dynamic network reorganization underlying neuroplasticity: the deficits-severity-related language network dynamics in patients with left hemispheric gliomas involving language network.

Brain network dynamics not only endow the brain with flexible coordination for various cognitive processes but also with a huge potential of neuroplasticity for development, skill learning, and after cerebral injury. Diffusive and progressive glioma infiltration triggers the neuroplasticity for functional compensation, which is an outstanding pathophysiological model for the investigation of network reorganization underlying neuroplasticity. In this study, we employed dynamic conditional correlation to construct framewise language networks and investigated dynamic reorganizations in 83 patients with left hemispheric gliomas involving language networks (40 patients without aphasia and 43 patients with aphasia).

Longitudinal assessment of network reorganizations and language recovery in postoperative patients with glioma.

For patients with glioma located in or adjacent to the linguistic eloquent cortex, awake surgery with an emphasis on the preservation of language function is preferred. However, the brain network basis of postoperative linguistic functional outcomes remains largely unknown. In this work, 34 patients with left cerebral gliomas who underwent awake surgery were assessed for language function and resting-state network properties before and after surgery.

Multivariate machine learning-based language mapping in glioma patients based on lesion topography.

Diffusive and progressive tumor infiltration within language-related areas of the brain induces functional reorganization. However, the macrostructural basis of subsequent language deficits is less clear. To address this issue, lesion topography data from 137 preoperative patients with left cerebral language-network gliomas (81 low-grade gliomas and 56 high-grade gliomas), were adopted for multivariate machine-learning-based lesion-language mapping analysis.

Individual differences in first-pass fixation duration in reading are related to resting-state functional connectivity.

Although there are considerable individual differences in eye movements during text reading, their neural correlates remain unclear. In this study, we investigated the relationship between the first-pass fixation duration (FPFD) in natural reading and resting-state functional connectivity (RSFC) in the brain. We defined the brain regions associated with early visual processing, word identification, attention shifts, and oculomotor control as seed regions.

Radiomic Features From Multi-Parameter MRI Combined With Clinical Parameters Predict Molecular Subgroups in Patients With Medulloblastoma.

The 2016 WHO classification of central nervous system tumors has included four molecular subgroups under medulloblastoma (MB) as sonic hedgehog (SHH), wingless (WNT), Grade 3, and Group 4. We aimed to develop machine learning models for predicting MB molecular subgroups based on multi-parameter magnetic resonance imaging (MRI) radiomics, tumor locations, and clinical factors. A total of 122 MB patients were enrolled retrospectively.

Incremental prognostic value and underlying biological pathways of radiomics patterns in medulloblastoma.

Background: To develop a radiomics signature for predicting overall survival (OS)/progression-free survival (PFS) in patients with medulloblastoma (MB), and to investigate the incremental prognostic value and biological pathways of the radiomics patterns.

Methods: A radiomics signature was constructed based on magnetic resonance imaging (MRI) from a training cohort (n = 83), and evaluated on a testing cohort (n = 83). Key pathways associated with the signature were identified by RNA-seq (GSE151519).

Tumor grade-related language and control network reorganization in patients with left cerebral glioma.

Language processing relies on both a functionally specialized language network and a domain-general cognitive control network. Yet, how the two networks reorganize after damage resulting from diffuse and progressive glioma remains largely unknown. To address this issue, 130 patients with left cerebral gliomas, including 77 patients with low-grade glioma (LGG, WHO grade Ⅰ/II), 53 patients with high-grade glioma (HGG, WHO grade III/IV) and 38 healthy controls (HC) were adopted.

Convergent syndromic atrophy of pain and emotional systems in patients with irritable bowel syndrome and depressive symptoms.

Irritable bowel syndrome (IBS) is a brain-gut disorder that is often accompanied by psychiatric comorbidities, particularly depression. However, the neuroanatomical substrates of IBS with depressive symptoms (DEP-IBS) and how depressive symptoms and brain morphology modulate IBS symptoms remain unknown. In this study, structural MRI data were processed using a voxel-based morphometry technique and one-way analysis of covariance (ANCOVA) and post-hoc t-tests were performed to compare gray matter volume (GMV) among 28 patients with DEP-IBS, 21 patients with IBS who lacked depressive symptoms (nDEP-IBS), and 36 healthy controls (HC).

Resting-state functional connectivity predicts individual language impairment of patients with left hemispheric gliomas involving language network.

Language deficits following brain tumors should consider the dynamic interactions between different tumor growth kinetics and functional network reorganization. We measured the resting-state functional connectivity of 126 patients with left cerebral gliomas involving language network areas, including 77 patients with low-grade gliomas (LGG) and 49 patients with high-grade gliomas (HGG). Functional network mapping for language was performed by construction of a multivariate machine learning-based prediction model of individual aphasia quotient (AQ), a summary score that indicates overall severity of language impairment.

Intrinsic functional connectivity of medial prefrontal cortex predicts the individual moral bias in economic valuation partially through the moral sensitivity trait.

An individual's economic valuation of a given object is biased by the moral status of the persons to whom the object is attached. The neural basis for how such "moral bias" occurs, especially how it is maintained in the resting state, are largely unknown. In the current study, we explored this question by correlating the functional connectivity with participants' behavioral performance measured in a novel task which captured how the economic valuation was influenced by given moral information.

Brain hubs in lesion models: Predicting functional network topology with lesion patterns in patients.

Various important topological properties of healthy brain connectome have recently been identified. However, the manner in which brain lesion changes the functional network topology is unknown. We examined how critical specific brain areas are in the maintenance of network topology using multivariate support vector regression analysis on brain structural and resting-state functional imaging data in 96 patients with brain damages.

Influences of Head Motion Regression on High-Frequency Oscillation Amplitudes of Resting-State fMRI Signals.

High-frequency oscillations (HFOs, >0.1 Hz) of resting-state fMRI (rs-fMRI) signals have received much attention in recent years. Denoising is critical for HFO studies.

Detecting static and dynamic differences between eyes-closed and eyes-open resting states using ASL and BOLD fMRI.

Resting-state fMRI studies have increasingly focused on multi-contrast techniques, such as BOLD and ASL imaging. However, these techniques may reveal different aspects of brain activity (e.g.

Neural correlates of decision making after unfair treatment.

Empirical evidence indicates that people are inequity averse. However, it is unclear whether and how suffering unfairness impacts subsequent behavior. We investigated the consequences of unfair treatment in subsequent interactions with new interaction partners and the associated neural mechanisms.

[Functional connectivity in ischemia stroke motor aphasia patients during resting state].

Objective: To investigate the changes of Broca's area functional connectivity in ischemia stroke patients with motor aphasia during resting state using functional magnetic resonance imaging (fMRI).

Methods: The functional connectivity of Broca's area was analyzed by observing the correlation between low frequency signal fluctuations in Broca's area and those in all brain regions.

Results: In the normal controls group, there was multiple brain area positively correlated with Broca's area during resting state.

Amplitude differences in high-frequency fMRI signals between eyes open and eyes closed resting states.

Recent studies employing rapid sampling techniques have demonstrated that the resting state fMRI (rs-fMRI) signal exhibits synchronized activities at frequencies much higher than the conventional frequency range (<0.1 Hz). However, little work has investigated the changes in the high-frequency fluctuations between different resting states.