Dynamic causal modeling analysis reveals the modulation of motor cortex and integration in superior temporal gyrus during multisensory speech perception.

The processing of speech information from various sensory modalities is crucial for human communication. Both left posterior superior temporal gyrus (pSTG) and motor cortex importantly involve in the multisensory speech perception. However, the dynamic integration of primary sensory regions to pSTG and the motor cortex remain unclear. Here, we implemented a behavioral experiment of classical McGurk effect paradigm and acquired the task functional magnetic resonance imaging (fMRI) data during synchronized audiovisual syllabic perception from 63 normal adults. We conducted dynamic causal modeling (DCM) analysis to explore the cross-modal interactions among the left pSTG, left precentral gyrus (PrG), left middle superior temporal gyrus (mSTG), and left fusiform gyrus (FuG). Bayesian model selection favored a winning model that included modulations of connections to PrG (mSTG → PrG, FuG → PrG), from PrG (PrG → mSTG, PrG → FuG), and to pSTG (mSTG → pSTG, FuG → pSTG). Moreover, the coupling strength of the above connections correlated with behavioral McGurk susceptibility. In addition, significant differences were found in the coupling strength of these connections between strong and weak McGurk perceivers. Strong perceivers modulated less inhibitory visual influence, allowed less excitatory auditory information flowing into PrG, but integrated more audiovisual information in pSTG. Taken together, our findings show that the PrG and pSTG interact dynamically with primary cortices during audiovisual speech, and support the motor cortex plays a specifically functional role in modulating the gain and salience between auditory and visual modalities. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-023-09945-z.

[18F]FDG PET metabolic patterns in mesial temporal lobe epilepsy with different pathological types.

OBJECTIVES: To investigate [18F]FDG PET patterns of mesial temporal lobe epilepsy (MTLE) patients with distinct pathologic types and provide possible guidance for predicting long-term prognoses of patients undergoing epilepsy surgery. METHODS: This was a retrospective review of MTLE patients who underwent anterior temporal lobectomy between 2016 and 2021. Patients were classified as having chronic inflammation and gliosis (gliosis, n = 44), hippocampal sclerosis (HS, n = 43), or focal cortical dysplasia plus HS (FCD-HS, n = 13) based on the postoperative pathological diagnosis. Metabolic patterns and the severity of metabolic abnormalities were investigated among MTLE patients and healthy controls (HCs). The standardized uptake value (SUV), SUV ratio (SUVr), and asymmetry index (AI) of regions of interest were applied to evaluate the severity of metabolic abnormalities. Imaging processing was performed with statistical parametric mapping (SPM12). RESULTS: With a mean follow-up of 2.8 years, the seizure freedom (Engel class IA) rates of gliosis, HS, and FCD-HS were 54.55%, 62.79%, and 69.23%, respectively. The patients in the gliosis group presented a metabolic pattern with a larger involvement of extratemporal areas, including the ipsilateral insula. SUV, SUVr, and AI in ROIs were decreased for patients in all three MTLE groups compared with those of HCs, but the differences among all three MTLE groups were not significant. CONCLUSIONS: MTLE patients with isolated gliosis had the worst prognosis and hypometabolism in the insula, but the degree of metabolic decrease did not differ from the other two groups. Hypometabolic regions should be prioritized for [18F]FDG PET presurgical evaluation rather than [18F]FDG uptake values. CLINICAL RELEVANCE STATEMENT: This study proposes guidance for optimizing the operation scheme in patients with refractory MTLE and emphasizes the potential of molecular neuroimaging with PET using selected tracers to predict the postsurgical histology of patients with refractory MTLE epilepsy. KEY POINTS: • MTLE patients with gliosis had poor surgical outcomes and showed a distinct pattern of decreased metabolism in the ipsilateral insula. • In the preoperative assessment of MTLE, it is recommended to prioritize the evaluation of glucose hypometabolism areas over [18F]FDG uptake values. • The degree of glucose hypometabolism in the epileptogenic focus was not associated with the surgical outcomes of MTLE.

Differences in whole-brain metabolism are associated with the expression of genes related to neurovascular unit integrity and synaptic plasticity in temporal lobe epilepsy.

PURPOSE: Temporal lobe epilepsy (TLE) is a common, polygenic epilepsy syndrome that involves glucose hypometabolism in the epileptogenic zone. However, the transcriptional and cellular signatures underlying the metabolism in TLE remain unclear. METHODS: In this retrospective study, 2-[18F]-fluoro-2-deoxy-D-glucose ([18F]FDG) positron emission tomography (PET) scans of TLE patients (n = 104) who underwent anterior temporal lobectomy were consecutively collected between 2016 and 2021. The transcriptional profiles of TLE risk genes across the brain were identified by the gene expression analyses from six TLE patients and twelve postmortem donors (six from the Allen Human Brain Atlas). Integrating the neuroimaging and transcriptomic data, we examined the relationship between the expression of TLE-associated genes and metabolic alterations in TLE. Furthermore, we performed functional enrichment analyses of the genes with higher weight in partial least squares regression using Metascape. RESULTS: A total of 104 patients with TLE (mean age 29 ± 9 years, 50% male) and 30 healthy controls (HCs) (mean age 31 ± 6 years, 53% male) were enrolled. Compared to that of HCs, patients with TLE showed hypometabolism in the temporal lobes and adjacent structures but hypermetabolism in the thalamus and basal ganglia. The cortical map of inter-group differences in cerebral metabolism was spatially correlated with the expression of a weighted combination of genes enriched in ontology terms and pathways related to neurovascular unit (NVU) integrity and synaptic plasticity. DISCUSSION: Our findings, combined with the analysis of neuroimaging and transcriptional data, suggest that genes related to NVU integrity and synaptic plasticity may drive alterations to brain metabolism that mediate the genetic risk of TLE.

Dynamic functional thalamocortical dysconnectivity in schizophrenia correlates to antipsychotics response.

Although many studies have showed abnormal thalamocortical networks in patients with schizophrenia (SCZ), the dynamic functional thalamocortical connectivity of individuals with SCZ and the effect of antipsychotics on this connectivity have not been investigated. Drug-naïve first-episode individuals with SCZ and healthy controls were recruited. Patients were treated with risperidone for 12 weeks. Resting-state functional magnetic resonance imaging was acquired at baseline and week 12. We identified six functional thalamic subdivisions. The sliding window strategy was used to determine the dynamic functional connectivity (dFC) of each functional thalamic subdivision. Individuals with SCZ displayed decreased or increased dFC variance in different thalamic subdivisions. The baseline dFC between ventral posterior-lateral (VPL) portions and right dorsolateral superior frontal gyrus (rdSFG) correlated with psychotic symptoms. The dFC variance between VPL and right medial orbital superior frontal gyrus (rmoSFG) or rdSFG decreased after 12-week risperidone treatment. The decreased dFC variance between VPL and rmoSFG correlated with the reduction of PANSS scores. Interestingly, the dFC between VPL and rmoSFG or rdSFG decreased in responders. The dFC variance change of VPL and the averaged whole brain signal correlated with the risperidone efficacy. Our study demonstrates abnormal variability in thalamocortical dFC may be implicated in psychopathological symptoms and risperidone response in individuals with schizophrenia, suggesting that thalamocortical dFC variance may be correlated to the efficacy of antipsychotic treatment.Registration: ClinicalTrials.gov Identifier: NCT00435370. https://www.clinicaltrials.gov/ct2/show/NCT00435370?term=NCT00435370&draw=2&rank=1.

Dissociable salience and default mode network modulation in generalized anxiety disorder: a connectome-wide association study.

Generalized anxiety disorder (GAD) is a common anxiety disorder experiencing psychological and somatic symptoms. Here, we explored the link between the individual variation in functional connectome and anxiety symptoms, especially psychological and somatic dimensions, which remains unknown. In a sample of 118 GAD patients and matched 85 healthy controls (HCs), we used multivariate distance-based matrix regression to examine the relationship between resting-state functional connectivity (FC) and the severity of anxiety. We identified multiple hub regions belonging to salience network (SN) and default mode network (DMN) where dysconnectivity associated with anxiety symptoms (P < 0.05, false discovery rate [FDR]-corrected). Follow-up analyses revealed that patient's psychological anxiety was dominated by the hyper-connectivity within DMN, whereas the somatic anxiety could be modulated by hyper-connectivity within SN and DMN. Moreover, hypo-connectivity between SN and DMN were related to both anxiety dimensions. Furthermore, GAD patients showed significant network-level FC changes compared with HCs (P < 0.01, FDR-corrected). Finally, we found the connectivity of DMN could predict the individual psychological symptom in an independent GAD sample. Together, our work emphasizes the potential dissociable roles of SN and DMN in the pathophysiology of GAD's anxiety symptoms, which may be crucial in providing a promising neuroimaging biomarker for novel personalized treatment strategies.

Interictal dynamic network transitions in mesial temporal lobe epilepsy.

OBJECTIVE: To reveal the possible routine of brain network dynamic alterations in patients with mesial temporal lobe epilepsy (mTLE) and to establish a predicted model of seizure recurrence during interictal periods. METHODS: Seventy-nine unilateral mTLE patients with hippocampal sclerosis and 97 healthy controls from two centers were retrospectively enrolled. Dynamic brain configuration analyses were performed with resting-state functional magnetic resonance imaging (MRI) data to quantify the functional stability over time and the dynamic interactions between brain regions. Relationships between seizure frequency and ipsilateral hippocampal module allegiance were evaluated using a machine learning predictive model. RESULTS: Compared to the healthy controls, patients with mTLE displayed an overall higher dynamic network, switching mainly in the epileptogenic regions (false discovery rate [FDR] corrected p-FDR < .05). Moreover, the dynamic network configuration in mTLE was characterized by decreased recruitment (intra-network communication), and increased integration (inter-network communication) among hippocampal systems and large-scale higher-order brain networks (p-FDR < .05). We further found that the dynamic interactions between the hippocampal system and the default-mode network (DMN) or control networks exhibited an opposite distribution pattern (p-FDR < .05). Strikingly, we showed that there was a robust association between predicted seizure frequency based on the ipsilateral hippocampal-DMN dynamics model and actual seizure frequency (p-perm < .001). SIGNIFICANCE: These findings suggest that the interictal brain of mTLE is characterized by dynamical shifts toward unstable state. Our study provides novel insights into the brain dynamic network alterations and supports the potential use of DMN dynamic parameters as candidate neuroimaging markers in monitoring the seizure frequency clinically during interictal periods.

Altered Temporal Variations of Functional Connectivity Associated With Surgical Outcomes in Drug-Resistant Temporal Lobe Epilepsy.

Background: Currently, more than one-third of patients with drug-resistant temporal lobe epilepsy (TLE) continue to develop seizures after resection surgery. Dynamic functional network connectivity (DFNC) analyses, capturing temporal properties of functional connectivity during MRI acquisition, may help us identify unfavorable surgical outcomes. The purpose of this work was to explore the association of DFNC variations of preoperative resting-state MRI and surgical outcomes in patients with drug-resistant TLE. Methods: We evaluated 61 patients with TLE matched for age and gender with 51 healthy controls (HC). Patients with TLE were classified as seizure-free (n = 39) and not seizure-free (n = 16) based on the Engel surgical outcome scale. Six patients were unable to confirm the postoperative status and were not included in the subgroup analysis. The DFNC was calculated using group spatial independent component analysis and the sliding window approach. Results: Dynamic functional network connectivity analyses suggested two distinct connectivity "States." The dynamic connectivity state of patients with TLE was different from HC. TLE subgroup analyses showed not seizure-free (NSF) patients spent significantly more time in State II compared to seizure-free (SF) patients and HC. Further, the number of transitions from State II to State I was significantly lower in NSF patients. SF patients had compensatory enhancement of DFNC strengths between default and dorsal attention network, as well as within the default network. While reduced DFNC strengths of within-network and inter-network were both observed in NSF patients, patients with abnormally temporal properties and more extension DFNC strength alterations were less likely to receive seizure freedom. Conclusions: Our study indicates that DFNC could offer a better understanding of dynamic neural impairment mechanisms of drug-resistant TLE functional network, epileptic brain network reorganization, and provide an additional preoperative evaluation support for surgical treatment of drug-resistant TLE.

Neural processing of personal, relational, and collective self-worth reflected individual differences of self-esteem.

INTRODUCTION: Self-esteem stems from an individual's attributes (PSE), relationships with important others (RSE), and collective membership (CSE). Our study aimed to identify neurological indicators in the processing of personal, relational, and collective self-worth, and to investigate whether these neural indicators could reflect individual differences of self-esteem. METHODS: Fifty students underwent the evaluation of personal, relational, and collective self-worth using a self-referential paradigm while brain activities were recorded using functional-magnetic-resonance-imaging. Meanwhile, their PSE, RSE, and CSE were measured through questionnaires. RESULTS: Conjunction analysis found self-worth processing recruited the precuneus, posterior cingulate cortex, and posterior insula. Multivariate pattern analysis showed compared to relational and collective self-worth, personal self-worth processing was distinguished by cortical-midline-structures and affective-related regions, including caudate and putamen, and that these neural patterns could reflect individual differences of PSE. Compared to personal self-worth, relational self-worth was distinguished by the neural activity of temporoparietal-junction, and this neural pattern reflected individual differences of RSE. Compared to relational self-worth, collective self-worth was distinguished by neural activity of the anterior insula, and this neural pattern reflected individual differences of CSE. DISCUSSION: These results suggested the neurological indicators of self-worth can be recognized as an alternative way to reflect individual differences of self-esteem.

Negative bias effects during audiovisual emotional processing in major depression disorder.

Aberrant affective neural processing and negative emotional bias are trait-marks of major depression disorders (MDDs). However, most research on biased emotional perception in depression has only focused on unimodal experimental stimuli, the neural basis of potentially biased emotional processing of multimodal inputs remains unclear. Here, we addressed this issue by implementing an audiovisual emotional task during functional MRI scanning sessions with 37 patients with MDD and 37 gender-, age- and education-matched healthy controls. Participants were asked to distinguish laughing and crying sounds while being exposed to faces with different emotional valences as background. We combined general linear model and psychophysiological interaction analyses to identify abnormal local functional activity and integrative processes during audiovisual emotional processing in MDD patients. At the local neural level, MDD patients showed increased bias activity in the ventromedial prefrontal cortex (vmPFC) while listening to negative auditory stimuli and concurrently processing visual facial expressions, along with decreased dorsolateral prefrontal cortex (dlPFC) activity in both the positive and negative visual facial conditions. At the network level, MDD exhibited significantly decreased connectivity in areas involved in automatic emotional processes and voluntary control systems during perception of negative stimuli, including the vmPFC, dlPFC, insula, as well as the subcortical regions of posterior cingulate cortex and striatum. These findings support a multimodal emotion dysregulation hypothesis for MDD by demonstrating that negative bias effects may be facilitated by the excessive ventral bottom-up negative emotional influences along with incapability in dorsal prefrontal top-down control system.

Integrating Multilevel Functional Characteristics Reveals Aberrant Neural Patterns during Audiovisual Emotional Processing in Depression.

Emotion dysregulation is one of the core features of major depressive disorder (MDD). However, most studies in depression have focused on unimodal emotion processing, whereas emotional perception in daily life is highly dependent on multimodal sensory inputs. Here, we proposed a novel multilevel discriminative framework to identify the altered neural patterns in processing audiovisual emotion in MDD. Seventy-four participants underwent an audiovisual emotional task functional magnetic resonance imaging scanning. Three levels of whole-brain functional features were extracted for each subject, including the task-evoked activation, task-modulated connectivity, combined activation and connectivity. Support vector machine classification and prediction models were built to identify MDD from controls and evaluate clinical relevance. We revealed that complex neural networks including the emotion regulation network (prefrontal areas and limbic-subcortical regions) and the multisensory integration network (lateral temporal cortex and motor areas) had the discriminative power. Moreover, by integrating comprehensive information of local and interactive processes, multilevel models could lead to a substantial increase in classification accuracy and depression severity prediction. Together, we highlight the high representational capacity of machine learning algorithms to characterize the complex network abnormalities associated with emotional regulation and multisensory integration in MDD. These findings provide novel evidence for the neural mechanisms underlying multimodal emotion dysregulation of depression.

Prevalence and Clinical Correlation of Decayed, Missing, and Filled Teeth in Elderly Inpatients With Schizophrenia.

Introduction: Schizophrenia is a mental disease with a profound impact on human health. Patients with schizophrenia have poor oral hygiene, increasing their risk of systemic diseases, such as respiratory infections, and declining their quality of life. Therefore, this study aims to assess the oral health status of inpatients with schizophrenia, analyze its related factors, and thus provide scientific evidence for further exploration of corresponding control strategies. Methods: A total of 425 inpatients older than 50 years with a diagnosis of schizophrenia from two psychiatric hospitals (mean age 58.49 ± 5.72 years) were enrolled. The demographic data of the patients were checked on admission. Two independent dentists examined caries, missing teeth, and fillings. Mini-Mental State Examination (MMSE) and Global Deterioration Scale were performed as cognitive tests. Positive and Negative Syndrome Scale and Repeatable Battery for the Assessment of Neuropsychological Status rating scale were used to determine their mental status. Results: The average decayed, missing, and filled teeth index was 12.99 ± 8.86. Linear regression analysis showed that the decayed, missing, and filled teeth index had a significantly positive relationship with age (p < 0.001) and smoking (p < 0.001) and a negative relationship with MMSE (p = 0.029). The missing teeth index had a positive relationship with age (p < 0.001), smoking (p < 0.001), and Global Deterioration Scale (p = 0.014) and a negative relationship with MMSE (p = 0.004). Conclusion: The oral health of elderly patients with schizophrenia is poor, which may be related to the cognitive level of patients and affect their quality of life. The focus should be provided to the oral care of patients with schizophrenia, and investment in their specialized oral treatment should be increased.

Motor Circuit and Superior Temporal Sulcus Activities Linked to Individual Differences in Multisensory Speech Perception.

Integrating multimodal information into a unified perception is a fundamental human capacity. McGurk effect is a remarkable multisensory illusion that demonstrates a percept different from incongruent auditory and visual syllables. However, not all listeners perceive the McGurk illusion to the same degree. The neural basis for individual differences in modulation of multisensory integration and syllabic perception remains largely unclear. To probe the possible involvement of specific neural circuits in individual differences in multisensory speech perception, we first implemented a behavioral experiment to examine the McGurk susceptibility. Then, functional magnetic resonance imaging was performed in 63 participants to measure the brain activity in response to non-McGurk audiovisual syllables. We revealed significant individual variability in McGurk illusion perception. Moreover, we found significant differential activations of the auditory and visual regions and the left Superior temporal sulcus (STS), as well as multiple motor areas between strong and weak McGurk perceivers. Importantly, the individual engagement of the STS and motor areas could specifically predict the behavioral McGurk susceptibility, contrary to the sensory regions. These findings suggest that the distinct multimodal integration in STS as well as coordinated phonemic modulatory processes in motor circuits may serve as a neural substrate for interindividual differences in multisensory speech perception.

Multivariable pattern classification differentiates relational self-esteem from personal self-esteem.

Relational self-esteem (RSE) refers to one's sense of self-worth based on the relationship with significant others, such as family and best friends. Although previous neuroimaging research has investigated the neural processes of RSE, it is less clear how RSE is represented in multivariable neural patterns. Being able to identify a stable RSE signature could contribute to knowledge about relational self-worth. Here, using multivariate pattern classification to differentiate RSE from personal self-esteem (PSE), which pertains to self-worth derived from personal attributes, we obtained a stable diagnostic signature of RSE relative to PSE. We found that multivariable neural activities in the superior/middle temporal gyrus, precuneus, posterior cingulate cortex, dorsal medial Prefrontal Cortex (dmPFC) and temporo-parietal junction were responsible for diagnosis of RSE, suggesting that the evaluation of RSE involves the retrieval of relational episodic memory, perspective-taking and value calculation. Further, these diagnostic neural signatures were able to sensitively decode neural activities related to RSE in another independent test sample, indicating the reliability of the brain state represented. By providing a reliable multivariate brain pattern for RSE relative to PSE, our results informed more cognitively prominent processing of RSE than that of PSE and enriched our knowledge about how relational self-worth is generated in the brain.